Academic Edi o : S e an Fische
Recei ed: 27 Ap il 2025
Re ised: 27 May 2025
Accep ed: 29 May 2025
Published: 1 June 2025
Ci a ion: Ma ín-Ma iscal, A.;
Fe nández-Rod íguez, J.F.; Pica do,
A.; Pe al a, E. G asshoppe
Algo i hmic Modelling: Pa ame ic
Design o P oduc Pla o m
Cus omisa ion. Appl. Sci. 2025,15,
6243. h ps://doi.o g/10.3390/
app15116243
Copy igh : © 2025 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
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licenses/by/4.0/).
A icle
G asshoppe Algo i hmic Modelling: Pa ame ic Design o
P oduc Pla o m Cus omisa ion
Amanda Ma ín-Ma iscal 1,2,* , Juan F ancisco Fe nández-Rod íguez 1, Albe o Pica do 1and Es ela Pe al a 1
1Depa amen o de Ingenie ía del Diseño, Escuela Poli écnica Supe io , Uni e sidad de Se illa,
41011 Se illa, Spain; [email p o ec ed] (J.F.F.-R.); [email p o ec ed] (A.P.); [email p o ec ed] (E.P.)
2Ins i u o Uni e si a io de A qui ec u a y Ciencias de la Cons ucción, Uni e sidad de Se illa,
41012 Se illa, Spain
*Co espondence: [email p o ec ed]
Abs ac :
Recen ad ances in isual p og amming ools o algo i hmic modelling ha e sig-
ni ican ly expanded he possibili ies o designing indus ial p oduc s. This s udy analyses
he capaci y and adap abili y o G asshoppe , a g aphical algo i hm edi o in eg a ed wi h
Rhinoce os 3D, as a pa ame ic design ool in he de elopmen o p oduc pla o ms. Th ee
case s udies we e conduc ed o e alua e he impac o pa ame e con igu a ion in p oduc
amilies: pe ume bo les, ou doo u ni u e, and desk o ganise s. The analysis p o ided
insigh in o he abili y o G asshoppe o (1) au oma e he gene a ion o p oduc a ian s
wi hin pla o ms; (2) enable he lexible c ea ion o scalable, cus omised design al e na i es;
and (3) imp o e e iciency in he pla o m design p ocess in e ms o ime and echnical
esou ces. The esul s show ha G asshoppe p o ides s ong capabili ies o cus omising
geome ic pa ame e s compa ed o adi ional modelling in Rhinoce os 3D. Howe e , i s
adap abili y is mo e limi ed when cus omisa ion in ol es in e dependen pa ame e s, such
as hose ela ed o e gonomics o usabili y, due o he di icul y o ansla ing hese e-
qui emen s in o algo i hmic s uc u es. In addi ion, he ini ial de ini ion o pa ame e s and
cons ain s may es ic modi ica ions in la e design phases. These indings unde line he
need o algo i hm models ha suppo i e a i e adjus men s and lexible econ igu a ion
h oughou all phases o he design p ocess.
Keywo ds:
G asshoppe algo i hmic modelling; pa ame ic design; compu a ional design;
indus ial design; p oduc design; p oduc pla o ms; cus omisa ion; concep ual design;
de ailed design
1. In oduc ion
Indus ial p og ess has been ma ked by he inco po a ion o echnologies ha ha e
ans o med socie ies and p oduc ion p ocesses [1]. In he ield o indus ial design, hese
ad ances ha e gene a ed he need o mo e agile me hodologies. These me hodologies
allow an e icien esponse o cu en ma ke demands, cha ac e ised by high a iabili y
and a g owing demand o cus omisa ion. Among hese, a i icial in elligence, ad anced
au oma ion, and in elligen manu ac u ing s and ou o hei abili y o d i e adap a ion o
a cons an ly changing ma ke [2–9].
Indus ial p oduc design is cha ac e ised by a high demand o cus omisa ion and
scalabili y based on use segmen s and p o iles. In esponse, companies and manu ac-
u e s equen ly employ p oduc pla o m s a egies. These pla o ms make i possible
o gene a e p oduc a ian s ha adap o he ma ke in a mo e e icien and s uc u ed
way. This is achie ed h ough a combina ion o s anda disa ion and cus omisa ion in
Appl. Sci. 2025,15, 6243 h ps://doi.o g/10.3390/app15116243
Appl. Sci. 2025,15, 6243 2 o 23
design and manu ac u e. On he one hand, he s anda disa ion o componen s, modules,
o manu ac u ing p ocesses acili a es mass p oduc ion and p omo es economies o scale.
This app oach con ibu es o educing cos s and educing de elopmen imes. On he
o he hand, hese pla o ms o e lexibili y o in oduce cus omisable elemen s ha adap
o speci ic use demands, sa is ying mo e indi idualised ma ke segmen needs. This
balance be ween s anda disa ion and cus omisa ion makes p oduc pla o ms a use ul
s a egy o op imise he use o echnical, human, and economic esou ces. Addi ionally,
i imp o es compe i i eness in an inc easingly dynamic ma ke . Howe e , al hough hey
o e he ad an ages men ioned abo e, he pla o m design p ocess is highly complex. This
is pa icula ly e iden in he gene a ion and managemen o p oduc a ian s, as well as in
he adap a ion o solu ions o speci ic use equi emen s. These equi emen s a e linked o
mul iple con ex s o use, a ian s o p oduc s, and con igu a ions. This si ua ion inc eases
wo kload and makes design ac i i ies mo e di icul . Gene ally, such p ojec s equi e engi-
nee ing eams o plan ex ensi ely o achie e a p ope in eg a ion be ween s anda dised
and cus omisable componen s. This le el o complexi y is usually add essed h ough he
applica ion o speci ic design me hodologies. The implemen a ion o hese me hodologies
equi es a signi ican in es men in echnical, human, and empo al esou ces, pa icula ly
du ing he ea ly s ages o concep ualisa ion [10,11].
