Industry 4.0: A Proposal of Paradigm Organization Schemes from a Systematic Literature Review

  Citation: Rocha-Jácome, C.; Carvajal, R.G.; Chavero, F.M.; Guevara-Cabezas, E.; Hidalgo Fort, E. Industry 4.0: A Proposal of Paradigm Organization Schemes from a Systematic Literature Review. Sensors 2022,22, 66. https:// doi.org/10.3390/s22010066 Academic Editors: Paulo Pedreiras and João Paulo Barraca Received: 3 November 2021 Accepted: 21 December 2021 Published: 23 December 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). sensors Review Industry 4.0: A Proposal of Paradigm Organization Schemes from a Systematic Literature Review Cristian Rocha-Jácome , Ramón González Carvajal * , Fernando Muñoz Chavero, Esteban Guevara-Cabezas and Eduardo Hidalgo Fort Department of Electronics Engineering, University of Seville, 41092 Seville, Spain; [email protected] (C.R.-J.); [email protected] (F.M.C.); [email protected] (E.G.-C.); [email protected] (E.H.F.) *Correspondence: [email protected] Abstract: Currently, the concept of Industry 4.0 is well known; however, it is extremely complex, as it is constantly evolving and innovating. It includes the participation of many disciplines and areas of knowledge as well as the integration of many technologies, both mature and emerging, but working in collaboration and relying on their study and implementation under the novel criteria of Cyber–Physical Systems. This study starts with an exhaustive search for updated scientific information of which a bibliometric analysis is carried out with results presented in different tables and graphs. Subsequently, based on the qualitative analysis of the references, we present two proposals for the schematic analysis of Industry 4.0 that will help academia and companies to support digital transformation studies. The results will allow us to perform a simple alternative analysis of Industry 4.0 to understand the functions and scope of the integrating technologies to achieve a better collaboration of each area of knowledge and each professional, considering the potential and limitations of each one, supporting the planning of an appropriate strategy, especially in the management of human resources, for the successful execution of the digital transformation of the industry. Keywords: Industry 4.0; cyber–physical system; IIoT; big data; cloud computing; digital twin; cyber security; artificial intelligent; digital maturity; blockchain 1. Introduction In a globalized and highly competitive world, an industry that is not willing to innovate, to constantly improve its processes or to use emerging technologies may be condemning itself to disappear. That is why the concept of Industry 4.0 has become a fundamental pillar, both in current research and in its application in the industrial sector. There is a classification made by The IMD World Digital Competitiveness Ranking 2021, which can be a benchmark of the technological reality of industrialized countries. This ranking annually conducts studies that measure the capacity and readiness of 63 economies to adopt and explore digital technologies for economic and social transformation, considering factors, such as knowledge, technology, and preparation for the future [1]. The Industry 4.0 transition offers many opportunities to reinvent global supply chains with sustainability in mind by significantly improving supply chain processes and achieving strategic results. This digitization drive has become the mainstay of engineering organizations, regardless of size. Industry 4.0 will help organizations achieve sustainable growth and generate higher values in profits and results through faster design and development, innovative products, lower risk and reducing waste to the minimum amount possible. The social point of view reveals that technological modernization is expected to influence the spread of social transformation, especially in developing countries. However, its implementation faces technological and social challenges. It is important to identify contemporary trends and future prospects of sustainable Industry 4.0 and to study more rigorously its impact on sustainable development [2]. Sensors 2022,22, 66. https://doi.org/10.3390/s22010066 https://www.mdpi.com/journal/sensors Sensors 2022,22, 66 2 of 22 The stages in the development of industrial manufacturing systems, from manual labor to the concept of Industry 4.0, can be presented as a path through the four industrial revolutions. This path has been covered in many scientific papers; among them, we can mention [ 3 , 4 ]. The First Industrial Revolution began in the late 18th and early 19th century and was characterized by the introduction of mechanical manufacturing systems, using water and steam. The Second Industrial Revolution began in the late 19th