Concept Development and Implementation of Online Monitoring Methods in the Transfer Molding Process for Electronic Packages vorgelegt von M.Sc. Burcu Kaya geb. in Izm ir, Türkei von der Fakultät IV- Elektrotechnik und I nformatik der Technischen Uni versität Berlin zur Erlangung des a kademischen Grades Doktor der I ngenieurwissensch aften - Dr.-Ing - genehmigte Dissertat ion Promotionauss chuss: Vorsitze nder: Prof. Dr.-Ing. Rolf Schuhm ann Gutachter: Prof. Dr.-Ing. D r. sc. techn. Klaus-Dieter La ng Gutachter: Prof. Dr.-Ing. Martin Schneider-Ra melow Gutachter: Prof. Dr.-In g. André Zimmerm ann Tag der wissen schaftlichen Aussprache: 23. Mai 2018 Berlin 2018 III Abstract The transfer molding process is one of the major processes for the encapsulation of electronic packages. T o p r o v i d e a s t r u c t u r a l s u pp o r t a n d t o p r o t e c t t h e e l e c t r o n i c c omponents fro m the en vironment, epoxy molding compounds (EMCs) are mainly used as encapsulation mater ial. The quality of the molded packages depends strongly on the process parameters of the tran sfer molding process and also the characteristics of EMC. Despite t he fact that the transfer mold in g pr ocess ha s ma ny adv anta ges suc h as cost-effectiveness and high volume applicability, there are som e challenges regarding process optimizati on. Parameter settings in transf er m oldin g pro cess ar e usually done in a trial and error manner and defi ning optimum param eters is m ostly labor ious. Moreover, the d efined machine process paramet ers are deviating fr om t he con ditions in the tool cavity e . g . p r e s s u r e m e a s u r e d i n t h e c a v i t y differs from the parameter settings in th e machine. In addition to process pa ramet ers, the EMC characteristic s also hav e great influen ce on th e package qualit y . The reactive nature of the epoxy resins can b e i nflu ence d by pr olo nged stor age dura tio n an d mo is tur e co ntent, and the possible variati ons from batch to batch may cause alterati ons in the charact eristics of the EMC, i.e. moldabilit y , change in the flow behavior of the material in t he cavity and excessive void formation. Yet, so me co mmon defects can occur i n the pac kage such as wir e swee p, del aminati on, v oid formation a nd warp age, which may ultimately lead to a total package failure. This work aims t o support a more co mprehensive understandi ng of t he i nfl ue nce of pr oce ss pa ra met ers and the variations in the material characteristics of EMC on t h e packa ge quality, to reduce the possibl e defects in the electronic pac kages and to ensure a stable transfer m o lding process. Sy stematic approaches are evalu ated to ge nerate mode ls which des cribe the correlati on s between process parameters, materi al characteristic s and pac kage quality . Detailed proc ess analy sis is conducted to co rrelate significant process p aram eters of the transfer mol ding process with quality features such as void for mation, wire sweep and warpage. T o determine the relationship between the pr ocess par ameters and the quality characteristic s mathematically , process models are generated. A n approach to g enerate and calibrate the models i s presented. The o ptimum process para meters of the tran sfer mol ding proce ss ar e deter mined with the generated model to achie ve the opti mal pac kage quality concer ning th e se lected qualit y fe atures and to reduce the failure costs. Moreover, with the generated m odels it is also possible to predict the package quality of the electronic p ackages. Thus, the esti matio n quality and the limitations of the process model are evaluated with validation expe riments. In addition t o that, the influence of variations of the materia l char acteristi cs of the EMC due to prolonged storage du ration, humidity and batch vari ations on the package qualit y is investigated. T he online mo nitoring m eth od, Di electri c Analy sis (DEA) i s implemented in the tran sfer molding process to observe the v ari ati ons in the ch aracteristics of the EMC. Suitability of the DEA t o monitor the alterations in t he materi al chara cteristics of t he EMC in-situ i n transfer molding process is assessed. In addition to DEA, addit ional temperat ure and pressur e sens ors are imple mented in the cavity of the transfer m olding process f or process control. Material mo dels are introduced to define the c orrela tion between the variations in the material c haracteristics of EMC a nd the package quality and to deter mine the processing li mitation s of t he preconditi oned EMC in ord er to achiev e pred efined packa ge quality . The vali dation of th e mater ial model is performed with a nother EMC to gener alize the observe d impact of material char acteristi cs of the EM C on package quality . IV Kurzzusammenfassung Das Tra nsfer Molding Ver fahren ist einer der wichti gsten Prozes se f ür di e Verka psel ung von elektronischen Komponenten. U m eine strukturelle U nterstützung zu gewährleisten und die elektronischen Kompo nenten vor Umwelteinflüssen zu s ch ützen, w e rden häufig Epoxi dformmassen als Verkapselungsmaterial verwendet. Die Qualität der ge moldeten Ba u t e i l e h ä n g t s t a r k v o n d e n Prozessparametern des Transfer Molding Verfahrens und v on den E igenschaften der Epoxidformmassen ab. O bwohl der Transfer Moldi ng Pr ozess viele Vorteile, wie z.B . geringe Kosten und gr oße Volumenanwendbarkeit, aufweist, g ibt es einige Hera usforder unge n hinsichtlich der Prozess optimieru ng. Die P arameterei nstellungen bei m Transfer Mo lding Prozes s werden in der Rege l auf Basis von Trial-and-Error Ve rfahren ermittelt, und die Defi nition der opti malen Paramete r ist sehr aufwän dig. Darüber hinau s weichen die defin i erten Prozessparam e ter d er Maschine von den gemessenen Zustän den in der Werkzeugkavität ab, z . B. stimmt de r in der Kavität ge messene Druck nicht mit d en Parametereinstellungen in der Maschine überein. N eben den Prozessparametern haben auch die Eigenschaften von Epoxidformmass en großen Einfluss auf die Bauteilqualität. Die rea ktive Natur der Epoxidharz e kann durch eine verlängerte Lagerdauer un d den Fe uchtigkeitsgeh a lt beeinflusst werden. Zusätzlich kön nen die möglichen Variationen von Charge z u Charge Verän derung en i n den Eigenschaften der Epoxidharze in sbesondere hi nsichtlich der For mbarkeit, Veränderung des Fließverhaltens des Mater ials in der Kavität und überm äßiger Lu nkerbi ld ung veru rsac hen. Den noch können einige charakteristische Defekte in den verkapselten Bau teilen auftreten, wie z. B. Drah tverwehu ng, Delaminatio n, Lunk er und Verzug , was letztendli ch z u einem G esa mtvers agen der verkapselten Bauteile füh ren kann. Diese Arbeit zielt darauf ab, ein umfassendere s Verst ändnis übe r d en Ein fluss von Proze sspa ramet ern und die Variatio nen in den M aterialeigens chaften von Epoxidf orm massen auf die Bauteilqualität zu erarbeiten. Weiterhin ist es das Ziel, mögliche Defekte in den verkapselten B auteilen zu reduzieren und einen stabilen Transfer Molding Prozess siche rzustellen. Sy stem atische Ansätze werden evalu iert, um Modelle zu generier en, die die Zusa mmenhänge zwis chen Prozess pa ramet ern, Materialei gensch aften und Bauteilqualität be schreiben. Zur Verknüpfung si gnifikanter Proz essparameter d es Transfer Molding Verfahrens m it Qualitätsmerkmale n wie Lunkerbildung, Drahtverwe hung und Verzug , wird eine detaillierte Prozessanalyse durch geführt. Um den Zusammenh ang z wischen den Prozessparametern und den Qualitätsm erkmalen mathematis ch zu er mitteln, werden Prozessmodelle generiert. Ein Ansatz zum Generieren u nd Kali brieren der Modelle wird vorgestellt. Mit de m gen erier ten Mo dell wer den di e optimale n Proze sspara meter des T ransfer Molding Prozesses ermit telt, damit eine optimale Bauteilqualität hinsichtlich der ausgewählten Qual itätsmerkmale sichergestellt und somit mögliche Fehlerkosten red u ziert werden können. Darü ber hinaus ist es mit den generierten Modellen auch möglich, die Bauteilqualität vorhe rzusagen. Daher werden die Pr ognosequalität und die Grenzen des Prozessmodells mit Validierungs versuchen evaluiert. Weiterhin w ird der Einfl uss von Veränderungen der Materialeigenschaften der E poxidformmass en aufgrund der Lag erdau er, Feuchte und Chargenschwankung en auf die Baute ilqualität un tersucht. Die Onl ine-Über wach ungs methode Dielektrisc he Analyse (DE A) wird im T ransfer Mol ding Proze ss im plementier t, um die Verän derung en i n d e n E i g e n s c h a f t e n d e r E p o x i d ha r z e z u b e o b a c h t e n. D i e E i g n u n g d e r D E A z u r i n - s i t u Ü b e r w a c h u n g der Verän derungen der Materialei genschaften der E poxidharze im Transfer Molding Pro zess wird bewertet. Zusätzlic h zu der D EA sind Temperat ur- und Drucks enso ren in der Kavität des Transfer Molding Werkzeuges zur Prozessste uerung i mplementiert. Um die K orrelation zwis chen den Veränderungen in den Materialei genschaften von Epoxidformasse u nd d er Bauteilqualität zu definier en, werden Material modelle eingeführt. Weiterhin w erden so die Verarbeitungsbeschränkungen der vorkonditionierten E poxidformmasse zum Erreichen ein er vordefi n ierten Baueilqualität besti mmt. Zur Überprüfung einer allgemeinen Gültigkeit des Materialmodells wi rd eine Validi erung des Modells mit einer zweit en Epoxidf ormmasse durchg eführt. V Acknowledgements I would like to use the opportunity and t hank all the p eople wh o supported me during the completion of this thesis. First of all, I would like to t hank Pr of. Klaus-Di eter Lang from TU B erlin a nd instit ute le ader of Fraunhofer IZM for accepting the supervisi on of t his t hesis, for the valuable discussions and for his mentoring. In addition, I would l ike to sincerely thank to Prof . Martin Schneider-R amelow and Prof. André Zimmermann for reviewin g of thesis and Prof. Rolf Schuhma nn as the chair man of t he d octoral admissi on committe e. Moreover, I would like to express my gratitu de to Dr. Jan-Marti n Kaise r from Rober t Bosch GmbH for accepting the co-s upervision of this thesi s. His continuou s s up port and deep discu ssions have g uided me through the intense journey of th is thesis and gav e me the moti vation for the completion of the thesis. I am grateful to have t he opportunity to work under h is supervisi o n. I w ou ld li ke t o a ls o si n ce r el y t h a nk Karl-Fried rich Becker and Dr. Tanja Braun fro m Fraunhofe r IZM f or valuable discussions, for sharing their knowledge about material science and process ing and their constant support. Last but not least, I w o u l d l i k e t o t h a n k m y c o l l e a g u e s a t C R / A P P a t R o b e r t B o s c h G m b H for the good collaboration, for continuous support and for helping me to realize this t hesis. I t was pleas ure for me to get to know them and have a ch a n ce working with them. I wou ld lik e to als o than k t he master students and interns who su ppor ted me d urin g t hi s t hesi s. Without their help, it would n ot be p ossible t o complete the thesis i n this form. Finally and most importantly, I would lik e to thank my fam ily f or their en dles s suppor t and gi vin g me a constant motivation, an d always being there for me. I am so gr a teful to have them . Contents VII Contents Abstract . .............. .............. ............... .......... .... .............. ........... ............... .............. .............. ............... ... III Kurzzusammenfassung . .............. ............... .......... ... ............ .............. .............. ............... .............. ....... IV Acknowledgement s ........ .............. ............... ......... ..... ........... .............. .............. ............... .... .......... ........ V Symbols and Abbreviations ............... ............... ....... ....... ........... .............. ............... .............. .. ............ . X 1 Introduction ......... .............. .............. ............... .............. ........... .............. ............... ..... ......... .............. .. 1 2 State of the Art ........ ............... .............. ....... .... ........... .............. .............. ............... ..... ......... .............. .. 3 2.1 Electronic Packaging .... ........... .............. ......... ......... ........... .............. ............... .............. .............. .. 3 2.2 Quality Criteria of Electr onic Packages ............... .... ...... ............... .............. .............. ........... ... ... ... 5 2.3 Transfer Moldi ng Process .......... ............... .............. .............. ........... ............... .............. .... .......... .. 6 2.4 Epoxy Molding Compou nds .......... .............. ........... .... .............. ............... .............. .............. .. ....... 9 2.5 Online Monitori ng Methods and Pro cess Optimization ........ ........ .............. ............... .......... ....... 13 2.6 Statistical Analysis ....... .............. ............... .............. ............... .......... ............... ........... ... .............. 19 2.7 Outline of the Dissertati on.............. .............. .... ........... .............. ............... .......... ............. ..... ....... 24 3 Materi als and Instrumentation ... .............. ........... .................. .............. ........... .............. ......... ......... 29 3.1 Materials ..... ........... .............. ............... .............. .............. ............... .............. .......... .... ............... ... 29 3.1.1 Epoxy Molding Compounds.... .............. ........... ..... .......... .............. .............. ............... .......... 2 9 3.1.2 Lead Frame . ............... .............. .............. .. ............. .............. ............... .............. ....... ....... ....... 31 3.2 Transfer Moldin g Process and Online Monitoring Methods .... ................... ............... .......... ....... 32 3.2.1 Molding Machine for Encapsulation of Demonstrator with Integrated Sensors .................. 32 3.2.2 Molding Machine for Producin g the Sample Bars ...... ..... ............. ........... .............. .............. 36 3.2.3 Dielectric Analysis (DEA) .. ............... .............. ............... .............. .............. ............... ..... ..... 37 3.3 Material Characterization Method s ....... .............. ............... .............. ............... .............. ......... ..... 39 3.3.1 Dy namic Mechanical Analy sis (DMA) ..... .............. .... ....... ............... .............. ........... .......... 40 3.3.2 Dy namic Scanning Calori metry (DSC) ................... ... ............ .............. ........... .............. ....... 40 3.3.3 Rotational Rheometer ....... .................. ........... ... .............. ............... .............. ............... .. .... .... 41 3.3.4 Squeeze Flow Rheometer ............... ............... .... .......... .............. ............... .............. .......... .... 41 3.3.5 Simultaneous DEA-Rheology M easurements ............. ..... ......... ............... .......... ............... ... 42 3.3.6 Karl-Fisch er Titration ....... .............. ........... .. ............ ............... .............. ............... ....... ....... ... 42 3.4 Quality Analysis Methods .................. .............. .. ............ ............... .............. ........... ........... ....... ... 43 3.4.1 Scanning Acoustic Microsco py (SAM) ........ .............. .... ............... ........... .............. .............. 43 3.4.2 Warpag e Analy sis .................... ........... ......... ......... ........... .............. .............. ............... .......... 45 3.4.3 Wire S weep Analysis ....... .............. ............... .............. .............. ............... .............. ....... ....... 45 4 Experimen tal Preparation ....... .............. ............... ........... .............. .............. ............... ......... ..... ....... 49 4.1 Layout Definition ............. .............. .............. ............... .............. ........... .............. ......... ...... .......... 49 Contents VIII 4.2 Sample Prepar ation .............. ............... .............. .............. ............... .............. ........... ...... ............ ... 50 4.2.1 Cleaning ................ .............. ............... .............. ........... .............. ............... ............ .. .............. 51 4.2.2 Bonding ..................... .............. ........... .................. .......... ............... .............. ......... ...... .......... 51 4.2.3 Chip-A ssembly .. ............... .............. ............ ... .............. ........... .............. ............... ...... ........ ... 52 4.3 Statistical Process Analy sis . ............... .............. .............. ............... .............. ........... ......... ......... ... 52 5 Preliminary Experi ments and Results ..................... .... ...... ............... .............. .............. .............. .... 53 5.1 Preliminary Experiments of Proces s Parameters ......... .... .......... ........... .............. ............... .......... 53 5.2 Results of Preliminary Process Expe riments ........ ........ .......... .............. .............. ............... .......... 5 6 5.2.1. Identification of Signifi cant Proce ss Paramet ers . ...... ..... .............. .............. ............... .......... 56 5.3 Preliminary Inves tigations of Material Characteristics .... ...... .............. .............. ............... .......... 63 5.3.1 Correlation of DE A with Rotational Rheometer and DSC . ... ................... ........... .............. ... 64 5.3.2 Storage Durati on ............... .............. ............... .............. .............. ............... ........... ..... ............ 65 5.3.3 Humidity ......... .............. ........... .............. ............... .............. ............... .......... ......... ......... ....... 65 5.3.4 Batch Variations ........... ............... .............. .... .............. ........... .............. ............... ..... ......... ... 66 5.4 Results of Preliminary Invest igations of Material Character istics .............. .............. ............... ... 66 5.4.1 Results of Correlatio n of D EA with Rotational Rh eometer a nd DSC ................. .......... ....... 66 5.4.2 Results of Investigations o f Mat erial Cha racter istics ... ...... ............... .......... ............... .......... 69 5.5 Summary ........... ............... .......... ............... .............. .............. ............... .............. ...... ...... ........ ..... 80 6 Main Experiment s and Results ... .............. ............... .......... ............... .............. ........... ............. ....... . 83 6.1 Main Experi m ents for Process A nalysis ........... .......... .... ............... .............. .............. ............... . .. 83 6.2 Results of Main Experi ments for Process Analy sis .......... ............. ........... .............. .............. ....... 84 6.2.1 Machine and Sensor Signal Analy sis .... .................. ............... .............. ............... .............. ... 8 5 6.2.2 Analy sis of Process Stability .......... ............... .. ............ .............. ............... ........... ........... ...... 87 6.2.3 Quality Analysis .................. ........... ........... .... .............. .............. ............... .............. .. ............ 91 6.3 Analy sis of Influence of Mat erial Ch aracteristics on Packag e Quality .... .............. ........... .......... 97 6.3.1 Storage Durati on ............... .............. ........... .... .............. ........... .............. ............... ..... ......... ... 97 6.3.2 Humidity ......... .............. ........... .............. ............... .............. ............... .......... ......... ......... ....... 97 6.3.3 Batch Variations ........... ............... .............. .... .............. ........... .............. ............... ..... ......... ... 98 6.4 Results of Influence of Materia l Characteristic s on Packag e Quality ......... ........... .............. ....... 98 6.4.1 Influence of Batch Variations on Package Quality ........ ........ .............. ............... .......... ....... 98 6.4.2 Influence of Storage Duratio n on Packag e Quality . ....... .... .............. ............... .............. ..... 100 6.4.3 Influence of Humidity on Package Quality ................ . .............. ........... .............. ............... . 102 6.5 Summary ........... ............... .......... ............... .............. .............. ............... .............. ...... ...... ........ ... 108 7 Evaluation of Statistical Corre l atio ns and Model Definition . .... .............. ............... ........... ........ 111 7.1 Evaluation of Process Analy s is and Process Model Definition ............... .............. ........... ........ 111 7.1.1 Objective of the Process Model ... .............. ......... ......... .............. ............... .......... ............... . 112 7.1.2 Model Definition ... .............. ........... .................. ........... .............. ............... .............. ... ......... 112 Contents IX 7.1.3 Evaluati on of Proces s Parameter Correlations wi th Regress ion Analy sis .............. ............ 1 1 4 7.1.4 Generat ion of Process Model ............. .............. .. ......... .............. ............... .............. ........... . 1 1 7 7.1.5 Model Prediction Quality ............ .............. ...... ............ .............. ............... .......... ............ .... 1 1 8 7.1.6 Optimum Process Para meters ...... .............. .......... .... ............... .............. ........... .............. ..... 1 2 1 7.2 Evaluati on of Material Analys is and Material Model Definiti on ......... .............. ........... ............ 1 2 3 7.2.1 Objective of the Mat erial Model . .............. .......... . .............. .............. ............... .............. ..... 1 2 3 7.2.2 Evaluati on of Material Paramet er Correlations .................. .............. ............... .............. ..... 125 7.2.3 Material Model Definition and Predicti on Quality......... ................... .......... ............... ........ 127 7.3 Summary ........... ............... .......... ............... .............. .............. ............... .............. ...... ...... ........ ... 128 8 Validation Experiments and Results ............ .............. .............. ............... .............. ........... ......... ... 131 8.1 Validation of Process Mod el .............. .............. ... ........... ............... ........... .............. ............ ...... . 131 8.1.1 Experi mental Design ........... ............... ........... ... ............... .............. .............. ............... .. ...... 132 8.1.2 Quality Analysis Results .. .............. ........... ..... ......... ........... .............. ............... ........... ........ 133 8.2 Validation of Material Model ............. .............. ....... ........... .............. ........... .............. ............. ... 1 3 7 8.2.1 Experimen tal Analysis ...... .............. ............... .................. .......... ............... .............. ............ 1 3 8 8.2.2 Experi mental Results ........... ............... .............. ............... .............. ........... .............. ............ 1 3 8 8.3 Summary ........... ............... .......... ............... .............. .............. ............... .............. ...... ...... ........ ... 145 9 Conclusions and Outlook ............. .............. .......... ..... .............. .............. ............... .............. . ........... 1 4 7 List of Figures .. .............. .............. ............... .............. .............. ........... .............. ............ ...... ........... ..... 151 List of Tables ....... .............. ........... ............... . ............. .............. ............... .............. ....... ....... ............... . 158 Bibliography .............. ............... .............. ....... ....... ............... .............. .............. ............. .. .............. ..... 159 Appendix .. ............... .............. .............. ......... ...... .............. .............. ........... ............... ... ........... ............ 168 Sy mbol s a nd Abbr evi ati ons X Symbols and Abbreviations A Electrode plate area C p Parallel capacitance C sub Substrate capacitance d Dista nce bet ween the elec trodes E´´ Loss modulus E´ Storag e modulu s ε " Dielectric loss factor έ Dielectric permittivity ε 0 Permittivity of vacuum (dielectric constant) e Error f Frequency T g Glass tr ansition temper ature P P r e s s u r e R p AC parallel resistance R 2 Coeffi cient of determin ation R 2 adj Adjusted co efficient of determination T Tempe rature t (Preheat) ti me tan δ Tang ent delta v Transfe r speed σ I onic conduct ivity Io n viscosi ty α Degr ee of cur e ∆ H(t) Enthalpy at tim e t ∆ H total Total reaction enthalpy BC Bou ndary con ditions CTE Coefficient of thermal expansion DEA Dielectric anal y sis DoE Design of ex periments DSC Dy namic s cannin g calori metry DMA Dynamic m echanical ana lysis EMC Epoxy molding compound FTIR Fourier-transform infrared spectroscopy IC Integrated ci rcuit OFAT One f actor at a time LIC Log arithmic of ion visc osity RH Relative humidity PMC Post mold cure SAM Scanning acoustic microscope TIM The rmal inter face mater ial 1 Introduction 1 1 Introduction S e m i c o n d u c t o r p a c k a g e s a r e w i d e l y u s e d i n m a n y a r e a s s u c h a s a u tomotive, m ilitary , aerospace, communication and computing applications [1], [2]. The market f o r semiconductor p ackages has experienced an e normous development in recent y ears. Acc ordingl y, a trend to decreas e the packa ge size by incr easin g int egrat ion de nsity on the lea d fr ame sign if ica ntly ra ises the requireme nts for the packaging. Thus, the demand for re lia ble robust packages ha s be come even more pronounced. To yield long-term reliability of the packa ges, i.e. to protect them fro m environ mental effects s uch as heat , temperat ure, pressure, me chanical stress and humidity , the ele c tronic package s ar e e ncapsu lated. Transfer molding is one of the major p rocesses for e ncapsulatio n of semiconductor devices due to its high productivity , cost effectiveness, a bility to mold complex fe atures a nd res ulting robust packages. As an e ncapsulation material for the electronic packages, mostly polymeric materials ar e used. Non- hermetic pac kages, which are enca psulated w ith p olymeric mat eri als, of fer some ad vantage s o ver hermetic packages such as light-weight, cost and flexibility. H ence, over 90 % of the electr onic packag es are encapsulated with polymeric m aterials [1], [3]. Among polym eric mater ials, epoxy molding compo unds (EMCs) ar e mainly used a s an en capsulation mate rial. EMCs po ssess superior properties such as high mech anical strengt h, thermal stability and good th ermo- mechanical matching to the materials typically used in packagi ng. The quality of the molded packages heavily d epends on the m ater ial properties of EMC and the process paramet ers of the transfer molding process. Although transfer m oldin g is a common process fo r producing electronic packages a nd billions of electronic packag es are manufactured with this pro cess every y ear, process opti mizati on is still challenging . Paramete r settings of the transfer molding process are mostly devel oped in a trial and erro r manner and opti mal se ttings are often not obtain ed [4]–[6]. Additionally, the m achine settings in the m o lding process do no t usually r eflect the real condition in the cavity, e.g. the machine pressure is often not equivalent to th e pr essure in the ca vity. In the case of power electronics, process control is even more challenging due to th e large vol ume of the modules. Dire ct information from t he cavit y of the mold tool cann ot b e o btained and the temperature and p ressure in the cavity can only be monitored via machine settings. In addition to process parameters, the EMC characteristics also have a large influence on the package quality . The reactive nature of the epoxy resins can be influen ced by th e variations in the characteristics of the EMC such as the moldabilit y and change in the flow behav ior of the material, which can be especially critical for large compl ex power modul es. Ther efore, acquiring i nformation abou t the c ure behavior of the EMC in-situ in the transfer molding process is very determining for an ultimate package quality. Due to this limited process knowledge and the alterati ons in the materi al char acteri stics of the EMC, during the encapsulation of t he electronic packages, some co mmon def ects can occu r in the package such as wire sweep, delamination, void for mation and wa rpa ge, w hich may l ead t o tota l pac kag e failure at the end. When t he failure mechanisms arise in the pa ckage during one of the l ast st eps in the assembly process, namely in the transfer molding process, it ca n cause high failure c osts, particularly for compl ex power modules. On that ac count, unders tanding the i mpacts of the material characteristics of the EMC and the process parameters on the package quality is essential. An established correlati on between process parameters, mate rial chara cteristics and the pa ckage qual ity c an i mprove process understanding, y et diminish the failure mechanisms in the molde d packages. The ai m of this work is to provide a conceptual un derstanding o f the influence of t he proces s par ameters of th e transfer molding process and the variations in the m ate r ial cha racteristics of E MC on the packag e quality. E xtensive process analy sis is conducted f or improved p rocess understan ding of transfer molding process. As an electro nic package, a te st vehicl e h aving simila r geom e tric al dimensions as a power module is used i n this work. Systematic approaches are evaluate d to genera te models , which desc ribe the relati onship between t he pro cess parameters, the variations in the material chara cteristics of E MC and the package quality. Additionall y , th e represented approach also all ows definition of the optimum 1 Introduction 2 process p arameter s of the transfer molding proces s to achieve t he best package quality . Online monitoring methods are imple mented in the transfer molding proc ess to gain more insight into the cavity of the transfer molding process and to obtain a stable process. Detailed material investi gations are conducted to increase t he kn owledge on the infl uence of alterat ions in the material proper ties of the EMC prior to the molding pro cess on the cure behavior of the EM C and on the pa ckage qu ality. On line monitoring method, DEA, is e mployed to monitor the variations i n the material properties of EMC in- situ during transfer molding process. 2 State of the Art 3 2 State of the Art In this chapter an overview of the state of the art on the enca psulation of the electronic p ackages, as well as the technologies and the materials em p loyed to produce the e lectronic packaging is given. In Section 2.1 the co mponents a nd the main functions o f the electr onic packaging as well as t he manufacturing process of an electro nic packaging are intro duced . Dif ferent d efects c an oc cur in a n electron ic package, wh ich can cau se a total package failure . Th us, i n Sec tio n 2. 2 po ssi bl e fai lur e mechanis ms of an ele ctronic pa ckage are summarize d. The transf e r molding process, which is the most established encapsulation process of semic onductor devices is e xplained in detail in S ection 2.3. The process steps, the significance of the p r ocess parameters, and t heir i nfluences on the package quality are discussed. I n Sectio n 2.4 an overvi ew on t he commonly used enca psulati on materials, na mely epoxy molding co mpounds (EMCs) is provided. Th e properties of t he E MC , and thei r impact on the package perfor mance ar e explai ned in detail. Recently , online m onito rin g techniques gain ed significant attention in terms of observing the cure reaction of t he EMC i n-situ in p ro cess. Various monitoring techniques are introduced in Section 2.5. T heir potentials and limitations are discussed. M ore focus is given to dielectric analysis (DEA) as an online monitoring technique, he nce the measure ment princi ple and so me impo rtant featur es o f the metho d are e xpres sed in Section 2 .5 i n det ai l. T o unde rs ta nd the in fluences of the material characteristics and the process parameters o n the p ackage quality and to describe the correlations in a best possible way, statistical analysis is us ed in this work. T hus, i n Sectio n 2.6 the statistical analysis and the i mportant ter ms regarding the Desi gn of Experi ments (DoE) are highlighted. Finally, in Section 2.7, a brief su mmary of the state of the ar t is done, and the unr esolved iss ues in terms of influ ence of material chara cteristics an d of proce ss paramet ers on the package quali ty are discus sed. Additionally, the outline of the thesis is introduced in Sectio n 2.7. 2.1 Electronic Packaging Semicon ductor packages have been used in man y elec tronic produc ts and equip ment s uch as personal computer s, consu mer elect ronics, and automotive el ectronics. Electronic packages i nclude transistors assembled in int egrated circuit (IC) chips, resistors, diodes, capacitors as well as housing [7] . In F igure 2.1 an electr onic pa ckage, co nsisting of electronic compo nents such as chips, and wire bonds as well as a dhesives a nd lead fra me plus the moldi ng compo und is de picted sch ematically . Figure 2.1: Schem atic illustration of structure of an elec troni c package The main fun ctions and the require ments of the electronic packa ges are: Protection of the chip from harsh environment Protection of the compone nts from heat, temperat ure, humi dity, moisture and radiation 2 State of the Art 4 Providing resistance to i onic conta m inations Protection fro m mechanical stress such a s pressure Reducing the ther mo-mechanical stresses Isolation of the electrical contacts Providing mechanical s upport [1]. Packaging material pl ays a very critical role in an electronic system so that the package can perform the desired function s and meet the aforementioned r equirements. Dep ending on the employ ed encaps ulation material, two different ty pes of p a ckages can be produced: herm etic or non-h erm e tic pa ckage s. In hermetic packaging, a ceramic o r metallic material is used as a package materia l, whereas in non- hermetic packages, a poly meric material is utilized as an encap sulant. In compa rison to hermeti c packaging, non-he rmetic packaging offers some advantages such a s weight, costs, handling, flexibility in design and availab ility [3 ], [8], [9]. Thu s, over 90 % of th e microelec tronic co mponents ar e encapsulated with plastic materials [1], [3]. Among plastic mat erials, EMCs are typically used in semiconducto r devices due to th ei r s uperior properties, which w ill be addressed in Section 2.4 in more detail. Electro nic pac kaging, describe d here for a lea d fra me based pac kage, starts with a chip on wafer level. After the fabrication of a wafer , the chip pre paration steps st art which involve grinding and dicing processes. After th e singulation of the chips, the assembly pro cess for the electr onic package starts with an attach ment of a chi p onto the le ad frame (di e attach pad). T he chips are attached onto the lead frame using typicall y a polymeric adhesive, which is subsequently sen t t o a n o v e n f o r c o m p l e t e a d h e s i v e c u r i n g [10]. To achi eve a smooth clean surface for the following wire bonding process, usua lly the lead fr a me is dispatched to a cleaning proc ess. F or an electrical c onnecti on, wire bond process is applied, where the chip is connected wit h wire bonds to the lead frame fingers. Fo llowing the wire bond process, the interconnected chip as sembly is encapsulated. To achieve the me chanical stability and high network density of molding com p ound, a post mold cure (PMC ) is performe d after the molding process. F inally, the leads are trimmed and formed to va rious shapes [1]. The sch ematic illustration of the assembly s teps for a lea d frame based ele ctroni c package is depicted in Figure 2 .2. Figu re 2.2: As sembly steps for el ectro nic pack ages [11], [ 12] The enca psul at ion pr oc ess is o ne of t he last st eps in the pro ce ss confi guration for manufacturing of electron ic packages, so it h as a major importance to satisfy th e desired package quality. W hen defects are i ntroduce d into the packag e in one of the last process step s, namely during the en capsulation process, it can cause high fa ilure costs due to the y ield loss. He nce, t he encapsulation step is very critical to yield 2 State of the Art 5 the stable package quality. Various encaps ulation methods are a vail able such as molding, potting, glop- top and underfill [1]. Among all methods, transfer molding is w ide ly used for an encapsulation of semiconducto r devices [5], [13], [14]. As mentione d above, some severe d efects can arise in an electronic package during transfer molding process, which m ay u ltimatel y cause a complete package failure . Th us, some of the essen tial quality criteria for the e lectr onic packages are summa rized i n following section. 