Wi hin his amewo k, compu a ional design, in i s di e en pa ame ic, algo i hmic,
o gene a i e scopes, is a solu ion o add ess hese limi a ions. This happens because
o he possibili y o au oma ing epe i i e asks gene a ing mul iple design a ian s and
con igu a ions acco ding o p ede ined c i e ia. These ools simpli y he p ocess and expand
c ea i e and echnical possibili ies by p o iding agile wo king en i onmen s. T adi ionally,
compu a ional design esou ces o p oduc pla o ms equi ed ad anced p og amming
knowledge and specialised echnical so wa e. The u ilisa ion o so wa e such as Ca ia
(Dassaul Sys èmes, Vélizy-Villacoublay, F ance), Ansys (Ansys Inc., Canonsbu g, PA, USA),
and Ma lab, (Ma hWo ks Inc., Na ick, MA, USA) in conjunc ion wi h speci ic p og amming
en i onmen s such as Ja a, Py hon, o C++, necessi a es he possession o ad anced
coding and p og amming abili ies. Consequen ly, hese ools a e p edominan ly used by
mul idisciplina y eams. Howe e , ecen de elopmen s in isual p og amming ools, such
as G asshoppe (an in eg a ed componen in Rhinoce os 3D (Robe McNeel & Associa es,
Sea le, WA, USA) [
12
], Fusion 360 Gene a i e Design (Au odesk Inc., San F ancisco,
CA, USA) [
13
] o Al ai Hype Wo ks (Al ai Enginee ing Inc., T oy, MI, USA) [
14
], a e
s eamlining design p ocesses h ough isual in e aces based on node manipula ion and
g aphical lows. In his con ex , non-p og amming enginee ing and design eams can ca y
ou bo h algo i hmic and gene a i e design (Figu e 1).
G asshoppe (GH) (McNeel Eu ope, Ba celona, Spain) is a isual pa ame ic p og am-
ming plug-in o Rhinoce os 3D (RH), used in a chi ec u e, enginee ing and compu a ional
design. I acili a es he gene a ion and manipula ion o complex geome ies using g aphi-
cal algo i hms wi hou he need o ex ual coding. I s compe ence in s uc u e algo i hmic
modelling p ocesses makes i a undamen al ool in s uc u al op imisa ion, ad anced
modelling and digi al ab ica ion. Nume ous s udies ha e analysed GH in he scien i ic
li e a u e [
15
–
21
]. Publica ions show how hese esou ces a e use ul o he gene a ion
o complex o ms, mass cus omisa ion, and design au oma ion based on speci ic pa am-
e e s [
17
,
22
,
23
]. Fu he mo e, GH has also been combined wi h op imisa ion s a egies,
including g adien -based me hods, mul i-objec i e op imisa ion [
24
,
25
] and me aheu is ic
algo i hms (e.g., gene ic algo i hm, neu al, o swa m ne wo ks) [
26
,
27
], o each he bes de-
sign solu ions. O he sec o s ha ha e aken ad an age o hese ools a e a chi ec u e [
28
],
ex ile design [
29
–
32
], jewelle y design [
33
,
34
], and co po a e iden i y [
35
,
36
]. Howe e , no
Appl. Sci. 2025,15, 6243 3 o 23
esul s ha e been ound o e alua e he applica ion o his ype o esou ce in he design o
p oduc pla o ms.
Figu e 1. Algo i hmic modelling p ocess applied o p oduc pla o ms.
The no el y o his s udy lies in he applica ion o algo i hmic modelling wi h
G asshoppe o p oduc amilies and pla o m-based design. While p e ious s udies ha e
assessed p oduc pla o ms de eloped h ough con en ional pa ame ic modelling [
37
–
40
],
no publica ions ha e iden i ied ha apply his app oach using G asshoppe . In addi ion,
he e is a lack o compa a i e esea ch add essing pla o m-based p oduc s wi h di e -
en unc ionali ies unde a uni ied me hodological amewo k. This s udy in oduces
unc ional di e si y ac oss case s udies, enabling b oade conclusions ha may be appli-
cable o a ious a eas o indus ial design. Mo eo e , he esea ch spans mul iple phases
o he p oduc design p ocess, including concep ual, embodimen , and de ailed design
s ages [
41
,
42
], suppo ed by he de ini ion o pa ame e s co e ing geome ic, ma e ial,
unc ional, e gonomic, and usabili y aspec s.
To e alua e he use o GH in he de elopmen o p oduc pla o ms, h ee case s ud-
ies we e selec ed. The chosen p oduc s (pe ume bo les, ou doo u ni u e, and desk
o ganise s) come om di e en sec o s o indus ial design o e alua e he applicabili y o
he me hodology in a ious p oduc ypologies. The selec ed case s udies ep esen he
ypologies o pla o ms [
10
,
11
]: (1) a scale-based pla o m wi h a ia ion o ou a iables
(colou , dimensions, ma e ials, and ounding), esul ing in a amily o pe ume bo les; (2) a
scale-based pla o m wi h a ia ion o se e al a iables (dimensions, p opo ions, colou ,
ounding, pa e n and ma e ials), esul ing in a amily o ou doo u ni u e; and (3) a mod-
ula design pla o m wi h a ia ion o mul iple a iables (dimensions, p opo ions, colou ,
shape, o m, ounding, ma e ials, and pa e n), esul ing in a amily o desk o ganise . The
a iables analysed we e only hose ha a ec ed he cus omisa ion o he p oduc . The
analysis p o ided insigh in o he e ec i eness o GH o (1) au oma e he gene a ion o
p oduc a ian s wi hin he pla o ms, (2) ha e he lexibili y o gene a e cus omised and
scalable design al e na i es o he a ge use g oup, and ha e (3) he e iciency in he
p oduc pla o m design p ocess, in e ms o ime and echnical esou ce usage.
This a icle is s uc u ed as ollows: Sec ion 2p o ides he necessa y backg ound o
unde s and he esea ch; Sec ion 3desc ibes he me hodology used in his s udy; Sec ion 4
builds he case s udies o he h ee p oduc pla o ms de eloped wi h GH; Sec ion 5shows
he esul s o he e alua ion o he abili y o he ool o adap and cus omise he design o a
Appl. Sci. 2025,15, 6243 4 o 23
p oduc pla o m; and Sec ion 6discusses he esul s, se ing ou he main conclusions o
his s udy in Sec ion 7.