century, symbolized by mass production based on the use of electric power. The Third Industrial Revolution began in the mid-20th century and introduced automation and microelectronic technology in manufacturing. Today, we are in the fourth industrial revolution driven by the development of information and communication technologies (ICT). Its technological basis is the intelligent automation of cyber–physical systems with decentralized control and advanced connectivity (IoT functionalities) [ 5 , 6 ]. The consequence of this new technology for industrial production systems is the reorganization of classical hierarchical automation systems to a self-organizing cyber–physical production system that enables customized and flexible mass production in production quantity [7,8]. The human factor is fundamental in Industry 4.0; its application translates into the “redefinition” of jobs, avoiding isolated knowledge and ensuring interconnectivity, collaboration, and knowledge sharing [ 9 , 10 ]. Therefore, it is necessary to talk about computer supported collaborative work (CSCW) in a way that includes the processes and resources that are involved and offers an integration of tools and methods that support the collaboration of work teams and can potentially improve the productivity and effectiveness of those who work collaboratively [ 11 , 12 ]. CSCW is generally structured around four disciplines: psychological, sociological, organizational and technological. For this paper, we focus only on the technological theme. We cannot talk about specific technologies, as the concept allows a constant evolution and a continuous integration of new technologies as they mature or adapt, i.e., several emerging technologies are converging to provide more and more digital solutions to the industry, but we will mention the main ones, and their application in this case study [ 13 ]. According to the authors of the papers [ 14 , 15 ], they clearly mention the technologies involved in the concept of Industry 4.0. They also propose in the paper [ 15 ] a conceptual framework, which they divide into front-end technologies and core technologies. The front-end technologies consider four dimensions (smart manufacturing, smart products, smart supply chain and smart work), while the base technologies consider four (Internet of Things, cloud services, big data and analytics). These works were of great help for our study, as they define a way to analyze the complex and multidisciplinary world of Industry 4.0; however, for our case, we will analyze in terms of paradigms with cyber–physical systems criteria. Our analysis proposal allowed us to clarify the concept and propose better roadmaps toward the fulfillment of each Industry 4.0 project objectives. Finally, the bibliometrics of the research is exposed in the most explicit and graphic way possible in order to not only deliver information to readers, but also as a motivation or inspiration for other researchers to have a vision of the opportunities presented by Industry 4.0 and digital transformation to see how world power countries invest in research in these areas and turn them into technological and economic leaders. 2. Materials and Methods For the development of this work, we analyzed almost two hundred scientific documents including scientific articles, books, web pages and conference proceedings of the paradigms and main mature and emerging technologies that encompass the concept of Industry 4.0 to ease the understanding of its complexity. We have tried to include as many of the technologies that are directly or indirectly involved in Industry 4.0 as possible in order to have a fairly broad and objective view of this concept. We mention the databases that were used for the collection of information: MDPI, IEEE, Taylor & Francis, Scopus, IET Inspect, dblp, EBSCO, DOAJ, Springer, Microsoft Academic, ULRICHS WEB, ELSEVIER, ScienceDirect, and Redalyc. Sensors 2022,22, 66 3 of 22 This study follows the systematic review guideline and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to ensure the soundness and reliability of the information used in this work. The main steps taken, including the protocols mentioned above, to validate our research are shown in Figure 1. Figure 1. The main steps taken to validate the research. The research strategy started with an initial search in the aforementioned databases for scientific information with the following terms or keywords: “Industry 4.0”, “Smart factory”, “Fourth industrial Revolution”, “I4.0” and “Connected Industry 4.0”. The results of this first search allowed us to understand in a general way the concept of Industry 4.0, the studies that were developed on this topic and specifically to identify the main key technologies and paradigms involved in the Fourth Industrial