2.2 Qual ity Cr iteri a of Elec tr onic Pac kages Differe nt defects can occu r in an electr onic package du e to var ious r easons such as selection and the propertie s of th e EMC , proce ss par ameters o f transfer molding o r the transfer mold design. Some of the most common defects in the molded p ackages are wire sweep, d ela m inati on, void formation, crac ks, warpa ge, inc omplete cure, blee d and flas h. Such defe cts can bec o me very critical in terms of the package quality since they may cause a total packag e fa ilure. For inst a nce, w arpage can occur in the package, which is defined as t he bending and deformation of the package [1]. Different warpage types can happen in a package such as convex or concave [15], [16]. The warpage can not only induce stre sses to the package and cau se d ie cracking and interface dela mination, but it can also l ead to assembly problems in the following process steps due to the dimensional instability and non-coplanarity of the pack age [17], [18]. P articularly , the warp age in large pow er mod ules can be v ery critical due to thermal management issues [16]. In the power modules lar ge amount of heat is gener ated due to the high voltage and large currents a pplied in the package. T hus, to r emove th e heat f rom the package, the power module is contacted wit h heat sin k, and betw een power modul e and the heat sink a ther mal interf ace material (T IM ) i s a pp lie d t o im pr ov e th e th erm al b eh av io r. Pos si bl e w a rp age issue in po wer modules can cau se poor connection to TIM, which may lead to in sufficient thermal conne ction. H ence, the heat gene rated in the power modu le cannot be ef fectively dissipated whic h may threaten long-term reliability and caus e a device f ailure. Another common problem is the existence of ga s o r a i r v o i ds i n t h e p ac k a g e. V o i d s c a n arise i n the package d ue t o the v olatile materials or organ ic v apors pres ent in resin encap sulant, which are likely released by polymerization reaction or o utgassing of the air trapped in the pressed pellet of EMC [19]–[ 22]. Alternatively the voids can arise due to air tha t enter s fro m t he runners d uring the transfer molding process or due to i mp roper molding conditions [21]–[23]. The voids in t he package can cause corrosion on the electro nic components suc h as al umin um wir es or on t he lea d fra me [22], [24]. In ad dition, they can lead to stress concentratio n and he nce, ind uce cra cks and thre aten packa ge reliability. Moreover, the voids connecting two leads of differ ent voltage level cause insulati on problems and migh t l ead t o a sh ort c irc uit. Eve n sma ll v oids bet wee n two leads of different voltage level might cause t o parti al discharg e. The detach ment of the mo lding compo und fr om a contiguous material at th e interface is defined as delamina tion [1]. Dela mination causes structural disintegri ty, and usually initiates an electrical failure [25]. Resin bleed happens when the encaps ulant flows onto the leads. So-called flash is also excess material that runs t hrou gh the moldi ng part but flash is usually thicke r tha n the blee d. When this materi al re mains on the leads, some proble ms may occu r in the subsequent operations such as lea d trimming and f orming [1], [24]. Another important defec t is the wire sweep. Wire sweep is defined as the defor mation and lateral displacement of the wire loop i nside the cavity of mold to ol [ 1], [20], [26], [ 27]. Differen t cr iteria are de fined as a wir e swee p tolerance depending on the package design. S o m e a u t h o r s s u g g e s t 1 0 % o f t h e w i r e s w e e p a s a m a x i m u m l a t e r a l displacement, some a dditionally try to reduce th e wire swee ping less than 2 wire diameters and less than 10 % of the lateral displ acement [28], [29]. Some authors have defined wire displacement exceedi ng half of the pad-to-pad distance as unacceptable [20]. When excessive wir e sweep occurs, this can l ead to short circuit and/or current leakage a nd can ev en ca use to packag e failur e [1], [3], [13], [ 30]. So me of the mentio ned defect s occurring i n an electronic packag e are ex emplarily sho wn in Fi g ure 2.3. 2 State of the Art 6 Figure 2.3: Exe mplary illustration of possible defects in plast ic enca p sulate d package [31] 2.3 Transf er Molding Process Transfer molding is an established pro cess to encapsulate t he m icroelectroni c components of semi con ducto r devices. T rans fer moldi ng proces s has ma ny adva nt ages s uch a s ability to mold complex features, high production volu me , and cost- e ffectiv e manufa ctur ing and to produce high qu ality and robust packa ges [32]–[35] . The equipment for the molding pr oces s consi sts of caviti es, a pot in w hich the EMC is placed, and t he plungers that help to tr ansfer the v iscous m aterial into the cavities. There ar e two types of transfer molding process: t he conventional method and the mu lti-plunger method. In a conventional method, there is one pot, where one large-size pel let i s placed a nd injected i nto mu ltiple cavities. In the multi-p lunger method, there are severa l pots, w here small pelle ts of EMC are injected to one or more cavities of the mold tool [2]. Transfer molding pro cess include s several process steps. Firstly , the lea d fra me, whi ch is asse mbled with electroni c co m ponents and bonded with wires, is placed i n t h e c a vi t y. Th e le a d f r am e is p re he a te d in th e c a v it y t o im p rove the adh esion between the ther moset materia l and lead fra me. The pellets of t he EMC are pla ced in t he pot, and then the tool is closed , the lead fra me is clam ped. Before the plungers move with a defi ned transfer speed, the required clamping pressure is applied to ensure th e com plete closure of the tool ha lves and th e pellets a re prehea ted in th e pot and re ach its melting temperat ure. The molten material is i n j e c t e d w i t h t h e h e l p o f t h e p l u n g e r s through the channels (called runners) and enters through the ga te into the cavity. The plungers ap ply the required pressure to fill the vi scous molding compound into the cavity and the pressure is maintained until the cavity is filled to assist the c uring reaction of the molding compound as well as to co m press any remaining voi ds to yield a void-free package [1]. The moldi ng compound undergoes an irreversible chemical reaction in the cavity a nd for ms a 3D cross-linked net work. During the curing reaction, the molecular weight of the material incre ases and material becomes solidified. Usually the cy cle time of 1 - 3 min at molding temperature of 175 ° C is required for material t o s o l i d i f y s o t h a t t h e e n c a p s u l a t e d modu le can be rem oved with the h elp of ejectors without da magin g the molded package [1]. Figure 2.4 illustrates the steps of the trans fer molding process for encap sulation of the s em iconductor packages. 2 State of the Art 7 Figure 2.4 : Process st eps of the transfer molding for encapsula tion of the semico nducto r pack ages; l ead f rame is placed in t he cavit ies of heated m old, the EMC pellets ar e brou ght to the p ots, E MC i s in jected, ejectio n of the encapsula ted lead frames after cycle time is over, enc apsulated electro nic pack ages aft er the mol ding process . Adopted fr om [2] After th e cycle time is completed, th e thermoset material achie ves a certai n d egree o f c ure. H owever, to complete curing reaction of the m o lding compound f or o btaining a desired mechanical stability, the post mold cure (PMC) is required [24], [36]. Depen ding on the proper ties of the molding c ompound, the conditions of the required PMC can vary, no net heless, PMC is ge nerally done at 170 °C - 180 °C for 2 - 4 hours in an oven depending on the material selected [2], [33] , [37]. The molding co mpound, which has a reactive nature, undergoes di fferent chemical reactions in the cavity. The m oldability duration of the EMC depends o n the gel ti me o f the material [3], [12], [33]. Gel time is defi ned as a point, where the molding compo und changes its state from a liquid into a gel [1]. Thus, the time for filling t he cavity is restricted a nd should not exceed the gel time of the material. On the othe r hand , the process para meters should be selected in a way that the sensitive components such as wire bonds are not da m aged due to set pr ocess paramet ers. Ye t, t he co mbina tion of t he pro cess paramet ers plays a significant r ole o n the curing r eaction of t he molding compound a nd on the quality o f t h e f i n a l m o l d e d p a c k a g e . S o m e o f t h e i m p o r t a n t p r o c e s s p a r a meters of the transfer molding are molding temperature, tran sfer speed, cl amping press ure, preheat time, holding pressure, cure time, and transfer ti me, which is the time to fill the cavities in the to ol. Higher molding temperatures ca n b e selected to d iminis h the curing time, which induce faster curin g r ate of the thermo set m ateri al (m olding compo und). However, at very high tempera tures, the materi al cur e s v e r y q u i c k l y , a n d t h e v i s c o s i t y increases so fast that the cavity cannot be filled compl etely w hich leads to an incomplete filling of package. Hence, the w indow f or processing time of the molding c ompoun d is restricted. Figure 2.5 depicts the limited processing w indow of the transfer molding p rocess. Figure 2. 5: Viscosity behavi o r of a molding material [ 38] According to Figure 2.5, the viscosity of the molding compound dr ops dr ast icall y at the be gin nin g du e to the high t emperat ure. As the cy cle time propagates, the cur e reaction takes place and the bigger 2 State of the Art 8 molecules are formed, which raises the viscosity of the materia l. The time to fill the cavity should not exceed the indicated process ing window to achieve g ood molded p ack age quality. During tran sfer molding, th e clamping force is crucial for keep ing th e tool halves together. If th e clamping p ressure is too low, the materi al can fl ow between two halves of the tool a nd causes flash on the package. The transfer pressure, which is applied via plunge rs, assists the moldi ng mat erial into th e cavity. During the chemical r eaction of the molding co mpound, c h e mical shri nkage of the material occu rs. T he pac kin g pres sure is ap plie d thr oug h plun gers to b ri ng more material into the cavity to compensate the s hri nkage a nd fill the cavity c ompletel y. This p rocess is also-called pack i ng [1]. Higher transfer speed can help to fill the cavity faster and provide a complete filling, however, it can also lead to severe wire sweep and even lift-off of the wire bonds in ext reme situati ons [39]. Decreasing the transfe r speed can help i mprove the wire sweep , but it may also c ause an incomplete filling p articularly for large mold tools [ 5]. This aspect is especially impo rt ant f or the power module s, where the large cavity volume for the modules has to be filled within th e gel t ime of the m aterial. When the wire bonds possibly attached at the cavity end are subjected to highl y vis cous molding co mpound, this may lead to w i r e s w e e p . T h u s , b y t h e s e l e c t i o n o f t h e p r o c e s s p a r a m e t e r s m a ny different mechanisms should be taken i nto account since achieving a good quality of the m oldin g packages in transfer molding process is a multi-objective optimization problem [4]. There fore, under standing the influe nce of the process paramet ers as well as the i nteractions b etween the process para meters and the material chara cteristics are very important to y ield a defined p ackage qu ality . Great efforts have been d one by many authors to apprehend the e ffect s of proce ss para meters on fail ure mechanisms and to define the optimum process param eters of tran s f e r m o l d in g p ro ce s s [ 4] , [ 1 4 ] , [ 40 ] . Among other defects void f ormation is one important concer n in the molded packages. T o remove volatile materials and air duri ng the molding and to achieve ho mogen ously filled packages, using the air vents in the molding t ool such as vacuum molding is favorab le [21], [41]. Nevertheless, t here may be still some voids wit hin t he p ackage o r some bubbles o n t he s urfa ce are a of th e pac kage. M . M. Prasa d investigated the impacts of the t ransfer time and preheat time on the void formation of package [34]. In particular, the same batch of th e EMC pellets was used to preve n t a n y p o s s i b l e v a r i a t i o n s i n t h e E M C properties. DoE w as con ducted, r egression a nalysis was carri ed out and the intera ctions between the significant pa rameters were disc ussed. T hey found t hat an incre ase in transfe r ti me and preheat time led to an overall decr ease in void occurre nce in the package. Regre ssion analysis indicates that there is an interaction between the tr ansfer time and the preheat time in w hich reducing the transfer ti me an d increasing the preh eat ti me caus e less void for mation. S. L. Li u e t a l . s t ud i ed th e i n fl u e n c e of m o l d i ng temperat ure, prehe at time, t ransfer ti me, curin g ti me and holdi ng pressur e of transfer mold ing pr ocess on short molding and on the void formation with n ovolac-type EM C [42]. They conducted a two-level DoE matrix consistin g of 3 2 experi ments. The scanning acoustic mi cr osco py ima g es sh owe d tha t th e void s were for med in l ow holdi ng pres sure an d short tr ansf er t i me, whereas the packages, which were molded with high holding pressure and longer transfer time show ed no void s. In addition the holdin g pressure, the selection of higher transfer pressure, lo wer mold tempe rature a nd faster transfer speeds were also suggested in t he literature i n favor of at taining red uced nu mber of voids in t he molded packages [21], [22]. The s uggested select ion of process para met er settings to reduce th e vo id form ation, however, can incre ase viscosity of EMC, which can be unf avorabl e for other package qualities such as wire sweep. Among oth er process parameter s, the transf er speed is fo und as a key proc ess parameter on the wire sweep. Decr easing the tra nsfer s peed reduc es the wire sweep by dimin i shing the viscous drag force exerted on t he wire bond [ 13], [20]. However, in jecting E MC w ith t oo slow transfer speed into the cavity can be critical since EMC already starts curing and the viscosity increases too much before t he complete filling [13], [20], [39] . T herefore, the chemo-rheolog ical p roperties and the curing reaction of EMC during molding must be considered in addition to the proces s para meter s to impr ove the wi re sweep. O n e o f t h e c h a l l e n g e s i n t h e t r a n s f e r m o l d i n g p r o c e s s i s t o d e f ine the optimum process para meters. Altho ugh tra nsfer m olding proce s s is one of the most establishe d processes for th e encapsulation of the 2 State of the Art 9 semiconductor packages and billions of parts are produced every y ear with the proces s, the opti mum process par ameters a re commonly unkn own [5], [13]. Us ually the o ptimu m proc ess parame ter s are identified in a trial and error m anner by experienced mo lding p ersonnel [6]. Moreove r, the d efinition of the opti mum process parameters i s considered as a multi-objective opti m ization, since several quality characteristic s of the tr ansfer molding pro cess ar e require d to be analy zed at the s ame t ime [4], [4 3]. Thus, obtaining t he opti mum process paramet ers is very laborio u s. At present, most of the work presented above, consider only one quality characteristic, whic h inv olves si ngle-objecti ve opti mization. As the multi-objective opti m i zation is challenging and very tim e consumin g, some authors stud ied simul ation me thods to investig ate the inf luence of process para meters on various quality characteristics at the same time and to define optimum p r ocess parameters [4], [ 6 ] , [ 1 4 ] , [ 4 4 ] , [ 45 ] . T o n g e t a l . u se d t h e process si mulation combined wit h Taguchi e xperiments, which all ow to determine the infl uence of significant parameters on the mold package quality and to deter mine the opti mum proces s parameters [14]. They investigated the i nfluence of fill time, mold temper ature, cla mping force, post-fill time on the wire sweep, incom p lete fill, f lash, voids and resin bleed. They conducted virtual experime nts wit h the process si mulation. Th e results showed that t he quality results can be improved by adjusting t he individual para meter, how ever, the interactions between the par a meters are not involved in Taguchi experiments and their effects are not considered on the package quality . Thus, the authors st ated t hat such kind approach c annot be helpful t o deal with the multi-obj ectiv e optimization problems [ 4]. The authors further studied the simulati on methods to generate proc ess models, which delivered t he optimu m process parameters of transfer molding process by imple menting the methods such as artificial neural networks, the DoE and multiple regression a nalysis [4]. T he res ults showed that the process models generated by using simulation methods could help to define the optimum process parame ters, however no validation experiments have b een conducted to verify the obt ained results. In addition, the author s noted t hat t he predicti on accuracy of the ge nerated pro cess mod els wa s not sufficient for a precise prediction and needs to be improved further. T hus, at present t he simulatio n methods are not sufficiently developed to solve th e complicated phenomenon of transfer molding process. Despite many efforts done in lite rature, complete understanding of the influence of the proce ss paramet ers o n the package quality and the definiti on of th e o pt imum process parameters a re still not achi eved. No syst ematic appro ach ha s been intr oduc ed to un derst and the influence of the process paramet ers o n th e package quality and to obtai n t he optimum pro cess para meters of the transf er molding process. Sinc e the comple x nature of the ther moset material, wh i ch undergoes chemical reaction d uring transfer molding process, plays a significant role on the packa ge quality as well, it is important to consider the pro perties of the EMC to achieve a g ood p ackage qu ality . Thus, to provide a conce ptual understanding, the properties and the characteristics of the EM C and their i mpact on the package quality will be explained in the foll owing section in detail. 2.4 Epoxy Molding Compounds Epox y mo lding compounds (E MCs) are mos tly used as encaps ulatio n mater ials due to their superior properties such as hi gh mechanical str ength, good thermo-mechan ical matching and good electrical properties, small shrinkage as well as good moisture resistance . Moreover, they possess good thermal stability; hence, they can withst and operation at elevated temp erature s. One of the important properties in terms o f moldability is that EMC has lo w melt viscosity befo re curin g and a short curing tim e [2]. To achiev e afore mentioned pr operties and to meet t he desired requi rements as a packaging material, various raw material ingredients are added to a n EMC. Some of the ing r e dients are fillers, cataly st or acceler ators, release a gent s, fla me r etarda nts, and c oloring ag ents. The ty pical ingredients in EMC are depic ted in Fig ure 2.6. 2 State of the Art 10 Figure 2.6: Ty pical ingre d ients i n an epoxy molding com pound wi th corresp onding composit ions [2] EMCs are based on epoxy resins, w hich are ther moset mater ials a nd c ured mostly with the polyaddition reactio n. Ep oxy resin is de fined as a ny mo l ecule having m o re t h a n o n e e p o x y g r o u p w h i c h h a s a capability to be conversed to u seful t hermoset form [46], [47]. T he chemical structure o f th e epoxy resin is illustrated in Figure 2.7. Figure 2. 7: Chemical struc ture of an epox y group Some of the co mmon e poxy resins sy ste ms are: novol ac epoxy resi ns, multifunctional epoxy resin, biphenyl epoxy resin, multiaromatic e poxy resin, orthocres ol novolac epoxy resin, an d cy cloaliphat ic epoxy resins [1], [48]. A mong all resin types, novolac r esin i s o n e o f t h e m o s t c o m m o n l y u s e d r e s i n t y p e due to their good moisture and chemi cal resistance, good adhesi o n to a substrate and h igh cross-linking density after curing [42] . For a cross-linking reaction of e poxy resin, a hardene r is nece ssary. With the help of hardeners, functional e poxies form a solid, three-di men sional network. Ali phatic amines, aromatic amines and phenol n ovolac r esins are some of the known hardene rs. Ph enol nov olac resins are mostly used as a hardener type since t hey have a good perfor man ce i n ter ms of heat and mois ture resistance, storage stability as well as curing property [2]. M oreover, phenol novolac resins offer an adva ntag e, w here th e n umber of th e r epeatin g unit s i n n ovolac s truct ure can be tailored to control the molecular weight distribution of EMC [2]. As illustrat ed in Figure 2.6, EMC co ntains high a mount of fille rs. High vo lume fraction of the filler particles is essential in EMC in order to r educe the water abso r p t i o n a n d t o i m p r o v e t h e t h e r m a l conductivity [1], [2], [49], [50]. W it h the help of th e filler particles, the coefficient of ther mal expansion ( C T E ) o f t h e E M C c a n b e l o w e r e d , w h i c h i s v e r y c r u c i a l i n t e r m s of package i ntegrity. The epoxy resins, which possess a high CTE and low thermal conductivity, can caus e s ome significant dimensio nal change in the package w ithout supplem e n tation of the filler particles. Moreover, the filler particles increase t he elastic modulus, and diminish E MC shrinkage d uring cu re [51]. It has been s hown that t he package warpage decreases with increasi ng the amount of filler particle s in the mol ding compo und [5 2]. On the other han d, t he amount of the particles in the EMC is very dete rmining in terms of the flowability of EMC during encapsulation proc ess as the visc osity of the EMC ca n increase with higher loading of filler particles [ 53]. Kiong et al. sho wed that by increasing the fill er c ontent from 87.5 % to 90 %, the wire sweep increased from an average of 2.5 % to 4.0 % [52]. Additio nally, the shape and the particle size of filler as well as the ty pe of filler can also influence fl owabi lity of the EM C, hence the perf orman ce of the elec tr onic packages [50] , [54], [55]. As filler particles usually silica, alumina or sili con nitride are used due to their high-thermal conductivity [2]. For higher vol ume fraction of fill er particles in the epoxy resins, mostly silica partic les are prefer red since t hey decrea se the warpage, yet enhance t he package reliability [42], [52], [56]. Usually spherical particles are u sed for higher filler content to ensure good flowabilit y of the EMC. To strengthen the interface between the epoxy resins and the filler particles, silane coupling a gent is added to the epoxy resins. The org anic f unctional groups in silane coupling 2 State of the Art 11 agent react with the epoxy resin and hardening agent and act as a bridge betwee n th e filler particles and the epoxy resin matrix [ 57]. Moreover, it promotes the adhesion b e tw een th e E MC an d lea d fr am e [2] , [12], [ 57]. To accel erate the curi ng speed of the r eaction and t o re duce t he cy cle time, cataly sts such as accel erator s a re u sed. Nitr ogen containi ng cat alys t, ami nes and imidazoles are some of the important catalysts types. In addition, some other additives are added to t he e p ox y r e si n su c h a s sy nt h e t ic w a x t o facilitate the part r emoval from the tool surface, carbon black as colorant, i on gette r to capture the ionic impurities such as Na + an d C l - , and flame retardant to satisfy the molded product inflammabil ity rating [2], [58]. After adding the additives to the epoxy resins, all raw materials are blended and subsequently kneaded by a pplyi ng heat a nd co oled d own in to a she et sh ape [2] . Sub seq ue ntly , they ar e pul ve rized a nd pelletized into a pellet shape in desired dimensions, which is then used in the transfer mo lding process for the encapsulation of semiconduct or devices. As the kneading proces s is co nducted und er heat, t he cross-lin king r eaction alre ady be gins. However , as the degree o f cure of EMC is only slightl y influenced by the kneadi ng pr ocess , it does not incr ease the viscosity of the EMC significantly. On th e other hand, after the preparation of the EM C , the pellets must be stored in a cold environment such as freezer at around -20 °C prior to t he molding process to prevent any possi ble reaction in EMC pellet, where the resin and hardene r are pressed together. Considering many ingredients i ncluded in to the ep oxy resins, an y possible variations in the E MC properti es might inf luence the p ackage quality. For instance, s ince the ele ctronic packages are built by comp osing of dissim ilar mate ria ls, CTE mism atch betw een the com ponents can cause some defects in the package such as warpage or delamination [16], [59 ]. In addi tion to that, a s the power modules can operate at high temperatures especially in automotive applicati ons, all the components in the packa ge should withst and the operation temperature. Currently the limit for the EMC i s around 175 °C and for the high te mperature a pplications exceeding 180 °C new formulat ions of the EMC a re necessar y fo r the thermal stability at elevated te mp eratures [60], [61], [62]. Mo reover, the viscosity of the EMC also play s a sig nificant role on t he packag e quality, especially for the l arge power mod ules where t he proces s control is challenging. The variations in the viscosity of the EMC can cause some severe defects in the package such as wire sweep, voiding, w hich may lead to failure mechanis ms. T hus, the ch aracteristics of the EMC h ave a det ermining i mpact on the end pac kage quality . One of the crucial problems regarding the EM C, w hich is extensi vely studied in literature, is the impact of humidity co ntent of cured EMC on the package quality [63]–[6 6]. Epoxy resins have a hydrophili c structure and they can abso rb hu midity easily from the envir onm ent. W ater, which is a polar molecule, has a capabil ity of hydrogen b ond ing with other polar species s uch as hy droxyl s and ami nes in the epoxies [67], [68]. It is suggested that in poly meric materials the water molecule s can be eithe r present i n f r e e v o l u m e o f t h e p o l y m e r o r t h e y c a n b e b o n d e d v i a h y d r o g e n bo nds to the polymer c hains [1], [69], [70]. The w ater molecule s can act as pla sticizers or craz ing ag ents in epoxides [67]. Moisture changes the thermo-mech anic al p ropertie s of the EMC, reduces modul us, s tr e ng th , d ec re a se s t he gl as s t ra ns it i on temperat ure (T g ) and it can additiona lly cause the swelling [53], [63], [71], [72]. T hus, the abs orbed humidity in the EMC can also lead t o i nternal stresses in the e lectronic packages [73], [ 74]. Popcorn cracking due to the moisture absorption during board level a sse mbly (assembly flow soldering process) is a well-known phen omenon [72], [75]–[78]. T herefore, mo isture absorption becomes one of the maj or reliability issues in the el ectronic packages a nd the moisture mechanisms in the package as well as influe nce of moistu re abso rption dur ing stor age or the serv ice are extensively studie d by many researchers [63], [64], [69], [79], [80]. In addition to that, the hu midity absorption of t he mold comp ound preforms i n uncured st ate before t he molding process can be als o very critical durin g encapsulatio n process for the manufactu rers. E special ly, in E ast Asian countr i e s , w h i c h h a v e a h i g h a t m o s p h e r i c humidity level, the EM C pellets are s ubjected to a highly humi d environment during manufacturing i n case they are not stored u nder dry vacuu m, which may induce var iations in t he EMC properties [81], [82]. The absorbed humid ity can influence the rheological prope rties of EMC, the spiral flow length, which is a typical indicati on of the rheological behavior of th e resin e ncapsula nt, so it can a ffect the 2 State of the Art 12 moldability [5], [82 ] . E xisting humidity in EMC can als o affect the curing pr operties of the molding compo und, and the thermo- mechanical properties of the cured material [72]. Absorb ed moisture in the EMC pellets can introduce voids into the pac kage, y et diminish th e qual ity of t he fi nal pac kage [5] , [83] . Although humidity ab sorption into the EMC preforms is a critica l issue for encap sulati on process, only few studies have addressed the impact of humidity of EMC prior to the molding process . T.Y. Lin et al. investigated the influence of the moist ure content on the w arpa ge [8 4]. They st ored the pelle ts of EMC for 0 h, 12 h, 24 h and 72 h in a clean room at room temperatur e with a relati ve humidity (RH) control between 35 % to 55 % RH and subseq uently molded the pack ages wi th the preconditioned pellets i n transfer molding pro cess. The y observed that increasing the moisture content causes an incre ment in t he shrinkage and also influ ences the warpage. They concluded that the humidity control in clean room environment is crucial to maintain high yield in mold ing proces s as well as to prevent war page rejects in th e S M T p ro ce ss . Li n e t al . e mp ha si z ed th e i m po rt a nce o f t he measu reme nt of t he moist ure upt ake in the EMC packag e prior to molding and compared the meth ods to me asure the moi sture content of the pellets [82]. Karl-Fischer Titra tion is given as a promising te st method for measuring the moisture content in the EMC pelle ts, an d they i nvestigated dy namic scann ing calori metry (DSC) as an alternative method [82]. They found that with DSC the change in the EMC pro perties due to humidity uptake can be detected, where t he area under the endothermic peak in DSC c urve is d ecreas ed, and the T g o f u n c u r e d resin shifts to lower temperature with increasing moisture con t ent. However, the impact of the abs orbed humidity in the EMC on the packa ge quality was not addressed in this work. In addition to humidity absorption, extended st orage duration o r floor life can also influence the EMC characteristics. With t he prolon ged st orage duration, the cross - linki ng d egr ee bef ore th e mol ding proc es s can incr ease and the gel ti me of EMC can de crease [85]. T he inc rease in the cross-linking degree or t he reduction in gel time can be critical during molding p r ocess by caus ing some severe defects such as wir e sweep or i ncomplete filling. The influence of floor life of the EMC on its gel time, spiral flow and on the w ire sweep we r e investig ated by Pen apung a et al. by var y ing the flo or ti me f ro m 0 to 6 0 h ours wi th steps of 12 hours [85]. It was found that the w ire sweep of wire bonds increases b y prolonging the fl oor life of EMC in all packages. The gel time does no t de crease sig nificantly w hereas the s piral flow length deteriorates with prol onged floor ti me. Spiral flow l ength is u sual ly defined by measur ing the dist ance of the flow of compound in a specific mold tool under specific mold process par ameters [24], [8 6]. The correlatio n be tween the flow cha racteris tics of EMC such as spi ral flow length and the gel time on the failure mechanisms are assessed by some other authors [21], [22 ]. Tanaka et al. inves tigated the relationship between the spiral flow length and the inner void formation by produci ng eight different molding compounds, w hich had different filler contents, raw res in viscosities, cataly st concentrations and ratio of the spherical filler particles [21]. However, no c lear r elationship is obs erved bet ween th e molding co mpounds having different sp iral flow leng ths and the numb er of inner voids in the package [21]. This is explained by the non-Newtonian viscosi ty behavior of the thermoset material, where the material viscosity depends on the shear r ate. Nonetheless, in g eneral it is suggested that resi n encapsulant with high viscosity offers some a dvantag es in terms of reducing th e voids in the package [21], [22]. On the other hand, it is important to consider that since the visc osity has a direct impact on the wire s weep, the EMC ha ving higher vis cosity can ca use also mor e severe wire sweep [8 7]. In a ddit ion t o the pr ol onged stor age d ura tion, an other kn own pr oblem in m anufac tur ing is the variat ion in EMC propertie s between differe nt batches [58], [86]. Studies emp hasized that different batches of the EMC can hav e different T g , different pre-cured levels, or different chemo-rheological ch aracteristics [34], [88] . Ho wever , no sy ste mati c inve stig atio n has be en r epor ted so far to understand the influence of the possible batch differenc es on the package quality . Another important iss ue is the transportatio n of the EMC from s uppliers to the ma nuf acturer s. Duri ng shipping of the EMC additional dry ice is peri odically added t o th e stora ge b oxes, but t he tra nspor t c hain may not be alway s continu ous, can be brok en whic h can r aise the temperature of EMC pellets during the shi pping. This may increase cros s-linking in EMC and t hus t he visc osity. When the E MC pellets arrive at the manuf acturer, there is u sually no quick wa y to de tect this situation about the prior curing 2 State of the Art 13 before the molding process. The only possibility to examine pos sible changes in EM C is in the laboratories with analy tical methods outside of t he producti on line. Evidently, such problems during transp ort can cause variations in th e properties of EMC such as reducing the shelf life in which the m anu fa ct ur er m a y n ot be aw ar e a t f ir st si gh t a nd ha ve n o p oss ib ilities to find out easily during transfer molding pro cess. Therefor e, those afor ementioned variations in the cha racteristi cs of EMC can y ield poor package quality by inducing voids, causing war page or wire sweep. Apart fro m th at, such varia tions in the EMC characteristic s can reduce the flexural strength of the p ackage , which p repares a suitable basis further in service or in application for increasing m o isture absorption in the package and endanger the reliability of t he package as well [25], [58]. Therefore, t he initial chara cte ris tics of t he E MC n ot o nly play a significant r ole on the f inal packag e qualit y, but also in term s of reliabilit y of the molded package. Yet, a systematic a pproach is required to under stand the influence o f the variations in the EMC characteristics prior to molding process on t he final packag e quality. In addit i o n t o t h a t , t h e b e s t p o s s i b l e w a y t o determine any possible variations in the material characteristi cs is seen in examining such changes directly during the molding process, before those variations cause sev ere problems during production. The infor mation about the viscosity of the EMC and the te mperat ure directly from the mol d cavity can be very useful to an alyze the c ure behav ior of the E MC and t he interaction s of process parameters with the material properties during t he encapsulation process in ord er t o decrea se possible wir e sweep is sues and void f ormation. In that m anner, the online process monitoring tech niques can be helpful to highligh t the complex phenomenon of the curing reacti on of EMC during mol din g process and to understand their influence on the package quality . Hence, different online monit o ring methods wi ll be addressed in t he following section. 