2. Backg ound
Compu a ional design uses algo i hms, compu e p og amming, and pa ame ic
modelling o gene a e, analyse, and op imise design solu ions. Usually, his app oach
equi es speci ic p og amming and coding skills. Howe e , ecen ad ances ha e enabled
he c ea ion o algo i hms h ough in ui i e ‘d ag-and-d op’ in e aces, simpli ying he
p ocess. Consequen ly, digi al ools ha inco po a e isual p og amming expand he
possibili ies o design and de elopmen .
Unlike adi ional design, which ollows a linea sequence o ske ching, CAD mod-
elling and p o o yping, compu a ional design uses algo i hms. These algo i hms gene a e
mul iple solu ions simul aneously. This enables g ea e speed and lexibili y in explo ing
a ia ions in p oduc design [
43
]. Compu a ional design is o en classi ied in o h ee ca e-
go ies: design o cus omisa ion, design o digi al ab ica ion, and gene a i e design and
c ea i e explo a ion [
44
]. The ocus o pa ame ic design is he de ini ion o pa ame e s o
a iables ha go e n he cha ac e is ics o a design. This enables au oma ic modi ica ion o
elemen s based on inpu alues. In his app oach, adjus men s occu h ough in e depen-
den ela ionships be ween elemen s. These a e go e ned by he o mula ion o ules and
algo i hms ha enable he gene a ion o complex s uc u es. On he o he hand, gene a i e
design allows he au oma ic gene a ion and e alua ion o mul iple design solu ions based
on speci ic objec i es [
45
]. This is an example o he unc ionali y o GH and o he RH
so wa e plug-ins, which acili a e he managemen o highly complex designs h ough
he use o speci ic pa ame e s. I s p ima y u ili y lies in he gene a ion o shapes ha
acili a e expansi e c ea i e possibili ies h ough luid, lexible, adap able, apid, and isual
modi ica ions. This so wa e helps de ine p ecise ins uc ions o de eloping p oduc s wi h
geome ies ha main ain he ini ial design concep . Simul aneously, i allows lexibili y in
making i e a ions and necessa y adap a ions o mee use needs [46].
GH os e s g ea e c ea i i y compa ed o adi ional design me hods ha do no ely
on algo i hms [
47
]. I in luences he c ea i e p ocess o designe s. I encou ages di e gen
hinking and he explo a ion o solu ions, al hough i s impac a ies acco ding o use
expe ience [
48
]. I allows apid i e a ions, hyb id o ms, and he explo a ion o inno a i e
ideas, al hough wi h he challenge o equi ing ad anced echnical skills [18,49].
P oduc cus omisa ion has gene a ed signi ican in e es in he p o essional and e-
sea ch ields. The aim is o achie e a high capaci y o modi y he cha ac e is ics o he
p oduc . The e a e case s udies whe e au oma ion is ocused on p oduc s whe e eal- ime
adap a ion o he use is impo an . Fo example, mass cus omisa ion o glasses, allowing
eal- ime adjus men o 3D models acco ding o use dimensions and p e e ences o he
use [
50
]; in eg a ing 3D acial da a ob ained wi h pho og amme y [
51
]; pe o ming 3D
scanning o he ace, imp o ing unc ionali y [
52
]; and designing glasses ames h ough
a pa ame ic algo i hm adap ed o use -speci ic ana omical da a [
53
]. Ano he ecu en
ype o p oduc is oo wea . This analysis is ca ied ou o e alua e he p ecision and
adap abili y o he p oduc , a capabili y enabled by he in eg a ion o indi idualised use
da a on he oo . Some s udies ocus on he design o pa e ns o he base o he shoe ha
las s [
54
–
56
], while o he s ocus on au oma ic i ing acco ding o speci ic da a o he use ’s
oo , op imising cos s and ime [
57
]. An addi ional sec o ep esen ed in his ype o s udy
is u ni u e. This ield in ol es he c ea ion o in e aces ha enable use s o di ec ly adjus
pa ame e s, he eby acili a ing he eal- ime isualisa ion o designed u ni u e. GH is
used o he adjus men o dimensions, ma e ials, and aes he ics, as well as o he c ea ion
o assembly ins uc ions and iles o 3D manu ac u ing pu poses [58,59].
Appl. Sci. 2025,15, 6243 5 o 23
The g owing demand o cus omised solu ions has d i en he use o algo i hmic mod-
elling ools such as GH. These ools make i possible o c ea e p oduc s ailo ed o he indi id-
ual needs o use s, op imising aes he ics and unc ionali y by au oma ing pa ame e s.
In he scien i ic li e a u e, GH has been used speci ically o cus omise o igami-inspi ed
s uc u es [
60
]. I has also been used o design su boa d and paddleboa d ins ha
op imise pe o mance and sui su e s’ pe sonal p e e ences [
61
]. O he uses include
gene a ing e ol ing mesh shapes om cus omised e olu ion p o iles based on ma e ial
densi y and mesh pa e ns [
62
], pe o ming isogeome ic analysis (IGA) in enginee ing by
op imising he design and analysis cycle [
43
], and c ea ing p oduc designs wi h Vo onoi
pa e ns inspi ed by na u e and adi ional Chinese cul u e [
63
]. GH has also been used o
op imise he c ea i e and p oduc ion p ocess in u ni u e design wi h g ea e lexibili y
and esponsi eness o ma ke demands [
59
], c ea e complex and cus omised pa e ns in
ex ile design by imp o ing e iciency and adap abili y in he ex ile indus y [
64
], and
design bo les ha adap hei shape and ex u e acco ding o use ac ile p e e ences,
combining Kansei enginee ing and design [
65
]. Fu he mo e, GH has been used o design
o namen al pa e ns based on adi ional cul u al mo i s [
66
] and o design e gonomic
sea ing by in eg a ing an h opome ic and e gonomic da a o op imise p oduc shape,
unc ionali y, and cus omisa ion [67].