Revolution. The inclusion/exclusion criteria from Table 1applied were Y01, Y02, Y03, Y04, N01, N02, and N03. In addition, it is worth mentioning that no exclusions were applied due to the region, university or research center, and for this initial search, no restriction was applied with respect to the year of publication. Table 1. Inclusion and exclusion criteria. Category Criteria Code Inclusion The article corresponds to a scientific database and formally published. Y01 Articles completely written in English or Spanish Y02 The article addresses the topic of Industry 4.0 in a major way. Y03 The article mentions key paradigms and technologies involved in Industry 4.0 concept. Y04 The article relates the key technology to Industry 4.0. Y05 The article is updated no more than 5 years in the case of key technologies. Y06 The article details the contribution of the technology in question to Industry 4.0. Y07 If it is a web page, it must correspond to official scientific dissemination sites. Y08 Exclusion The article is not published in scientific databases and/or indexed journals. N01 The quality of the information is irrelevant for this study. N02 The information is redundant and of lower quality than previously included articles. N03 The article deals with emerging technologies but does not relate them to Industry 4.0. N04 The article deals with very particular case studies and with little detail. N05 The article mentions Industry 4.0 in its title or key words but does not address the topic in its content. N06 The information in the article is outdated with respect to others previously included. N07 If it is a web page, it corresponds to blogs or unofficial web pages. N08 Sensors 2022,22, 66 4 of 22 Once the key technologies and paradigms of Industry 4.0 were identified, the search for scientific information on each of them was individualized with a query as follows: “key technology” and “Industry 4.0”; “key technology” and “Smart factory”; “key technology” and “Fourth industrial Revolution”; “key technology” and “I4.0”, “key technology” and “Connected Industry 4.0”. This type of search was performed to ensure that the article studies the technology in question, but within the concept of Industry 4.0. The inclusion/exclusion criteria applied and present in Table 1were Y01, Y02, Y05, Y06, Y07, Y08, N01, N02, N03, N04, N05, N06, N07, and N08. It should be noted that there are very few exceptions of articles that did not meet the year inclusion criteria (Y06); however, the content was relevant enough to be included in this study. Furthermore, this study contains a bibliometric analysis technique to provide details of scientific production through statistical methods. The bibliometric analysis allows us to quantitatively evaluate the articles and recognize measurable patterns of interest, such as the occurrence of keywords, the geographical distribution of articles, year of publication, leading journals and databases. On the other hand, we used a content-centric analysis to identify qualitatively patterns, concepts and interrelation between the paradigms and the key technologies of Industry 4.0. Finally, this study offers two alternative schemes to analyze the complex concept of Industry 4.0 from a practical perspective to provide industries with a clearer vision of the resources needed for a successful digital transformation. The search for information for the preparation of this manuscript began in early April 2021, with the aim of presenting some preliminary data at the “XVI International Multidisciplinary Congress of Science and Technology CIT2021” held in June, where it was accepted and successfully presented. After that, the search for specific information intensified until mid-October. The number of articles of each key technology and paradigm found, excluded and included, are mentioned in Table 2. Table 2. Technologies and paradigms of Industry 4.0 analyzed. Technology/Paradigm Identified Documents Excluded Documents Included Documents References Industry 4.0 55 40 15 [1–15] Cyber–Physical Systems 61 55 6 [16–21] IoT–IIoT 120 103 17 [22–38] Cyber security 44 30 14 [39–52] Big Data and Analytics 82 73 9 [53–61] Big Data in Industry 4.0 68 55 13 [62–74] Digital Twin 45 29 16 [75–90] Cloud, Fog, Edge computing 265 240 25 [91–115] 5G in Industry 4.0 78 64 14 [116–129] AI in Industry 4.0 198 177 21 [130–150] Digital Maturity of Industry 46 36 10 [151–160] Virtual/Augmented Reality 72 55 17 [161–177] Blockchain in Industry 4.0 52 32 20 [178–196] Total 1186 989 197 2.1. Inclusion and Exclusion Criteria Table 1shows the inclusion and exclusion criteria used in this study, following the PRISMA protocols and the methodology of a systematic literature review. The criteria were coded in order to be more easily used and understood in the