2.5 Online Monitori ng Methods and Process Optimization In t he pre vi ous sec tio ns, t he i nflue nce of visc osity and cur e b ehavior of the EMC on packa ge q uality during transfer m ol ding pro cess, as well as the dependency of E M C b e h a vi o r o n t he p r o c es s p a r a me t e r s are descri bed in d etail. It is emphasized that EMC, which u nder goes different chemica l reactions during molding has a vital influence on the perfor mance of the pack age . Theref ore, monitori ng the cure stat e of the EMC during moldi ng with defined set proces s para meters i s a key issue to i mprove package quality . In that ma nner, many studies have been already carried out to study the curing mechanism s of EMC and to model the cure behavi or of the EMC with different me tho ds, such as rheo metery [89]–[93], DSC [90], [94]–[96], Raman spectroscopy [97] and Fouri er-transf orm infrared spect roscopy (FTIR) [98]–[101]. However, such methods can only deliver i nformation under laborato ry environme nt and not in-situ or, in other words, under real time process conditions. Real time implies that the measurem e nt s are perfor med on a time scale in whi ch any chang e in the pr oces s conditi ons is possible before the measurem ents are completed [102]. T h e r e f o r e , i n p r o c e s s c u r e m o n i t o r i n g i n r e a l t i m e i s o f u t m o s t importance to gather more infor mation from t he process conditio ns in the c avity and to monitor the chang es in physic al state of m ateria l du ring the progress of th e cure reaction. Additionally, the material characteristic s ca n have variations such as viscosity , batch to batch di fference whic h is already address ed in Section 2.3 , thus in-sit u real time monitoring not only help s to monitor the cure mec hanisms of epoxy resins but also ensures the pro cess stabilit y in order to achie ve stable package quality [103], [104]. Many different metho ds a re investigated for monitoring the cure process such as fiber optic sensors [105]–[107], pressure and t emperature sens ors (thermocouple s) [ 108], [109], ultrasonic methods [110], [111] and dielectric analy sis (DEA) [103], [ 104], [112]–[116]. With fiber optic sensors, the monitoring of the resin is possible by refracti ng t he infr ared s ignal whe n the resin gets in c ontact with the sensor [117]. However, the sensitivity of the method for onli ne monito ring of the cure reaction of poly mers is not very high since the o ptical properties of the polymers do n ot vary much during the curing process [118]. Thermocouple sensors deliver information about the temperature of the media in the tool. The temperature drops when the resin, which is colder than the tool surface, arrives at the sensor and indi cates the arrival of the resin flow front. As the reaction progresses , the te mperatur e increas es due t o the hea t 2 State of the Art 14 release durin g t he exothermic curin g r eaction of the epoxy resi ns. These sensors are low-cost, durable and they do not influen ce the flow o f the resin [108]. Thus, th e y a r e s u i t a b l e t o c o n t r o l a n d a d j u s t t h e temperat ure i n the pr ocess. P ressure transducer s can a lso be us ed for monitoring the process. When the cavity of the t ool is filled with the resin, the diaphragm of t he pressure transducer deflects. This strain- gage, which is a ttached to the d i aphragm o f the p res sure sensor , causes a change of electrical r esistance, which is proportional to the pre s s u r e [ 1 1 7 ] . T h e p r e s s u r e s e n s o rs are hel pful for measuri ng the cavity pressure, which mostly deviates from th e pressur e set at t he ma chine. Thus, they are also very valuable to monitor and contro l the cavity pressure. Those mentioned met hods, however, ca n only be useful i n controlling t he process conditions but not in monitorin g the cu re r eact ion of t he resi n. Ultrasonic monitoring is o ne of the common technique b oth f or m onitoring resin cure an d t he f low fr ont of the resin. Piezoelectri c element s gene rate an acoustic wave, which propag ates through the material with a specific v elocity . When any irregularities or boundaries exi st on the way , so me of t he si gna ls ar e reflected and some travel through to the second sens or, which c ollects t he signal. Thus, ultrasonic measurement usually requires two sensors; one t o ge nerate th e a coustic pul se, the other to c ollect the signals, which s hould be mounted on opposite side of the tool [ 119]. Ther e i s also a direc t reflecti on method which requires only one sensor for transmitting and coll ecting the sign al; however, some disturbing echoes can be recorde d in this cas e which ca n cause improper measure ment [110]. The transmitted and reflected waves are collected by so-called ultr asonic tr ansducers. The ultrasonic sound speed is calculated based o n the distance and the time informat ion. When the resin arri ves t o the sensor, it leads to a variation in th e velocity and the attenuation of th e soun d wave [11 7]. T wo t ypes of information can be derived fro m the ultrasonic measurements: so und velocity and attenuation. The correlation of the gathered information from ultrasonic monitoring to th e progress of t he cure reaction of the EMC are studied by numer ous authors [11 0], [111], [119]. The c hange in the so und velocity is associat ed wit h the change in the viscosity and t he cure stat e. When the vi scosity of the material decreases, t he ac oustic w ave vel ocity decreases as well. With t he propagati on of the cure re action, lar ger molecu lar structure is formed irreversibly, the degree of cure increases, thereby decr eases the diffusivity. Due to the r educed diffusivity , the configurational motion of t he mol ecules inc reases, w hich raises the acoustic w ave v elocity [120], [121]. R ath et al. investigate d d iffer ent types of molding compo unds a nd the impacts of vario us parameter s such as fiber filler volume o f molding comp ounds, moisture content , storage duration and amount of harden er on the sound v e locity w ith ultrasonic cure monitoring [121 ]. It was stated that each materia l has a specific sound velocity lik e fingerprint d epending on their che mical composition and reactivity . To understand t he impact of storage duration on the epoxy r esins, the epox y molding compou nds were stored for 3 hours and 24 hours at 90 °C to gener ate t hermal degra dation i n the properties and measured with the ultrasonic cure monitoring in co mpression molding. T he res ults showed that th e sound velocity and the m i nimum of sound velocit y increased for th e stored materia ls in comparison to the fresh m aterials. This indicates that th e resi n and hardener already started curing under thermal load duri ng storage time, w hich leaded to an i ncreas e i n sto rage m o dulus, a nd thus o n the sound velocity of the m aterial. Th e values at the end of rea ction als o i n d i c a t e d t h a t t h e s a m p l e s h a d a c e r t a i n amount of cross-linking during the storage ti m e. In addition, t he samples were stor ed in a humidity cabinet to observe the impact of humi dity on the sound velocity of the material. An increased amount of water in epoxy resins caused a remarkable decrease on the mi nimum sound velocity. It was emphasized t hat a bsorbed water molecules in t he resi n do not di sappear, stay entrapped and lead to a micro-por ous structure in the materi al, which causes crack or m oisture induced mechanic al da mag e. T h i s c a n b e o b s e r v e d w i t h t h e u ltrasonic mon itoring, where th e absor bed water acts as plasti cizer and decreases t he elastic modul i, and thus decreases t he sound velo city [121]. Another su itable method for in-situ cure monitoring is DEA. Wit h DE A, the capacit ance of the me dia between the plates and conductance in accordance to temperature , time and frequency are measured [122], [123]. DEA delivers infor mation such as degree of c ure, change in ion viscosity in real-time during the process. DEA is a suitable method to characterize th e poly meric materials to obtain information about the t hermal, rheol ogical and dielec tric infor m a t i o n f o r a w i d e r a n g e o f m a t e r i a l s . I n 2 State of the Art 15 addition, it c orrelates well with t he chemo-r heologi cal pr opert ies of the resin durin g poly merization [122 ], [124], [125]. DEA is usual ly compared with the ultrasonic methods in ter ms of sensit ivity of monit orin g the cur e reaction of the resins. The advantages a nd disadvant ages of the se two methods are frequently discussed [126], [127]. The ad vantages of the ultrasonic cure monitoring ar e stated as that t he senso rs ca n be implemented in the tool without having any contact with the mat e r i a l , a n d h e n c e t h e s e n s o r s l e a v e n o m a r k s o n t h e m o l d e d p a r t s . O n t h e o t h e r h a n d , s p e c i a l a t t e n t i o n n e e d s t o b e g i v e n d u r i n g m o l d t o o l constr uction t o a chieve a goo d co ntact between the piezoelectr i c element of the ultrasonic sensor and the tool. Furthermore, in ultrasonic measurement, perpendicular ity of the sensor to th e sample geometry is very determining sinc e to have a correct signal, the wav e sh ould meet perpendicular ly with the surface boundary, otherwise it will change the direction. T hus, the too l must be pr ecisely machi ned to achiev e this necessary perpendicu larity for the meas uremen t tech nique [ 119], [120]. In addition, for the ultrasonic measurement, the part m u st h a v e a si g n i fi ca n t t h i ck n ess (at least 2 mm), and it should be of homo geneous ma terial [126]. Non- ho m ogeneous par ts c an cause spu ri ous reflection, which can prevent successful measurements. This fe ature can make it difficult to use the ultrasonic method for electronic packages as they involve many different components inside. Mor e over, for an accurate measurement the part thicknes s needs to be measured. If the part thickness changes during process ing, it may also prevent an accu rate m easuremen t [126]. Compared to the ultrasonic technique, DEA is a highly sensitive meth od d etecting th e small var iations in the materia l characteristics, especi ally at molec ular level [128]. M oreover, DEA is the most sensitive method of measuring especially the local motions of the polar m olecule chains due to the fact that polar molecules are strongly influenced by the electrical sti m ulation [129]. Further more, DEA is also found to be extreme ly sensitive to t he end of the cure reaction [130] , [131], [132]. An other advantage of t he DEA is t hat the cure state can b e measured simultaneously with multiple sensors and at various positions on the sam ple [133]. DEA sensors are available in many different f orms i.e. implanta ble o r o ne-way dispo sabl e s ens ors whic h can be e mbedded into the measured material. Thus, the ability t o use DEA method in many different applications makes it a suita ble method in diverse online monit oring app lications [126]. In addition, DEA results show good correlatio n wit h ot her a nalytical methods such as DSC, Raman spectroscopy and rheology [103], [134], [135]. Large amount o f information a bout the rheological state of the epoxy - base d p oly mers d urin g poly meri zation can be deri ved fr om DE A. A ccordin gly, amon g other online monitoring met hods, DE A i s na med the most pro mising method to m on itor the cure state o f thermosetting materials [103], [136]. Therefor e, based on th e given ov erview, as the most promising o nline m onitoring method, DEA can be a suitable selection for i n-s itu cure m onitoring o f EMC in tran sf er moldi ng proces s. Thu s, t he measuremen t principle of DEA method will be h ighli ghted in more d etail in following secti on. Die lectric Anal ysis DEA can be used for pr ocess control, wh ere cure reacti on of t he pol y mers is measured in-situ continuously in process. In a DEA measure ment, the i on viscosit y of t he materi al is measur ed, w hich originates from io ns and the dipoles movements, which exist as impu rities like charged ions such as sodium and chloride ions [137], [ 1 3 8 ] . A D E A s e n s o r m e a s u r e s t h e a l t e r a t i o n i n t h e i o n i c m o b i l i ty of the samples in correlation to the curing time. According to Sen turia and Sheppard [139], during the poly m e r manufacturi ng dielectric response is a funct ion of the ionic conductivity , which is caused by the impurities and the components. Althoug h the concentration o f ions in the EMC is in ppm range, it has been shown that even an amount b elow 1 ppm i s suffici ent to cause a signifi cant c hange in the ioni c conductivity [139] –[142]. In DEA measurements, the EMC sample is in direct contact with t he sensor. A thermosetting res in which is a dielectric materi al for ms a capacitor w hen placed bet ween the electr odes [ 136]. I ons and di poles have a random orientation prior t o appl ication of an electrical field [13 8]. A sinus oid al vo ltage (AC 2 State of the Art 16 signal of freque ncy) is applied on one electrode and the resulting current is rec eived by the second electrode along with the phas e s hift between the voltage and cu rrent [143]. When the sinusoidal v oltag e is applied, the electrical f ield is creat ed in th e sampl e. The sample becomes electrically polarized , the dipoles orie nt with the electrical field and the cha rge carrier s in polymers such as ions, electrons, charged atoms or charged molecules and impurities are forced to move i n the direction of the electrode with opposite char ge [139], [1 43]. This r esults in a phase shift in the response between the voltage and current which is a functi on of ion and dipole mobility [130], [137]. Fi g u r e 2 . 8 d e p i c t s a n e x c i t a t i o n a n d a response bet ween two e lectrodes and the behavior of dipoles and io ns betwee n two electrodes. Dielectric measuremen t can b e performed in a large range of frequencies fr om 1 mHz to 100 kHz [144]. Figure 2.8: Ex citation a nd response of the polymeric material b etwe en two ele ctrode s (left ), ori ent ation of dipoles and charge d ions i n a po lym er due to an external elec tr ical field (right) [ 130], [143] When the exact distance between the electrodes , freque ncy of th e excitation, a nd the exact area of the electrodes are known, the change in the phase shif t an d the amp litud e can be converted i nto t wo fundamental dielectric prop er ties: dielectric per mittiv ity έ an d dielectric loss factor ε" [ 143]. The phase shift can be correlated with the dielect ric los s fact or ε", whe reas t he cha nge i n ampl itu de ca n be correlated with dielectric permittivity έ [143]. Dielectric per mittivity indicates the number of dipo lar groups in the resin and is a measure of the polarizati on of the m edium per applied electric field [141]. Dielectric loss factor is as sociated wit h the conducti ve nature of a material and is a measure of the total energy lost due to the work d one while alig ning dipoles and mov ing ions in a material [128], [141]. Predominantly, permittivity chan ges due to the dipole motion du ring a ty pical poly m erization. Th e dielectric los s factor is affected by both dipole moti on and io nic con ductivity. During poly merization, the contri bution of the dipole motion on the loss factor is rel atively small, thus the loss factor is mainly dominated by the ionic conducti vity [126]. As the i onic c onduct ivity indicates the ion mobility in the samples, it is in v ersely proportional t o t he visco sity before gelation and the rigidity after gelati on [1 26]. Dielectri c lo ss factor ε " i s d efined as shown in Equ ation ( 1) w her e R p is equivalent A C par allel resist ance, d is the dista nce betwee n the electrod es, A is the electrode plate area, f is the measure ment freq uency and ε 0 is the permittivity of vacuum (8 .854 pF/m) or also nam ed as di electric constant [ 144]. " 2 (1) The rel ative permittivity can b e calculated as following (Equat ion 2) where C p i s the parall el capacitance , C sub is the substrate capacitanc e. έ (2) Ionic co nductivity, σ is proportional to the diel ectric l oss fa ctor , ε" and is a reciprocal value of the ion viscosity . Equat ion (3) re pres ents t he ca lcul atio n of the i on vi scosi ty , . Ion viscosity is the most relevant paramet er in ter ms of the cure r eaction of th e EMC. 2 State of the Art 17 1 1 " 2 (3) T h e d i s s i p a t i o n f a c t o r , o r l o s s t a n g e n t of a m e d i u m , t a n ( δ ) i s defin ed as the ratio of the die lect ric lo ss factor ε" to the dielectri c permittivity έ (Eq uation 4). tan " έ (4) The cha nges in the dielectri c pro perties of the resi n can b e co rrelated with the variations of che mical and rheol ogical behavior of the ep oxy r esin during poly merizati o n p r o c e s s [ 1 0 4 ] , [ 1 4 5 ] . D u r i n g poly m e rization of t he thermoset r esin i n th e transfer molding p rocess, the resin un dergoes differen t transitions. At the beginning o f the process, when the epoxy re sin pellets c ome in to contact with the hot wall of the mold tool, the re sin starts melting a nd liquidizes. In DEA meas urements, the ionic conductivity indicates t he ease of the m o vements of the ionic i mpurities in r esin, thus d ir ectly correlat ed w it h th e v i sc o s it y [ 1 2 6 ], [ 13 7 ]. F or e p ox y re si n s, c hl o ri de an d sodium ions are considered to domi nate the i onic conductivity since their concentration remains consta nt dur ing t he po lymeri zati on rea cti on [122 ], [146], [147 ]. Figure 2.9 shows the DEA curve during the poly m erization reactio n of EMC in transfer molding process. As se en in Figure 2.9, the moment, wh ere the cond uctivity reaches its maximum matches with the mom ent where th e viscosity has the low est point [118], [148], [149]. Figure 2.9 : Perm it tivity and loss factor with respect to time ( le ft), and logarithm ic ion conductivi ty as w ell as logarit hmic ion viscosity with respect to time ( right) Following the minimum vi scosity, t he res in poly merization conti nues, larger molecules are fo rmed and another important stage, where significant transformations in t he phy sical properties of the thermosetting polymer occur, is achieved, nam ely gelation. In g elation, the system chang es its state and resin transfo r ms from a liquid into a covalently cro ss-linked g el [150]. Gel point indicate s the point that all m onomers are attached t o the network by a t least one chemic al bond, and three dimensional network is formed [96], [151]. Gel po i nt is a criti cal point in polymer process ing, since after epoxy r esin reaches this point, t he flowability of the resin is reduced dramaticall y. Large efforts have b een done to define the gelation point by using the DEA method [122], [148], [152]–[155]. Maistros et al. defined the point for initiati on of the gelation as the inflection po int in t he d rop of the logarithmic ion conductivity [149]. Inflection p oint is defined as the time, w here the cur e reactio n be gi ns t o s low do wn [ 156] . T he gel atio n point in t he DEA curve is described as a point of inflection wh ich is d 2 (LIC )/dt 2 =0 where LIC is the logarithm of the ionic conductivity . Mcllhagger et al. correlat ed this defined onset of gelation point fo r composite m aterials from DEA meas urements with gel point obtain ed fr om th e dy namic mechani cal ana lysis (DM A) meas uremen ts [122]. Th ey have foun d that the gel point obtained in DEA with a point 0 30 60 90 120 150 180 210 240 0 2000 4000 6000 8000 10000 Permittivity Time [s] Permit tivity 0 20000 40000 60000 80000 100000 Loss factor Loss factor 0 50 100 150 2 00 -10 -9 -8 -7 -6 Log. ion con ductivity [S /cm] Time [s] Ion con ductivity 6 7 8 9 10 Ion v iscosi ty Log. ion v iscos ity [O hm*cm] 2 State of the Art 18 of inflection i s v ery close t o t he gel poi nt d etermined with th e DMA measure ments, where the tan ( δ ) is equal to 1 is taken as the gel point. Slight variations between gel poi nts obt aine d f rom t wo meas ure ments were observed, w hich is attributed t o the small variat ions in t he temperat ure-time profile between the measurements. However, it should be pointed out that the defini tion of the gel point with the DEA is difficult to generalize for all chemical systems, since the exp eriments were based on specific epoxy systems, where the ionic conductivity was dominated by the spec ies of that certain system. Thus, to meet a univer sal conclusion for identification of the c omplex p henomenon of gelation with DEA, m ore research is required [131], [150]. With the propagation of the c uring reaction, 3D net work of the poly mer forms, cross lin king degree increases, th us cau sing an increase i n T g [ 157]. T g indicates the temperature required to change the molecules from glassy to rubbery state. The logarithmic ion vis c o s i t y c u r v e i s a l s o f o u n d i n a g o o d correlation with the rate of change i n T g an d D EA is taken a s se nsi tive met ho d to d et ect t he cha nge s in T g [ 132], [13 8]. Another i mportant point in p olymerization reacti on is vitrification. V itrification is defined as the point where the p olymer ch ains get cl osely packe d, t he network becomes tighter due to the cross-lin king and there is no suffi cient volume for the io n ic motions in the structure [130], [158]. During vitrification, the system tra nsforms f rom a gel into a g lass, and vitrification ends when the T g of the material reaches t he isother mal cure t emperat ure [1 22], [15 0]. Accor din g to t he inf or mati on given above , so me cr uci al inf or mat ion about the poly merization reaction of the resi n can be obtai ned in-s itu fr om the DEA suc h a s react ion onset, processing time of the resin, min imum ion viscos ity, ti me at m inimum ion viscosit y , maxim um i o n viscosity, and the reaction rate. During th e cu ring pr ocess, t he i on v iscos ity of the poly mers c a n increase in a range of several decades, thus d ata for ion viscosity is represented usually in a logarit hmic scale [ 159]. The slope of the logarithmic ion viscosity versus ti me curve correlates wit h the reaction rate of curing. Higher temperat ure l eads to a high er reacti on rate, he nce faste r curin g [1 52]. Moreover, the differences between the max imum and minimum viscosity can deliver infor mation ab out t he degree of cure of the thermose t material [160]. A typical DEA curv e, which is taken in-situ dur ing poly merization of the E MC d uring the transfer molding process, and the characteris tic informatio n , w h i c h c a n b e d e r i v e d f r o m t h e D E A signal, are depicted in Figure 2.10. Figure 2.10: Ion viscos ity with r espect to cur i ng time in tran s fer m olding process and the important cha racteristic inform ation derive d from the DEA signal There are diff erent types of D EA sensors available i n various c onfigurations, which make the m suitable for different applications such as monitoring the curing reacti on for dental filling, composite materials for aircraft or m ilitary applica tions [122], [1 61], [162 ]. Some of the DEA sens or types are parallel-plat e sensors, disposable one way sensors or i mplantable sensors. Dis posable one way sensors and implantable s ensors require one single s urface with comb struct ures or inter digitated electr odes, whereas 2 State of the Art 19 the parallel-pl ate sensors must be implemented on both si de of the tool. Disposable sensors have a comb electrode structure an d they measure t he penetration depth of t he alt ernating electric field of the sensor which is the distance between th e electr odes [130], [162]. P ara llel plate sensors allow the measurement through bulk material, however, the dimensional ch ange of the r esin matrix during polymerization, w h i c h i s t y p i c a l f o r m o s t o f t h e r e s i n s , c a n c a u s e s o m e d i f f i c u lties to keep the spacing bet ween the electrodes. Thus, it can be diffi cult to main tain the calibrati on of the parallel-plates and t his can lead to artifacts duri ng measurement [139]. One of the key advan tages o f the comb electr odes over the parall el- plate configuratio n is that the calibration of the i nterdigitat ed electrodes is independent of the temperature and other changes, which leads to more reproduci ble measurements [13 9], [163]. Mod ern dielectric measurement s etups, n am ely m onotrode sen sors, employ two interdigitated electrodes, which enable one sided measurement without employ ing two sensors [141 ]. With the monotrode sensor, it i s possible to measure the die lectric const ant of sampl es even for t h o s e w h i c h h a v e a t h i c k n e s s o f a f e w millimeters [159], [164 ], [ 165]. Therefore, with the help o f the DEA sensors, detaile d infor m ati on a bout the molding compounds can be determined during the polymeriz ation regarding any possible cha nge in the rheolo gical state of the EM C. Moreover, the actual cure state of the poly mers during processi ng, the optimum molding cy cle time for the required curing of the poly mers can be detected online whic h can help to increase the productivity and mold ed part q uality [86]. Due to such advantages, as already mentioned, DEA finds a pplica tion in various processes such as dent al application, composites manufacturing for aircraft industry or wind energy applications. Surp risingly, in spite of its numerous advantages in terms of process monitor ing, there is only little work done on using the DEA for transf er molding process charact erization in the field of electronic packages . One of the r are repor ts is pr ovided by Chen et al. wher e DEA wa s us ed as an in-situ monitoring metho d to observe the cure state of the plastic encapsulate d EMC in tra ns fer moldi ng process [166]. They implemented at six locati ons the reusable, monotr ode DEA sensor s with a diam eter of 6 mm. The measurem ents were perform ed in a co nventional single p ot mold t ransfer molding process. Influence of the process parameters such as m old temperature, transfer press ur e, preh eat t ime o n the ion v iscosi ty of EMC were investigated with DEA. They conducted statistical anal ysis and selecte d full fa ctorial analy sis with three par ameter set s i n three different le vels. Th e result s showed that the minimum ion viscosity was strongly i nfluence d es pecially by the mold tem perature. Wit h increasing mold temperature from 155 °C to 195 °C, the minimum ion viscosity decreased. On the o th er han d, tra nsfe r p ressur e and p rehe at time demonstrated very little effe ct on the minimum ion vis cosi ty. All in all, although not many work on the topic of implementing the DEA for t ransfer molding process analy sis is published, it is possible to conclude that by given advantages DEA can be a suitable online monitoring method for in-situ cure m onitoring of EMC in trans fe r m oldi ng process for encapsulation of electroni c pac kages. 2.6 Statistical Analysis In this section, methods o f statistical analy sis, also known as D e s i g n o f E x p e r i m e n t s ( D o E ) , a r e introduced. In man y technical ar eas, ex periments are perfor med to examine the chara cteristics of process, and to i mprove a nd optimize the operations. DoE is a m ethod to plan experiments and to analy ze the results s ystematically [167]. The aim of a DoE is to o btain knowledge from experi mental i n v e s t i g a t i o n s a n d d e t e r m i n e t h e c o r r e l a t i o n s b e t w e e n i n p u t a n d output para meters with least possible effort, time and costs. Thus, for this work statistical analysi s is applied to design ex periments and to evaluate the r esults sy stematically as well as t o describe the relati onship between process paramet ers, material characteristics and pac kage quality in a model. Hence, detailed description o f the statistical analy sis methods is given in th is section. The major aspects on d e s i g n i n g t h e e x p e r i m e n t s a r e highlighted. The essential step s t o a c h i e v e a p r o c e s s m o d e l w i t h the help of the statistical analy sis are explaine d in detail. 2 State of the Art 20 Definition of Models in Statistical Analysis The goal of statistical a nalysis is to establish mo dels, whi ch deliver the relations hip between the in put paramet ers and the output para meters. I n Fig ure 2. 11 a schemati c descripti on of a sy stem for a process is represented with in fluencing q uantities, target quantities and e rrors. Figure 2. 11: A schem atic description of a system, adopted fr o m [168] As s hown in Figure 2.1 1, the syst em involves the input parameters, which are the influencing qu antities (factors), and the output p aram eters, which are the target quantities (res ponses). As an input in the syste m, t he fa ctors are chosen in w hich their variati on affects the responses, hence they help to improve the performance of a process [167]. In almost all operations, t here are known and unknown disturbance factors or noises, which i nfluence the process [168], [169]. Th e disturbance f actors cannot be easily controlled, thus they must be kept as constant as possible [170 ]. Therein , the aim is to determ ine the relationship between the input para meters and the target quanti ties, which can b e quantified despite of disturbances in the sy stem [168]. T o determine t he correlations b e t w e e n t h e i n f l u e n c i n g f a c t o r s a n d target quantities and to des cribe the relat ionshi p mat hematica l ly in a mo del, regression a nalysis i s used in statistical analy sis. When the responses or the target quant ities are denominated as y , the influenci ng factors are c hosen a s x 1 , x 2 …. x p and th e measurement error as well as the noises are considered to ge t he r as errors, e , the relationshi p in a system between the influencing quantiti es and target quantities can be described in a model with a regression fu nction as y = f(x 1, x 2 ,…x p ) + e . One o f the most i m portant steps to achieve a go od m o del f or thi s system is to list the influencing factors and the target quantities [170]. Definition of the system is ve ry crucial in ter ms of obtaining a go od correlation between t he i nfluenc ing factors and tar get quantiti es. The selection of the infl uencing and target quantities determines the success of the experiments, an d thus the q uality of the generated models. I f m a n y p a r a m e t e r s a r e i n c l u d e d i n t o t h e s y s t e m , t h e i n f l u e n c e s of the input parameters on the target quantities cannot be deter mined ea sily due to the participation of too many factors, which may prevent a clear correlation. On the other hand, if the system is kept t oo small and less factors are selected, som e important factors may be neglected, thus the generated model cannot describe the correlatio ns adequate ly due to th e lack of imp ortant factor s. Selection of Target Quantities ( Responses) and Influen cing Quan tities (Factors) In m any systems, the target quantities ar e the q u ality characte ristics and the pu r pose is to improve them by adjusting the infl uencing i nput parameters and eventually to f i n d a n o p t i m u m f o r t h e s y s t e m . However, to improve the target quantities, it is i m portant that the target quantities are quantitatively m e a s u r a b l e a n d i n b e s t c a s e t h e y a r e k n o w n t o b e i n f l u e n c e d b y the selected input parameters. Moreove r, selection of too many target quantities or qualit y characteris t ics makes it difficult to define an optimum for a system . By the selection of the influencing quantities, i.e. the fact or s in a DoE, it is im p ortant to ensure the reproducibility of the factors in the course of an experimental p l a n [ 1 6 9 ] . I n a n e x p e r i m e n t a l a n a l y s i s , 2 State of the Art 21 factors ar e var ied in diffe rent l evels to test their eff ects. L evels are the set or defined values for each factor [167], [169]. In an expe ri mental plan, each factor shoul d be varied at least i n two level s to determi ne t heir res pective i nfluence on t he r espo nses [169]. Wh en the factors are varied in two levels, the c orrelatio ns can be describe d with a linear model. For some system, w hen quadratic influences and the inter actions between the parameters are n ot significant, th e linear mod el can descri be the rel ationship between th e influencing quantitie s and the target quantities ad equately. However, when complex correlatio ns betwee n the paramet ers exist, such as the para mete rs have interacti ons with each other, the correlatio ns b etween f actors and respon ses cannot be described with a linear model thoroughly . At this point, quadratic models should be selected, which i nvolve the i nteractio ns betwee n the paramet ers and the quadratic influ ences of the pa r ameters. To achiev e quadrati c models, the f actors s hould b e varied a t least in three levels. In ad dition to the nu mber of levels, th e distance betwe en the s et l evels is also very crucial. The distance between the levels can strongly in fluence their i mpact on the r esponses (target q uantities). When the distance between the levels for a factor is selecte d too small, only small influences of the corresponding factor can be observe d o n the target quantity . Hence, a higher numb er of ex peri ments is re quire d to examine some distinguished effe cts on the responses. M oreover, i n a s m a l l d i s t a n c e b e t w e e n t h e s e t levels, influences of the factors on the respons es are consider ed a s chance due to s ome possi ble o v er l a p p i ng ef fe ct s b e t we e n t he fa c t o rs , s o th e c l e a r e f fe c t s c annot be detected [ 171]. On the contrary, the distance between t he levels should not be selected too larg e either. If the distance between the levels is too large, s ome side eff ects can appea r between the level s, which pre vent deter mining the clea r effects on the res ponses and de crease the mo del precisio n [171]. T he l a rge distan ce betw een th e level s is recomme nded usually at t he very early phase of t he experime nts, when the impacts o f t he factors on th e responses are not known in order to get to know the system and to induce gr eater effects on th e responses. However, it is also i m po rt ant to li mit the level s in the realistic parameter range in order t o assure the operability of a system. For this reason, it is reco mmended to prov e with the help of the preliminary experiments, if the process operates with the plann ed paramet er ra nge [16 9]. Selection of Experimental Plan In DoE, various ex perimental designs exis t to set up an ex perim ental plan, whic h can be select ed depending on the system and the purpose. Based on the selected design, generally the correlations can be expressed either with a linear model or a quadratic model. W it h some experim e ntal des igns, only the mai n e ffect s of f actor s can be i nves tigat ed on the res pons es, w hereas some other designs can deliver the impacts of the i nteractions between the factors on the response s as well. Interactio ns betwee n two fact ors means that the effect of one fact or depends on the set value of another fact or [171]. In addition, ther e are some design s, wher e quadratic influences can be investi gate d a s w e l l . T a b l e 2 . 1 s u m m a r i z e s s o m e of the main experimental designs in DoE and the corresponding e ffects, which can be investigated with the respectiv e design. Tabl e 2. 1: Se lecti on o f t he ex peri mental des ign Experimental design Inv e stigated Eff ects Mathema tical Mo del Full factorial Main effects, Interactions Linear Fractional Factorial Main effects Linear Placket-Bur man Main effe cts Linear D-optimal Main effects, Inter action s, Quadratic Non-linear Central composite Main effects , Interaction s, Quadratic Non-li near 3 K Main ef fects, Interac tions, Quadratic Non-line ar Wit h the full factor ial des ign, the main effects and in fluence of the interactions betwee n the parameters can be studi ed. To generat e the exper imental desi gn, the factor s ar e varie d in two levels and t he desi gn includes all possible combinations between the factors. With K factors, 2 K single experim ents are 2 State of the Art 22 required for t his desi gn. T he drawback of the f ull factorial de sign is that if the i nvestigated number of f a c t o r s i s h i g h , t h e n u m b e r o f e x p e r i m e n t s c a n r a i s e d r a m a t i c a l ly. Th e schema tic representation of the experi mental desig ns is shown in F igure 2.12, where the e xperim ental design is depicted in a building block. The b uilding block represents the experi ment zone (room) for th ree facto rs, wher e each fact or is repr ese nted throu gh one dimensi on and corner s show t he facto r c ombinati ons. As shown in Figure 2.12, in full factorial desi gn all the corner points are covered. I f necessa ry, some center- poin t experiments can be also suppl emented to the full factorial design. Figure 2. 12 : E xperimental de sign illustrate d schematically for three fa ctors, full factorial des ign (left), fractional factoria l (middle) , and the D - optima l design (right) Statistical ex perimental designs are orthogonal and b alanced. I n this sense, orthogonal means that the columns in the experi mental matrix in the design are independen t and balanced means that all factors are tested with the sa me repe titions i n the design [170]. When a new probl em occ urs in th e process and an expan ded proces s knowledge does not exist to solve the problem, usually many factor s are studied to understand the main influencing factors on the target quantities. In that point, it is m ainly important to know which fa ctors are the majo r inf luencin g factors, and how those factors are affecting the target quantities [171] . In such cases, screeni ng experimen ts can be used. Screening experimen ts are u sually recomme nded when eig ht or eve n more factors are examined in ord er to reduce the numbe r of experiments. For the screening s experimen ts Plackett-B urman or fractional factorial designs can be used to obtain required inf o r m a t i o n w i t h a l e a s t p o s s i b l e n u m b e r o f experi ments. With those designs, only the main fact ors are dete r m i n e d a n d i n t e r a c t i o n b e t w e e n t h e factors is not co nsidered [168]. The corr elations b etween the f act ors and the responses can be described only with a linear model. As depi cted in Figure 2.12, fractiona l design does not co nsider all corner points. The design select s only a fraction of full factori al d e sign, thus reducing t he number of experi mental runs. One of the most straightforward methods to evaluate the effect of each factor on the responses is to use one fact or at a time (OFAT) design [171]. In OFAT design, only one factor is varied while the o ther factors ar e kept constant. T hus, the impa ct of each f actor can be eas ily detected on th e responses [17 1]. However, one of the disadvantages of the design is that the num ber of required experiments can increas e rapidly with increasing factors [171]. In addition, with this p lan the interaction s between the parameter cannot be identified and the o p timum for a process can be found only by chance [172]. For non-linear dependenc y of the t arget quan tities, the factors should be varied at least in three levels. As shown in Table 2.1, DoE offers some experimental designs, wh ich help to ach ieve quadrati c models with reduced number of experiments. 