Al hough nume ous applica ions o GH ha e been explo ed in o he a eas o design,
he cu en li e a u e on i s use in pla o m design is limi ed. P oduc pla o ms a e
cu en ly he s a egies ollowed by he indus y o manage hei p oduc po olios in
he ma ke place [
10
,
11
]. They o e signi ican ad an ages, such as educing de elopmen
ime and cos s h ough componen euse and inc easing p oduc a ie y wi hou adding
excessi e p oduc ion complexi y. Mo eo e , hey acili a e mass cus omisa ion o add ess
di e se consume needs. Howe e , p oduc pla o m design also p esen s impo an
challenges. These include he complexi y o managing in e dependen componen s, he
need o e icien modula isa ion s a egies, and he di icul y o balancing s anda disa ion
wi h cus omisa ion. In his sense, GH could s eamline he p oduc pla o m design p ocess
by au oma ing he gene a ion o mul iple cus omised p oduc a ian s h ough a single
algo i hm. By in eg a ing pa ame ic modelling, GH enables designe s o de ine ules and
cons ain s ha ensu e consis ency ac oss pla o m a ian s. I also acili a es eal- ime
isualisa ion o design al e na i es while allowing adjus men s o pa ame e s such as
dimensions, ma e ials, and unc ional cha ac e is ics.
Finally, i is in e es ing o conside he ela ionship be ween design pa ame e s and
manu ac u ing c i e ia om he ea ly s ages o he p ocess. Decisions aken du ing pa a-
me ic modelling condi ion he echnical and economic easibili y o he p oduc . Ce ain
combina ions o geome ies, ma e ials, o con igu a ions may be complex o un easible
o manu ac u e wi h con en ional echnologies. The e o e, inco po a ing manu ac u ing
c i e ia in o algo i hmic models allows he cons ain s o he p oduc ion p ocess o be
conside ed in he concep ual design phase.
3. Me hodology
This s udy adop s a mul iple case s udy me hod wi h an explo a o y, compa a i e
app oach [
68
] o e alua e he easibili y and e ec i eness o algo i hmic modelling using
GH in he design o p oduc pla o ms. Th ee ep esen a i e cases om di e en a eas o
indus ial design we e selec ed o co e a a ie y o unc ional and use- ela ed con ex s.
The me hodology was s uc u ed in o he h ee phases shown in Figu e 2: (1) de ini ion
and modelling o each pla o m using GH; (2) iden i ica ion and classi ica ion o design
pa ame e s, dis inguishing hose ela ed o he p oduc and he pla o m; and (3) mul i-
c i e ia analysis o quan i y he in luence o each pa ame e on pla o m cus omisa ion.
Appl. Sci. 2025,15, 6243 6 o 23
Figu e 2. Resea ch me hodology.
In he i s phase, h ee p oduc pla o ms we e selec ed, each ep esen a i e o di -
e en a eas o indus ial design (packaging, u ni u e, and o ice o ganisa ion), wi h he
aim o co e ing a ange o unc ional, aes he ic, and con ex ual equi emen s. The selec ed
cases encompass all pla o m ypologies desc ibed in he li e a u e and commonly used in
indus y [
10
,
11
]: (1) scale-based pla o ms, which allow esizing o adap ing a base design
o o e p oduc s wi h di e en capabili ies o pe o mance le els, and (2) module-based
pla o ms, which ely on he combina ion and in e changeabili y o s anda dised modules
wi h a sha ed a chi ec u e and de ined in e aces. Pa ame ic models we e de eloped
by cons uc ing algo i hms in G asshoppe 1.0 and Rhinoce os 8.0, allowing o lexible
con igu a ion o each pla o m h ough au oma ic modi ica ion o design pa ame e s (di-
mensions, p opo ions, colou , shape, ounding, ma e ials, and pa e n). This p ocess
enables he cus omisa ion o he de i ed p oduc s, adap ing hem o speci ic use needs
and use con ex s.
The second phase iden i ied he analysis a iables equi ed o assess he easibili y
and e ec i eness o GH algo i hmic modelling in he design o he p oduc pla o ms.
These a iables we e s uc u ed in o wo g oups: G oup 1 wi h p oduc design pa ame e s
and G oup 2 wi h pla o m design pa ame e s. In his con ex , design pa ame e s a e
unde s ood as con igu able a ibu es in GH ha de ine he unc ionali y, appea ance, o
use adap a ion o a p oduc (G oup 1) o a pla o m (G oup 2).
Table 1p esen s bo h se s o pa ame e s and de ines hei scope in e ms o cus omisa-
ion o p oduc design cus omisa ion. G oup 1 (PR
i
) includes he a ibu es and p ope ies
o he p oduc ha allow e alua ion o i s le el o cus omisa ion (o use adap a ion): di-
mensions, p opo ions, colou , shape, ounding, ma e ials, and pa e n. These pa ame e s
can be con igu ed di ec ly wi hin he pa ame ic model. The selec ion was based on i s
abili y o con ol he isual and aes he ic aspec s o he p oduc ; in addi ion, only hose
pa ame e s whose manipula ion is echnically easible in GH wi hou he use o ex e nal
esou ces we e included. G oup 2 (PL
j
) includes pa ame e s o e alua e he p oduc pla -
o m om a ma ke pe spec i e: scalabili y, modula i y, usabili y, e gonomics and con ex
o use. An app op ia e combina ion o hese p ope ies allows manu ac u e s o de elop a
di e si ied p oduc o e ing ailo ed o use g oups wi h highly di e en ia ed needs. The
selec ion was based on hei ele ance as essen ial equi emen s ha a pla o m mus mee
o e ec i ely adap o a speci ic ma ke segmen and ensu e i s economic iabili y.
In phase 3, he le el o cus omisa ion o e ed by each pa ame ic model de eloped
in GH was e alua ed. A sys ema ic obse a ion p ocess was ca ied ou o documen he
beha iou o he model when modi ying he pa ame e s lis ed in Table 1. The esul s we e
used o analyse he easibili y and e ec i eness o algo i hmic modelling wi h GH in he
design o p oduc pla o ms.
Appl. Sci. 2025,15, 6243 7 o 23
Table 1. Pa ame e s o mul i-c i e ia analysis.
Pa ame e G oup Design
Pa ame e De ini ion Cus omisa ion Scope
GROUP 1. P oduc Design Pa ame e s (PRi)
Dimensions
Leng h, wid h, and heigh o he p oduc .
De ines p oduc scale.
Func ional and spa ial cons ain s.
P opo ions
Ra io be ween he dimensional a ibu es
ha de ine he olume ic balance o
he p oduc .
Visual ha mony and
pe cei ed e gonomics.
Use accep ance and in eg a ion wi h
o he componen s.
Colou Hue, alue, and sa u a ion used in he
su ace appea ance.
Aes he ic pe cep ion, use p e e ence,
and con ex ual i ( isibili y,
b anding, cul u e).