context of this manuscript. Basically, these criteria allow us to guarantee the trustworthiness of the scientific information, that the sources are rigorous and reliable, and that the information is useful for the purposes of this study. Sensors 2022,22, 66 5 of 22 2.2. Metadata Extraction for Analysis The strategy applied for the extraction of metadata for subsequent analysis was simple and manual. As an article was included under the inclusion and exclusion criteria, the following data were extracted for each one: geographical origin (country), year of publication, keywords, journal, or scientific publisher where it was published, and language. All this information was stored and classified in Excel spreadsheets for subsequent analysis and elaboration of diagrams. The results of this analysis can be found in the Bibliometric Analysis section. 3. Bibliometric Analysis All this information allowed us to clarify the evolution of this concept to better abstract it from the academy and to propose strategies for its better analysis and treatment, due to the multidisciplinarity and constant evolution of the concept. This concept is understood as a point of convergence of technologies that is in constant expansion, in parity with technological advances to which new techniques and technologies are progressively annexed. 3.1. Summary of Information Selection Table 2summarizes the technologies, number of documents and their respective references analyzed for the elaboration of this work, the graphical representation of the data in this table is shown in Figure 2. Figure 2. ( a ) Ratio of exclusion and inclusion of documents of each paradigm and key technology; ( b ) Percentage of documents included and excluded with respect to the total. 3.2. Geographical Distribution of Scientific Information In Table 3, we identified the origin of each document used in this work in order to have a reference indicator of the countries that contribute scientifically to this topic. This indicator can give us a brief idea of the direct relationship between scientific research and the industrial development of each country. Sensors 2022,22, 66 6 of 22 Table 3. Scientific contribution by country. Country Number of Documents U.S.A. 28 China 27 Spain 22 Italy 18 Germany 16 India 12 Australia 10 United Kingdom 10 Canada, South Korea 8 France 7 Brazil 7 Austria 5 Colombia, Sweden, Turkey, Portugal, Greece 4 Ireland, Poland, Romania, Finland, Saudi Arabia, Malaysia, Denmark 3 Switzerland, Lithuania, Taiwan, Singapore, Pakistan, Iran, Belgium, New Zealand, Hungary 2 Slovakia, Ecuador, Russia, Norway, México, Morocco, Egypt, Estonia, Argentina, Macedonia, Malta, Czech Republic, the Netherlands, Jordan, Seoul, Israel, Mexico, Palestine, Lebanon, Tunisia, Iraq 1 A map helps us to visualize geographically all the scientific contributions analyzed. It can be noticed that the United States and China are the countries that do the most research and contribute to this topic; in turn, we can suggest that they are the technologically, industrially, and economically dominant countries. It is shown in Figure 3. Figure 3. Geographical distribution and density of publications. Sensors 2022,22, 66 7 of 22 To find how much each country has contributed with its research to the elaboration of this study, each scientific paper was individualized, and its contribution was summed according to its authors and their affiliations. Each different affiliation per article was considered with a value of 1, represented as a percentage in Figure 4. Figure 4. Percentage of countries’ contribution. 3.3. Chronology of Scientific Information Table 4shows a chronological classification of the scientific papers according to the key technology analyzed. In addition, two schematic diagrams are presented in Figures 5and 6. Table 4. Technologies and paradigms publication year. Technology/Paradigm 2008 2009 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Industry 4.0 1 4 3 3 1 3 Cyber–Physical Systems 1 1 2 2 IoT–IIoT 1 2 1 1 3 2 7 Cyber security 2 4 1 1 6 Big Data and Analytics 1 2 1 1 1 3 Big Data and Industry 4.0 1 1 1 2 2 1 2 3 Digital Twin 1 2 1 12 Cloud computing, Fog computing, Edge computing 1 1 4 5 14 5G and Industry 4.0 1 1 1 3 2 6 AI and Industry 4.0 4 1 9 7 Digital Maturity of Industry 5 1 3 1 Virtual/Augmented Reality 2 3 6 2 4 Blockchain in Industry 4.0 1 4 6 8 Sensors 2022,22, 66 8 of 22 Figure 5. Chronology of scientific information on each technology and paradigm. Figure 6. ( a ) Percentage ratio of scientific production by years; ( b ) distribution of scientific information by year. Sensors 2022,22, 66 9 of 22 3.4. Keywords Most Frequently Used A total of 457 different keywords were identified throughout the reference literature. 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