3 K , central compo site design or D-opti mal design are so me of the known experimental designs to generate quadratic models. In 3 K experimental desi gn all corner points of t he building block, e dges and side middle points as well as the middle points of t he building blocks are covered. T he dr awback of the 3 K design is with increasing numb er of facto rs, th e number of experim ents in the e xper imenta l desig n can inc rease e normously . For instance, for fou r fact ors 3 4 equally 81 experimental points are req uired for this design. 2 State of the Art 23 Another ex perimental design f or quadratic models is the central composite design. This d esign is constructed in th r ee parts, from a c omplete factorial plan (cor ners in building block, the corner points of a star and one cen tral poin t ). The de sign is usu all y used if th e number of the required experiments does not increase with increasing factors [169]. An alternative experi mental design f or the quadrati c model is t h e D - o p t i m a l d e s i g n . T h e “ D ” i s t h e designation for determinant. Determina nt includes th e total a mo unt of infor mation for the design matrix, which is formed from a ll factors and th e factor levels [173]. D -optimal design is computer ai ded d esign, and it deliv ers the b est parameter set considering all possible c ombinations t o cover the e xperimental room with less pos sible number of experiments [174]. The experi mental design of D-optimal method is depicted schematically in Figure 2.12. The advantage of the D-o ptimal plan is that the experimental plan can be adapted depending on the fo cus of the system. This means that in a conventional experimental design, all the factors should v ary in the same level whereas i n D-optimal design the levels for fact ors can be selec ted freel y. For D-o ptimal des ign, a n algo rithm me th od is u sed, the des ired combin ations o f the f actors a re desi gned i n the ex perimental pla n selective ly a n d unnece ssary comb inations are taken out from t he experimental plan so that the required number of e xperi ments can be reduced. The select ed experi mental points in the design are distributed into the expe r i m en t z o ne i n s u c h a wa y t ha t i s ad e q ua t e to generate a quadratic model. To illustrate the remarkable dif ference between the conventional ful l factorial desi gn and D- optimal design, the necessary nu mber of experimental points for both designs are shown in Figure 2 . 13 with the sam e number of factor s, namel y wi th tw o facto rs X and Y and the ta rget quantity Z. Figure 2.13: Compar ison bet ween full facto rial design (left), a nd D -optimal des ign (right) w ith two fact ors X, Y and a targe t quanti t y Z [1 75] As seen apparently from Figu re 2.13, D-optimal model-b ased desi gn can c over the inv estigated room for the experim ental plan with a reduced number of expe riments compar ed t o th e conventional approach of full factori al pla n. Another advantage of the D- optimal experimental design is that it is possible to consider the experimental results, which already exist for a gi ven sy stem. The results from previous experi ments can be incl uded int o the model and be eval uated tog e ther. Moreov er, after all neces sary experi ments ar e incl uded i n the desi gn, an d t he ex perime ntal pl an can be broadened by supplementing new si ngle experi mental points or by suppl ementing new factors into the design [171]. On the other hand, a drawback of the D-optimal design is that due to its com plex algorithms, D-o ptimal designs can only be desi gned with a suitable software. After obtaining the ex perimental result s with a selec ted desi gn , the regression model s can be generated and the fitting quality of the re gression models can be evaluated. Fitting quality det ermines how good the model fits t o real data. One of the mos t important t erms t o d escribe th e mode l quality is the “R 2 ”, which is the coefficient of dete rmination. This term indicates the deter m ination quality of the m odel. In other words, this quantity describes the proportion of t he vari abilit y in the responses. R 2 varies between 0 and 1 and higher values of R 2 indicat e that the model follows the res ponses very closely. One i m p o r t a n t aspect r egardi ng R 2 is, tha t when extra te rms are add ed to the model, R 2 always increases, although the supplemented terms do no t nece ssarily improv e the model qu ality . Thus, the increase in the R 2 does not 2 State of the Art 24 inevitably mean the i mp rove ment in the model quality. For this reason, it is more consistent to u se the modif ied version of the R 2 n a m e l y , R 2 adj , for an estimation of the model quality . R 2 adj is an adjusted version of R 2 in re gard of the terms, whi ch means that R 2 adj does not increase by an addition of the new terms into t he model, unless t he added terms improve the model quality . In other words, R 2 adj incre ases only if the new added term improves the model more than it woul d be e xpected by chan ce. T herefor e, R 2 adj delivers more steady results in terms of estimating the m o del quality . As a matter of f act, there ar e a l s o t h e e r r o r s i n t h e m o d e l . T h e e r r o r s i n o t h e r w o r d s t h e r e s iduals in the regr ession function give an estimation of the standard deviation in a model due to the meas urement error or disturbance s in the process, whi ch are also illustrated in Figure 2.11. As addresse d earli er, regre ssion analy sis is applied to generate a mathematical mo del based on the select ed design, whi ch esti mates the relati onship betwee n the fa ctors a nd the responses. It is important to emphasize tha t the models can only express th e correlatio ns in the defined pr ocess window (ex periment zone) a n d t he extrapolation outside of the process wi ndow is ri sky since the sy stem behavior c an change ou t side o f the system borders drastically [169], [171]. After generation of t he regression models, optimization for the target quantities can be done. In the optimization step target quan tity or th e quality characteristic s can be minimi zed, m aximized, or a ta rget value can b e defin ed [ 167], [176]. The target quantity gets an optimum value at the end of the optimizatio n process. For statistical r easons, usually the aver age valu e is considered f or an optimum value of t he target quantities [ 171]. In most of the s y stems, t here is more than one tar get q uantity, which sho uld be optim ized at the sa me time. Moreo ver , the p aramete r a dju stment, which is the optimum for one target quantity , is not alwa y s an o pti mum for the other qu a ntity. Bas ed on the quantitative knowledge of the dependency of a ll target quantities on the fac tor and with the help of the generated mathematical model, a c ompromise can be found, which deliver s o pt imu m v alue s for mor e t han one target q uantity at the same time [171]. Consequently, by considering the aforementioned designs, if the obje ctive is to gener ate a quadr atic model, which def ines the correla ti on between the input paramete rs and the target quantities mathematically a nd optimize the system, one can follow three steps to achieve this goal: screeni ng, modeling and optimization [177]. The number of steps can be dec reased depending on the kno wledge on the sys tem and if enough knowledge on t he system is av ailabl e, one can reduc e the nu mber of t he steps. 2.7 Outline of t he Dissertation Based on the given o verview in this chapter, it is shown that t he quality of the molded p ackages heavily depends on t he process parameters of tran sfer molding pro cess, character istics of EMC, package assembly inside and the desig n para meters. It is indicated that alt hough transfer molding is a co mmon process for producing electronic pac kages, paramet er settings o f a transfer mo l ding process are mostly done in a trial and error m a nner and defining the optimum proce ss parameters is laborious. Ma ny w orks are re present ed in this section, which were do ne to optimize th e process parameters o f transfer molding process, how ever, no sy stemati c appro ach has be en establis hed s o far to obt ain optimum process paramet ers a nd to establish a process model, which describes th e correlation between the proce ss paramet ers and the quality of the package. Additionally , it is shown that the mater ial characteri stics ha ve a drastic influence on the quality of the molded packages. The viscosity and cure behavior o f EMC are of prime importance for underst anding the infl uence of the mate rial on the package quality. T he reactiv e nature of the epoxy resins can be influenced by prolonged st ora ge duration, moisture content and the possible variations from batch to batch. Such impacts m ay cause alterations in the cha racteri stics of the EMC such as moldability and change i n the flow behavior of the material in the cavity . However, no systematic in vestigations are c onducted to u nderstand the infl u e nce of the variations in the cure behavior of the EM C prior to molding proce ss on the q uality charac terist ics. Additionally, the material investigations are performed usually in laborato ry conditio ns w ith conventional methods, but it is shown that online monitoring methods i n the transfer molding process are necessary to gather some 2 State of the Art 25 consequential information about the cure behavior of the EMC di rectly from t he cavity to diminish the defects. In lit erature there are not suf ficient studie s availa b le on the investigation of the mentioned variations in the cure behavior of EMC directly in transf er mol ding process to date. Due to this limited knowledge of the process and t he impact of EMC characteristics on th e p ac ka ge q ual i ty , se ve ra l d ef ec ts may occur i n t he pac kage duri ng the encap sulatio n of the se mico nductor devices such as voids, wire sweep and d elamina tion, which may cause total package failure a t the e nd. Therein, understanding the in fl uenc e of the ma ter ial c h ara cter ist ics of the E MC an d th e pr oces s parameters on the pack age quality is essential. In this context, an online monitoring technique c an deliver consequential information ab out the cure reactio n behavior of the EMC to y ield a sta ble packag e qu ali ty i n tr ansf er mo ldi ng proce ss. Consideri ng the afore mention ed as pects, an establi shed co rrelat ion between process param eters, material characteristics and the package quality can i mprove pr o cess understanding an d dimi nish the failure m echanisms in the molded p a cka ge, th us reduc ing th e fai lure costs. Theref ore, this work aims to give a c onceptual understanding on t he influence of the process parameters and the i mpact of mat erial characteristic s of EMC on the pack age quality in transfer mold i ng process in order to reduce the failur e costs in the mol ded packages. In addition, i n this work an appr oach is e valuated to esta blish models , which deliver the correlati on between the process para meters, m aterial c haracteristics and the package quality. With established process models, the optim u m process p arameters of t he tran sfer molding process c an be defined. T hree quality characteristics are inves tigat ed in this work, namely void formation, warpage and wire sweep in the molded packages. A ccor ding t o quality criteria given i n Section 2. 2, the target of this work is to reduce the wire swee p bel ow 4 % in the molded package, w hich i s t h e h a l f o f t h e d i s t a n c e b e t w e e n t h e w i r e b o n d s a t t a c h e d o n the layout (More information about th e wire bonds on the lay out will be given in Chapter 4). As void f ormation is one o f the major concer ns in terms of the reliability aspect, the aim of this work is to obt ain voi d-free pac kages. Howe ver, it is important to mention that the s mallest detectable void diameter is 100 µm with a corresponding area o f approxi mately 0.009 mm 2 for the sele cted package geo metry with an ap plied transducer f o r the SAM a n a l ys i s , t h u s t h e v o i d s w i t h a d i a m e t e r s m a l l e r t h a n 1 0 0 µ m c a nnot be detected (Details on the SAM analy sis will be given in Section 3.4). In add iti on, to prov i de good thermal interconnection between the power module and the heat sink, as a warpage qualit y criterion for the used package, warpage bigg er than 1 00 µm is c onsidere d critical in term s of an ef fective the rmal m anagement. Most important, for all quality featur es st udied i n this wor k t he major con dition for t he quality feature s is that the selected quality characteristics, namely void f ormation, wire sweep a nd warpage should be influenced by the variations in the pr oces s parame t e r s . A s t h i s w o r k a i m s t o g e n e rate the models , which can b e used to estimate the qu ality characteristic as a function of th e proces s param eters, the selected quality characteristics should be i nfluenced by the variatio n in th e pr ocess parameters. Thus, to an alyze the influences of the process para meters on the quality features, e xte nsive pr ocess analy s is i s carr ied out in this w ork. Do E methods are used to design an d evaluate the expe riments and in addition to the OFAT design, due to the afore mentioned a dvantages (Sect ion 2.6), D-o ptimal desig n is selecte d t o establis h the proc ess model and r egressi on a naly sis is perf ormed. In addi tion to the process m odel, the material mo del is also gen erate d, whic h deliv ers the correlat ion bet ween t h e v a r i a t i o n s i n t h e m a t e r i a l characteristics of EMC i n terms of storage duration, humidity a nd batch to batch variations and the package quality. Due to the given a dvantages, DE A method i s sel ected as a n online monitoring of th e material c haracteristic in t he transfer molding process to inve stigate the variati ons in the properties of the EMC. Additionally, temperature and pressure sensors are imp lemented in transf er molding process to contr ol the process. As indicated earlier in Section 2. 1, ma nufacturing of electronic packages requires different assembly processes. However, it is i mportant to empha size that this work concentrates on the transfer molding process itself and t he variations whi ch are or igi nated by the transfer molding process. The i nfluences of other a ssembly processes on t he package qual i t y a r e n o t t h e s c o p e o f t h i s w o r k . Figure 2.14 displays the sche matic representatio n of s equence o f th e asse mbly process es employ ed in this work with a focus o n the transfer molding process. 2 State of the Art 26 Figure 2.14: Schem atic illustratio n of the processes employ ed in this wor k, and the transf er m olding proce s s as a focus of this work As shown in Fig ure 2. 14, to constru ct and evaluate the de monstr ator in this wor k, many different assembly processes ar e employed. However, the focus of this wor k is on the transfer molding process a n d p a r a m e t e r s f o r t h e r e s t o f t h e a s s e m b l y p r o c e s s e s a r e k e p t c onsta nt after obtai ning a suit abl e parameter set for a qualified assembly. As illustrated also i n Figure 2.14, th e aim of thi s work is t o describe the relatio nship betwee n the process parameters, ma ter ial characteristics and the package quality with t he help of the process and material models. The o bjective of t he pr ocess mod el is to desc ribe the relationsh ip betw een the process param eters and th e packag e quality . Wit h the help of this model, it should be also possible to predict the quality charac teristics. Additionally, the model represents a sy stematic approach to identify the process para meters which enable optimal package qual ity. The goal of the material model is to describe the relationship b etw een the materi al characte ristics and t he package. With the help of the model, it is possible to describe the impact of preco nditioned EMCs on package quality . Additionally, the model represents a systemati c approach to estimate t he processing limitations of EMCs which are subjected t o t he differ ent pr econ dition ing (sto rage duration and humidity ) in order to achie ve a predefined package quality . Mor eover, the valid ation of both mod els is performed to deter mine the possibility and the limitations of t h e m o d e l s w i t h o t h e r E M C . T h e r e f o r e , these sy stematic ap proaches described above which are used to g enerate these models can also be applied for other molded packages and for different EMCs to des cribe t he r elation ships between the input a nd output par ameters an d to generate differen t models fo r such systems. Accordingly, in the following an outline of this thesis is brief ly explained. Chapter 3 provides a brief over view on the materials and i nstru ment ati on u sed i n thi s w ork. The selection of the sensors for process co ntrol an d the positions o f the DEA sensors in the cavity of the tool for in-situ cure monitoring in transfer molding process are int rod uced. Chapter 4 presents the a ssembly s teps, whi ch a re u sed to prepar e the demonstrator in o rder to study the package quali ty. The important feat ures of the preparation step s from cleaning the lead frame until wire bonding process are explained. Chapter 5 is dedicated to the preliminary experime nts and their re sults, where the basis characte rization of the pr ocess and materi al are per formed. Preli minary experime nts are cond ucte d t o dete rmi ne th e dominant process parameters, which have an i mpac t on the qualit y characteristics an d to exa mine the package qualities, which are strongly influenced by th e process par ameters. In addition, the main 2 State of the Art 27 characteriz ation of the EM C and the impact of storag e dur ation, humidity and the batc h variations on the c ure behavior of the EMC are examined with thermal and m ec h anical analy sis methods. Furthermore, the suitability of the DEA method for o nline monit oring in trans fer moldi ng process is assessed in terms of observing possi ble variations in the cure b e havior of EMC due to prolonged storage duration, humidity and batch variations. M a i n e x p e r i m e n t s o f t h i s w o r k a n d t h e i r r e s u l t s a r e s h o w n i n C h apter 6. The influence of t he process parameters in D-optimal design o n the package quality are discu ssed. The sens or si gnals and the proces s stability are evaluated. F urthermore, the influence of the vari ations in the EMC characteristics originating from prolonged storage duration, humidity and batch variations on the package quality are analy zed. Chapter 7 involves the evaluation of the results of main experi ments with the statistical analysis. Regression an aly sis is applied to evaluate the results a nd t he im portant results of regression a nalysis are introduced. Moreover, a mathe ma tical process model is establish ed which expresses t he correlation between the process parameters and t he package quality and esti mates the quality characteristics of the package. Optimum pr ocess para meters o f the transfer moldin g pro ce ss are deter mined. Furth ermore, t he estimation quality of the process model is assessed. In additio n to t h e p r oc e ss mo de l , a m a te r ia l m o d e l is established, which e xpresses th e influence of the variations of the material characteristics on the quality characteristics. The established process model an d the materi al model are verifi ed with validatio ns experim ents. The applied experi mental design and the results of validation exper imen ts ar e giv en in Chap ter 8. Bas ed on the comparis on between the pre dicted quality characteristics gi ven by the process model and the results of validati on experi ments, the predi ction quality of the proces s model is assessed. Additionally, to determine bo undary conditions of the establi shed models, furt he r experiments with another molding compound, which has substan tially different material properties , are conducted. The limitations and the possibilities of the process and the material models ar e discus sed. Chapter 9 sum marizes the m ain fi nding s from the conducted resea rch work. Conclusions ar e drawn and recommendations for furth er work are proposed. 3 Materials and Instrumentation 29 3 Materials and Instrumentation In this chapter an overview of the m aterials a nd the instrument ation employed in this w ork is given. The first pa rt of the ch apter f ocuses on the prope rties of the EMC and transf er moldin g proce sses which are used to pro duce the s pecimens of E MC. The properties of the sel ec te d E MC s a s w el l a s t he le ad fr am e are given in Section 3.1. Online monitoring of the t ransfer mol di ng proc ess is on e o f th e i mport ant aspects investigated in this work. To accomplish this aspect, s everal temperature and pressu r e sensors are implemented into the transfer molding tools t o gain more in form atio n about the process parameters in the cavity and filling behavior of the EMC. The selected sen sor types for this purpose are describ e d in detail in Section 3.2. The properties of EMC have significa n t i mpact on the quality of the molded packages. Hence, monitoring the poly merization reaction of EMC during molding process can deliver crucial information, which can be correlated with the final p ac kage quality. In this manner, DEA is chosen as an online monitoring method to observe the curing rea ct io n of EM C in mo ldi ng proc ess . T he characteristic inf ormation about t he cure reaction of the EMC, which can be determined in-situ with DEA is described extensively in Section 3.2. 3. To characterize the EM C, and to c orrelate the information about the cure reaction of EMC obtained fro m DEA, several chara cterization t ools such as rotational r h e o m e t e r , D S C , s q u e e z e f l o w r h e o m e t e r a n d D M A a r e e m p l o ye d i n t his w ork. Inf or matio n abo ut t he corre spo ndi ng tes tin g e qui pment i s prov ide d i n S ecti on 3.3. Due t o the i neligibl e proces s condi tions and poor material characteristics seve ral d efects such as void form ation, wire sw eep and warpage can o ccur in the molded packages. The methods, which are employed to anal y ze the defects in the molded packages, are introduced in Section 3.4. The i mportant feat ures on the analysis of void f ormation, warpag e and wire sweep are disc u ssed. 3.1 Materials In this s e ction the properties of the two selecte d EMCs a nd t he lead frame are given in Section 3.1.1 a nd in Section 3.1.2 res pectively. 3.1.1 Epoxy Molding Comp ounds As an encapsulation m a terial, highly filled EMC i s used. An ash test i s applied according to the ISO 3451-1 to determine the filler content in t he EMC in which the filler content is calc ulated by decomposing the EMC in the furnace at 600 °C under air and s ubs equently by weighing the remaining material, whi ch are t he sili ca filler particles. The filler con t en t of E M C i s fo u nd t o b e a pp ro x . 8 3 % b y weight of molding co mpound, where the fill er particle has aroun d 75 µm cut off size as a data shee t value. F ormulations of the EMC are mostly considered as a black box, since the supplier keeps the information about the chemical composition of the EMC strictly confi dential. Nevertheless, so me information can be derived from the material datasheet about t h e E M C . E M C u s e d i n t h i s w o r k i s specified as phenol novolac ty pe epoxy resin, which is produced by polyaddition reacti on as typical for the cure r eaction of t he epoxy resins. Based on the i nformation a nd t he c hemical substances given in material datasheet, it is ass umed that the structure of resin s y s t e m o f t h e E M C i s f o r m u l a t e d b y composing di fferent ty pes of ep oxies such as multiaromatic a nd multifunctional epoxy resins. As a hardener phenol novolac resin is used for t he curing reaction. Sche matic of chemical str uctures of multiaromatic, multifunctional epoxy resins and phenol novolac are illustrated in Figure 3.1. 3 Materials and Instrumentatio n 30 Figure 3.1: S chematic of che mical structur es of multi-func tional, multi-aromatic e poxy resins, and phe nol novolac as a hardener for the curing reaction of EMC For the validation of process and m aterial models, a second EM C is sel ected, w hich is purc hased fr om a different supplier. To prevent any confusion in no m enclat ure between selected EMCs, main E MC used in this work is design ated simp ly as EMC 1 and the se cond EM C, which is only used f or the va lidatio n experi ments (Chapter 8) i s marked as E MC 2. Altho ugh both EM Cs are e mployed for encapsulation purposes, which requires genera lly hav ing si milar properties in terms of moldability, the chemical form ulations of different suppliers are usually different . The resin structure of EMC 2 contains only multifunctional resin sy stem and phenol resins. The material pr operties of E MC 1 and EMC 2 a re summarized in Table 3.1. Table 3.1: M aterial Properties of EMC 1 and EMC 2 (According to material datashee ts) Properties EMC 1 EMC 2 Filler type Silica spherical Silica spherical Filler cutoff size (µm) 75 75 Max. filler content (%) 82.9 83.5 Spiral flow (cm) 104 73 Gelation time (s) 40 46 Melt viscosity (Pas. ) 16 16.3 Hot hardness (Shore D) 81 85 Specific gravity / Density (g/cm 3 ) 1.93 1.88 Flexural strength (MPa) at RT 95 136 Flexural modulus (GPa) 17 16 Glass transition temp (°C) 185 192 CTE α1 (p pm/C) 12 11 CTE α2 (p pm/C) 44 44 Post mold cure condition 180 °C x 4 h 180 °C x 4 h Due t o its different chem ical formulation, EMC 2 show s also dif ferent flow behavior. Differen ces in the v i s c o s i t y b e h a v i o r s b e t w e e n E M C 1 a n d E M C 2 a r e e v a l u a t e d w i t h DE A at 175 °C and are shown in Figure 3.2. 3 Materials and Instrumentation 31 Figure 3.2: Lo garithmic ion visco sit ies of E MC 1 and EMC 2 m eas ured with DE A at 175 °C The detailed description of the interpretation of the DEA signa l will be given in Section 3.2.3, nonetheless some ele mentary p oints in terms of comparison of v i scosity behaviors of t wo EMCs can be discussed here. As seen from Fi gure 3.2, which illustrates the viscosity behavior of EMCs versus ti me, the cure reaction behavior of the two EMCs is quite different. The prop agation of t he cure re action of EMC 2 is faster compare d to EMC 1, which can b e identified from the slope of the curves. The mini mum ion viscosities of the mold compounds are a lso differentiating. At the end of 350 s, both molding compo unds arrive the same maximum level of i on visco sity. Howev er, EMC 2 achieves this level much faster in comparison to EMC 1. Due to such significant differen ces in the flow b ehavior, EMC 2 is seen as a suita ble materi al for t he v alidation of process and materi al models. As alrea dy expl ained i n S ection 2. 4, EMCs ar e usually deliver ed in pellet form, which contains resin and h ardener togeth er. To prevent any unde sired chemical reacti on between the resin and hardener prior to the moldi ng process, t he pellets are usually stored at -20 ° C in refrigerator. Bef ore ea ch measure ment, the pell ets ar e f irstly thawed at ambi ent temperatur e for 1 hou r i n a d e s i c c a t o r s o t h e t e m p e r a t u r e o f EMC p ellets reaches roo m temperature. According to the require m ents of the tran sfer molding machines, pellets with a diameter of 14 mm with a weight of 6.5 g are used in this work. Standard deviation of the pellet weight is calculated by measuring 100 p ellets and is ± 0.04 g. 3.1.2 Lead Frame A co pp er ba se d a ll o y le a d fr am e wi th a t hi ck n e s s of 1 m m is us e d as a substrate to provide mechanical suppo rt to the co m ponents and the wire bond s. The chemi cal comp osition of lead fr ame is shown in Tabl e 3.2. Table 3. 2: Chemic al composition o f copper ba sed lead frame ( Acc ording to the material datasheet) Composition of lead frame % Cu ≥ 99.95 % P ≈ 0.003 % The dimensions of the lead frame and th e toler ances of corres po nding dimensions which are a veraged out of 50 lead frames are ill ustrated in Figure 3. 3. 0 50 100 150 200 25 0 300 350 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 Log. ion viscosity [Ohm*cm] Time [s] EMC 2 [10 Hz] EMC 1 [10 Hz] 3 Materials and Instrumentatio n 32 Figure 3.3 : Design and dimensions of lead fram e wit h corr espond ing toler ances 3.2 Transfer Molding Process a nd Onl ine Monitoring Methods The main process, namely transfer molding is perf ormed by usin g two different molding machines and tools to produce differen t types of specimen s in this work: One i s t o p r o d u c e s a m p l e b a r s f o r t h e t h e r m a l and mech anical measure ments and the other is to enca psulate the demonstrat or to ev a luate the quality characteristic s such as wi re sweep and voiding. In each molding machine, additional sensors ar e mounted into the tool to monitor the process parameters and to ensure the process stability. The dimensions a nd ty pe of sensors selected for this purpose are in t rodu ced i n Sect ion 3.2. 1 an d 3. 2.2. I n addition, to obser ve the m at eria l characteristics of EMC in the cavity during the molding process, DEA is employ ed. For this rea son, DEA se nsors, more pr ecisely monot rode senso rs, are integr ated in bot h m o ld i ng t oo l s i n t he t wo di ff e re n t m a ch in es . Th e D E A s e ns o rs a n d ty pical signals obtained from DEA sensors with its main chara cteristics are e xplained in more det ailed in Section 3.2.3. 3.2.1 Molding Machine for Encap s ulation of Demonstrator with In tegrated Sensors Lau ffer transfer mold ing machine LHMS 28 with a clamping force o f ma x. 2 8 k N i s u s e d t o e n c a p s u l a t e the demon strator. Tra nsfer molding machine with lower and upper halves of the tool are depicted in Figure 3.4. The layout o f the d emons tr ator will be described in det ail in Section 4.1. Figure 3. 4: Transfer mol ding press LH MS 28 (left), up per and lo we r half of the to ol (righ t) The tool has two cavities and f our plun gers. Each cavity volume can be filled with two EMC pellets. A vacuum sy stem i s integrat ed int o the tool to prevent the air en trapments in the package and to obtai n homogeneou sly filled mo ld packages. The schematic of the mold f orm used in this transfer molding press is demo nstrated in Figure 3.5. 3 Materials and Instrumentation 33 Figure 3. 5: Mold tool used to encapsu late the demonstrator in t rans fer molding ma chine The mol ding process incl udes several steps, which are de monstra ted sequentially in Figure 3.6. The step 1 illustrates the pots and cavities at starting position o f the molding. As a beginni ng of t he mold p ro c es s , fi r s t t h e l e a d f r am e b a se d de m on st r a to r , w h ic h co n ta in s t he ass embled du mmy chips and wir e bonds, is pl aced in the mold tool and preheated for 4 5 s before the c ycle ti m e star ts in order t o enhance the a dhesion between the EM C and the lead frame as depicted in s t e p 2. A s a n e x t st e p , t he E M C pe l l e t s are brought into the pots (step 3) with a special carrier for b etter handling, which assists to put the EMC pellets at the same t ime into the pots to avoid any unequal pre heating ti me i n pots. Subsequently , the to ol is cl os e d a nd the cl a mp pr es su re is a ppl i ed t o p ro v id e a t ight contact between two hal ves o f the tool (ste p 4) . Afte r t he clos ing of the too l, t he de sire d pr eheat ti m e o f E M C f o l l o w s . W h e n t h e s e t p r e h e a t time is over, t he plungers move forward, and with the help of t he applied transfer pressure t he now liquid EMC is injected into the cavities. A fter the in- mold cu re cycle is finished, the mo lded packag es a re e je c te d a s s h ow n in s te p 5 wi t h t h e h el p o f th e e j ec to r s. F i na l ly, the packa ges are fully encapsulated as illustrated in step 6. As it can be understood from the aforeme nti o ned st eps, so me pr oces s p ar ame ter s such as preheat time, tran sfer speed of the plungers, clamping pressure, moldi ng temperature, holding pressure and time are major rele vant process parame ters of tran sf er moldin g p rocess f or a succ essful enca psula tion of the packages . Figure 3. 6: Process steps of t he transfe r molding for encapsula t ion of the semicon ductor packages, m old tool with cavit ies and pots ( 1), lead frames are pl aced in t he cavit ie s of h eat ed mol d ( 2), E MC p ell ets are br ought to the pots (3), tool is closed for i njection of EMC and in-mold c ure (4), ejectio n of the e ncapsula ted lead frames afte r cycle t ime is ov er (5), encap sulated electroni c pack ages after the molding pr ocess (6) The filling behav ior of the EMC during the m olding process can be observed wit h short-shots in which the cy cle ti me is interrupted and the final position of the plu nger is set in different val ues prior t o complete filling. In this way, the flow front of the EMC can be obs e rved in differen t filling positions i n the ca vity . F igure 3.7 sh ow s t he sh ort- shot i ma ges, whic h de mon strate the filling behavior of the EMC into the cavity from the beginning of the filling until the com plete filling of the cavity. 3 Materials and Instrumentatio n 34 Figure 3. 7: Short-sho t images dem onstrate flow front of the EMC during the cavi ty filli ng To monitor the process parameters and to ensure stable temperat ure and pressure profile in the tool cavities throughout the process, in total eight te mperature and pressure sensors ar e implemented into th e cavitie s. Except o ne temperature sensor from Priamus System Te c hnologies AG, all temper ature and p r e s s u r e s e n s o r s a r e p u r c h a s e d f r o m K i s t l e r I n s t r u m e n t e G m b H . T he sensors ar e mounted at different positions in the cavities. In add ition, two DEA Sensors are i mp lemented in runner areas of two cavities. The p ositions of the sensors are shown i n Fig ure 3. 8. T he ty pes o f the sensors i mplemented into the tool with corresponding diamet ers and the positions are ill ustrated in Tab le 3.3. Figu re 3.8: Mounted senso rs to the upp er ha lf of th e t ool (lef t ) and to lowe r half of the to ol (right) 3 Materials and Instrumentation 35 Table 3. 3: T ypes, diame ters and pos itions of the sensors imple m en ted in the tool cavities in transfer moldi ng machine Description Sensor Type Diameter Position T1 Te mperat ure Kist ler 6 195 B 2 .5 mm Upper half of the tool – left cavity T2 Te mperat ure Kist ler 6 195 B 2 .5 mm Upper half of the too l – right cavity DEA 1 Dielectric Netz sch Mono trode 4/3RC 6 mm Upper half of the tool – left cavity DEA 2 Dielectric Netz sch Mono trode 4/3RC 6 mm Upper half of the tool – right cavity P1 Pressure (diaphra g m sensor) Kistler M5 SKB 4 mm Lower half of the tool – right cavity P2 Pressure (diaphra g m sensor) Kistler M5 SKB 4 mm Lower half of the tool – right cavity P3 Pressure (diaphra g m sensor) Kistler 6163AA 6 mm Lower half of the tool – left cavity P4 Pressure (diaphra g m sensor) Kistler 6162AA 6 mm Lower half of the tool – left cavity T3 Te mperat ure Kist ler 6 195 B 2 .5 mm Lower half of the tool – left cavity T4 Tempe rature Priamus 4014A0.2- 101 2.5 mm Lower half of the tool – left cavity (Implemented under the cavity surface) On the l ower half of the tool, t hree temperature sensors an d fo ur pressure sensors are mounted in cavities as well as at t he gates. As seen in Table 3.3, different types of pressu re sensors are chosen, which also have different measurement sensitivities, so that the suitable sensors can be tested and i dentified providing the larg est amount of information with accuracy about the cavity filling behavior of th e EMC. Two pressure sensors are located at the same positi ons in the l eft and in the right cavity on the lower half of the tool, opposite t o the tempera ture sensors to ascert ain possible pressure differences . As temperature sensors, mostly Type K thermocouples are u sed in th is work apart from o ne Ty pe N temperature sensor. On t he upper half of the tool, two tem perat ure s ensors are i mplemente d, where one temperature sensor is located in the l eft cavity and another te mper ature sensor is located in the right cavity. Two tem perature sensor s are m o unted at the same positio n i n t w o c a v i t i e s t o d e t e c t t h e temperature difference between t he cav ities. Ty pical signals ob tained from dif ferent te mperature and pressure sensors during the m o ld filling process are shown i n F igure 3.9. 