Shape
Geome ic o o ganic con igu a ion o he
o e all o m o he p oduc .
Visual iden i y and usabili y; emo ional
connec ion and ecogni ion.
Rounding
Deg ee o cu a u e a edges and co ne s
o imp o e ac ile and isual quali y.
Imp o es sa e y, com o , and
ac ile in e ac ion.
Ma e ials Type, ex u e and su ace inish o he
ma e ials applied o each elemen .
Du abili y, aes he ics, sus ainabili y,
senso y in e ac ion, and sa is ac ion.
Pa e n
Repe i ion o a angemen o g aphical o
s uc u al mo i s ac oss he
p oduc su ace.
Aes he ics; allows di e en ia ion o
p oduc a ian s and cul u al adap a ion.
GROUP 2. Pla o m Design Pa ame e s (PLj)
Scalabili y
Abili y o he pla o m o gene a e
e sions o he p oduc in di e en sizes
o pe o mance le els.
Adap a ion o di e en ma ke segmen s
o use needs.
Modula i y
Abili y o con igu e he p oduc by
combining o eplacing s anda dised
modules.
Suppo s a ia ion, epai abili y, and
manu ac u ing (economies o scale);
mass cus omisa ion.
Usabili y
E ec i eness, e iciency, and sa is ac ion
o he use , in acco dance wi h
ISO 9241-11:2018 [69].
In ui i e and sa is ac o y use in
di e en se ups.
E gonomics
Adap a ion o he p oduc o physical
cha ac e is ics o use s, ollowing EN
1005 se ies [70–73] and ISO 15534
se ies [74–76].
Com o and physical i ; sa e y,
pe o mance, and e gonomic compliance.
Con ex o Use
Cha ac e is ics ha allow he p oduc o
be adap ed o speci ic
en i onmen al condi ions.
Adap a ion o en i onmen al ac o s
(indoo /ou doo , empe a u e,
humidi y, space).
The e alua ion p ocess was based on a mul i-c i e ia analysis o quan i y he ela ion-
ship be ween he pa ame e s o g oup 1 (PR
i
, p oduc design) and g oup 2 (PL
j
, pla o m
design). Each ela ionship was nume ically assessed using a h ee-le el scale (low, medium,
and high), indica ing he deg ee o in luence o each pa ame e on p oduc cus omisa-
ion. Each le el was de e mined by a combina ion o h ee c i e ia: (i) he numbe o
con igu able pa ame e s in he GH en i onmen , (ii) he scope o cus omisa ion (aes he ic,
unc ional, o s uc u al), and (iii) he ime equi ed o con igu e he pa ame e wi hin
he pa ame ic model in GH. Table 2shows he h esholds used. All h ee c i e ia a e
s uc u ed inc emen ally, e lec ing inc easing deg ees o complexi y o design in e en ion.
Speci ically, in c i e ion (ii), he scope o cus omisa ion p og esses om aes he ic ( ela ed o
pe cep ual a ibu es) o unc ional (modi ica ions a ec ing he use and ope a ional ea u es
o p oduc s) and inally o s uc u al (in ol ing he physical con igu a ion and in e ela ion
o componen s). Each le el ep esen s a deepe deg ee o ans o ma ion and builds upon
he p e ious one. The h esholds we e de ined based on obse ed alues and compa a i e
Appl. Sci. 2025,15, 6243 8 o 23
analysis ac oss he h ee case s udies, wi h he aim o consis en ly dis inguishing pa ame e
complexi y and pla o m esponsi eness using expe -based c i e ia.
Table 2. C i e ia o classi ica ion le els.
Classi ica ion Le els Vij
Low (1) Medium (2) High (3)
C i e ia
(i) Numbe o
con igu able pa ame e s
<5 pa ame e s 6–10 pa ame e s >10 pa ame e s
(ii) Impac on p oduc
cus omisa ion
Aes he ic
a ia ions
Aes he ic and
unc ional
a ia ions
Aes he ic,
unc ional, and
s uc u al a ia ions
(iii) Time equi ed o
con igu a ion <1 min 1–5 min >5 min
Fo he quan i a i e analysis, he classi ica ion by le els in Table 2was ans o med
in o disc e e nume ical alues, assigning 1 o he low le el, 2 o he medium le el, and 3
o he high le el. A double-en y ma ix was cons uc ed o ela e each p oduc design
pa ame e o PR
i
(G oup 1, Table 1) wi h each pla o m design pa ame e o PL
j
(G oup 2,
Table 1). Each ma ix cell con ains he sco e assigned
Vij
o he ela ionship be ween a pai
o pa ame e s. The o al sco e
PDi
o each p oduc design pa ame e was calcula ed using
Equa ion (1); whe e
PDi
is he o al sco e o he p oduc design pa ame e PR
i
and
Vij
is
he alue assigned o he ela ionship be ween he p oduc pa ame e PR
i
and he pla o m
pa ame e PLj:
PDi=
5
∑
j=1
Vij (1)
To exp ess he ela i e in luence o each ela ionship, he alues we e no malised using
Equa ion (2) agains a ixed maximum o al sco e, de ined as he hypo he ical case in which
a p oduc design pa ame e ecei es he maximum sco e (3) in all i e pla o m pa ame e s;
whe e
Ni
is he no malised alue o ela i e deg ee o cus omisa ion o pa ame e PR
i
wi h
espec o he heo e ical maximum (MAX):
Ni=
PDi
MAX (2)
The goal was o ep esen he ela i e dis ibu ion o he in luence o each p oduc
pa ame e (G oup 1) on he pla o m pa ame e s (G oup 2). The esul s we e isualised
using s acked ba cha s; each ba ep esen s a p oduc design pa ame e (dimensions,
p opo ions, colou , shape, ounding, ma e ials, and pa e n), and i s segmen a ion e lec s
i s impac on he pla o m (scalabili y, modula i y, usabili y, e gonomics, and con ex o
use) based on he ela i e weigh o each pai wise sco e as de ined by Equa ion (3); whe e
SiJ
ep esen s he ela i e con ibu ion o he pla o m pa ame e PL
j
o he o al sco e o
he p oduc pa ame e PRi:
SiJ =
Vij
MAX (3)
4. Case S udies
4.1. Case S udy 1: Pe ume Bo le Pla o m
The i s pla o m is based on scales. All con aine s sha e he p ima y unc ion o
s o ing pe ume. Howe e , he p oduc s di e in hei pe o mance le el, wi h di e en
capaci ies o 30 mL, 50 mL, and 100 mL. This example combines algo i hmic modelling
ools wi h adi ional design p ocesses [77].
