Production Management from Intelligent Models-Driven for Industry 4.0: Challenges and Opportunities

Authors

  • Jenny Ruiz-de la Peña Universidad de Holguín, Cuba
  • Reyner Pérez-Campdesuñer Universidad UTE, Ecuador
  • Pablo Gustavo Andrade-Molina Instituto Superior Tecnológico ATLANTIC, Ecuador

DOI:

https://doi.org/10.29019/eyn.v13i2.1084

Keywords:

Production management, Engineering, Industry 4.0, Manufacture, Model-driven, Integrated systems

Abstract

In the past decade, the term Industry 4.0 has received increasing attention in both industry and academia. The manufacturing industry has evolved thanks to the digital revolution with the use of smart devices for intelligent manufacturing information systems. Working with intelligent production systems in this Industry 4.0 is a complex task that requires innovative ways of developing systems. One way to manage complexity is the use of intelligent model-driven engineering techniques. Although model-based approaches have several advantages and can be used to reduce complexity, studies to support Industry 4.0 are still limited. This article uses the bibliometric method to analyze the scientific performance of articles, countries, authors and journals based on the number of citations and cooperation networks. Most of the articles were published in conferences. The keywords industry 4.0 and model-driven engineering and embedded systems were the most used and represent the main areas of research. Most of the research related to the field was carried out in Austria and Germany. This study presents the evolution of the scientific literature on Industry 4.0 and intelligent model-based approaches and identifies areas of current research interest.

Downloads

Download data is not yet available.

Author Biographies

Jenny Ruiz-de la Peña, Universidad de Holguín, Cuba

Professor and researcher at the Faculty of Mathematics and Informatics of the University of Holguín, Cuba.

Reyner Pérez-Campdesuñer, Universidad UTE, Ecuador

Director of Research and professor of the Faculty of Administrative Sciences at the UTE University. Quito, Ecuador.

Pablo Gustavo Andrade-Molina, Instituto Superior Tecnológico ATLANTIC, Ecuador

Professor and researcher in the Administration Department at the Atlantic Higher Technological Institute. Santo Domingo, Ecuador.

References

Ahmi, A., Elbardan, H., & Ali, R. H. (2019). Bibliometric Analysis of Published Literature on Industry 4.0. 2019 International Conference on Electronics, Information, and Communication (ICEIC), 1-6.

Akdur, D., Garousi, V., & Demirörs, O. (2018). A Survey on Modeling and Model-Driven Engineering Practices in the Embedded Software Industry. Journal of Systems Architecture, 91, 62-82.

Almorsy, M., Grundy, J., & Ibrahim, A.S. (2014). Adaptable, Model-Driven Security Engineering For Saas Cloud-Based Applications. Automated Software Engineering, 21(2), 187-224.

Barangi, H., Kolahdouz Rahimi, S., Zamani, B., & Khasseh, A.A. (2021). Model-Driven Software Engineering: A Bibliometric Analysis. Journal of Computing and Security, 8(1), 93-108.

Bézivin, J. (2004). In Search of a Basic Principle for Model Driven Engineering. The European Journal for the Informatics Professional, 5(2), 21-24.

Binder, C., Calà, A., Vollmar, J., Neureiter, C., & Lüder, A. (2021). Automated Model Transformation in modeling Digital Twins of Industrial Internet-of-Things Applications utilizing AutomationML. 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 1-6. https://doi.org/10.1109/ETFA45728.2021.9613172

Brambilla, M., Cabot, J., & Wimmer, M. (2017). Model-Driven Software Engineering in Practice. Synthesis Lectures on Software Engineering, 3(1), 1-207.

Cobo, M. J., López, A. G., Herrera, E., & Herrera, F. (2011). Science Mapping Software Tools: Review, Analysis, and Cooperative Study Among Tools. Journal of the American Society for Information Science and Technology, 62(7).

Erazo-Rivera, R.P., Pancorbo-Sandoval, J.A., Leyva-Ricardo, S.E., & Barba-Mosquera, Á.E. (2021). La Innovación como Herramienta de Gestión Comercial en las Pymes de Santo Domingo de los Tsáchilas. Economía y Negocios, 12(2), 52-63. https://doi.org/10.29019/eyn.v12i2.957

Gajdzik, B., Grabowska, S., Saniuk, S., & Wieczorek, T. (2020). Sustainable Development and Industry 4.0: A Bibliometric Analysis Identifying Key Scientific Problems of the Sustainable Industry 4.0. Energies, 13(16), 4254.

Gascueña, J. M., Navarro, E., & Fernández-Caballero, A. (2012). Model-Driven Engineering Techniques for the Development of Multi-Agent Systems. Engineering Applications of Artificial Intelligence, 25(1), 159–173.