3 Materials and Instrumentatio n 36 Figure 3.9: Signals obtained from various tem perature (left ) an d pressure ( right) sensors dur ing the m old filling in transfer m olding proce s s As seen in Figure 3.9 on t he left hand s ide, T1 and T2 sensors show a sharp temper ature decr ease after around 16 s. This indicates the arri val of the EM C at the tempe rature sensor, which c auses a tem perature d r o p s i n c e E M C h a s a l o w e r t e m p e r a t u r e c o m p a r e d t o t h e t o o l s u r face at the beginning. Similar behavior is als o observed at T 3 sensor with sli ght difference due to the f a c t t h a t T 3 r e s i d e s o n t h e l o w er h a l f o f the tool in the cavit y. In contrary to other temperature sensor s , T 4 d o e s n o t s h o w s u c h d r o p i n temperature si nce t he sensor i s implemented under the tool surf ace an d has no co ntact with the m olding compou nd. As seen on the right hand s ide of Figure 3 .9, all pre ssure sensors s how dra matic i ncrease in the pres sure profile e xactly at the same ti me around 24 s. This s harp incre ase of pr essure sig nal indicates the co mplete filling of the cavity. The sli ght differences obse r ved i n the pre ssure signals can be d ue t o different positioning of pressure sensors namely in the cavitie s, g ate area a s we ll as in uppe r and l ower half of the tool. The signals obtained fr om temperature and pre ssure sensors are used to inspect the process stabil ity and als o to compar e t he pro cess para meters me asured in t he caviti es with the set machine parameters. As T1 and T2 are mounted at similar positio ns in both cavities, for practica l r easons only T1 an d T2 sensor signals will be shown in the results, in or de r to c om pa r e t he te mpe ra tu r e p ro fi l es between two cavities. D ue to similar r easons, the pres sure sens or s, P 1 a n d P 2 w h i c h a r e i mp l e me n t e d i n two cavities at the similar positions will be used to compare t he filling behavior of the molding in the cavities. In addition to temperature and pre ssure sensors, to measure the material characteristics of EMC in the molding process, two reusable monotrode sensors are implemented in the upper half of the tool, where one i s in t he l eft cavity at gate, and the other one is at the sa m e position in th e rig ht cavity. The monotrode sensors are explicitly located at the g ate area, becau se t his p osition can d eliver all steps of the curing behavior of the EMC from being liquid state d uring injection phase whil e flowing into the cavity until the gelation of ep oxy resin. Moreover, since the viscosity of E MC is stron gly influenced by the temperature, it is i mportant to measure the te mperature profile nea r the monotrode sensors. Thus, for more precise measu rements and better interpretation of the resu l t s , m o n o t r o d e s e n s o r s a r e m o u n t e d closely to temperature sensors of T1 and T2 (see Figure 3.8). 3.2.2 Molding Machine for Producing th e Sample Bars Lauf fer t ran sfer mol ding machi ne V SKO 25 with a max 25 kN cl amp ing force is used to produce the sample bars to ch aracterize the EMC with various analytical too ls . Wit h the molding press, it is possible to produce the sample bar geometry of 80 x 1 0 mm 2 with th ickness va riation s of 1 , 2 or 4 mm. A reusable monotrode sensor with overall 6 mm diameter is im ple mented into the cavity of the transfer molding press to analyze characteristics of EMC with DEA duri ng mold ing process. Additiona lly, to monitor the process and t o ensure t he process stabil ity during moldi ng pr oce ss, temp era tur e (Ki stl er Instrum e nte GmbH, Ty pe K, 2.5 mm) and pressure (Kistler Instrum ente G mbH, diaphragm sensor, 0 2 04 06 08 0 1 0 0 1 2 0 1 4 0 166 168 170 172 174 176 178 180 182 184 Temperature [°C] Time [s] T1 T2 T3 T4 0 2 04 06 08 0 1 0 0 1 2 0 1 4 0 0 20 40 60 80 100 120 140 160 180 Pressure [bar] Time [s] P1 P2 P3 P4 3 Materials and Instrumentation 37 6 mm) sensors are mou nted in th e cavit y. As in the other moldin g machine (see Section 3.2.1 ), in this molding ma chine the temp erature se nsor is also imple mented very close to the DEA sensor in the tool. A s t e m p e r a t u r e h a s a s i g n i f i c a n t influence on the viscosity beh avio r of the molding compound, im p lem en ti ng a t em per a t ur e s en so r c los er to th e D EA se ns or al lo ws to correlate the vis cosity behavior directly with te mperature. All sensors are mo unted on the upper hal f of the moldi ng tool. Considering that the sensors can leave marks on the sample bars, the sensor s a re i mple mente d on tw o en ds of t he cavity a nd as far as pos sible fro m the middle of the cav ity to pre vent any mark s in cent er of the spe cimen bar which can in fluence the results of mechanical analy sis such as DM A. T h e c a vi ty o f t h e m o l d i n g t o o l and the positions of t he integrated senso rs are shown in Fig ure 3.10. Figure 3.10: Tr ansfer molding press to produce the sam ple bars ( left), mold tool geometry for produc tion of t he sample bars (right) 3.2.3 Dielectric Analysis (DEA) DEA is e mployed as monitoring technique to obser ve the variatio ns in the materia l characteristics in t ra n sfe r m ol di ng pr oc es s. Fo r t hi s r ea s on , r eu sa b le se ns or s a re implemented in the tool cavities of b oth transfe r mol ding presses, which are alr eady explai ned i n detail ed i n Section 3.2.1 and 3.2. 2. The same type o f monot rode sensors are mou nted in cavities o f bo t h trans fer m olding press es in o rder to co mpa re the results. The mon otrode sen sor 4/ 3RC is selecte d, whi ch has o v e r a l l 6 m m d i a m e t e r . T h e s e n s i n g surface of the m o notrode sensor 4/3RC i s only 4 mm and t he rest of 2 mm is the isolation layer as it ca n be s een from Figure 3.11. The isolation lay er is neces sary acco rding to measurement pri nciple in order to separate the se nsing surface of t he sens or fr om the tool sur face to create an electrica l field between the tool and the sensor. With the h elp of t he generate d ele ctri cal field the mobility of the ions can be measured. DEA meas urements ar e carried out with dielectric cure a n a ly z e r , D E A 2 8 8 E p s i l o n , N e t z s c h - Gerätebau GmbH, Selb. The DE A 288 offer s two dielectric channel s , w h i c h a l l o w t o c o n d u c t t w o simu ltaneous measurements at the same time. Thus, two channels are used at the sa me time during the measuremen ts in the transfer molding press wit h two cavities ha ving two monotrode sensors (Section 3.2.1). The mon otrode se nsor and dielectri c analy zer u s e d i n t h i s w o r k a r e s h o w n i n Figure 3.11. Figure 3.1 1 : Monotro de sensor wit h its plug to conne ct to the a nalyzer (left), the surface struct ure of the monotro de sensor ( middle) and the dielec tric ana l yzer w ith two measu rement channel s (right ) In a DEA curve the l ogarithmic io n viscosity is plotted over cu ring time of the E MC in t he transfer molding process. The implemented DE A setup allows a lso to monit or the temperature a nd the press ure 3 Materials and Instrumentatio n 38 sensors tog ether with the DEA signal d uring the molding process . A ty pic al DEA sign al o btai ned fro m DEA analy zer and corresponding te mperature and pressure signals from the mo lding cycl e are shown in Figure 3.12. The cycle ti me in transfe r molding is typically in the order of 2 minutes. For the DE A measuremen ts, however, the cycle tim e is prolonged to 4 -6 m inut es to record the cu ring behavior o f the EMC until the end stages. All DEA measurements in both transfer molding presses are started with trigger signal beginning with a plunger m ovement conveyed from the ma chines to DEA analy zer to avoid any m anual triggeri ng, which can cause a n undesired time shift at the beginning of measurements. Figure 3. 12: DEA signal of EMC 1 in-situ monitore d with DEA Analyzer a nd co rr esponding tem perature and pressure signal s from the molding c ycle As seen in Figure 3.12, temperat ure drop s sharply at the b eginn ing of a c y cle indicatin g that the m ateri al arrives at the sen sor. At the same ti me, ion viscosity starts d ropping also r evealing the materi al arrival at the DEA sens or. The following continu ous drop on the ion vis cosity until around 30 s i s due to the melting of EMC, which is heated through t he h ot molding tool an d ca usi ng the dec re ment in th e ioni c viscosity. Subsequentl y, the EMC reaches the minim u m ion viscos i t y a t a r o u n d 3 5 s . A f t e r t h i s p o i n t , the r eaction propag ates quickly and th e slop e of rea ction incre ases. As the time goes by, t he slope o f the viscosity curve decreases by indicating that the r eaction rat e slows down. After around 250 s, i on viscosity achieves its maximum ind ic ating that the cure reactio n is terminated. DEA is a temperat ure and f requency depen dent method. Thus, befor e con ducting any measurement with DEA, it is important to evaluate the temperature i nfluence on i on viscosity as well as the ion viscosity curve with differ ent frequencies for the selected m aterial. The selecti on of the ri ght measu reme nt frequency is very crucial to pur sue the ion viscosity signal th roughout the curin g ti me in all phases of the m ol ding co mpound continuously without any noises a nd interr uptio ns. To determine th e measuremen t frequency for EMC 1, ion viscosities are examined w ith five different frequencies; 1 Hz, 10 Hz, 100 Hz, 1 kHz and 10 kHz at a constant mol ding temperat u re of 175 ° C as depicted in Figure 3. 13. As a criter ion f or the select ion of suitable frequ encies, frequencies which d eliver the lowest minimum ion viscosity combined with maximum ion viscosity level in a s mooth cur ve is applie d. In other words, the fre quencies, which can demonstrate the hi ghest delta (∆) bet ween the minimum ion viscosity and maxi mum i on vis c osity, are selected as the suitab le f requencies. Among measured f r e q u e n c i e s f r o m 1 H z t o 1 0 k H z , t h e f r e q u e n c i e s 1 H z , 1 0 H z , a nd 100 Hz are selected as suitable frequencies for the DEA measure ments of EMC 1 (see Figure 3.13) . Neverthel ess, as the choice of 1 0 Hz d e l i v e r s t h e s m o o t h e s t s i g n a l w i t h l a r g e s t d e l t a b e t w e e n t h e m i nimum ion viscosity and the maxi mum ion viscosity, the ion viscosity curves at 10 Hz will be used a s r epresentation in the results. As mentioned, the second important aspect when interpreting the D EA r esults is the temperature. Temper ature has a direct impac t on capac itance, on the ene rgy o f the sy stem , y et on the mobility of the ions. In Figure 3.13 DEA measurem ent s are illustrated which are conducted with EMC 1 with different molding temperatures from 155 °C to 185 °C at 10 Hz. Higher tem peratures show faster cure reaction 0 50 100 150 200 250 300 350 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 Log. ion vis cosity [Ohm*cm] Time [s] 0 20 40 60 80 100 120 Pressure [bar] 169 170 171 172 173 174 175 176 177 Temperature [°C] 3 Materials and Instrumentation 39 by owning high er slope a nd achieving the correspon ding maximum ion viscosities fast er. On the othe r hand, as it can be seen i n Figure 3.13, at the very beginning of reaction, the starti ng le vel of the logarithmic ion viscosities varies depending on t he molding tem perature. Additionally , maximum ion viscosities achieved at the end of measurement are al so varied remarkably depend i ng on the molding temperatures. Therefore, it is important to keep in mind that, when co mparing the result s of D EA with each other, the similar temperat ures and freq uencies shoul d be selected for the corr ect interpretation of the results. Figure 3.1 3 : DEA si gnals me asured with diffe rent frequencies ; 1 Hz, 10 Hz, 100 H z , 1 kHz a nd 10 kHz at constant molding temperature of 175 °C (left), influence o f m ol ding tem perature on the ion viscosity cur ves; temper ature is varied from 155 °C to 185 °C at constant fre quency of 10 H z (right) 3.3 Materi al Characterization Met hods In this section, thermal and mechanic al measu r ements are explai ned, which are performed t o characteriz e the properties of E MC. DMA method is use d to measu re glass transition temperature (T g ) of t he EMC. The applied measurement mode of th e DMA and more i n formation about the para meters are given in Section 3.3.1. DSC m easurement is conducted to d et er mine the degr ee of cur e of the EM C. Detailed inform ation ab out the s elected parameters for the DSC as well as the calculation of the degree of the cure of EMC are i ntroduced in Section 3.3.2. As high ligh ted in Section 2.3, the v iscosity behavior of the EMC plays an important ro le on the quality of th e molded packa ge. Theref ore, to under stand and s i m u l a t e t h e v i s c o s i t y b e h a v i o r o f E M C s u n d e r d i f f e r e n t c o n d i t i ons, rheological measurements with d if fe r en t a na lys is eq u ipm en t a re pe rf or me d. As a s ta n da rd me th o d, rotational rheometer measurements are perf ormed to exa mine the shear viscosity of EMC. The sel ect ed para meters for the rotational rheometer measurements are expla ined in Section 3.3.3. As an al ternati ve viscosity measurement, a squeeze flow rh e ometer is u sed. A squeeze flow r heometer allows t o examine the viscosity behavior of EMCs at higher temperatures in c omparison to the rotational rhe ometer. Moreover, as th e tool setup of the squeeze flow rheo meter is constructe d in a similar way as t he mold i ng process, it allows to s imulate the cure rea ction o f EMCs as in the tr ansfe r molding process. D etailed infor mation about the tool setup and the measurement prin ciple of the s queeze flow rheometer a re i ntroduced in Section 3.3 . 4. Since th e DEA is u sed as a n o nline mon itoring technique in thi s work, for b etter u nderstanding of the ion viscosity curves in terms of the progres s o f the cure re action, it is imp ortant to compare the ion viscosity with the shear viscosity. Thu s, simultaneous DE A-Rotational Rheology met hod is conducted, which is sh own i n Section 3.3.5. Las t but not least, as t he i nfluence of the humi dity of the E MC on the quality features are the focus of this w ork, for a precise measurement, K arl-Fisc her titration metho d is used t o measure the moisture content in the pellets. The detailed information about the Karl-Fischer method is given i n Section 3.3.6. 0 50 100 150 200 250 300 3 50 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 Log. ion viscosity [Ohm*cm] Time [s] 1 Hz 10 Hz 100 Hz 1 kHz 10 kHz 175 °C 0 50 1 00 150 200 25 0 300 350 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 Log ion viscosity [Oh m *cm] Time [s ] 155 °C 160 °C 165 °C 170 °C 175 °C 180 °C 185 °C 10 Hz 3 Materials and Instrumentatio n 40 3.3.1 Dynamic Mechanical Analysis (D MA) Dynamic mechanical analy sis (DMA) y ields information about the v iscoelastic behavior of the thermoset ma terials. T g and the modulus of elasticity of the material can be determine d with DMA. DMA measurements are carried out in a Bose ElectroForce 320 und er a har monic load applicatio n. Maximum f orce used in this instrument can be selected from 100 N t o 45 0 N in a tem pe ratu re r ang e of -50 °C to 260 °C. Three-point bending mode is applied on the sp ecimen with a sinusoidal deformation of 0.03 mm. DMA delivers also information about the frequency d ependency of properties of mo lding compo und w hen meas ured at differ ent frequenc ies. However, this asp ect of in vestigation is not a focus of this wor k. DMA is employed in th is study to co r relate the T g of the material with curing d egree of t he EMC, thus only one fre quency is used t o det ermine the T g of t he m ate rial a nd to c ompa re the res ults o f different preconditioned EMC with each other. For this reason, the typical frequency of 1 Hz is select ed in DMA measure ment. T he speci mens ar e he ated from ambie nt te mpe rature to th e 250 °C with a heating rate of 10 K/min. The molding compound sp ecimens h ave the dimen s i o n s o f 1 0 m m l e n g t h x 8 m m width x 4 mm thickness. Typically , loss modulus ( E´´ ), storage modulus ( E´ ) and tangent delta ( tan δ ) can be measur ed with DMA. Usually, the los s modulus is correlat ed with viscous part of the mater ial, storage modulus is with the elasticity of the co mpound, and tan gent d elta deli vers t he rati o of loss modulus to storag e modu lus [178] . A typical DMA curve obtained for EMC 1 is shown in Figu re 3.14 . Figure 3. 14: Storage m odulus, loss modulus a nd tangent del ta ob ta ined from DMA me asurement for EMC 1 at 1 Hz The continuous decrease in the storage modu lus and the peak obs e rve d in l oss mod ulu s i n F igur e 3.14 are due to t he T g of the EMC in which the sample becomes rubbery above this temp erature. T g can be measured i n diffe rent positions o f the curves; by the E´ onset point, by the peak of E´´ o r t h e p e a k o f tan δ [179] . However, the position of t he peak of tan δ is usually used t o determine the T g o f p olym eri c mate ria ls [32], [157], [180]. Thus, ta n δ will be used to define the T g of EMC 1 in this work. 3.3.2 Dynamic Scanning Calorimetry (DSC) Differential scanning calorimetr y (DSC) is freque ntly used to s tudy the cure k inetics of epoxy based materials. According t o ASTM standard E473, in DSC measurement the heat flow rate difference into the speci men and an in ert referenc e sample is measu red as a fun ction of temperature under a controlled temperature program [181] . Two kinds of DSC meas urements can be perf ormed, na mely isother mal a nd non-isother mal. In an is othermal DSC, the sample is heated up r apidly to a defined temperature and the temperature i s hel d constant until no change i n enthalpy i s det ecte d. I sothermal DSC can have so me drawbacks due to the fact that during h eating up the sample to a certai n temper ature, the sampl e can already start curing, and for a fast curing sample the r eaction can be over before the desire d te mperature is reached . In no n-i sothe rma l or dyna mic DS C, the sa mple i s heat ed up wit h a constant heating rate to the de sired temperat ure an d the change i n ent halpy is recorded [182] . Sever al cruci al infor mation can 50 1 00 150 200 250 0 5000 10000 15000 20000 Storage m odulus [MPa] Temper ature [°C] 200 400 600 800 1000 1200 1400 Loss mo dulus [MPa] 0.00 0.05 0.10 0.15 0.20 0.25 0.30 tan del ta 3 Materials and Instrumentation 41 be derived about the curing reactions from DSC curves. The star ting t emperatu re of the rea ction, T g , reactio n e nthalpy generat ed b y curing are some of the import ant informati on [183]. Additionally, the degree of cure can b e calculated from t he DSC c urves, which is also the m a in purpose of e mploying the DSC in t his work. The de gree of cure, α , can be determined b y c alculating the enthalpy at tim e t, ∆H( t) and dividin g by the reactio n enthal py of a fully cure d samp le ∆ H total [47], [184], [185]. ( 5 ) DSC measurem ents ar e performed with TA Instruments Q20 00 having a m easurement accurac y aro und 0.2 µW and a temperature accuracy around ± 0.1 °C in a temperat ure rang e of -18 0 °C t o 725 °C [186]. For the m e asurements, the pellets are s mashed into granular for m and put in t he aluminu m pans in th e D S C . D S C m e a s u r e m e n t s a r e p e r f o r m e d w i t h a h e a t i n g r a t e o f 1 0 K /min over a range of -30 °C t o 260 °C under nitrogen purge. Figure 3.15 shows a representative DSC curve of EMC 1 un der non- isothermal conditi on. Figure 3.15: D SC curve of EMC 1 under non-is othermal conditi on from - 30 °C to 260 °C with a heat ing ra t e of 10 K/min The curi ng reaction of EMC is mo stly exot hermic, whic h can be i dentified from the positive value of the h eat flo w and the peak of th e reaction pointing downwards [ 187]. Moreover, the area under the peak delivers t he e nthalpy of reaction. The first peak seen around 4 0 °C is due to the melting of some additives in EMC 1. 3.3.3 Rotational Rheometer Rheology m eas urements are p erformed using a parallel-plate rota tional viscometer. A rotational viscometer AR G2 from TA Instruments w ith a plate diameter of 6 mm and a gap height of 1.5 mm is employ ed. The measurements are carried out under isothermal con dition at 100 °C and under non-isother mal condition with a heating rate of 2 K/min startin g at 70 °C until the end of measurement range. The vi scosity is measured in oscillation mode with a fre quency of 1 rad/s and 2 kPa oscillation stress. For the measurements, th e pe ll e t s a r e sm a s h e d i n to th e granul ate form, t hen pr essed tog ether as a tablet having 12 mm diameter a nd a thickness of 1.5 mm. T he r heol ogy meas ure men ts are repe ate d three times. 3.3.4 Squeeze Flow Rheometer The molding temperature for the E MC is usually at 175 °C. To un derstand the viscosity behavior o f the EMC during the molding process, d etermining th e viscosity behav ior at elevated temperature s is important. Unfortu nately, the measure ment of the viscosity beha vior of EM C 1 at 175 ° C with a rotational rheometer is mostl y ch alleng ing and the viscosity b e havi or of the E MC can be meas ured o nly -25 0 25 50 75 100 125 150 175 200 225 250 0.00 0.05 0.10 0.15 0.20 Heat flow [W/g] Temperature [°C] uncured EMC 3 Materials and Instrumentatio n 42 up to a temperature around 140 °C. The reason f or that is that the reactive EM C can start curing v ery fast at elevated tempera ture before the measurem ent even starts and the information about the initial pha se of vi sc osity behavio r c anno t be re corde d with a rot atio na l rheometer. O nly possibility to yield rheological data at process te mperature i s an extrapolation of mea surements t aken at lower temper ature s. Alternatively, another method can be applied to measure the vis cosity behavior of the EMC at 175 °C, a squeeze flow rheom eter. Squeeze flow rheometr y is designed as an annula r gap rheometer, to simulate the viscosity behavior of the EMC in the molding machine. The c onstruction of the tool is shown in Figure 3.16. During the measurement, the plunger moves downward s with a cons ta nt disp lacement and p r e s s e s o n t h e E M C p e l l e t . T h e E MC, which m elts at e levated tem perature, flows through th e both open side of t he p lunger in the capillary . The force required t o m ov e the plunger is recorded during measuremen ts and is used to calcu late the viscosity of the EMC. Figure 3.16: S queeze flow rheome t er setu p (left), assem b ly of t he squeeze flow rheometry (r i ght) [18 8 ] 3.3.5 Simultaneous D EA-Rheology Measurements The si multaneo us DEA-R heology measur ements are cond ucted at Fra unh ofer IZM with an impedance spectr oscopy s y stem Alpha AN from Nov ocontro l T echno l og ies and wi th a AR G2 rhe ometer from TA Instrum e nts. A rheometer with plate-plate geometry is used with a gap height of 1 mm in oscillation mode with a frequency of 1 rad/s. The impedance of EMC 1 is mea sured and then co nverted to the ion viscosity of EMC 1. Simultaneous rheology and i m pedance spectroscopy with an integrated interdigital capacitor is performed under isothermal condition at 100 °C and under n on-isothermal condition fr om 70 °C at a constant heating rate of 2 K/min until the gelation. T h e f r e qu en c ie s o f 1 0 H z, 1 0 0 H z a nd 1 kHz are s elected. The measureme nts are repeate d two times. 3.3.6 Karl-Fischer Titration To m easure the amount o f water in the pellets , the gravimetric determination o f the water content i n the pellets before and after preconditioning in humid atmosphere is done. The weight diff erence of the pellets befor e and af ter pr econditi oning are compare d. In addit ion to gravi metri c deter mination, for a more accurate determination of t he a moun t of water in the pe lle ts the calorimetric Karl-Fischer titration is used according to DI N EN ISO 15512 [189] . Cal orimetric Karl-Fischer titration is a method for precise measure ments o f especially the l ow level of hu midity in t h e s a m p l e [ 8 2 ] . T o d e t e r m i n e t h e amount of water, the water in the sample is evaporated by heat and transferred into the titrat ion cell. Then, th e Karl-Fischer titration starts, which is based on the reduction of the iodine by sulfur diox ide in the presence o f water to f orm sulfurtrioxide and hydroiodine ac id [189]. Titration is performed until the water is consumed. Aft er the e ndpoi nt is reached, the amount of water in th e sample is recorded. Karl-Fischer-Titrator AQUA 40.00 from Jena Analytic is used t o measu r e the water up take in EMC pellets. The measurement parameters for the titration are set t o 200 °C o ven temperature, 20 m in measuremen t time and 8.0 µg/min drif t . The measurem ents are rep eated t hree times for an acc urate determination of the a mount of water i n the EMC pell ets and t he ave rage values ar e shown in the results. 3 Materials and Instrumentation 43 Moreov er, th e sa mples f or the m easure ment a re take n from t he sa me o uter lay er of the pellet s to prevent any deviation in th e water con tent due to the position of the s amples in the pellets. 3.4 Quality Analysis Methods In this section, qualit y analysis method s are introduced which are applied to exa mine the quality characteristics of the pac kage aft er the molding process. First , the void for mation i n the molded packages is anal yzed with scanning acoustic m i croscop y ( SAM) after the m olding process. The detailed information about t he setup an d t he measur ement is given in Sec tion 3.4.1. Subsequently, the warpage analy sis is co nducted with the molded packages, which is sh own i n S e c t i o n 3 . 4 . 2 . A s a l a s t s t e p , t h e molded packages are sent to laser o pening, to remove the EM C a n d t o relie ve t he w ire bonds in order to analyze the wire sweep in the packages. After package opening, the wir e bonds are ins pected w ith optical microscopy and initial and final position of the wire bonds are compared. More information about the wire sweep analy sis is given i n Secti on 3.4. 3. The methods t o a naly ze the void formation and warpage are non-destructive, w hereas the laser opening process, which i s used to examine the wire sweep of aluminum wire bonds, is a destructive met hod. Thus, the or der o f the analy sis steps is i mpo rtant to complete all quality characteris tics examinations. Fi gure 3. 17 sh ows the sequence of the analy sis steps after th e molding process. The q uality analysis m ethods are giv en in this section in a respective order as shown in Figure 3.17. Figure 3. 17: Sequence of quality analysis ex aminati ons afte r th e molding p rocess 3.4.1 Scanning Acou stic M icroscopy (SAM) For the analysis of voids in the molded pac kages, sc anning aco u stic micr oscope (SAM) is used. The analy sis i s carried out in SAM Winsam Vario III with a transdu c er of 1 5 M Hz frequency. SAM is a non- destructive method, which can d etect inhom ogeneities and discon tinuities i n the speci mens. Ultr asound can be spread through gases, liquids as well as solids. Typical frequency range used f or t he ultrasonic measurement is in the range of 5 MHz to 500 M Hz . I n SAM ther e are two differen t types of measure ment methods, namely through-transmission method and pulse echo meth od. In thro ugh transmission met hod, two components are required, w he re the transmitter sends the si gnal, and the receiver records it. The other method is the pulse-echo method, where only one co mponent , a transducer is used, which transmits and receives the signal. I n this w ork, p ulse-echo method is use d . T h e p u l s e w i t h a h i g h f r e q u e n c y i s generated b y pul se generat or and d irected t o the sam ple th r ough the acou stic lens. After transm itting th e s i g n a l t o t h e s p e c i m e n , a p a u s e f o l l o w s a n d t h e t r a n s m i t t e r s w i tches to the receiv er mode. Transducer transmits the signal to the speci men and also r eceives the sign al, which is r eflect ed from the speci men. R e f l e c t i o n s o c c u r d u e t o t h e s u r f a c e s o f t h e s p e c i m e n s a s w e l l as the presence of t he discontinuities. Between the transducer and the speci men, a medium is r equired i n order to transmit and recei ve th e signal. To prevent any undesired i nhomogeneities between th e tr ansducer and the speci men, distilled w a t e r i s u s e d a s a m e d i u m i n a n u l t r a s o n i c b a t h . T h e s e t u p o f t he S AM and an e xemplary signal detected during the measurement are illustrated in Figure 3.18. 3 Materials and Instrumentatio n 44 Figure 3. 18: Scanning ac oustic microscope, sche matic of the tes t setup (left), the transduce r on top of the sample measured (righ t above), and the a mplitude signals duri ng the me asurement which are reflected from the surfa ce and from t he inhomogeneitie s (right be low) For the pulse-ec ho acousti c microsc opy, there ar e di fferent sca n m o d e s , w h i c h a l l o w t o o b t a i n a l l required in formation and details regarding to specimen. The sca n m o d e s o f A , X , B a n d C a r e a p p l i e d in this work. X-scan delivers information in different horizont a l l e v e l s , A - s c a n a l l o w s t o i d e n t i f y o n l y one point in a vertical line, B-scan can be applied to obtain a picture on a cross-section, and C-scan gives a pi ctur e on h oriz ontal le vel w ith a de fined th ickne ss. The p ri nciple of A, B and C scan modes in SAM can be seen in Figur e 3.19. Althou gh frequen tly C-sca n is used in this work as a scan mode, oth er scan modes are al so applied to acquire nec essary information. The th ickness range of the C-scan level is adjusted to the thickness of the molded pack ages to deliver all the information through the package within one picture. Figure 3.19: Principle of A, B and C S can modes in S AM which ar e em ployed in th is work for the m easurement of the voi d formation in the molded packag es After measuri ng the sa mples with SAM , the pictures a re evaluated to obtain the number of voids, the size of the voids as well as the location of th e voids on the l ay out. For a precise evaluation, a software is used. T he open source i mage processing program I mageJ is used, which incl udes the analy sis modules such as plugins, which are d eveloped for the void analysis purp ose of the s elect ed de mons tra tor for th is work. The software detects the voids by setting the threshold i n terms of the resolution. Threshold for t h e r e so lu t i on i s s e t i n s u c h a wa y t ha t s o f tw a r e s e le c t s t h e d ark points (potentially void s) on the SAM image which can also be discretely identified by a visual obser vation. Nonetheless, the s oftware has difficulty to differentiate the voids, in other words the darke r points on the SAM i m age, which a re close to contours , edges or the borders of the la y out, which are also seen as black a reas on the SAM image. There in, f or an accu rate void analysis, the im ages, wh ich a re e xam ined with the softwar e, ar e examined subsequentl y by an additional visual inspection. Additionally, as a transducer frequency of 15 MHz is selected in SAM analy sis, which allows through-thicknes s measur em ent for this demon str ato r geom etry, the minimum detectable void si ze is determined a s 100 µm. 3 Materials and Instrumentation 45 3.4.2 Warpage Analysis The warpage analysis is measured with the help of digital image correlation. The investigations are carried out with th e DANTEC Analys is Q400. For t he preparation of t he s amples, t he su rfaces of the m o ld e d p a ck a g es a re m a rk ed wi th a wh i t e s p r a y t o di s t in gu is h t h e s mall i mpurities on t he surface. For each sample , the images are r ecorded from different angles of t he cameras and t he obtained images are analy zed with the progra m Istra4D. First step in the evaluati on of t he imag es is to de fine the examinati on area on the sa mple. For t his reason, a mask is place d on the surface a nd the a rea wit hin t his mask is analy zed with t he sof tware. The soft ware measures the s urface c ontour of the packages within the defined ma sk and creat e a false-colo r image (Figure 3.20 lef t). After obta ini ng the false- col or ima ges, a circle is placed in the middle of i mage and four lines are set within the circle (Figure 3.20 right). The p u r p o s e o f t h e c i r c l e i s t o e n s u r e t h a t a l l f o u r l i n e s h a v e t h e same le ngth withi n the circle and the position of the lines are the same for each s ample . The four line contou rs on t he false-color image deliver t he information about deviation in z-direction on t he s urface. The values obtaine d from the software about the z -direction f or ea ch line are analy zed. The ty pe of warpage is iden tified between c oncav e o r c onve x. All the warpage analysis for the molded packag es are performed after PMC. Figure 3.2 0 : Image correlation, the variati on is shown with the colored scale (lef t), the four lines placed wit hin the circ l e on the false-color im age to evaluate t he dev iation i n z-direction (ri ght) For the warpage, fir stly the maximum value on the line in z dir ection i s calculated and selec t ed as the maximu m warpage. However, so me s urface defects on the molded pa ckage can cause one single maximum point although the other measured values on the lines l ie significantly under this value, yet this may result in false interpretation of the results. Theref o re, in addition to m a ximum po ints of warpage, the area under t he curve of the lines are also eval uat ed. 3.4.3 Wire Sweep An alysis Wire sweep is evaluated by v isual inspection. Each w ire bon d is exami ned before an d after the molding process with an optical microscope. To analyze wire swee p after the molding process, the p ackage is opened up with laser ablation tech nique at two locations of the speci men to exp ose t he aluminum wire bonds (Figu re 3.21). For the laser ablation proce ss, Laser VMC1 fr om Tr u mpf Gm bH + C o K G i s us e d. Figure 3.21: M olded packa ge after the mo lding pr ocess (left), o pene d molded pa ckage to expose the w ire bonds which ar e bonded on two locati ons on the le ad fram e (middle), w ire bond groups close to the gate (righ t) 3 Materials and Instrumentatio n 46 Wire sweep evaluation is done w ith an image editing software Im ageJ. To e nsure reproducible wire sweep measu rement, on each wire bond 10 poi nts are repla ced on an outer vertical line of the wire bond as it is shown in Figure 3.2 2. The coordinates of these 10 poin ts f or each wire bond are measured and recorded before and after the molding process. To compare the p oints before and after the molding process, the c oordinate s a re cali brated and th e ve rtical displa cement is measured. The maximum displacement between initial position and the position after th e molding process is measured and defined as a wire swe ep. Wire b onds i mages be fore and afte r the molding process as w ell as the defi nition of wire sweep are shown in Figure 3.23. Figure 3.22: Wire sweep ana lysi s with 10 p oints place d on the o uter l ine of a wire bond Figure 3.23: W i re bonds before th e molding process (le ft), aft e r the molding and laser ablation proc ess, definition o f wire swee p (right) As explained previously, wire sweep is acco mplished by manual e valuatio n of th e obtained i mages by locating 10 points on th e outer vertical layer of one wire bond (Figure 3.22). T his is do ne fo r eac h wire bon d before and aft er the moldi ng pr ocess. To find o ut the d evi ation caused by the manual wire swee p evaluation, each 24 wire bonds o n the tes t vehicle are measured 1 0 t im e s b e fo r e a n d a f t e r t h e m o ld i n g process. The wire sweeps of the wire bon ds are examined and the standard deviati on between the measur ed wir e swe ep v alues are calculated. The maximu m standa rd d e v i a t i o n o b s e r v e d i n w ir e s w e e p for the same wire bond is found as ±10 µm. In addition, d uring th e visual inspection of the wire bonds bef ore and after the molding process, the wire bonds cannot be positioned exactly at the exact area on the i ma ge. In order to identify , whether this positioning of the wire bond on the image causes any significan t deviation in w ire sweep ex amination, four i m ages a re taken with optic al microscope, where the same w ire b ond gro up is position ed purpo sely i n d i f f e r e n t a r e a s o n t h e i m a g e s a n d p o s s i b l y f a r f r o m t h e m i d d l e ar ea of the i mage. The i mages ar e shown in Figure 3.24. 3 Materials and Instrumentation 47 Figure 3. 24: S ame wire bond group is inspe cted b y locatin g the wire bonds in differe nt area of the im age and t he stand ard deviati on of t he posit ioning of the wire b onds on the im age is c alcula ted . W i r e s w e e p f o r t h e s a m e w i r e b o n d su c h a s th e f i rs t l o n g wi r e b o n d f r om a bo ve wh i ch is m a r k ed w i th white arrow in Figure 3.24 i s measured in fo ur i mages and t he s tandard deviation of t he wire sweep values are calculated. The standard deviation is found as 9 µm. As expl ained above, 1 0 µ m sta ndard deviation in wire swee p originated due to the manual evaluation of the wire sweep, which i mplies that this 9 µm standard deviation measured in the same wire bond loc ated at different p ositions on the four i m a g e s ( F i g u r e 3 . 2 4 ) i s t o a l a r g e e x t e n t d u e t o t h e m a n u a l e v a luation, and not due to the positions of the wire bonds on the image. 