Appl. Sci. 2025,15, 6243 9 o 23
The objec i e o he p ojec was o de elop a amily o pe ume bo les inspi ed by
ma ine hemes. The p oposal ocused on c ea ing a single algo i hm capable o gene a ing
he main design. This design was de ined du ing he ea ly s ages o p oduc design and
de elopmen , along wi h i s a ian s in di e en sizes. Al hough all con aine s ea u e he
same ma e ials, h ee di e en colou anges a e o e ed.
Concep ual de elopmen began wi h concep ske ches, which we e e alua ed o selec
he mos app op ia e solu ion. Subsequen ly, he de ailed design was de eloped using
isual p og amming in G asshoppe 01 and Rhinoce os 08.
The de elopmen o he algo i hm (Figu e 3) o design a con aine ocused on gene a -
ing pa ame ic geome ies om a speci ied olume. This was ca ied ou while main aining
he aes he ic design ha had been es ablished p e iously. GH does no allow olume
o be used di ec ly as an inpu pa ame e . The e o e, a ank wi h apezoidal geome y
was designed, adjus able h ough a scaling ac o ha modi ies he wid h and heigh ,
while keeping he dep h ixed. This ac o was calib a ed o ob ain speci ic olumes and
in eg a ed as a disc e e pa ame e in he algo i hm. The ou e geome y o he con aine
was c ea ed om an o se o he ank, gene a ing a guide su ace ha de ined he con ou
and was adjus ed p opo ionally. The algo i hm also included he design o a co al-like
slee e using he ‘Dend o’ plug-in, gene a ing a qua e o he ini ial design and eplica ing
i symme ically. The slee e was adap ed o all a ia ions o he con aine by scaling,
ans o ming i in o ‘SubD’ geome y o an o ganic appea ance. Finally, he algo i hm
made i possible o p e iew all pa s and con igu a ions o he p oduc . The ull sc ip o
he case s udy can be consul ed (see Da a A ailabili y S a emen ).
Figu e 3. G asshoppe algo i hm o Case S udy 1.
Wi h espec o he selec ion o a iables in Table 1(see Sec ion 2), G oup 1 includes
only hose pa ame e s ha ha e a di ec impac on p oduc cus omisa ion: dimensions,
colou , ounding, and ma e ials. In con as , all pla o m- ela ed pa ame e s om G oup 2
we e included in he analysis.
4.2. Case S udy 2: Ou doo Fu ni u e Pla o m
The second case co esponds o he design o a amily o ou doo u ni u e. I is
de eloped as a scale-based pla o m whose main unc ion is o p o ide sea ing wi h
di e en cha ac e is ics. The pa icula i y o his pla o m lies in he di e si y o posi ions
o use, which gi es ise o a ia ions in shapes. On his pla o m, algo i hmic modelling
plays a key ole, allowing adjus men s o be made o he dimensions o he p oduc .
Appl. Sci. 2025,15, 6243 16 o 23
This pla o m is he only one ha eaches a pe cen age o 100% in one o he p oduc
pa ame e s, namely, he dimension pa ame e . In his case, he adjus men o leng h, heigh ,
and dep h allows o a high deg ee o lexibili y in he modi ica ion. This modi ica ion
posi i ely a ec s scalabili y, modula i y, usabili y, e gonomics, and con ex o use. Simila ly,
he colou pa ame e , bo h in one and in alue and sa u a ion, has a high in luence on
almos all pla o m pa ame e s. I should be no ed ha , o his ype o p oduc , he
in luence o colou on he adap a ion o he pla o m o a ious con ex s o use is e y
impo an . The e o e, he con ex o use is one o he pla o m pa ame e s ha mos bene i
om he algo i hm design in his case s udy.
5.4. Compa a i e Analysis o Case S udies
The compa a i e analysis (Table 6) e eals signi ican di e ences in he capaci y o
each pla o m o gene a e cus omised a ian s h ough he pa ame ic con igu a ion o
models in GH.
The h ee case s udies allow o he assessmen o how e ec i ely he algo i hmic
model has been s uc u ed o enable p oduc cus omisa ion while p ese ing he in eg i y
o he base a chi ec u e used in he pla o m.
The pla o m o desk o ganise s (Case 3) s ands ou as he mos obus in e ms o
pa ame ic design. The algo i hm ha was de eloped makes i possible o gene a e a ian s
by modi ying bo h geome ic and unc ional aspec s, while main aining a cohe en sha ed
s uc u e. This is he only case ha inco po a es explici modula i y in o he a chi ec u e
o he p oduc , which signi ican ly inc eases he po en ial o adap a ion o di e en use
needs and con ex s o use.
The pla o m o ou doo u ni u e (Case 2) also suppo s a high le el o cus omisa ion,
especially in o mal a ibu es such as dimensions and p opo ions. Howe e , i is based
on scaling a single p oduc ypology wi hou al e ing i s s uc u e. As a esul , i does no
inco po a e a modula app oach o enable eo ganisa ion o componen s. This limi a ion
e lec s a design s a egy ha emphasises scalabili y o e componen econ igu a ion.
In he case o pe ume bo les (Case 1), al hough he model allows some a ia ion
h ough adjus men s in colou , olume, and inish, he o e all capaci y o cus omisa ion
emains limi ed.
Among he analysed pa ame e s, dimension appea s as he mos commonly con igu able
aspec in all h ee cases, con i ming i s ele ance as a key a iable in pa ame ic modelling. In
con as , deco a i e pa e n has limi ed p esence, possibly because i is no associa ed wi h
s uc u al o unc ional di e en ia ion, bu a he wi h pu ely aes he ic a ia ion.
In conclusion, he desk o ganise pla o m (Case 3) achie ed he highes deg ee o
p oduc a ie y, suppo ed by a modula a chi ec u e ha enables bo h geome ic and
unc ional di e en ia ion. The ou doo u ni u e pla o m (Case 2) was o ien ed owa ds
scalabili y h ough dimensional a ia ion o a ixed p oduc ype. In con as , he pe ume
bo le pla o m (Case 1) exhibi ed he lowes le el o con igu abili y, limi ed p ima ily
o aes he ic modi ica ions. These indings highligh he impo ance o ea ly a chi ec u al
decisions in enhancing pla o m obus ness and enabling he euse o co e design elemen s
ac oss mul iple a ian s.
Appl. Sci. 2025,15, 6243 17 o 23
Table 6. Syn hesis o esul s.
Pla o m Pa ame e s
Scalabili y Modula i y Usabili y E gonomics Con ex
o Use
P oduc Pa ame e s
Dimensions
P opo ions
Colou
Shape
Rounding _
Ma e ials
Pa e n _
Pla o m 1:
, Pla o m 2: , Pla o m 3: .
6. Discussion
This esea ch aligns wi h a b oad consensus ha algo i hmic modelling e ec i ely
suppo s eal- ime upda es and i e a i e modi ica ions in design. This is a i med by s udies
on cus omisa ion o p oduc design, such as, o example, hose o Mana is, Mad igal, and
Bai [
19
,
50
,
58
]. In e ms o mass cus omisa ion, some s udies ha e included in e aces whe e
use s can adjus pa ame e s and ob ain immedia e isualisa ions [
24
,
53
,
80
]. Fu he mo e,
his app oach encou ages collabo a ion wi h clien s o end-use s in he ield o indus ial
design while simul aneously acili a ing design lexibili y in he inal ou come. These a e
ad an ages in p oduc cus omisa ion ha can also be applicable o pla o ms, al hough
hey ha e no been he speci ic objec o s udy.
In he con ex o p oduc pla o ms, i is wo h men ioning a sys ema ic e iew pub-
lished in 2019 [
81
]. This s udy es ablishes he ounda ions o u u e esea ch on pla o m
design unde unce ain y. Speci ically, a e e ence is made o algo i hmic modelling, in i s
gene a i e aspec , as an oppo uni y o mul i-objec i e p oduc op imisa ion. Howe e ,
he e is cu en ly no esea ch whose esul s can be compa ed wi h he wo k p esen ed
he e. In any case, i is impo an o no e ha some publica ions yield some in e es ing
conclusions ha could be use ul o he gene a i e design o p oduc amilies. Among hem,
he a icles published by K ish and Ba bie i [
16
,
18
] a e wo h no ing. Al hough he ocus is
no on pla o ms, he esul s ob ained a e o g ea in e es in his a ea. In he explo a ion o
gene a ed solu ions, i can be obse ed ha gene a i e design me hodology can con ibu e
o he design o pla o ms. In his sense, i would no be complica ed o modi y he objec i e
o explo ing design al e na i es o he gene a ion o p oduc s wi h simila cha ac e is ics
wi hin he p oduc pla o m amewo k. An MP3 playe , using Solidwo ks Geno o m
so wa e, and a s ool, using Au odesk Fusion 360 so wa e, a e used as case s udies. In bo h
cases, a mul i ude o i e a ions is ob ained. I hese a e well- ocused and es ic he limi s
o he algo i hm, hey ha e he po en ial o se e as a basis o he de elopmen o amilies.
In his sense, he gene a ion o p oduc pla o ms h ough gene a i e design would be an
in e es ing line o u u e esea ch.
Appl. Sci. 2025,15, 6243 18 o 23
In addi ion, e e ences o esea ch on shape g amma ha e been aluable o he
de eloped s udy. Au ho s such as Dy, Cos a, Re alian, Kiela o a, Mad igal, and Alcaide-
Ma zal ha e ag eed on he impo ance o he con ol o g amma ules o co ec ly encode
algo i hms [
15
,
19
,
24
,
82
–
84
]. We ag ee wi h hei iew ha de e mining design pa ame-
e s based on o mal g amma p o ides lexible and accu a e solu ions. This app oach
includes ea u es such as shapes, dimensions, colou , p opo ional ela ionships, and o he
pa ame e isable a ibu es. In all cases, he bene i becomes e iden in he design ou comes.
Pa ame ic logic enables au oma ic adap a ion o ou pu s in esponse o changes in inpu s.
I his p ocedu e is p ope ly con olled, design p ocesses could be simpli ied. The main
goal is o gene a e mul iple solu ions and p ese e hei common cha ac e is ics wi hin he
de ini ion o a p oduc pla o m.
Based on he esul s ob ained, algo i hmic modelling p o ides a iable solu ion o
imp o e he p oduc pla o m design p ocess in ela ion o cus omisa ion. I is wo h
men ioning ha i was expec ed ha he e would be a no iceable di e ence be ween he
h ee pla o ms s udied. Howe e , he la ge gap be ween he case s udies in e ms o
hei cus omisa ion possibili ies has been su p ising. Fu he mo e, i was ound ha he
p elimina y design s a egy used du ing he algo i hm de elopmen p ocess played an
impo an ole. This s a egy was key o achie ing an op imal deg ee o e sa ili y. I also
emphasises he need o a change in he design pa adigm o ensu e accu a e adap a ion
and use o he algo i hmic me hod.
The applica ion o GH has se e al limi a ions in indus ial con ex s. One o he mos
ele an is ha i does no include he necessa y complemen s o he de ailed design phase
o p oduc pla o ms. This includes simula ion ools (mechanical beha iou , e gonomics,
e c.), cos es ima ion o echnical documen a ion esou ces o au oma ically gene a ing
manu ac u ing plans, bills o ma e ials, o assembly ins uc ions. This limi a ion can be
pa ially o e come by in eg a ing GH wi h ex e nal so wa e o plug-ins, al hough his
esul s in a agmen ed wo k low. In he con ex o p oduc design, e gonomic analysis can
be app oxima ed by expo ing geome y o ools such as AnyBody (AnyBody Technology
A/S, Aalbo g, Denma k) o Au odesk Fusion. Plug-ins like Ka amba3D (s uc u al analysis)
(Ka amba3D GmbH, Vienna, Aus ia), Wallacei (mul i-objec i e op imisa ion) (Wallacei
L d., London, Uni ed Kingdom), C ys allon (in e nal s uc u es o addi i e manu ac u ing)
(FATHOM, Oakland, CA, USA), and Millipede ( opology op imisa ion and basic s uc u al
simula ion) (Digi al S uc u es, Massachuse s Ins i u e o Technology, Camb idge, MA,
USA) allow o he in eg a ion o pe o mance c i e ia om ea ly design s ages, signi ican ly
expanding he capabili ies o he pa ame ic en i onmen . Ano he limi a ion lies in he
educed capaci y o add ess complex mul idimensional pa ame e s (such as hose ela ed
o e gonomics o usabili y), which canno always be easily ansla ed in o algo i hmic ules
o simula ions.