4 Experi mental Preparation 49 4 Experimental Preparation To st udy the quality characteris tics in the molded packages, fi rstly it is necessary to define a s uitable layout. In t his chapter, the layout of t he test vehicle in cludi ng respective wire bonds and com p onents as well as t he ste ps necess ary to prepare this lay out for the test v e hi cl e a r e i n t r od u c e d. T h e o v e r v i e w o f t h e q u a l i t y a n a l y s i s a f t e r t h e m o l d i n g p r o c e s s i s a l r e a d y s c h e m a t i c ally described is Section 3.4. In this chap ter, the steps which take place before the mold ing process i n order t o prep are t he t est ve hicle, in other wor ds the demonstrator, are introduced. Fig ure 4.1 depicts the steps, which are essential to apply in order to prepar e the test vehicle b efore the mol ding pr ocess . The sequ ence of the steps is adopt ed t o the respective layout of the dem onstrator used in this work. Figure 4.1: Overvie w of the s teps required t o prepar e the demon strator before the m olding process In Section 4. 1, the defined layout for the demonstrator for i ns tance the positions, the lengths and the types of the selected wire bonds is introduced. Subsequently, t he steps, which are necessary to produ ce the test vehicle with a defined lay out are given in Section 4.2 . The cl eanin g pr ocess of the lea d f rames, bonding process and chi p asse mbly are give n in detail in a resp ective order as sho wn in Figure 4.1. 4.1 Layout Defi nition In this wo rk, as a test vehicle sim ilar geometrical dimensions as a pow er module packa ge is ch osen. Th e demo nstr ator p acka ge i s a tes t v ehicle a nd not a functional pow er module, thus to realize the components volu me in t he pac kage du mmy comp one nts are us ed and t hin al umi n um wire bonds are bonded directly on a lead frame. The layout of the demonstrat or is designed in a way enabling to study different w ire bond ch aracteristics on the wire sweep. 50 µm alu minu m wire bo n d s ( A l + 1 % S i ) f r o m H e r a e u s a r e used and all wire bo nds are bonded directly on the copper lead f rame. T he influence of various wire b o n d p r o p e r t i e s o n w i r e s w e e p i s e x a m i n e d i n t h i s w o r k . T o a n a l y ze the inf lue nce of the wire bond length on the wire sweep, two differe nt lengths of wire bonds, namely 2.75 mm and 5.5 mm with an identical loop height of 0.5 mm are chosen. Long wire bonds and high loop heights are p r eferred s o that the wire sweep is sufficiently large to be measured accurate ly and to identify the corresp onding effect s of i nvestigated parameters. In addition, the influence of the w ire bond location with respect to the gate on the lea d fr ame ar e in vestigat ed. To ac complis h this , wire bo nds are placed in two locations on the l e a d f r am e a t ne a r t o t h e ga t e an d f ar f ro m t h e g a t e a r e a s. Fu r thermore, in order t o study th e impact of angle of t he wire bonds to the gate, the wire bon ds are bonded at three different angles to the gate; 180 ° , 90 ° a n d 4 5 ° . In tot al, each test v ehicle consist s of 24 wire bonds, in w hi ch 12 wire bond s are attached close to the g ate and 12 wire bonds are bo nded far from the gat e. The 12 wire bonds of each group are divided into t hree subgr oups and each subgroup is attached i n t hree differe nt angles t o the gate. Each subgroup contains 4 wire bon ds, 2 short and 2 long wire bonds w ith an identical loop h eight. Bond to bond distance is kept identical for all wire bon ds on the lay ou t and is approximatel y 450 µ m . The schematic description of layout of the test vehicle is shown in F igure 4.2. The amplified images of the wire bond groups, which are bonded close to the gate an d far fr om the gate with corresponding subgroups are depicted in Figure 4.3. To su m u p, followin g thre e effects of w ire bond properties ar e studied with this layout with regard to wi re sweep: Influence of wire bond length: 2.75 mm and 5.5 mm with an ident ical loop heigh t of 0.5 mm 4 Experi mental Preparation 50 Influence of position of the wire bonds on test vehicle: wire b onds attached in near gate an d far fr om the gate areas Influence of angle of wire b onds to the gate: wire bonds attach ed at 180 ° , 90 ° and 45 ° to the gate in near gat e and fa r from the gate are as Figure 4.2 : Test vehic le with three dummy compo nents and tw o grou ps of w i re bon ds with respect to gate positio n, wire bon ds attached at thre e different bo nd angles at 180 ° , 90 ° and 4 5 ° relati ve to gate positio n Figure 4. 3: General overvi ew of the layout o f the dem onstrator with all wire bon ds (left), a mplified ima ge of the wire bonds a ttached at three dire ctions to the gate 180 ° , 90 ° and 45 ° in ne ar gate are a (middle), and am plified image of the wire bonds attached i n far from the gate a rea at t hree directions to t he ga t e 180 ° , 90 ° and 45 ° (right) As already mentioned, the wire bonds are directly bonded on the lea d fra me surfa ces. This is also the reason of t he modified a ssembly sequence shown in Figure 4.1. N everthel ess, to realize t he volume of the electronic components in the package, passive units like re sistors and condenser s are assembl ed on the lead frame substrate [190] . Since an electrical functionality of the package is out of the scope of this work, passi ve dummy co mponents without an electrical functi on a re sel ected for the layout of t he demonstrator. Two different sizes of t he du mmy co mponents, whic h have the identical vol ume, as active compo nents a re chosen (Quart z NX8045GB 8,000MHz and NX1255 GB 4 ,000MHz FRG Frischer Electronic GmbH). Overall three dummy components are i mplemente d on to the substra te, wher e t wo of them have a pack age size of 8 mm x 4. 5 mm x 1. 8 mm and one bi gg er component has a package size o f 1 x 5.5 mm x 2.5 mm (Figure 4.3). 4.2 Sam ple P repar ation Test vehicles ar e prepared in three steps. Firstly , the lead fr a m e s a r e c l e a n e d t o r e m o v e a n y s u r f a c e contamination in order to prepar e the surface for the bondi ng p rocess. The detailed information about steps of the cleani ng process is introduced in Sectio n 4.2.1. A s t he wire bonds are bond ed directly on the copper lead fra m e and not on a chip f or t his defined lay out of the demonstrator, the bonding process is done subsequent to the cleaning process. More information about the bonding process is given in 4 Experi mental Preparation 51 Section 4.2.2. As a last step, the dummy co mponents are assembl ed onto the lead frame substrate. The selected adhesive and the setu p for a chip as sembly is explaine d in Section 4. 2.3. 4.2.1 Cleaning Lead f rames are clean ed to remov e the contaminati on fro m the su rface a nd to provide a good s urface cleanliness for the subsequent bonding process. To achieve th e highest cleanliness on the surface without any impurities or flux residues, water-based cleaning medium, n amely Vigon A200 (Zestr on, Dr. O.K. Wack Chemie GmbH) is used as a cleaning agent. I n addition, t o prevent any possible oxidation or corrosion o n the lead frame, corrosion inhibiter Vi gon plus Cl 2 0 ( Z e s t r o n , D r . O . K . W a c k C h e m i e GmbH), w hich is an aqueous mix of corro sion preventing additive s, is supp lemented into the so lution. The pre paration of t he cle aning solution is completed b y adding up dei onized water. The mixing ratio s for the ingredients in the cleani ng solution are sho wn in Table 4.1. Table 4.1: M ixing rati os of ingredients for the cleaning solu ti on Medi um Concentratio n Vigon A200 30 vol. % Vigon Cl20 2 vol. % Deion ized water 68 vo l. % Lead frames are first placed into a carrier and dipped into the beake r gla ss, w hic h cont ains the cleani ng solution. Then, the beaker gla ss is tra nsferred into the ultras onic bath, which has a temperat ure of 45 ° C. Lead fra me s are cleaned for 5 min at 45 °C in the ultrasonic ba th. Subse quently , lead fr ames a re ri nsed into the next beaker, which is filled with deionized water, and c l e a n e d f o r 5 m i n a t 4 5 ° C f u r t h e r i n ultrasonic bath to rem ove th e rest of clea ning solu tion. After the cleaning of the lead frames in distilled water is completed, the cleaning step in the cascad e rinsing fo llows. The clea ning of the lead frame i n the cascade rinsi ng helps to remove th e possible rest of cleani ng s oluti on or i mpur iti es and to ac hie ve highest possible su rface cleanliness on the lead frames. For t h is purpo se, the lea d frame s are rinsed i nto three separate beakers filled with deionized water. The cleanin g process in t he ultrasonic bath and the cascade cleaning a re shown in Fig ure 4. 4. Figure 4.4: Cle aning pr ocess of the l ead frames, first pla cing of lead frames int o the carrier (l eft), cl eaning in the ultrasonic bath in clea ning solution and in distilled water (mi ddle), cleaning solu tion, which change s the col or from transparent t o violet after the cleaning (right) W h e n t h e c l e a n i n g p r o c e s s i s f i n i s h e d , e a c h l e a d f r a m e i s d r i e d by blowing nitrogen gas onto the lead frame surface to re move the remaining humidity. Finally, the le ad frames are transferred into the storage cabinet under nitrogen atmosphere before the lead fr ames are co nvey ed to the bonding process. 4.2.2 Bonding To attach the Al wires to the lead fra me an ultrasonic wedg e wedge bonding process is employed, which is typically app lied to bond aluminum wires and does not requir e higher te mperature [39], [191], [192]. The require d ultrasonic energy is prod uced by th e vibrat ion o f the b ondi ng to ol ty pical ly i n a freque ncy range of 20-300 Hz [191] . For bonding t he aluminum wire bond onto the l ead frame, wir e w edge bon der 4 Experi mental Preparation 52 Model 3700 from Kulicke & Soffa I ndustries is u sed, which has a capability to be utilized in a fully automatic production line, and the bonding pro cess is conducted at room temperatu re in this work . The bonding process should be perfor med directly after cl eaning pro cess to hav e the highest cleanliness of surface for a good quality of bondin g. The wire b ond quality is crucial to ensure that no lift-off occu rs due to the p oor bonding quality , and that the wire bonds can wi t hstand the high tran sfer speed d uring the molding p rocess. The precision of the positioning of the wire bonds with the bon ding mach ine is evalua ted by meas uring the position of different wire bonds on the lead frames 50 ti me s and the stan dard deviations are calculat e d. The standard devia tion obtained fro m the measurem en ts i s found to be approximately 12 µ m. 4.2.3 Chip-Assembly In the last step of the sample preparation, the dummy chips are assembled on the surface of the lead frame with Infotech IP 520 from Infotech AG. PD 955 SMT thermos etting po lymer ad hesive is u sed in order to fix th e dummy components on the lead fra me. Firs tly , t he adhesive is d ispensed b y the machine on a defi ned target position and the dumm y components are picke d and placed on top of a dhes ive d epot s automatically. After placing all the c omp onents o n the lead fra me, the a dhesive is cured at 125 °C in a n ove n f or 1 0 min utes . 4.3 St atisti cal Pr ocess Anal ysis Statistical evaluati on softwar e, Corner stone, is used in this w ork to gen erate the exp eriment al plan and to analy ze the results obtained from the measurem ents. The corr elation between the input parameters such as process parame ters and material characte ristics and out p u t p a r a m e t e r s s u c h a s w i r e s w e e p , voiding and warpage ar e done by using regres sion analy sis. The pro cess and materi al models, whi ch will be presented in Chap ter 7 ar e also generated wit h the help of regression analy sis. 5 Prelimi nary Experi ments and Re sults 53 5 Preliminary Experiments and Results In this chapter prelim inary experimen ts are introduced, which a re performed to gain more understanding on t he infl uence of the process parameters on quality character isti cs such as void formation, wire sweep and warpage. In addition, the va riations in the m a terial charac t e r i s t i c s o f E M C 1 d u e t o t h e preconditioning in prolon ged storage duration in dry and humid environment are analyzed. The information acquired in this chapter in terms of material chara cteristics and the influence of process parameters on the quality features are essential to c onstrain t he main experi ments in C hapter 6. In this chapter focus is on two main matters. The first matter is to de termin e domina nt process parameters o f transfer molding process on v oid formation, wire sweep and warp age and to analy ze the qualit y characteristics, which are strongl y influenced by the process p a r a m e t e r s . T h e s e c o n d m a t t e r i s t o evaluate the suitability of the D EA in terms of observing the p o ssible variations in the material characteristics of EMC due to prolonged storage du ration, humid ity and bat ch variations. More over, the basic characterization of t he preconditioned EMC 1 is carri ed o ut with rheology methods t o gain mor e understanding in the cure reaction of EMC 1 and to comprehend t he variati ons in the materia l characteristic s of EMC 1. The planned experi ments to study the impact of individual proce ss parame ters on th e pa ckage quality are introduced in Secti on 5.1. In this study , four main process pa rameters ar e examined, whic h are molding temperat ure, tra nsfer s peed, pre heat ti me of the pellet s and holding pressure. To study the significance of process p arameters on the pack age quality, a Do E is des igned. The results of the DoE, and t he dominant process parameters on the v oid formatio n, wire s w e e p a n d w a r p a g e a r e d i s c u s s e d i n Section 5.2. Based on t he acquired results, the quality feature s, which are stron gly influenced by the variation in the process para meters, ar e deter mined. In Section 5.3 the i nvestigations to assess the suitability of the D EA as an in-sit u cure monit oring for the transfer molding process are show n. At first, for a better u nderstanding of the DEA as an online monitoring m et hod, DEA results are correlated with standard l ab oratory tech niques of DSC and rotational v isco meter. T he applied ap proaches for correlation o f the methods are introduced in S e c t i o n 5 . 3 . 1 . S u b s e q u e n t l y , t h e i m p a c t o f t h e p r o l o n g e d s t o r a g e durati on, hu midit y and the bat ch variations on the cure behavior of EMC 1 is st udied with DEA in -situ in transfer molding process. The obtained DEA resu lts are co r related with the rheol ogy results. The results of t he correlation of the DEA with DSC and rotati onal r heometer as w ell as the feas ibility of the DEA as an in-situ cure monitoring in transfer molding process ar e given in Section 5.4. 5.1 Prelim inary Experiments of Process Param eters Preliminary experiments of proce ss parameters are pe rformed to investig ate three aspects. T he first aspect is to exa mine the do minant process para meters on void fo rm ation, wire sweep and warpag e. For this reason, molding te mperature, holding pressur e, preheat ti m e an d transfe r speed are selec ted a s molding parameters. In order to define a suitable process windo w, which does not lead to any inco mplete filling of the package for the selected m olding parameters, thr ee steps a re applied for process analy sis. In the first step, an experimen tal setup with 13 experimental p oints is condu cted to test the limitations of the pro cess an d to dec ide for a suitable r ange of the pro ces s window which allow s a complete filling of the p ackage. Th e m o lding parameters are varied as f ollowing: te mperature between 155 °C – 185 °C, preheat time between 0 s – 20 s, t ransfer s peed between 0.5 mm/ s – 6.5 mm / s a nd holding pressure between 80 bar – 180 bar. The de monstrators are molded wit h cri tical parameter combi nation s such as fast transfer speed with a low t emperatu re a nd no preheat time to analyze whether the cavity is fille d compl etely or whether the selecte d process paramet er combinatio ns cause inco mp lete filling of the demonstrator or stron g sticking of the molding material at the cull area, which req uires long cleani ng time of the cavity after the cycle is over. The selected proces s par a me ter comb inatio ns fo r t his experiment and the results in te rms of incom plet e filing of the demonstrator are given in A ppendix A1. 5 Preliminary Exp eriments and Results 54 Based on the results from the first step of process analysis, t he pro cess window is s elected , which as sures the complete filling of the de monstrator. The selected process window of the molding para meters and the levels are shown in Table 5.1. Table 5. 1: Proc ess parameter s and levels used in the D oE for pr eli minary exp erime nts Factor s Level -1 0 +1 Molding temperature [°C] 165 175 185 Holding pressure [bar] 80 110 140 Preheat time [s] 0 8 16 Transfer speed [ mm/s] 1.5 4 6.5 In the second step of the p rocess analy sis, an additi onal set o f exper iments is con ducted with t he defined range of the proces s wind ow as show n in Table 5.1 to determine whether package q uality can be improved and void free packages can be obtained within this sel ected process wi ndow. Since th e selected process window will be used also f or the main experiments, w hic h includes an optimi zation step, it i s important to verify that the voids can b e diminished within the selecte d process parameter s. Otherwise , a r eal opti mum pro cess pa ramet er c ombinati on for voi d fre e pac k ages lies outside of the selecte d proces s window and cannot be achieved with the defined process window. Voids are one of the e asily investigated quality features in compari son to warpa ge and wire sweep, thus for this feasibilit y analysis of the pr ocess window only the void formation is evaluated. In addition, the impact of vacuum is also investigated to d ecide whether the vacuum has si gnificant impac t o n void formati on and should b e used during the experi ments throu ghout this work. Therefore, an addi tional set of 9 experi mental runs is perfor med. The select ed pr ocess para meter combi nations and the results of void formation analy sis are given in Appendix A2. Based on t he obtained results, it is obse rved that the sel ected proces s range of the proces s parameters yields void free package s a nd the vacuum sh ould be used during t he rest of t he experi ments in this study since it shows a positive i mpact on r eduction of the void s in the package. These t w o s t e p s o f p r o c e s s a n a l y s i s d o n o t i n v o l v e a d e t a i l e d i n v e s t i gati on of th e quali ty characteris tics an d are done o nly to define t he processing conditions a nd limitatio ns of t he transfer molding process t o prepare a suitable process windo w for the third step, which is the main focus of this chapter. In the third and mai n step of the process analysis, a detailed analy sis of the influenc e o f process paramet ers on void formati on, wire sweep and warpage is done. I n previous steps of the pro cess analysis, since the goal is on l y to determine the com plete filling and th e void free packages, o nly the lead fram es without any wire bonds and dummy components are used. In this s t e p o f t h e p r o c e s s a n a l y s i s , t h e demonstrator with a given layout as sh own in Figure 4.2 is util ized. As all the named quality features are analy zed in detail wi th the defined l ayout, t he results of t h i s s t e p o f t h e p r o c e s s a n a l y s i s a r e elementary for definition of the e xperiment matrix and the qu al ity features which will be then analyzed in t he main e xper imen ts. Thu s, th e re sult s of this mai n pr ocess analy sis are the focus of the pre liminary experi ments an d they will be give n in detail. To identify the d ominant process parameters, DoE is generated and desi gned in a way that only one process parameter is varied in e ach paramet er set. As previously exp lained i n Chapter 2, s uch kind of experimental de sign is called one-factor-at-a-time ( O F A T ) w h e r e a d i r e c t i m p a c t o f i n d i v i d u a l p r o c e s s p a r a m e t e r s o n the quality char acteristics can be identifie d. On th e o ther hand, the interacti ons between the pro cess parameters and t he qua dratic influences of the process para meter s on the package quality can not be studied with this design. Only a linear correlation between th e input p arameter such as varied p ro cess parameters and output parameters such as quality characteristics is possible. 5 Prelimi nary Experi ments and Re sults 55 In OFAT design four p rocess paramet ers; molding temperature (T) , transfer speed (v), preheat time (t) and holding p ressure (P) are set in three levels, which gives a lt ogether ni ne para meter combina tions. In addition, one central point, that i s t he middle of three levels f or eac h pro cess pa ra meter, a nd t hree addition al extr eme cas e combinati ons are supple mented in the Do E suc h a s pa ramet er set no. 2, no. 3 and no. 12. Extre me cas e c ombinations are t he parameter s ets wh ich affe ct the mat erial viscosi ty at most such as low temperatures, s hort pre heat time a nd very fast tran sfer speed. Experi ment no. 5 is the central point, where all the pr ocess parameters are in their middle lev el. In total 13 different combinat ions are studied and each para meter set is run 5 times to maintain repea table results. Considering that the mold tool has two cavities, overall te n samples are investigated f or eac h parameter set. The experi mental design f or the preli minary experi ments is illustrated in Table 5.2. In all experiment al designs studied throughout this work, the parameter set no. is arrang ed based o n the ease of var ying t he process parameter. C onsidering t he fact that varying the temperature be tween the param eter set number s requires the longest time u ntil to reach the set te m perature, the experi me ntal pla n i s seq uenc ed fro m l ower temperat ure to higher tempe rature. Table 5.2: E xperimental des ign for the p reli minary experime nts Parameter set no. T [°C] v [mm/ s] t [s] P [bar] 1 165 4 8 110 2 165 1.5 0 80 3 165 6.5 0 140 4 175 1.5 8 110 5 175 4 8 110 6 175 4 0 110 7 175 4 8 80 8 175 6.5 8 110 9 175 4 16 110 10 175 4 8 140 11 185 4 8 110 12 185 6.5 16 140 13 185 1.5 16 140 The second aspect studied in preliminary experiments is the ide ntification of the quality characteristics, which are strongly influenced by the process parameters. Accord ingly , a mong void for mation, wire sweep an d warpage, the q uality chara cteristics, w hich ar e signi ficantly influenced by t he change in the p r o c e s s p a r a m e t e r s a r e d e t e r m i n e d . T h i s i s a n i m p o r t a n t a s p e c t since this work ai ms to i mprove the package quali ty with the variations of t he process par ameters, t hus only the qual ity features whic h ar e greatly affected by the varia tion s in th e process param eters ar e r eleva nt f or t his work. Third aspect of t he pre liminary experiments is t o anal yze the s uitability of the layout of demon strat or. This w ork co nsid ers the wir e bon ds on the la yo ut as mec hani cal structures in which their deformatio ns due to the selected process para meters a re the focus. Hence, it i s i m p o r t a n t t h a t t h e s e l e c t e d la y o u t f o r 5 Preliminary Exp eriments and Results 56 the test vehicl e is qualified to study the influence of process parameters on wire s weep. To evaluate that, the layout of the test vehicle is tested with preliminary exper im ents in ord er to dete r min e wheth er the wire bonds withstand the extre me process p arameter combinations such as high transf er speed, short preheat time an d low mol ding temperat ure so that no w ire bond l ift-off occurs due t o sele cted process paramet ers. 5.2 Results of Preliminary Process Exper iments In t his secti on the results of preliminary experi ments are give n where t he influenc e of the i ndividual process parameters on the void f ormation, wire sweep and warpag e are illustrated re spectively. The quality characteristics, which are strongly influenced by the p rocess para meters are deter mined. 5.2.1. Identification of Significant Process Parameters Before the results of t he qualit y characteristics are shown in this section, it is i m portant to emphasize that all the examinations on the quality characteristics are pe rformed after the PM C process. First, th e demonstrators are molded with t ransfer molding process a nd subs equently transferred to an oven for PMC pro cess. PMC is done at 180 °C for 4 h to achieve complete polymerizat ion of the EMC. The results of the investigations on the influence of t he process p arameters on the void formatio n, warpage and wire sweep ar e given in followi ng. Voi d For mation In Figure 5.1 the results of the void formation with r espect to 13 experimental runs (Table 5.1) are shown. In this work not only the number of v oids is measured, b ut als o th e area of the voids is eval uated. The r eason f or t hat is, that a pac kage may contai n l arge nu mber o f vo ids b ut the voi ds ca n ha ve very small areas. On the contra ry, a package may have a lo w number o f voids, however, those voids can have very large areas, which may be c ritical for package quality . He nce, analysis of the number of voids as we ll a s th e ar ea o f v oid s ca n g ive an i dea ab out the p ropo rtio n of the number to the corresponding area of th e voi ds i n the pac kag e. T he nu mber of voi ds an d the ar ea o f voids with respect to parameter set no. can be see n i n Fi gure 5.1. Figure 5.1: Effect of processing par ameters on void for mation, ave rage number of voids with respect to 13 experimenta l runs (left), and corre sponding a verage area of voi ds with respect to 1 3 expe rimental run (right) It is obvious, that the nu mber of voids for med i n the molded pa ckage is influenced b y diffe rent parameter settings. Some parameter combina tions cause large void formatio n, whereas s ome process p arameter combi nation s lead to less void formati on in the packag es. For i nstance, the p ackages, which are molded with para meter set no. 3, show a low n umber of voids i n c ombina tion with very small area s. On t he other hand, one of the extre me pr ocess p aram e ter such as parame ter set no. 2 causes large void formation in the package. Figure 5.2 displays the exa mple of such package s with l arge vo id f ormation as well as the molding package with very little void for m ation to visualiz e th e eff ect of processing parameters on 123456789 1 0 1 1 1 2 1 3 0 2 4 6 8 10 12 14 16 18 Average number of voids Parameter set no. 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 6 7 8 9 Average area of voids [mm 2 ] Param ete r set no. 5 Prelimi nary Experi ments and Re sults 57 the void f ormation in t he p ackage. The pac kage o n the left han d side in Figure 5.2 is molded with an experi ment run no. 10, from wh i ch very low void formation is ob serv ed in the packages. As a m atter of fact, in some of the packa ges, wh ich are mold ed with exp eriment run no. 10 n o void formati on in the package is observed. In Figure 5. 2 (left), one of suc h molded p ackages is presented. In addition, in Figure 5.2 (middle), another package is depicted, which is molded with the experimen tal run no. 2, and has ma ny large voids having differ ent sizes in the pa ckage. Figure 5. 2: SAM images of the molding packa ges which show the i nf luence of the proc essing con dition on the void for mation in the molde d packages. The package which is m ol ded with experim ental run no. 10 sh ows no voids (left), the package w hich i s m o lded w ith experimen tal run no. 2 shows many v oids (middle). To analyze the positions of the voi ds on the l ayout, the layout of th e dem onstrator is div ided into fo ur zones a nd the voids detected b y the software are i ndicated with yellow circl es on t he image exemplar ily (right) As se en i n pack ages dep icted in F igur e 5. 2, v oids are f or med in different positions in the package. Identification of the positions of the voids in the package is impo rta nt to d etermine t he zones, where the voids are formed at most and to define the critical areas o n th e la yout. For t his reason, the voids ar e divided into four different zones as illustrated in Figure 5.2 (r ight), where the z one 1 is the are a close to th e gate and the zo ne 4 i s the are a whi ch is fa r fr om th e ga te. Figure 5.3 depicts the average number of voids, and the corresponding area of voids which are observed i n differe nt zones on the lay out of the mold ed p acka ge. Figure 5. 3: Void form ation in di fferent zones on the layout of the packa ge w ith respect t o different p roce ss parameters, the num ber of voids formed in four differe nt zones (left), the corresponding are a of the voids in four different zones (right) Apart fro m the extreme process parameter combinations, s uch as pa ramet er se t no . 2, in whi ch very large voi ds are formed (see Figure 5.2 middle), the voi ds are f orme d us ual ly in zon e 4, w hic h i s far away from the gate. On the other hand, reduced void f ormation is obs erved near the gate area. According to the DoE plan given in Table 5.2, when the vo i d for mation in the parameter set no. 6, 5 and 9 are compare d with each other, t he infl uence of prehe at time o n the void for mation can be analyzed. Similarly , when the void forma tion in the parameter set no. 1, 5 an d 11 are co mpare d, t he i mpac t of th e 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 Average number of voids Parameter set no. Zone 1 Zone 2 Zone 3 Zone 4 123456789 1 0 1 1 1 2 1 3 0.0 0.5 1.0 1.5 2.0 Average area of t he voids [mm 2 ] Parameter set no. Zone 1 Zone 2 Zone 3 Zone 4 5 Preliminary Exp eriments and Results 58 mold temperature o n the void for mation c an be analy zed. The inf l uence of ho l ding pressure on the vo i d formation can be observed by comparing the results of the param eter set no. 7, 5 and 10. Moreover, the effect o f transfer speed can be deter m ined by comparin g the re s ults of parameter set no. 4, 5 and 8. The influence of t he individual process para meters on the void for m ation by co m paring th e aforementioned paramet er set numbers are depicted in Figure 5.4 and Figur e 5.5 . Figure 5.4 : Influence of transfer speed of plunger (left) a nd h olding pressure (r i ght) on the aver age area of voids Figure 5.5: Influence of mold tempe rature (left) a nd preheat t i me (right ) on t he averag e area of v oids Among four varied process parame ters, transfer speed and holdin g pressure show the major impa ct o n the void formation. By increasing transfer speed, less voids are formed in the package (Figure 5.4 left). The largest in fluence is observed in ho l ding pressure. The void s are formed at low holding p ressure and with increasing the holding pres sure, the void formation is r ed uced (Figure 5. 4 right). According to Figure 5.3, whe n the voi d for mati on i n para meter s et no. 7, 5 a nd 10 a re compared which delivers the influence of holdi ng press ure, it can be seen that t he number o f voids as well as t he correspon ding area of th e voids, especially which are f ormed in the zone 4, are de crease d by incre asing the holdi ng pressure . On the other ha nd, as seen i n Figur e 5.5, molding temp erat ure a nd preheat time show only slight i mpact on the void formation. Th us, void formation is not strongly aff ected by the change in mold temperature or preheat time. Wire Swe ep In Figure 5.6, the e ffects of processing conditions on the wire sweep of the long wire bonds a ttached in near gate and far from gate area as well as s hort wire bond att ach ed in n ea r ga te a nd f ar f rom ga te a rea are presente d. 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Average area of voids [mm 2 ] Transfer speed [mm/s] 80 90 100 110 120 1 30 140 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Average area of voids [mm 2 ] Holding pressure [bar] 165 170 1 75 180 185 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Average area of voids [mm 2 ] Mold temperature [°C] 02468 1 0 1 2 1 4 1 6 1 8 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Average area of voids [mm 2 ] Preheat time [s] 5 Prelimi nary Experi ments and Re sults 59 Figure 5. 6: Effect of processing conditions on long wire bonds l ocated in ne ar gat e and f ar fro m th e gate (left), and on s hor t wire bonds located in ne ar gate and far fr om the gate (right). F or the represented co mparison of the p ositions and the len gths, wire bonds w ith a direction o f 4 5 ° to the gate are chosen. According to Figure 5.6, the long wire bonds attached in both p ositions on the test vehicle, namely near gate and far from the gate area are str ongly i nfluenced by the process parameters. Lo ng wire bonds attached close to the gate area s how more wire sweep compared t o the long wire b o nds attache d f ar from the gate. Similarly, the short wire bonds attached close to the gate area sho w mor e wire swee p comp ared t o t h e s h o r t w i r e b o n d s l o c a t e d f a r f r o m t h e g a t e a r e a . M o r e o v e r, long wire bonds exhi bit larger wire sweep in c omparison to the s hort wire bon ds. Nev ertheless, in c ertain parameter combinations, short wires attached at the close to the gate area also exhibit lar ge w i r e s w e e p . S h o r t w i r e b o n d s r e p r e s e n t especially large wire s weep in para meter set no. 1, 3, 8 a nd 12 . According to Table 5.2, those are the processing conditi ons, w hich are c haract erized by an incre ased transfer speed. In particular, in p aramete r s et n o . 3 , w h e r e t h e e x tr e me p ro cess parameter combination is s electe d, the shor t wire bo nds represent excessiv e wire sweep. Figure 5.7 depicts the influence of the processing conditions o n the lo ng wire bonds which are attached at differe nt angles t o the g ate, namely at 90 ° , 180 ° and 45 ° in near gate and far fro m the gate area on the test vehicle (see Figure 4.2 for th e layout). Figure 5.7: Effects o f the proc essing conditions on the differe nt dire c tion of the lo ng wire bonds w hich are attached at 90 ° , 180 ° , and 45 ° t o gate in nea r gate (left), and far from the gate area (right ) Different processin g parameters show the similar i mpact on the w i r e b o n d s w h i c h a r e a t t a c h e d a t different angles to the gate. The tendency of the wire sweep wi th respect t o the different proce ss parameters is very similar in all angles of the wire bonds. Non etheless, sli ght variations in the wire 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Wire sweep [%] Parameter set no. Long w ire bonds - Near gate Long wire bonds - Far fr om gate 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Wire sweep [%] Parameter set no. Short w ire bonds - Near g ate Short wire bonds - Far from gate 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Wire sweep [%] Parameter set no. Long wire bonds - Near gate - 90 ° to ga te Long wire bonds - Near gate - 180 ° to gate Long wire bonds - Near gate - 45 ° to ga te 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Wire sweep [%] Parameter set no. Long wire bon ds - Far from gate - 90 ° to ga te Long wire bon ds - Far from gate - 180 ° to ga te Long wire bon ds - Far from gate - 45 ° to ga te 5 Preliminary Exp eriments and Results 60 sweep are obser ved within diff erent ang les of t he wire b onds to t h e g a t e . A m o n g d i f f e r e n t w i r e b o n d angles t o gat e, the mean values of t he wire sweep f or the long wire bonds whi ch are attached in near gate area with 180 ° t o t h e g a te i s s li gh tl y l o we r co m pa r e d t o t he m ea n v a lu e s of t he wire sweep for the wires bond ed at 90 ° and 45 ° to the gate. Similar results are also obs erved for the long wi re bon ds att ache d far fro m the g ate (Figure 5.7 right) . Figur e 5. 8 i llus trates t he i nflue nce of the proce ss para meters on t he short wire bonds attached at 9 0 ° , 180 ° and 45 ° angle to th e gate which are bonded in near gate (Figure 5.8 le ft) a nd far from the gate ar ea (Figure 5.8 right). Figure 5.8: Effects of t he proce ssing condit ions on the d i ffere nt direction of the short wire bonds which are attached at 90 ° , 180 ° , and 45 ° t o gate in nea r gate (left), and far from the gate area (right ) For the short wire b onds, especially for the ones whi ch are b on ded far fro m t he gate area, it is difficult to identify any difference in wire sweep for different angles o f th e wire bond due to min imal wire swee p observed in all wire bond directi ons (Fi gure 5.8 right). For th e short wires attached in near gate area, especially for the pa rameter set no. 1, 3, and 8, where large w ire sweep occurs, the difference in the wire sweep between the diff erent angles of the wir e bon ds can be rec ognized ea sily. In these param eter sets, the mean values of the wir e swee p for the wir e b onds att ached a t 45 ° to the gate is slightly higher i n comparison to t he mean values of the w ire sweep for t he wire bo nds attached at 180 ° and 90 ° to the gate. Figure 5.9 an d F igure 5.10 show the influence of transfer speed , m o ld te mperature, preheat time as well as ho l d ing pressure on the wire sweep of sho rt wire bonds and l ong wire bonds at tached in near gate and far fr om th e gate area. Figure 5. 9: Influence of mold te m perature on wir e sweep (left), influe n ce o f transfer speed on wire sw eep (righ t) for shor t and long wire bonds attache d in nea r and far from the gate are a 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Wire sweep [%] Parameter set no. Short wire bonds - Near gate - 90 ° to gate Short wire bonds - Near gate - 180 ° to gate Short wire bonds - Near gate - 45 ° to gate 123456789 1 0 1 1 1 2 1 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Wire sweep [%] Parameter set no. Short wire bonds - Far from gate - 90 ° to gate Short wire bonds - Far from gate - 180 ° to gate Short wire bonds - Far from gate - 45 ° to gate 165 170 17 5 180 185 0 1 2 3 4 5 6 7 8 Wire sweep [%] Mold temperature [°C] Short wire bon ds - Far from gate Short wire bonds - Near gate Long wir e bonds - Fa r from gate Long wire bonds - Near gat e 1 . 01 . 52 . 02 . 53 . 03 . 54 . 04 . 55 . 05 . 56 . 06 . 57 . 0 0 1 2 3 4 5 6 7 8 Wire swee p [%] Transfer speed [mm/s] Short wire bonds - F ar from gate Short wire bonds - Near gate Long wire bo nds - Far from gate Long wire bonds - Near gate 5 Prelimi nary Experi ments and Re sults 61 Figure 5. 10: Influe nce of preheat t ime on wire sweep (left), in fluence of holding pressure on (right) for short and long wire bonds attached i n near and far from the gat e area Among fo ur process parameters, transfer speed a nd mold temper at ure are found as the most significant process parameter s on the wire sweep. As seen in Figure 5.9, ra ising the mold tempe ra ture leads to less wire sweep for short wire bonds a nd long wire bon ds attac hed in near gate and far from the gate area. Increasing transfer speed, however, causes more wire sweep on s hort and long wire bonds. As previ ousl y shown in Figure 5.4, increasing transfer speed causes less void formation in the package which is the opposite effect of transfer speed observed on wire sweep. There fore, to achieve be tter package quality, whic h in volves imp rovi ng bo th quality featur es, a comp romi se s h ould be done when defining opti mum p r o c e s s p a r a m e t e r s . O n t h e o t h e r h a n d , a s s e e n i n F i g u r e 5 . 1 0 , the vari ations in holding pressur e and preheat time do not de monstrate any significant changes in t he w i r e s w e e p f o r s h o r t a n d l o n g w i r e b o n d s both in near gate and far from th e gate area. O nly for the shor t wire bonds attached near to gate, increasing preheat time causes s lightly more wire sweep. On the oth er hand, the impact o f the diffe rent process parameters on the short wire bonds at the far fro m the gate area cannot be d etermined clearly as the short wire bonds at f ar fro m the gate area illustrate mini m ized wire sweep almost in all para meter combinati ons (see Figure 5. 8 right). Warpage For the warpage analysis four line contours, namely line 1, li n e 2, line 3 and line 4 are set on t he mol ded package, which are already depicted in Figure 3.20 and the devi ati ons in the z-dir ection are measure d along these lines. The maximu m valu es obtained i n z -directio n o n t he s urface of the package deliver the maximu m warpage, which is present ed in Fi gure 5. 11. In addition t o the maxi mum war page value measur ed for eac h of those lines, the average warpage is al so c alculated, which represent s the mea n value of all four lines ( Fig ure 5.11 right). 02468 1 0 1 2 1 4 1 6 0 1 2 3 4 5 6 7 8 Wire sweep [%] Preheat time [s] Short wi re bonds - Far from ga te Short wi re bonds - N ear gate Long wire bon ds - Far fro m gate Long wire bon ds - Near gate 80 90 100 110 1 20 130 1 40 0 1 2 3 4 5 6 7 8 Wire sweep [%] Holding pressure [bar] Short wi re bonds - Far from gate Short wi re bonds - Near gat e Long wire bo nds - Far from gate Long wire bo nds - Near g ate 5 Preliminary Exp eriments and Results 62 Figure 5. 11: M aximum warpage va lue for each measured line on the m olded packa ges with respec t to 13 process pa rameter no. (left ), average val ue obta ined c onside ring all four li nes tog ether wi th resp ect t o parameter set no. (right) Based on t he results obtained from the warpage measurements, it is observed that the s urface of th e molded packages bends upwards in all packages and the data of t he warpage has a positive value. This indicates that the type of the warpage in the package is convex . Nev ertheless, based on the results of all 13 pr ocess parameter set nu mbers, w hich are illustrated in Figu re 5.11, the a verage of the maximu m warpage value lies under 100 µm. However, as it can be seen fr o m t he pl otted curv es, the re are also large sta ndard deviations within a singl e process paramet er set , such as parameter set no. 8. Moreover, the standard deviation in su c h parameter sets, e.g. parameter s et n o. 8 show a lar ge scatter that it co vers all the range of variations i n warpage values within the 13 par ameter se t num bers. Thus , to ana ly ze the differen ces in the warpag e values m ore preci sely , the measur ed warpage for each molded part for all paramet er set numbers is plotted in Figure 5.12. Consideri ng le f t a n d r i g h t c a v i t y a s w e l l a s t h e f i v e repetitions of each p arameter set , ten parts are an aly zed for e very single p arameter set, which are represented between the black vertical lines in Figure 5.12. Th e warpage of overall 130 parts are illustrated in the diagram. Figure 5. 12: Maximum wa rpage values i n four line contour s for all me asured parts. The points betw een the black lines be long to one parameter set beginnin g from the parameter set no. 1 until parameter set n o. 13. For instance, the number of parts be tween 70 and 80 belongs to the parameter set no. 8. 123456789 1 0 1 1 1 2 1 3 0 20 40 60 80 100 120 140 160 Warpage [ m] Parameter set no. Lin e 1 Lin e 2 Lin e 3 Lin e 4 123456789 1 0 1 1 1 2 1 3 0 20 40 60 80 100 120 140 160 Warpage [ m] Parameter set no. Average maximum values of four lines 0 1 0 20 30 40 50 60 70 80 9 0 100 110 120 130 0 20 40 60 80 100 120 140 160 Line 1 Line 2 Line 3 Line 4 Warpage [ m] Numb er of pa rts 5 Prelimi nary Experi ments and Re sults 63 The results show that in some pa rameter sets, such as parameter s e t n o . 6 , 7 a n d 8 , t h e r e a r e l a r g e devia tions between the measu red maximum warpage values within o ne singl e proce ss parame ter set. For instance, for p arameter set no. 8 the warp age valu es vary f rom 20 µm to 160 µm. On the contrary , although there is 20 °C differenc e in tem perature bet ween the n um ber of parts until 30, and the number of parts after 80, no big variation is observed in maximum warp age. Therefore, based on the warpage values shown in Figure 5.12 it is evi dent that, the deviati on o f the warpage values within one single paramet er set is much larg er in compari son to the deviation i n the warpage val ues between 13 different par a m eter sets. It is important to mention that, during the measurements, i t is re cognized that across the measured lines, in s ome ca ses there may be one or t wo p oint s ha ving very high v alues in the z directio n possibly due to some surf ace artifact s on t he sur face of the molded packa ge. On ly considering the distinct maximu m value as a w arpage, which may be caused possibly due t o some su rface artifacts can lead to false interpretations. Thus, to assure the r esults, in addition to the maximum point observed al ong the lines which are illustrated in Figure 5.12 , the area under the four li nes, nam ely line 1, line 2, line 3 and line 4 (see Figure 3.20) are al so calculated to build an ov erall image in terms of the package surface. The r e s u l t s o f t h e a r e a u n d e r t h e c u r v e o f t h e l i n e s a r e c o m p a r e d w ith the re sults of the maximum point observed on t he lines. However, the warpage valu es obtained by calculating area under the lines also show similar results as the maximum warpage value shown in Figu re 5.12. No significant difference in the warpage values o btained from t he area under the curves are observ ed betw een the differ ent proces s parameters a nd still a lar ge scatter exi sts within a single par a m e t e r s e t . T h u s , h e r e b y t h e r e s u l t s a r e approved with an additional consid eration. Therefore, consi deri ng the obtained results, it can be stated that, alt hough the proces s par ameters are significant ly varied such as 20 °C diff erence in the mold temperature between the process parameter sets, whic h may indee d influence the package warpage , no significan t variations in the warpage are observed between the different process parameters. Addi tional ly , the dev iati on o f th e war pa ge val ues ob serve d wit h in one para meter set i s fou nd much lar ger i n co mpar ison to the devi atio n of the war page valu es b et ween different process parameter sets. 5.3 Preliminary Investigations of Material C haracteristics In this sectio n the preliminary experi ments are intro duced, whi ch are conducted to assess the suitability of th e DEA method to o bserve th e possible variations in the mat erial characteristics of EMC 1 in -situ in the transfer mol ding process. How ever, before explaining the DE A results, it is crucial t o understand and interpret the DEA results corr ectly. Thus, the obtained DEA signals are correlated and compared with rotational rheometer and DS C measu re men ts. The app roaches used for the correlation of the DE A with DSC and rotational rheometer are introduced in Section 5.3 .1. Furthermore, the infl uence of prolonged storage duration, humid ity and batch variations on the material characteristic s of EMC 1 are studie d. Rotati onal rheo meter a nd squeeze flow rheo meter are used to analy ze the variations i n the vi scosity of EMC 1. The precondit ioned materials ar e also m easur ed with DEA in-situ in transfer molding process to e valuate any possibl e changes i n ion viscosities of the material. All measurements performed with DEA in the tr ansfer m olding process in this s ection are conducted with central process p arameters at a te mperature o f 1 75 °C, transfer s peed of 4 mm /s, preheat time of 8 s and a holding pressure of 110 bar. T he experimental approach performed to in vestigate the influence of storage duration, humid ity and batch variations on EM C 1 characteristics are i ntroduced in Section 5.3.2, 5.3.3 and 5.3.4 r espectively . To assure whether humidity and temperature stay constant during humid and dry storage in the chambers and also to contro l the measurements, a data logger Multimetrix DL 53 is used. Humidity and te mperature are recorde d with data logger during the whole storage duration time in the chamber s for each measurement in t his work. To p roduce the sample bars for t he analy sis with t hermal a nd mech anical methods, t he tra ns fer molding pres s Lauffer VS KO 25 is use d. Mo re inf or mati on ab out t he mol d too l and t he ca vity geo metry can be f oun d in Sect ion 3.2. 2. T he results of the measurem ents descr ibed in this section a re given in Section 5. 4. 5 Preliminary Exp eriments and Results 64 5.3.1 Correlation of DEA with Rotational Rheometer and DSC DEA is chos en in this work as an online monitorin g m et hod in tr ansfer mol ding process in order to observe small variations in the characteristics of the EMC. To interpret the information delivered from the DEA correctly , it is essential to understand the course of ion viscosity curve an d the impo rtant characteristics of th e ion viscosity curves. Therefore, the DEA i s c o m p a r e d a n d c o r r e l a t e d w i t h t h e rotational rheometer and DSC meas urements. The specific d etails a bout the DEA -Rotational Rheomete r and DEA- DSC correlatio n are e xplained in this s ection respectiv ely. DEA-Rotational Rheometer Correlation DEA is a mo nit oring technique where the m obility of ion s in a s am ple is measured during the polymerization of EMC and indicated as ion viscosity as explain ed previously in Chapter 2. Since t he rotational rheometer measurement is a standard conventiona l lab orat ory method t o me asure the shea r viscosity of the material and to analy ze th e rheological behavi o r o f th e E M C , d y na m i c v i s c o s i t y i n ot h e r words, shear viscosity is m ore s traightforwar d in understanding compared to the ion viscosity . Thus, the correlatio n of the ion vis cosity t o shear visc osity can help to comprehend the course of i on vi scosity curve. Simultane ous rotati onal rh eometer-D EA measurement is per formed to dete rmine the correla tion between ion visc osity and the dy nam ic viscosity. The progress o f curing reaction, w hich is observed simult aneousl y with DEA and rota tional r heometer ar e correl ated . Correlation of D egree of Cure Obtained from D EA with DSC The DEA signal represents the c uring reaction of the EMC from t h e b e gi nn in g o f th e u n c ur e d st a ge of epoxy resin until the end of cure. An ion viscosity curve shows the p rogre ss of reacti on ste p by step during poly merization of EMC, h owev er, t he degree of cure at di fferent stages of the reaction cannot b e directly measured with DEA. DEA can only deliver the ratio of the crosslinking degree at a corresponding ti me, by taking the maximum ion viscosity as 100 % a nd mi nim um i on vi scos ity as 0 % crosslinki ng degree. However, that does not exa ctly reflect t he real situation of crosslinking degree in the EMC because ne ither the cr osslinking degre e r eaches 100 % a t maximum ion viscosity nor th e poly m e r has 0 % crosslinking degree at the minimu m ion visc osit y. EMC already star ts curi ng at earl y stages of the reaction ev en before reaching the minimum i on vis cos ity. For this reas on, to determine the actual cross linking d egree of EMC, DS C measurements are perfor med and the reactio n enthalpy of EMC 1 is measured and correlated with the ion viscosity curve o btained fr om DEA. To e xamine the degree of curing in EMC 1 at differe nt st ages of cure reaction, the molding proc ess is stopped after the defined cy cle times such as 30 s, 6 0 s , 90 s, 120 s, 18 0 s, and 2 4 0 s , t h e n t h e s a m p l e b a r s a r e s u c c e s s f u l l y removed from the mol ding machine. To suspend the cure reaction after the ter mination of the molding process, the sample bars are co oled down in a liquid nitrogen c hamber and i mmediately submitted to DSC to measure the residual heat of reactio n of the samples cor r espo ndin g t o th e portio n that is not polymerized during molding. In addition to EMC 1 pellets, which are molded at various lengt hs of cycle t i m e s i n t h e m o l d i n g m a c h i n e , 0 h E M C 1 p e l l e t s i n o t h e r w o r d s fresh EMC 1 pellets, which are only thawed i n room te mperature for 1 hour are also measured with DS C to d etermine the initial status of EMC 1. The experimental approach a pplied is shown schematically in Figure 5.13. 5 Prelimi nary Experi ments and Re sults 65 Figure 5.13: E xperimental ap proach to correlate the ion viscosi ty curve w ith reactio n enthalpy obta ined from DSC mea suremen ts, t he mold ing cy cles are termi nat ed after c ert a in times i.e. 0 s, 30 s, 6 0 s, 90 s, 120 s, 180 s , 240 s and the specimen s are cooled down in a liquid n it ro gen co nta iner to ter minate the reacti on and conveyed immedia t ely to DSC measureme n t After the measurement wit h DSC, the residual heat of reacti on o f the samples is measured and the degree of cr osslinking of the s amples at correspondin g mol ding cy cle t ime is cal culated as de scribed in Section 3.3.2. 5.3.2 Storage Duration The impact of the prolonged storage duration o n the characteris tics of EMC 1 is investigated by preconditio ning the samples for 0 h, 8 h, 16 h and 2 4 h in a va cuum ove n at 0 % RH an d 30 °C. Before preconditioning EMC 1 pellets, all pellets a re thawed at room t emperature in a desiccator for 1 hour. The preconditioned EMC 1 pellets are then measured wit h a rotat ional rheometer t o examine the influence of t he st orage duration on the viscosity behavior of EMC 1. Furt hermore, additional pellets which are preconditioned with similar approach are molded in tr ansfer molding process and measured w it h DE A si m ul t a n eo u sl y. E ac h DE A m ea su r em e n t f o r th e pr ec on d i t ioned sample s is rep eated at least 8 times and the average v al ue o f the measurements is calculated . Th e rheolog y behavior of the preconditioned EMC 1 pellets obtained from the rotational rheom eter measurements and the D EA measuremen ts are compa red with eac h other. In order to clarify whether a period of storage time longe r tha n 24 h has an influence on EMC 1 curing characteristics, the storage duratio n is extended until 72 h. T he pe llets are precondition ed additionally for 48 h and 72 h at 30 °C and 0 % RH. The precon ditioned pelle ts are mea sured with rot ationa l rheometer to deter mine the influen ce of the e xtended storage du ration of 48 h and 72 h on the viscosity behavior of the EMC. Moreover, the precondition e d pellets are m olded in transfer mol ding process by monitoring with DEA. The results of DEA are compared with the r esults obtained fr om rotational rheom eter. 5.3.3 Humidity The impact o f the moisture on the EMC chara cteristics is analy z ed by preconditioning EMC 1 pellets in a climate chamber with 90 % RH, at 30 °C. First, all samples ar e thawed in a desiccat or for 1 hour a nd subsequently prec onditioned for 0 h, 8 h, 16 h and 24 h in hu mi d environment. The p e llets with different preconditio ning d urations in humid environ ments are analyzed wi th rotational rheometer under isothermal and n on-isothermal c onditions to understand the effe ct of humidity on dy namic vis cosity of EMC 1. Mo reover, additional pelle ts, which are p reconditioned i n the same way , are molded in transfer molding process and measured with DEA si multaneously. The effec ts of th e humidity on the ion viscosity behavior and the dynamic viscosity behavior of EMC 1 ar e disc ussed. The similar approach as in the storage duration is also used he re in terms of prolonging the storage duration of EMC 1 pellets in a humid environ m ent. EMC 1 pellets are further stored in a climate oven 5 Preliminary Exp eriments and Results 66 at 9 0 % RH a nd 30 ° C for 48 h and 72 h t o obs erve whet her th e p ellets reach any saturation point in terms of water uptake and whet her the ion visco sity is i nfluenc ed by the extended preconditioning in humid environment. The preconditioned pellets are m o lded and me asured with DEA to identify any possible effects of hu midity of EMC 1 on the ion viscosity . To determ ine the moistu re uptak e during the humidity storage time in E MC 1 until 72 h, preconditioned p e l l e t s a r e a n a l y z e d w i t h K a r l - F i s c h e r Titration. To identify the water uptake trend in EMC 1 pellets until 8 h storage duration, additional 2h and 4 h storages are performed and the moisture content of the pellets is measured with Karl-Fischer Titration as well. To understa nd the humidity influence on curing behavio r of E MC in d etail, it is i mp ortant to differentiat e, whether the effect origin ates f rom the extend ed sto rage duration itself only by preconditio ning i n dry environment, or whether the effect resul ts due to hum i di ty storage. Thus, the results obtained from Section 5.3.2 are comp ared with th e res ul ts obtained fro m S ection 5.3.3. Table 5. 3 summarizes the i nvestigations perfor m ed in ter ms of preconditio ning the p ellets in dry and humid environ ments. Table 5.3: P reconditioning of the sam ples in dry and humid envi ronmen t Fresh samples Precondition ing at 30 °C / 0 % RH Preconditioning at 30 °C / 90 % RH 0 h - - - 8 h 8 h - 16 h 16 h - 24 h 24 h - 48 h 48 h - 72 h 72 h 5.3.4 Batch Variations P o s s i b l e a l t e r a t i o n s b e t w e e n d i f f e r e n t b a t c h e s a r e e x a m i n e d b y selecting three batches marked as batch 1, batch 2 and batch 3. Am ong all batches, batch 3 is the o ne characteriz ed by a m i nimu m storage dura tion, whereas batch 1 is charac terized by a longe st storage duration. The rh eological behavior of three batches is analy zed with rot ational rheometer to identify any variations in properties. In addition, DEA measurem ents are performed t o detect possible alterati ons i n the properties of EMC 1 batches i n the transfer moldin g process. 5.4 Resul ts of P reliminar y Inves tigati ons of Mate rial Char acter istics In this section, the results of the char acteriz ation of EMC 1 a r e i n t r o d u c e d , w h i c h a r e d e s c r i b e d i n Section 5.3. The results obtained fro m the simultaneous DEA-Rot ational R heom e ter measuremen t and DEA-DSC correlati on are represent ed i n Section 5.4.1. The obtai ned correlation should help to gain more underst anding o n the cure r eaction of EMC 1 and the progre ss of ion viscosity curve observed with DEA. The results of the impact of the prolonged storage du ration, humidity and batch variatio ns on t he curi ng chara cteris tic s of EMC 1 are giv en i n S ectio n 5. 4 .2. The preconditioned EMC 1 pellets are cha racteri zed with r heological me thods as well as with DE A and the results obtained from the methods are compared. The suitability of t he DEA to detect the possible var iations in the material characteristics of EMC 1 due to stor age duration, humidity and batch variati ons is discussed. 5.4.1 Results of Correlation of DEA with Rotational Rheometer a nd DSC In this secti on, the results of the c orrelation of DEA with rot ational rheometer as well as with DSC method are given respectively . The i mportant featu r es of the ob tained correlations are discussed . Correlation of DEA wit h Rotational Rheometer Measurement Figure 5.14 depicts the results of the si multaneou s DEA-Rotatio nal Rheometer measuremen t, where t he ion viscosity measured with imped anc e spectroscopy at 10 Hz and the shear v iscosity is m easured wit h a rotati onal rhe ometer. 5 Prelimi nary Experi ments and Re sults 67 Figure 5.14: S imultaneous DE A-rotational rhe ometer me asurement cond ucted at isothe rmally at 100 °C measur ing the io n viscosit y wit h an inte rdigital capaci tor at 1 0 Hz and the shear viscos ity w ith rotat ional rhe omet er The results of the simultaneous DEA-rotational rheology measure ment show that the cure reacti on behavior of EMC 1 re presents the similar behavior at the same t ime scale in both methods. At the ti me around 300 s, where the mold ing com pound has its minimum viscos i ty , t h e io n v i sc o s i ty me as ur e d wi t h DEA shows also its mini mum value. When the cure r eaction starts acceler ating, the shear visco sity of material rais e s quickly, correspondingly the io n viscosity of E MC 1 is raising as w ell. T he slop es of the curves, whic h represent th e reaction speed of EMC 1, match very well with each other in both met hods. After around 2000 s the slo pe of the dynamic viscosity curve st ar ts decreasi ng which indicates that the reactio n co mes slowly to the e nd. At the same time, the sl ope o f the ion viscosity curve decreases as well. When the dy namic viscosity r eaches its maxi mum v alue aft e r aroun d 4000 s and no signifi cant c ha n g es i n t he v i sc o si t y o cc u rs a n ym o re , t h e i o n v is co s i ty al s o r eaches its maximum val ue. Theref ore, the si multaneou s DEA-rotational rheology m easurement s hows that t h e i o n v i s c o s i t y o f E M C 1 observed with DEA s hows very good correlation to the shear visc osi ty m ea sure d with the rota tion al rheom eter. Correlation of D EA with DSC measurement A typical DEA curve measured wit h EMC 1 is show n in Figure 5.15 (right). The indicated points on the di a gr am o f t he DE A cur v e a re t he sa mp l es , w hi ch ar e m ol de d f or 30 s, 60 s, 90 s, 120 s, 180 s and 2 40 s in transfer molding and subsequently measured wit h DSC to deter mi ne the r esidual heat of reaction. Figure 5.15 (left) illustrates th e results of measured residual heat of reaction of the samples which ar e molded i n correspondi ng cy cle times. Moreover, in Figure 5.15 ( right) the d egree of cure calculated based o n the DSC res ults according to the selected points are a l so implemented in t he DEA curve to illustrate the correlation of the progress of the ion viscosity with the degree of cure sche matically. Additional information derived fro m the DSC measure ments such a s heat of reaction and T g for different cycle times are listed in Table 5.4. 0 1000 2000 30 00 4000 5000 60 00 1E+04 1E+05 1E+06 1E+07 1E+08 1E+09 Shear viscosity [Pas] Time [s] Shear viscosity - 1 Shear viscosity - 2 100 °C 1E+09 1E+10 1E+11 1E+12 1E+13 1E+14 1E+15 Ion viscosity - 1 (10 H z ) Ion viscosity - 2 (10 H z ) Ion viscosity [Ohm*cm] 5 Preliminary Exp eriments and Results 68 Figure 5. 15: Results of the non-isothermal DSC curves for the s amples, which are molde d for different moldin g cycle time s of 30 s, 60 s, 90 s, 120 s, 180 s and 2 40 s in tran sfe r moldin g (left), DEA curve w ith a calculated degree o f cure fro m DSC resul ts for th e corres ponding cy cle tim es (right) Table 5.4: Results of non-is otherm al DSC mea surements w i th diff erent moldi ng cycle ti mes Represented points Cycle ti me [s] Reacti on onset [°C] Reaction yield [J/g] T g 1 st Run [°C] T g 2 nd Run [°C] Degree of cure [%] A 0 97 25.1 31 177 - B 30 94 13.5 78 167 46 C 60 109 8.1 91 163 68 D 90 118 5.2 105 162 79 E 120 133 2.0 111 162 92 F 180 152 0.6 135 162 98 G 240 162 0.2 140 161 99 Based on the DSC results (Figure 5.15), it is a pparent that the residual heat of reaction of the samples decreases with increasing cy cle ti me in dicating the progre ss of curing. At 30 s molding ti me, the ion viscosity of EM C 1 first r eaches its minimum value, where the m a terial has the lowest netw ork density (Figure 5 . 15 (right), point B) and large heat of reaction (Tabl e 5.4). As the cure reacti on pro pagates , the ion viscosity escal ates indicating the increase in the network density . By the time at around 2 40 s, ion viscosity reaches the plateau revealing that the cure reaction is almost completed. This correlates very well with the DSC results, as the remaining heat of reaction at p o i n t G w i t h 2 4 0 s c y cl e t i me i s v e r y l o w , which signifi es that the cur e r eaction is a lmost finished. Based on the measured residual heat of reaction, the degree of cure with res pect to sel ected points is c alculate d (Table 5.4), which is also illustrated in Figure 5.15 ( right). The r esults apparen tly show th at the progr e s s i n t h e i o n v i s c o s i t y o b s e r v e d w i t h DEA corr elates very well with t he degree of cure re sults, where with increasing in ion viscosity, the degree of cure of EMC 1 increa ses. When the cu re r eaction is al most over at 240 s, the mater ial reaches its maxi mum network densit y . In f act, T g of t he samples also incr eases with in creasing network density. Highest T g in the first run can be observed with 240 s molding. Theref ore , consid ering the results observed fro m the DSC, it is evident that the results of the DE A show good correlation with the results of the DSC. T he i on vi scos ity expres ses t he prog re ss of th e c ur e reacti on a nd the networ k de nsity of EMC 1 excellently . 0 50 100 150 200 250 0.00 0.05 0.10 0.15 0.20 Heat flow [W/g] Temperature [°C] A (Uncure d) B (30 s curing) C (60 s curing) D (90 s cu ring) E (120 s curing) F ( 180 s cu ring) G (240 s c uring) 5 Prelimi nary Experi ments and Re sults 69 5.4.2 Results of Investigations of Material Chara cteristics I n t h i s s e c t i o n , t h e r e s u l t s o f the investigation in regard of th e infl uence o f the pro longe d stor age duration, humidity and the batch variations on th e cure reacti o n of EMC 1 are pre sent ed. The var iati ons in the viscosity o f EMC 1 are ch aracteri zed w ith a r otational r he ometer as well as with a squeeze flo w rheometer. The obtained results from the rheology methods are c ompar ed and correlat ed wit h the res ults obtained from the DEA. The suitability of DEA to determine poss ible variations in the EMC characteristics in-situ during tra nsfer molding proces s is disc ussed. All DEA results, which are shown i n t h i s s e c t i o n , a r e p e r f o r m e d w ith 10 Hz and the average value s of t he ion viscosities out of 8 measurem ents are represented in the diagrams . Investigation of the Influence of Storag e Duration on EMC Chara cteristi cs Figure 5.16 illustrates the average logarithmic ion viscosity for the samples preconditioned for a time interval of 0 h, 8 h, 16 h and 24 h in vacuum oven with 0 % RH at 30 °C. Figure 5. 16: D EA curves f or prec onditione d EMC 1 pe llet s for st orage tim e of 8 h, 16 h and 24 h in dry environm ent at 30 °C / 0 % RH as w ell as fresh pellets (0 h) Only slight di ffere nce s in the cure reactio n of EM C 1 are obser ved with different sto rage durations. The minimum ion viscosities slightly increase with prolonging the s torage duration. Correspondi ngly, the maximum ion viscosities at the e nd of the curi ng time also illu strate sli ght variations, which may howeve r deliver the similar de lta (∆), which is the difference bet ween the maximum and minimum ion viscosities. As mentioned previously, th e delt a can deliver inf ormation about the degree of cure of the molding c ompound [160]. The slopes of the reactio ns for differe nt storage du rations are f ound to be almost identical. In or der to as certain whet her the stora ge dur ation has an im pact on the dynamic viscosity behavi or of EMC 1, rheologi cal measurement s are per fo rmed. Figure 5.17 depicts the isothermal and non-isothermal rotational rheometer results, whe r e t h e v i s c o s i t y b e h a v i o r o f t h e preconditioned pellets with respect to time and te mperature are plotted respectively. 0 50 100 150 200 250 300 350 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 Log. ion viscosity [Ohm*cm] Time [s] 0 h 8 h - dry storage 16 h - dry stora ge 24 h - dry stora ge 5 Preliminary Exp eriments and Results 70 Figure 5.17 : Isotherm al rotational rheometer m easurement at 100 °C ( left) an d non-isother mal rotatio nal rheometer measurement w ith 2 K/min (r ight) for EMC 1 pel lets pr e conditioned for 8 h, 16 h and 24 h in dry environm ent as we l l as fresh pellets (0 h) The storage duration until 24 h does not affect the d y namic vis cosity of EMC 1 remarkab ly. Only a s l i g h t d i f f e r e n c e o n t h e d y n a m i c v i s c o s i t y b e t w e e n t h e f r e s h s a m ples (0 h) and the samples preconditio ned for a n extended period of time can be observed. The gel time diminishes moderately with ext end ed st orag e dur atio n, w hich can be identified by the shift of the curve to the l eft on time scale . Similarly , no distinguishable trend f or the dynamic viscosity o f EMC 1 can be noticed with increasi ng s t o r a g e t i m e u n d e r t e m p e r a t u r e r a m p i n F i g u r e 5 . 1 7 ( r i g h t ) . O n l y a slight increase in t he mini mum viscosity of the pellets ca n be seen i n t he vi scosity curves, w hich also confirms the res ults of the ion viscosities obtain ed from the DEA. The sto r age duration is extended until 72 h to assure w hether t he material characteristics of EMC 1 stay further constant or any changes happen in the i on viscosity wit h the stor age time exceeding 2 4 h. The pellets, which are pre conditioned for 4 8 h and 72 h, are measur ed with DE A and t he io n viscosity curves are a nalyzed. Figure 5.18 shows ion viscosities of the pellet s as well as characteristic information derived fro m these ion viscosity curves such as minimum ion vis c o s i t y a n d t h e d e l t a , w h i c h i s t h e difference bet ween the maximum and minimum ion vi scosity. Storage duration Minimum ion visc osity [Ohm*cm] ∆ (Difference max-min ion viscosity) at 350 s [Ohm*cm] 0 h 5.60 2.93 24 h 5.67 2.93 48 h 5.71 2.89 72 h 5.88 2.74 Figure 5. 18: Logarit hmic ion viscosity (left) and the charac ter istic inf ormation der i ve d from t he DEA curves such as m i nimum ion viscosity and the delta (righ t ) for EMC 1 p e l lets, which are preconditioned for a storage ti me o f 24 h, 4 8 h , 72 h a t 3 0 °C / 0 % RH a s we ll as f resh pe l lets (0 h) No signific ant difference s can be seen in the sl ope of the cur v es between the 24 h storage and 72 h storage, the speed of the reaction are almost found to be ident ical for a ll ion viscosity curves. Except the 0 5 10 15 20 25 30 35 40 45 10 3 10 4 10 5 10 6 10 7 Shear viscosity [Pas] Time [s] 0 h 8 h - dry stor age 16 h - dry s torage 24 h - dry s torage 100 °C 70 80 9 0 100 110 120 130 10 4 10 5 10 6 10 7 Shear visc osity [Pas] Temperature [°C] 0 h 8 h - dry sto rage 16 h - d ry storage 24 h - d ry storage 0 50 100 150 200 250 300 3 50 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 Log. ion viscosity [O hm*cm] Time [s] 0 h 24 h - dry stor age 48 h - dry stor age 72 h - dry stor age 5 Prelimi nary Experi ments and Re sults 71 ion viscosity curve for fresh sa mples (0 h), all curves arrive at the same maximum ion viscosities at the end of the reaction at around 35 0 s. However, the m ini mum ion v iscosity slightly inc reases with prolonging storage du ration which causes a difference in th e de lta. The d elta between the m aximum ion viscosity at 350 s and the mini mum ion viscosity are calculated from the curves for each storage dura tion and depicted i n Figure 5.18 (right). A s it can be seen fro m the calculated values, the delta decre ases with increasing t he storage dura tion. How ever, to de termine whether the difference in measured deltas are significant, the process stabilit y analysis i s done for the tra nsfe r moldin g m achine with DEA measuremen ts. The process stability analy sis is conducted in a Lauffer VSKO 25 transfer m o lding pres s by perfor ming 25 moldin g cycles with the same process parameter to observe t he maximu m deviations in the ch aracteristics features of the DEA curves at 10 Hz s uch as maxi mu m standar d devi ation o bser ved in minimum i on viscosity, maximum ion viscosity, an d the delta between the maxi mum and mi nimu m ion viscosity . In t his way, it can be pos sible to determine whe ther the differenc e betwe en t he measured deltas are significant. T he maximum standard d eviation measured in the delta out of 25 molding cycles is f ound a s 0. 08 O hm*c m. S imil arly , the stand ard d evi ation f or the mini mum ion visco sity are foun d as 0.08 Ohm*cm whereas the standard deviation for the maximum ion viscosity is found fairly lower and as 0.02 Ohm*cm. Thus, any difference bi gger than these deviatio ns can be considered as significant. Yet, based on the differen ce in t he min imum viscosities an d the differences in the delta gi ven in Figure 5.18, it is evident that there is slight difference in characte ristics of EMC 1 with prolonging storag e duration. To approve the resu lts obtained fro m t he D EA a nd t o d etermin e whether the dynami c viscosities of EMC 1 also affected by the prolonged storage dur ati on, rotati onal rheometer measurement are conducted. I n Figure 5.19, the dynamic viscosities obtained from th e rot ational rheometer measurem ent are show n. Figure 5.19: D ynamic v iscosity of the preco nditioned EMC 1 pe ll ets for 24 h, 48 h, 72 h at 30 °C / 0 % RH as well as 0 h samples with respect t o time measured w i th rota tion al rheometer at 100 °C As seen in Fi gure 5.19, the dynamic viscosity or also -called sh ear viscosity sh ows si m ilar results as in the ion viscosit y where t he viscosity of EMC 1 is in fluenced b y extended storage duration. The viscosities of the pellets, whic h are preconditioned for 48 h a nd 72 h are foun d to be higher at the same time scale suc h as at around 10 00 s in comparison to the pellet s preconditioned for 24 h as well as fresh samples. This may indicate pre- cr osslinking of the material dur ing storage dura tion. The material m ay start alre ady cros s-linking at room te mperatur e which may cause a raise in the viscosity. In a ddition to the r otationa l rheo meter, sq ueeze fl ow rhe ometer measure ments a re a lso co nduc ted. I n Figure 5.20, the measurements are illustrated, w hich are perfor med wit h the preconditioned pellet s for storage durations of 0 h, 8 h, 16 h, 2 4 h, 48 h and 72 h in squ eeze flow rheometer at 175 °C. Additional 4 h storage duration is also imple men ted in the di agram. 0 200 40 0 600 800 100 0 1200 10 4 10 5 10 6 10 7 Shear viscosity [Pas] Time [s] 0 h 24 h - dry s torage 48 h - dry s torage 72 h - dry s torage 100 °C 5 Preliminary Exp eriments and Results 72 Figure 5. 20: Vi scosity measureme nt with squ eeze flow rheo meter at 175 ° C for preconditio ned EMC 1 pelle ts with storage dura tions of 0 h, 4 h , 8 h, 16 h, 24 h, 48 h, 72 h in dry env ironment at 3 0 °C / 0 % RH The results of the sque eze flow rheomet er also appro ve the resu lts obtained from the rotational r h e o m e t e r , w h e r e w i t h e x t e n d e d s t o r a g e d u r a t i o n , t h e v i s c o s i t y behav ior of EMC 1 c hanges. The squeeze flow rheometer results, which are obtained at 175 °C, i llustrate that with increasing storage duration the gel ti m e of t he pelle ts decreases in wh ich th e vis cosity curves shifted to left in the time scale. The first m ost significant cha nge in the viscosity h appe ns b e t w e e n t h e f r e s h p e l l e ts a nd t he p e l l et s preconditio ned f or 8 h. Subsequently , no remarkable changes hap pen in the viscosities of EMC 1 between the storage duration of 8 h and 24 h. These results als o confir m the r esults obtai ned from th e rotational rheometer shown in Figure 5.17, where n o large deviation happen in the dynamic viscosity curves of the pellets between the storage duration of 8 h to 24 h. T he next variation in the cu r ves is seen, when t he storage duratio n is e xtended to 48 h, where the viscos ity curves shift furt her to th e left and indicate a decrease i n the gel time. Following, no significant changes happen in t he v iscosities between the pellets stored for 48 h and 72 h. T herefore, by considering the results obtained fro m t he rheology measuremen t s, it is possible to say that the extended storage d uration i n dry environment shows some influence on the cure react ion of E MC 1. Additionally, the rheo lo gy measurements obtained from the rotational rhe ometer as wel l as squ eeze flow rheo meter repres en t good correlation to the results o btain ed f r o m t h e D E A . H e n c e , t h e v a r i a t i o n s i n t h e c u r e r e a c t i o n a n d t h e viscosity of EMC 1 due to the prolonged storage duration ca n be also observed from the DEA curves i n-si tu during transf er molding process. 