In addi ion, GH is mainly based on isual p og amming. Th ough i s sys em o nodes
and g aphical connec ions, i is possible o de ine pa ame ic ela ionships be ween compo-
nen s, gene a e and modi y geome ies, and au oma e he design o p oduc a ian s. This
app oach acili a es he c ea ion o algo i hms wi hou he need o ad anced p og amming
skills. Howe e , in complex p oduc pla o m p ojec s, such as hose in ol ing amilies
wi h di e en p oduc anges, a la ge numbe o a ian s o modula designs, isual p o-
g amming is no su icien . The design p ocess demands a ange o challenging asks,
including he condi ional use o geome ies and he e i ica ion o compa ibili y be ween
modules o combina ions o p ope ies wi hin he pla o m a chi ec u e. Addi ionally, i
does no suppo he di ec implemen a ion o op imisa ion me hods. In hese cases, i is
necessa y o complemen he isual lows wi h sc ip ing using languages such as Py hon
o C# in eg a ed in GH. This makes i possible o c ea e mo e sophis ica ed CAD models
Appl. Sci. 2025,15, 6243 19 o 23
using s uc u es such as condi ionals ( o example, o gene a e one geome y o ano he
depending on he ype o use o he con ex o use) o loops (which make i possible o
au oma e he gene a ion o mul iple i e a ions o he same pa wi h di e en con igu a-
ions). Th ough sc ip ing, i is also possible o access ex e nal da a o au oma ically adap
he design acco ding o echnical, economic, o con ex ual c i e ia. This includes he use
o ma e ial da abases, s anda dised componen ca alogues, o cos in o ma ion. I is also
possible o implemen dynamic il e ing, such as au oma ically selec ing a ian s ha mee
es ic ions on mass, maximum dimensions, cos s, o mechanical p ope ies. This p ocess
in ol es he elimina ion o con igu a ions ha a e no easible.
The scope o his s udy is limi ed o he use o G asshoppe as he only algo i hmic
modelling en i onmen unde analysis. While his allowed o an in-dep h e alua ion o
i s capabili ies, he esul s canno be di ec ly compa ed wi h hose om o he pa ame ic o
isual p og amming ools. These limi a ions open oppo uni ies o expand he esea ch,
including he in eg a ion o ex e nal simula ion ools such as Ka amba3D o s uc u al
analysis, AnyBody o e gonomic e alua ion, o Ladybug Tools o en i onmen al pe o -
mance (Ladybug Tools LLC, Washing on, DC, USA). Also, u u e wo k could s udy he
applica ion o his me hodology in sec o s whe e p oduc pla o ms a e widely used, such
as au omo i e, consume elec onics, medical de ices, o modula cons uc ion, he eby
assessing i s adap abili y in mo e echnically demanding design con ex s.
7. Conclusions
This s udy demons a es ha he use o G asshoppe o he de elopmen o pa ame -
ic design algo i hms imp o es he e iciency and con ol o he p oduc pla o m design
p ocess. Algo i hmic modelling suppo s he managemen and adjus men o design pa-
ame e s, suppo ing a high deg ee o cus omisa ion while main aining he s uc u al
cohe ence o he pla o m. G asshoppe also acili a es he au oma ion o epe i i e asks
and he sys ema ic gene a ion o p oduc a ian s, eo ganisa ion o he inhe en ly complex
p ocess o pla o m-based design, and imp o emen o i s adap abili y and scalabili y
ac oss di e se scena ios.
The esul s unde sco e he impo ance o es ablishing a p ecise and well-s uc u ed al-
go i hmic s a egy om he ea ly s ages o he design p ocess, as he ini ial con igu a ion o
pa ame e s signi ican ly a ec s he lexibili y and esponsi eness o he esul ing pla o m.
G asshoppe has p o en o be an e ec i e en i onmen o his pu pose, allowing o apid
i e a ion, adap a ion o di e en use con ex s, and in eg a ion o use -cen ed aspec s such
as usabili y and e gonomics.
O e all, his s udy con i ms he ele ance o algo i hmic modelling as a s a egic
app oach o de eloping adap able and cus omisable p oduc pla o ms. A he same ime,
i e eals impo an limi a ions and opens a enues o u u e esea ch, including he in e-
g a ion o ex e nal simula ion ools and he e alua ion o mo e complex, mul idimensional
design pa ame e s.
Au ho Con ibu ions:
Concep ualiza ion, A.M.-M. and E.P.; Me hodology, A.M.-M.; So wa e, J.F.F.-
R. and A.P.; Valida ion, J.F.F.-R. and A.P.; Fo mal Analysis, A.M.-M.; In es iga ion, A.M.-M., E.P.,
J.F.F.-R., and A.P.; Resou ces, E.P.; Da a Cu a ion, A.M.-M.; W i ing—O iginal D a P epa a ion,
A.M.-M. and E.P.; W i ing—Re iew and Edi ing, A.P. and J.F.F.-R.; Visualiza ion, A.M.-M.; Supe i-
sion, E.P.; Funding Acquisi ion, E.P. All au ho s ha e ead and ag eed o he published e sion o
he manusc ip .
Funding:
This publica ion is pa o he R&D&I p ojec /G an PID2023-149083OA-I00 unded by 595
MICIU/AEI/10.13039/501100011033 and by FEDER EU.
Ins i u ional Re iew Boa d S a emen : No applicable.
Appl. Sci. 2025,15, 6243 20 o 23
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen :
The da a p esen ed in his s udy a e only a ailable upon eques om
he co esponding au ho due o p i acy easons.
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
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Disclaime /Publishe ’s No e:
The s a emen s, opinions and da a con ained in all publica ions a e solely hose o he indi idual
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people o p ope y esul ing om any ideas, me hods, ins uc ions o p oduc s e e ed o in he con en .