0 1 02 03 04 05 06 07 08 0 0 100 200 300 400 Viscosity [Pas] Time [s] 0 h 4 h - dry storage 8 h - dry storage 16 h - dry storage 24 h - dry storage 48 h - dry storage 72 h - dry storage 175 °C 5 Prelimi nary Experi ments and Re sults 73 Investigation of the Influence of Humidity on EMC Characteristi cs In Figure 5.21, aver age logarith mic ion viscosity curves for th e precond itioned pellets i n humid environ men t at 30 °C and 90 % RH for 8 h, 16 h, 24 h as well as f r e s h s a m p l e s ( 0 h ) a n d t h e c h a r a c t e r i s t i c information a bout the c ure reaction of EMC 1 deriv ed from t he i on visc osit y curves are sh own. Storage duration Minimum ion visc osity [Ohm*cm] ∆ (Difference max-min ion viscos ity) at 350 s [Ohm*cm] 0 h 5.60 2.93 8 h 5.53 2.42 16 h 5.59 2.23 24 h 5.59 2.23 Figure 5.21: Logar i thm ic ion vi scosity with respect to t i me ( l e ft) and characteristic inform ation (right) of precondi t ioned EMC 1 pellets for 8 h, 16 h and 24 h at 30 °C and 90 % RH as well a s fresh samples (0 h) The progr ess of the c ure reaction ch anges re markably when the p e l l e t s a r e e x p o s e d t o h u m i d environment. The slo pe of the reactions for the preconditioned pellets differentiate to a gr eat extent from the fresh samples (0 h). T he time required to reach the maximum ion viscos ity is longer w hen the pelle ts are prec onditioned. Th e ion viscosity curves are diffe rent for humid sa m ples in comparison to t he dry samples. T he delta between the maximum a nd minimum ion viscosit y is signifi cantly l arger for the fre sh samples in com parison to the preconditioned samples, wh ich can be al s o s ee n f rom t h e v al ue s g iv en in Fig ure 5.2 1 (r ight ). To dete rmin e w heth er the dy nami c visc osit i es of EMC 1 pellets ar e also in f luenced by the storage duration in humid environmen t, the r otational rh eometer measurements are performed for preconditioned pellets. Figure 5.22 de picts the results of the rhe olo gy measure ments whi ch ar e conducted under isothermal and n on-isothermal conditions for pe llets preconditioned in hum id environ ments in climate oven at 30 °C and 90 % R H. Figure 5.22: Isothermal at 100 °C (lef t) and non-is ot herm al with 2 K / min (r i ght) viscosit y plot for EMC 1 pe llets precondi t ioned in humid environm ent for 8h, 16 h a nd 24 h at 30 ° C / 90 % RH and for fresh pellets Both rheological m easurements w ith isothermal and tem perat ure r am p of EMC 1 with d ifferent storage durations in a climate cham ber show differences in viscosities with extended storage duratio n in humid environ ment. The gel ti me decreases gradually by inc reasing t he preconditioning duration of EMC 1 in 0 50 100 150 200 250 300 350 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 Log. ion visco sity [Ohm*cm] Time [s] 0 h 8 h - humid storag e 16 h - humid storage 24 h - humid storage 0 5 10 15 20 25 30 35 40 45 10 3 10 4 10 5 10 6 10 7 Shear visc osity [Pas] Time [min] 0 h 8 h - humid storage 16 h - humid storage 24 h - humid storage 100°C 70 80 90 100 110 1 20 130 10 4 10 5 10 6 10 7 Shear visc osity [Pas] Temperature [°C] 0 h 8 h - humid sto rage 16 h - humid storage 24 h - humid storage 5 Preliminary Exp eriments and Results 74 humid enviro nment. As a matter of fact, the alteration in t he v iscosity beco mes mor e pro nounce d with 24 h hu mid s tora ge. A s se en in F igur e 5 .22 (r igh t), th e mini mum visc osity of EMC 1 raises when the pellets are preconditio ned fo r 24 h in humid environm ent. As e xplained in the p revious section, there is a slight c hange in the viscosity of EMC 1 with prolonged storage duration in dry environ ment. Hence, to d etermine solely t h e e f f e c t o f h u m i d i t y o n t h e c u r e reaction of EMC 1 and to eli minate the effect of dry storage du ration, the viscosity curves for the pellets, which are preconditioned for 24 h in dry en viro nment and for 24 h i n hu mid en vir onme nt, ar e represented together in Fi gure 5.2 3. In addition, the vi scosity c u r v e f o r t h e 0 h s a m p l e s a r e s u p p l e m e n t e d into the diagrams to consider t he viscos ity of EMC 1 at initial s tate. Figure 5.23: D ynamic viscosity curve (left) and t he ionic visc o sity curve ( right) wit h respect t o time for EMC 1pelle t s whic h are precondit ioned f or 24 h at 3 0 °C / 0 % R H a nd for 24 h at 30 °C / 90 % RH as well as fresh samples The ex cessive i mpact of th e humidity on the dy namic viscosity o f EMC 1 as well as on the ion viscos ity of EMC 1 can be seen in Fi gure 5.23. As the difference between the i on visco sity curves und er humi dity are si gnificantly larger and easily identifiable, t he standard deviation of the curves is also imp lemented in the ion viscosity diagram in Figure 5.23 (right) to visu aliz e the deviation in t he ion viscosities. The ion viscosity of the samples preconditi oned for 24 h in humi d s torage differs remar kably from 0 h and 24 h dry samples. The m i nimum ion viscosity for 24 h h umid samp les i s found lower in comparison to the fresh samples as well as 24 h stored dry samples . In a dditi on, the i on vi scos ity cur ve for 24 h h umi d samples propagates much slower than the ion viscosity curve for d r y s a m p l e s a n d f r e s h s a m p l e s . Sim ilarl y, the d ifferenc e b etween max imum and min im um io n visco s ity is larger fo r fresh samp les and for 24 h stored dry samples in co mparison to t he 24 h stored h u mid sample s. To an alyze w hether t he diff eren ces in m a xi mum an d mi nimu m i on v isc osity , n ame ly delta observed in DEA are caused by the variations in the degree of t he cure of the preconditio ned EMC, T g ‘s of EMC 1 are meas ured with DMA . Figure 5.2 4 depicts the results of the DMA measurement of molde d s amples made fr om f resh pel lets and from pellet s stored in humid and d ry e nvi ronment. I t is imp ortant to note that as t he purpose to perform the DMA measurem ent is to find correlation between the T g and the delta observed in DEA, DMA meas urements of the sa mples are carrie d out d irectly after the molding proces s and without conducting PM C to prevent any PMC effect in between. 0 5 10 15 20 25 30 35 40 45 10 4 10 5 10 6 10 7 0 h 24 h - dry s torag e 24 h - humid stor age Shear viscosity [Pas] Time [min] 100 °C 0 50 100 150 20 0 250 300 350 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 Log. ion viscosity [O hm*cm] Time [s] 0 h 24 h - dry stor age 24 h - hu mid storage 5 Prelimi nary Experi ments and Re sults 75 Figure 5.24: DMA measurements o f the EMC 1 pe llets precond ition e d for 24 h in humid and dr y environment as well as fresh samples (0h) As previously explained in Section 3.3.1, the p eak point observ ed a t the curve of tan delta v e r s u s temperat ure i s defin ed as T g of t he material i n DMA m easurement. Accor ding to the DMA result s, th e T g for 0 h fresh samples and for the 24 h dry samples are found v e ry sim ilar which is aro und 180 °C. On the other hand, the T g of 24 h humid samples shifts to the left to a value of 170 °C and decreases. Yet, 10 ° C difference is observed in the T g of EMC 1 between the humid and dry samples of 24 h of storage. This implies t hat the difference observed in the delta in the i on visc osity curve r eflects the chan ge i n t he T g of the molding compo und. T hus, a g ood correl ation is found b et ween DEA and DMA meas urement where the var iation in the delta i n th e io n viscosity curve cor relates well with the variation in the T g of the mol ding compo und. As a next ste p, the pellets are further preconditioned for 48 h a n d 7 2 h t o d e t e r m i n e t h e l i m i t o f t h e humidity influence whether the humidity has furt her i mpact on t he viscosity behavior or whether the pellets achieve saturation point. Figure 5.25 depicts the ion v iscosity curve as well as the characteristic information d erived from the i on viscosity curves for 0 h, 24 h , 48 h as well as 72 h of storage durati on in humid e nvironment. Storage duration Minimum ion visc osity [Ohm*cm] ∆ (Difference max-min ion viscosity) at 350 s [Ohm*cm] 0 h 5.60 2.93 24 h 5.59 2.23 48 h 5.67 2.04 72 h 5.66 2.04 Figure 5.25: Average logarithm i c ion v iscosity w ith respec t to time for EM C 1 pellets preconditioned for 24 h, 48 h and 72 h in hum id environm ent at 30 °C / 90 % RH as wel l a s fr esh samp les ( 0 h ) (l eft ), t he minimum ion vi scosities and the difference in de lta measure d wi th prolonge d st orage duration at hu mid environment (right) With extended storage of the molding compound, the cure reactio n of EMC 1 is further in fluenced. The minimum viscosity of the samples increases and the time o f mini mum viscosity shifts slightly to earlier time with further storage of 48 h and 72 h in h umid e nvironment . The varia tion in the minim um ion 25 50 75 100 125 150 175 20 0 225 250 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 Tan delta Temperature [°C] 0 h 24 h - dry storage 24 h - humid storage 0 50 1 00 150 200 250 300 3 50 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 Log. ion viscosity [O hm*cm] Time [s] 0 h 24 h - humid sto rage 48 h - humid sto rage 72 h - humid sto rage 5 Preliminary Exp eriments and Results 76 viscosity and the delt a between the maximum and minimum ion vis cosity (Figure 5.25 right) shows th at the largest change in de lta happens between the fre sh sam ples a nd 24 h humid samples. Afterward s, the delta varies slightly between the 24 h humid samples and the 72 h humid samples. DMA measurem ents are carried out also for the samples and T g of the samples which are preconditioned for 24 h, 48 h as well as 72 h are measured. Figure 5.26 illust rates the results of the DMA measurements of the precon ditioned samples as w ell as fres h samples. Figure 5.26: DMA measureme nts of EMC 1 pellets precond itioned f or 24 h, 48 and 7 2 h at 30 ° C and 90 % RH as well as fresh s amples (0h) The preconditioned sampl es for 24 h, 48 h as well as 72 h h ave almost identical T g , which is around 170 °C. The unconditioned samples, in other words fresh samples ( 0 h) hav e the T g around 180 °C. This implies that t he most significant variation in T g hap pen bet ween the fresh sa mples and 24 h humid samples. No remarkable changes happen in T g with f urther extension of longer than 24 h in humid environ ment. This also verifies the r esults of delta obtaine d f rom the DEA, where the lar ge variation in the delta happens between the fres h samples and 24 h humid samp les. Af ter analy zing the mechani cal properties of the preconditioned samples with the DMA measureme nts, rotational rh eometer measurem ents are condu cted to observe wheth er t he viscosity of the EMC 1 varies with e xtende d storage duration o f the pellets in humid en vironment. Figure 5.27 depic ts the shear viscosities of the preconditioned sa mples for 24 h, 48 h, 72 h as well as 0 h fres h samples. Figure 5. 27: Isot hermal r heology m easurement at 100 °C for prec ondi tioned EMC 1 p ellet s f or a sto rage t ime of 0 h, 24 h, 48 h as w ell as 72 h at humid environme nt at 3 0 °C / 90 % R H The exte nded storage duration has a n influen ce on the shear vis cosity of the analy zed pell ets. The viscosity increases with furthe r preconditioning of the pellets for 48 h and 72 h i n humid environ ment. 25 50 75 10 0 125 150 175 200 225 250 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 Tan delta Temperature [°C] 0 h 24 h - hum id stor age 48 h - hum id stor age 72 h - hum id stor age 0 200 40 0 600 800 1000 1200 10 4 10 5 10 6 10 7 Shear viscosity [Pas] Time [s] 0 h 24 h - humid stor age 48 h - humid stor age 72 h - humid stor age 100 °C 5 Prelimi nary Experi ments and Re sults 77 As seen in Fi gure 5.27 after 1000 s a minimal decrease in the v iscosit y curve of 72 h hum id samples can be observed. T he reason for that although t he measurements ar e repeated three ti mes, each ti me 72 h preconditio ned humid EMC 1 samp les lose th eir contact to the me asurement tool most pro bably due t o the significant alterations in t he material charact eristics, wh ich does not allow a good adhesion to tool surface. Addition al rheol ogy measure ments are car ried out with the squeeze flow rheome ter to observe the viscosity behavior at molding temperature. Figure 5 .28 ill u strates t he r esults of the squeeze fl ow rheometer for all preconditioning durations in humid en vironmen t, n amely for 4 h, 8 h, 16 h, 24 h, 4 8 h, 72 h as well as fresh sa mples. Figure 5.2 8: Viscosity me asured with squeez e flow rheometer a t 175 °C of precondi tioned EMC 1 pe llets for 4 h, 8 h, 16 h, 24, 48 h, 72 h as well as fresh sam pl es The vari ations in the vi scosities of all analyzed pellets, whic h ar e preconditioned until 72 h as well as fresh samples, can be observed in Fig ure 5.28. Wit h ex tended st orage duration, th e sharp increase of the viscosity curves shifts to the earlier time intervals, indicati ng a decrement in gel ti me. Prono unced differences in the viscos ities ar e observed with further precon ditioning of the pellets fro m 24 h to 72 h which correlate well with the results obtained from rotati onal rh eometer. Thus, the results of the rheology measu rement show that cure reaction o f EMC 1 is re mark ably influ enced by extended storage duration in humid environm ent. To deter mine the moisture content of the pellets wit h prolongin g storage d uration in humid environment, Karl-Fischer titration is a pplied. Figure 5.29 illustrate s the moisture content i n the pellets stored until 72 h i n humi d en viron ment as we ll as the moi stur e con tent of t h e pellets, which are stored i n dry environ men t for comparis on. To observe the trend of th e ion vis cosity curves for all storage durations in humid environment by taking into account t he moisture conten t i n the pellets, ion viscosity curves are illustrated together i n Figure 5.29 (right). As the moisture co ntent of the preconditioned pellets for 4 h is measured, DEA measurem e nt for 4 h hum i d storage duration is also conducted additionally to compar e the variati on in t he ion viscosity by considering the r aise in the moisture content o f the pellets. 0 1 02 03 04 05 06 07 08 0 0 100 200 300 400 175 °C Viscosity [Pas] Time [s] 0 h 4 h - Humid storage 8 h - Humid storage 16 h - Humid storage 24 h - Humid storage 48 h - Humid storage 72 h - Humid storagee 5 Preliminary Exp eriments and Results 78 Figure 5. 29: Moisture con tent in EM C 1 pelle ts precond itioned i n dry and humid environment ( left), ion viscosi t y cur ves for EMC 1 pellets prec onditioned for 4 h, 8 h, 16 h, 24 h, 48 h, 72 h as w ell as fres h samp l es (0 h) (right) Karl-Fischer titration results show that the m oi sture content o f th e pellets preconditioned in dry environ men t at 30 °C and 0 % RH stays constant during 72 h stor age duration . Around after 24 h dry storage, the moisture content in the pellets decreases slightly most prob ably due to dry ing of th e moi stur e initially present in the pellets. On the other h and, the moistu re content of the preconditioned pellets in humid environment raises with prolonging storage duration at 30 ° C a n d 9 0 % R H . A p p r o x i m a t e l y around 4 8 h, pellets arrive saturation poi nt and the mo isture c ontent does not change significantly after 48 h humid storage a nd stays almost constant until 72 h of stor age. T he i nfluence of the moistur e conten t on the i on viscosity curves can be observed for all storage dur atio ns in Figure 5.29 (right). The humidity plays a major role on the ion visco sity of the pellets especial ly until 24 h of storage. Ion visco sit y curves for the pellets, which are store d until 24 h, show similar cure reaction. However, after 48 h of hu m id storage, the min imum i on v iscosity changes it s behavi or a nd the ion viscosity curve s hifts to ea rlier ti me scale as see n in F igure 5.29 (right) . Wh en ta king int o ac count the results observed f rom the rheology measurements for the preconditione d samples in dry enviro nment, w h e r e t h e v i s c o s i t y o f E M C 1 i s influenced by the prolonged dry storage duration, it is apparen t that there are some overlapping effects on the viscosity of EMC 1 seen in Figu re 5.29 (right). The vari ation in the ion viscos ities after 48 h and until 72 h observed in Figure 5.29 (ri ght) is most probab ly a c ombi nat ion of t he imp act of a bs orbe d humidity in the pellets and als o starting cross-linking reactio n d ue to the prolonged st orage duration. 0 1 02 03 04 05 06 07 0 0.10 0.15 0.20 0.25 0.30 0.35 0.40 Moistu re content [wt . %] Storag e dura tion [h] Dry storage a t 30 °C / 0 % RH Humid storage at 30 °C / 90 % RH 0 50 100 150 200 25 0 300 350 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 Log. ion viscosity [Ohm*cm] Time [s] 0 h 4 h - hum id storag e 8 h - hum id storag e 16 h - hu mid storage 24 h - hu mid storage 48 h - hu mid storage 72 h - hu mid storage 5 Prelimi nary Experi ments and Re sults 79 Investigation of Influence of Batch Variations of EMC with DEA Figure 5.30 dem onstrates th e dyn amic viscosity of three batches of E MC 1 n amely ba tch 1, batc h 2 and batch 3 with respect to ti me and te mperature. Figure 5.30: Isothermal rheology measurement (left), non- isothe rmal viscos ity curves (right) of batch 1, batch 2 and batc h 3 of EMC 1 Three bat ches of EMC 1 show different viscosity behavior under non-isother mal condition. The mini mum vis cosities of three batches at the s ame te mperature di ffer entiate from each other. On t he other hand, u nder isothermal condition, batch 1 and batch 2 show al mo st i dentical visc osity behavior, whereas viscosity of batch 3 differs notably regarding dy namic viscosit y behavior as wel l as reaction time. T o determi ne w hether si milar diffe rences ca n be also o bserved fr om t he ion viscosity curve of the thr ee batches of EMC 1, DEA measurements are performed. Figure 5.31 p resents the ion viscosities of three batches of EMC 1. Figure 5.3 1 : Ion visc osities for batch 1, batc h 2 and batch 3 o f EMC 1 The ion viscosity curves for batch 1 a nd batc h 2 are al most ide ntical a nd no significant differences are noticea ble in the c ure r eaction curves e. g. re garding the slo pe of the curve. Batch 3, however, shows a slightly different re action p ath. The sl ope of t he reacti on is rather l arger, thus cure reaction f or batch 3 is faster and the maximum ion viscosity is reached in a shorter ti me in compa rison to batch 1 and batch 2 . This re sult correlates well with t he rheology results obtained under isother mal condition, which show s that the d ynamic vis cosity c urves for bat ch 1 a nd batch 2 behav e almost iden tic al and dynamic viscos ity of batch 3 differs from b atch 1 and batch 2. 0 1 02 03 04 05 06 0 10 4 10 5 10 6 10 7 10 8 10 9 Viscosity [Pas] Time [min] Batch 3 Batch 2 Batch 1 70 80 90 100 110 120 130 10 4 10 5 10 6 10 7 10 8 Viscosity [Pas] Temperature [°C] Batch 3 Batch 2 Batch 1 0 50 100 150 200 250 300 6 7 8 9 10 11 Log. ion viscosity [Ohm*cm] Time [s] Batch 1 Batch 2 Batch 3 5 Preliminary Exp eriments and Results 80 5.5 Summary The results of the preli minary process experi ments show that th e void for mation in the m ol ded packages is strongly influenced by the process paramet ers. Some process parameter combinatio n s c au se re du ce d void formatio n in the molded packages, whereas so me process p ar ameters s uch as parameter set no. 2, one of the extreme process para meter combi nations, causes large void formation in t he package. It is assumed t hat the reason for this large void for mation in the pa ckage is the hi gh viscosity du r ing the molding stage, caused by low mo l ding tempera ture, low preheat t i m e , a s w e l l as l o w h o l d i n g p r e s s u r e applied in para meter set no . 2. In addition to that, it is obse rve d t hat the voi ds a re f or med as a t ende ncy in the zon e 4 area whi ch is far from the gate. This tendency of the void f ormation to form in the zone 4 can be attributed to the fact th at the flow behavior of the mol d compound wh ere t he flow front collapses at the very end of the layout in zone 4 and forms so me voids es pecially in this area. However, the detailed analy sis in regard of the origin of the void formation in the m olded packages is not the scope of this thesis. Thus, t o comprehend and to analyze the actual origin of the voids i n the mo lded package in detail, additional work should b e done. Further more, among the investig ated process p arameters, transfer speed and holding press ure are found t o be dominant process paramet er s on the void formation, w hereas the preheat time and the temp erature does not show pronounced imp ac t on the void formation. Moreo ver, wire swe ep in the pack age is a lso stron gly influenced by th e process parameters. In con trary to the r esults seen in the void for mation, parameter set no. 2 causes re duced wire sweep, whereas paramet er s et no. 3 l eads to lar ge wire sweep i n the package. T he reaso n for the lar ge wire s weep i n paramet er set no. 3 can be possibly attributed to the fact that t h e p a r a m e t e r s e t n o . 3 , w h i c h h a s h i g h transfer speed combined with the least p reheat ti me and low mold temperature, can cause high viscosity of EMC. This high viscosity of the EMC can cause lar ge viscous drag forces on the wire bon ds, which then leads t o such lar ge wire sweep eve n on the shor t wire bond s . I n ge ner al, t he lon g wi re bo nds sho w more wire sweep in comparison to the short wire bonds. The wire bond s attac h ed in fa r from the gate area show les s wire sweep compared to the wire bonds attached i n near gate ar ea. For t he wire bonds attached at different angles to t he gate, the w ire bonds attac h ed at 18 0 ° to the gate s how slightly s m aller w i r e s w e e p i n n e a r g a t e a n d f a r f r o m t h e g a t e a r e a . A m o n g t h e s elect ed pr ocess p ara mete rs, the temperature and the transfer speed are found to be the do minant process para meters o n the wire s weep. The i mpact of the te mperature on the w ire sweep can be dire ctly correlated wi th the viscosity of the molding co mpound, where the high er temperatures lead to a reduc ti on i n the vi scosi ty of t he mol din g compo und, thus less f orce is ap plied on t he wire bon ds. Furthermore, the warpage measure ment results show that t he w arp age of the selected package is n ot influenced by the variations in the process parameters and the deviation in the warpage in one para me ter set is much larger i n co m parison to the variations in the warpa ge within 13 para meter sets. In addition, the ma ximum average w arpage value o bserved i n all 13 process pa rameters is under 1 00 µm, which is consid ered as non-cr itical r egardi ng the defined quality criter ion for this test vehicle (see Section 2.7). The reason f or the small variations in the warp age obs erved in this test vehicle can be due t o the stabl e thickness of the lead frame which is around 1 mm and th e small surface ar ea of t he test ve hicle. Therefore, by consi dering all qua lity cha racteristics investiga ted in this chap ter, it is possible to sa y that the wire s w eep a nd t he void formation of the molded packages ar e strongly influenced by the variati ons in the proces s parameters. Thus, it is possible to improve thes e quality fea tures of the m olded packages by the variations in the process parameters. On the other hand, t he war page for the investigated test vehicle is not affected r emarka bl y by the change in th e process paramete rs due to the sele cted substrate dimensions. Hence, as the target of the work is to find an opti mum set of process para me ters of the transfer molding process which deliver the best package quality, warpage will not be investigat ed further as a quality characteristic in the main experi ments. In the second part o f this chap te r, it is observed that the pro longed storage duration has an influence on the cure reaction of EM C 1. With extended stora ge duration, the d e g r e e o f c ur e i n c r e a s e s , w h i c h i m p l i e s that cross-linking reacti on starts already during storage i n va cuum oven and EMC 1 a chieves certai n 5 Prelimi nary Experi ments and Re sults 81 cross-linking degree before the pellet s are molded. In addition , the st orage duration in humid environment shows a more pronounced influence on the c ure react ion of EMC 1. The ion viscosity signal is strongly influenced when EMC 1 pellets are subjected to humi d environment. Good c orrelation between the delta in the io n viscosity and T g from the DMA is found, which implies that the io n viscosity delivers also consequen tial infor mation about t he var iation i n the T g of the material. Moreover, the rotational rheom eter results sho w that a variation in the curin g reaction between different batches exist, and this dif ferenc e can be obser ved also with DEA measurement i n-situ in transfer molding process . Additionally, the result s obtained from the DEA match very well w i t h t h e r e s u l t s o b t a i n e d f r o m t h e rotational rheometer, DSC and s queeze fl ow rheo meter. T he feasi bility analy sis of the DE A demonstrates that DEA delivers valuable information about the c ure reaction of the EMC and is found suitable as an in-situ monitoring technique in transfer molding p r o c e s s t o o b s e r v e t h e v a r i a t i o n s i n t h e EMC characteristics due to batch variation, and prol onged stora ge duration in dry and humid environ ment. 6 Main Experiments and Results 83 6 Main Experiments and Results After gai ning a co mprehensive understandi ng with t he prelimi nar y experi ments in terms of significant process parameters and the imp act of the variati ons i n t he mate rial charact eristics on the c ure behavior of EMC 1, the main experi ments are con ducted. The main experi me nts are performed to define a process model and a materi al mod el whic h deli vers t he c orrelation betwe e n t h e p r o c e s s p a r a m e t e r s , m a t e r i a l characteristics and the package quality. Hence, in this chapter , the selected experi mental designs and applied approaches are shown, which are e mployed to generate mo dels, and the results of the main experi ments are dis cussed. Since differ ent experime ntal plans a re conduct ed for the generation of process and the material models, the main experiments consi st o f t w o p a r t s . T h e f i r s t p a r t i s d e d i c a t e d to the main experiments for pro ces s an aly sis, which ar e co nduct ed to establish a process model. The selected experimental design t o ge ne r at e a pr o ces s mo de l, w hic h expresses the r elationship between the process para meters and the quality c haracteristi cs parameter s i s introduced in Section 6. 1. Th e q uality analy sis of t he conducted experi menta l design is given in S ecti on 6.2. The important findings about quality analysis of void formati on and wire sweep and relevant aspects, w hich are necessary to consid er i n g e n e r a t i o n o f t h e p r o c e s s m o d e l , a r e d i s c u s s e d . B e f o r e t h e r esults of the quality analysis are introduced, the process is exami ned in order to determine t he p ossible variat ions in temperature and p r e s s u r e . T h u s , t h e p r e s s u r e a n d t e m p e r a t u r e s e n s o r s a r e a n a l y z ed and i mportant f eatures on the observed si gnals are assessed. M oreover, process stability anal ysis is conducted t o determine th e max imu m de viatio ns i n th e t emp erat ure an d t he pr ess ure se nsor s in the pr oces s as w ell as in void form ation and wire sweep. In the second part of the main experim ents, an applied experime ntal approach t o generate a material model, which deli vers the i mpact of t he variati ons in t he mater ial c haracteristics on the quality features is given. In the preliminary experiments, the influence of the variations in the material characteristics on the c ure behavior of EMC 1 are discussed. I n the main experi ments, however, the impac t of the variations in the material characteristics of EMC 1 directly on the wire sweep and void formation in the molde d p ackages are examined. The exp erimental approach, which is carried out to asses s t he i nfluence of the variati ons in the material c haracter istics du e to the st orage duration, the batch variations a nd t he humidity on the quality characteristics is illustrated in Secti on 6. 3. The results of the experimental analy sis are discussed in S ection 6.4. I n Section 6.5 t he su mma ry of th e impor tant finding s abou t the main experim ents i s given . 6.1 Main Experiments f or Process Analysis The objective of the main experi ments in this work is to establ ish a correl ation bet ween the process p a r a m e t e r s a n d t h e q u a l i t y c h a r a c teristics in order to estima te the quality characteristics beforehand as well as to def ine opti mum process parameters, whic h delivers th e best package qualit y. In that manner, it is crucial that the selected quality characteristics are inf luenced by the process parameters. For this reason, as alr eady mentioned warpa ge by being a quality charact eri stic, which is not i nfluenced by the variations i n the process parameters for this package geometry, will not be furt her i nvestigated in the main experim ents. For the main experimen ts D-optimal design is selected. The reas on for the selection of the D-o ptimal design is that with D-op ti mal design, the interaction s between the pr oce ss para meters and the i mpa ct o f quadratic influences of parame t er s on t he vo id fo rmat ion and th e wire sweep c an be studied . Thus, a quadratic model c an be established based on the resul ts of t he experimental plan which is constructed according to D-optimal design. Four process parameters, which a re moldin g temperature, holding pressure, preheat time a nd transfer speed, are investi gated wit hi n the sele cted process window w hich is already shown in Table 5 . 1. The process parameters are set in 3 levels. For four factors, which are set in 3 levels, the m i nimum number of the required param eter set in D -optimal design is 15. As explained in Chapter 2, in D-optimal design , the parameter combinations whic h are c hosen ba sed on the algorit hm, 6 Main Experiments and Results 84 are distributed within a given matrix or in other words within a p r ocess wind ow, and some of the corner points in the matrix may no t be occupied. In order to cover t he investigated process w indow thoroughly to obtain better interpolation with the established model, five additional parameter c ombinations are supplemented into the experimental design. In total 20 differen t par a me ter com binatio ns are stu died. The experimental pl an executed t o generate a process model is s hown in Table 6.1. Table 6. 1 : D-opt imal exper i mental plan in main experim ents with four pro cess param eters set in 3 levels to generate a process model Parameter set no. T [°C] v [mm/s] t [s] P [bar] 1 165 6.5 0 80 2 165 6.5 16 140 3 165 1.5 0 80 4 165 1.5 16 80 5 165 1.5 0 140 6 165 4 8 110 7 175 6.5 0 110 8 175 4 0 80 9 175 6.5 8 80 10 175 1.5 16 110 11 175 1.5 0 140 12 175 4 8 110 13 185 1.5 16 80 14 185 1.5 16 140 15 185 6.5 16 80 16 185 1.5 0 140 17 185 6.5 0 140 18 185 6.5 0 80 19 185 4 16 140 20 185 4 0 110 Each para meter set is repeated five times to eval uate the repro ducibility of the results. Considering the left and right cavity together, the v oi d formati on and the wire sweep of overall ten samples are analyzed for each parameter s et. 6.2 Result s of Mai n Experi ments for P rocess Analysi s To gain more insight into cavities of the molding process, pre s s u r e a n d t e m p e r a t u r e s i g n a l s a n d t h e i r important characteristics are discu ssed in Secti on 6.2.1. Furth e r m o r e , t o e x a m i n e t h e d e v i a t i o n s i n t h e temperature and the pressure of the transfer molding process du ring molding, a process stabilit y analy sis is perf orm ed. The process stability analysis is carried out by conducting 2 5 molding cycles at the same process parameter set t o observe t he deviations in t he pressure a n d t h e t e m p e r a t u r e a s w e l l a s i n t h e quality characteristics, namely void formation and wire sweep i n the package. Results of the process stability analysis are given in S ection 6.2.2. Moreover, the i n flue nce of the proc ess para me ter combination sets depicted in Table 6.1 on the void f ormation an d the wire sweep are investigated . The main aspects of the experiments on the void formation and the w ire sw eep are intr oduced i n Section 6.2.3 in the quality analysis part. 6 Main Experiments and Results 85 6.2.1 Machine and S ensor Signal Analysis As already illustrated in Chapter 3, the transfer molding proce ss i s monitored with t emperature a nd pressure sensors during molding in this work. Mo nitoring the mo lding proces s is crucial to a ssure the process stabil ity and to dis clos e any possibl e variations f rom cycle to cycle. Moreover, the machine settings are usually not reflec ting the real situation in the cavity. There are c ertain deviations between the set parame ters in the machi ne and the real c onditions meas u red in the cavity. Thus, it is important to measu re the tempera ture and the pressure dir ectly in the cav it y to control the p rocess. In ad diti on t o the difference between the set machine para meter and the cavity conditions , there m ay be also deviations bet ween the left and th e ri ght caviti es. To hi g hli ght the situations in the left and the right cavities, some of the sensor signals from the cavities are anal y zed. Consi dering the nine t emperature and pressure signals implemented in the cavities of the molding tool (see Chapter 3 for exact position of the sensors), only repres entative exampl es of t he signals fr om th e s el ec te d s en so rs ar e s ho wn in t h is section. Figure 6.1 illustrates the temperature si gnals measure d in the left cavity and in the right cavity for three parameter set no. 1, 7 and 1 8 where the tool tem perat ure i s varie d as 165 ° C, 175 ° C and 185 ° C respectively . Figure 6. 1: Tem perature signals obta ined fr om tem perature senso r T1 in left cavity ( left), and from temperat ure sensor T 2 in right cavi ty (right). As an illustrati o n of sig nals paramet er s et no . 1, 7, 1 8 a re se lec ted. According to Figure 6.1, the temperature for five cycles within each parameter set number stays constant. The representative para meter set no. 1, 7 and 18 are select ed purp osely , since all those parame ter sets have the same preheat time (0 s) and transfer sp eed (6.5 mm/s) but have differe nt molding temperat ures. The set tra nsfer s peed and preheat time are deci s ive f or the peak in which the tem perature goes down. Exactly at this point, which is circa after 12 secon ds for t he parameter s et wit h 6.5 mm/ s transfer speed and 0 s preheat ti me, the molding compound rea ch es at temper ature sen sor and ca uses this peak in downwards due to its c older temperature in co mpari s on to the to o l te mp e ra t ur e. T he s i mil ar peak can b e also observed on the temperature senso r in the righ t cavit y onl y with a sm all difference that i n t h e r i g h t ca vi t y t h e m e a s u r e d t e mp e ra t u r e h a s a s h a r pe r p e ak . The reas on for that i s there is a minimal position difference (~ 2 mm) between t he T1 i n the l eft cavity and T2 in the right cavity and due to t he irregular cross secti on of the gate area, slightly more materia l flo ws through T2 sensors, wh ich causes larger down peak. Howe ver, for t he co mparison of the temperatur e b e t w ee n t he s e n so r s in l ef t a nd t h e right cavity , it is more representati ve to inspect t he start te mperatur e a t time 0 s. As see n in si gnals from T1 in the left cavity, for the set temp eratures of 165 °C, 175 °C and 185 °C, the left c avity has a slightly higher temperature whereas in the right cavity the temperature lies slightl y below t he set te m perature. The differ ence betwe en t he temper atures in t he l eft and the rig ht cavity is between 1 °C – 2 °C. This variation is also confirmed with t h e o t h e r t e m p e r a t u r e s e n s o r s i n t h e c a v i t i e s n a m e l y T 3 a n d T 4 implemented on the lower half of the tool as well as with an ad ditional examination by a temperature 0 30 60 90 120 150 180 2 10 240 160 165 170 175 180 185 190 Temp erature Sensor - T1 - Left Ca v ity Temperature [°C] Time [s] 0 30 60 90 120 150 180 2 10 240 160 165 170 175 180 185 190 Temperature [°C] Time [s] Temperature Sen sor - T2 - Right Cavity [Document text truncated for crawler view.] Why institutions use Plag.ai for originality review, entry 39 Plag.ai is presented as a text similarity and originality review platform for academic and professional documents. 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