Hutchinson, J., Whittle, J., Rouncefield, M., & Kristoffersen, S. (2011). Empirical Assessment of MDE in Industry. Proceedings of the 33rd International Conference on Software Engineering, 471-480.

Kipper, L.M., Furstenau, L.B., Hoppe, D., Frozza, R., & Iepsen, S. (2020). Scopus Scientific Mapping Production in Industry 4.0 (2011-2018): A Bibliometric Analysis. International Journal of Production Research, 58(6), 1605–1627.

Kitchenham, B., & Charters, S. (2007). Guidelines for Performing Systematic Literature Reviews in Software Engineering. In Engineering (2), Issue 1051.

Liu, B., Glock, T., Betancourt, V. P., Kern, M., Sax, E., & Becker, J. (2020). Model Driven Development Process for a Service-oriented Industry 4.0 System. 2020 9th International Conference on Industrial Technology and Management (ICITM), 78-83. https://doi.org/10.1109/ICITM48982.2020.9080344

Livieri, B., Di Cagno, P., & Bochicchio, M. (2015). A Bibliometric Analysis and Review on Performance Modeling Literature. Complex Systems Informatics and Modeling Quarterly, 2, 56-71.

López-Robles, J.-R., Otegi-Olaso, J.-R., Cobo, M.-J., Bertolin-Furstenau, L., Kremer-Sott, M., López-Robles, L.-D., & Gamboa-Rosales, N.-K. (2020). The Relationship Between Project Management and Industry 4.0: Bibliometric Analysis of Main Research Areas Through Scopus.

Mahdavi-Hezavehi, S., Durelli, V. H. S., Weyns, D., & Avgeriou, P. (2017). A Systematic Literature Review on Methods that Handle Multiple Quality Attributes in Architecture-Based Self-Adaptive Systems. Information and Software Technology, 90, 1-26.

Melean Romero, R., & Torres, F. (2021). Gestión de costos en las cadenas productivas: reflexiones sobre su génesis. Retos, Revista de Ciencias de Administración y Economía, 11(21), 131-146. https://doi.org/10.17163/ret.n21.2021.08

Mohagheghi, P., Gilani, W., Stefanescu, A., & Fernandez, M. A. (2013). An Empirical Study of the State of the Practice and Acceptance of Model-Driven Engineering in Four Industrial Cases. Empirical Software Engineering, 18(1), 89-116.

Molano, J. I. R., Lovelle, J. M. C., Montenegro, C. E., Granados, J., & Crespo, R. G. (2018). Metamodel for Integration of Internet of Things, Social Networks, The Cloud and Industry 4.0. Journal of Ambient Intelligence and Humanized Computing, 9(3), 709-723.

Mora-Sánchez, D., & Guerrero-Marín, L. (2020). Industria 4.0: el reto en la ruta hacia las organizaciones digitales. Estudios de la Gestión: Revista Internacional de Administración, (8), 186–209. https://doi.org/10.32719/25506641.2020.8.7

Muhuri, P. K., Shukla, A. K., & Abraham, A. (2019). Industry 4.0: A Bibliometric Analysis and Detailed Overview. Engineering Applications of Artificial Intelligence, 78, 218-235.

Parveen, R., Thaker, P., & Goveas, N. (2019). Model-Based Approach for Cyber-Physical Systems Applications Development. Conference Paper in 23rd Pacific Asia Conference on Information Systems: Secure ICT Platform for the 4th Industrial Revolution, PACIS 2019. July 8-12 2019, Xi’an, China. https://doi.org/10.23919/ELINFOCOM.2019.8706445

Petersen, K., Feldt, R., Mujtaba, S., & Mattsson, M. (2008). Systematic Mapping Studies in Software Engineering. EASE, 8, 68-77.

Ruiz, J., Serral, E., & Snoeck, M. (2018). Evaluating User Interface Generation Approaches: Model-Based Versus Model-Driven Development. Software & Systems Modeling, 1-24. https://doi.org/10.1007/s10270-018-0698-x

Samaniego Guevara, H. (2021). Plan de producción farmacéutica de soluciones parentales con programación lineal. Estudios de la Gestión: Revista Internacional de Administración, (10), 187–210. https://doi.org/10.32719/25506641.2021.10.9

Samimi, D. L., Zamani, B., & Kolahdouz, R. S. (2016). Bidirectional Model Transformation Approaches. A Comparative Study. Conference Paper in 6th International Conference on Computer and Knowledge Engineering (ICCKE 2016). October 20-21 2016, Mashhad, Iran. https://doi.org/10.1109/ICCKE.2016.7802159

Szvetits, M., & Zdun, U. (2016). Systematic Literature Review of the Objectives, Techniques, Kinds, and Architectures of Models at Runtime. Software & Systems Modeling, 15(1), 31-69.

Usman, M., Iqbal, M. Z., & Khan, M. U. (2017). A Product-Line Model-Driven Engineering Approach for Generating Feature-Based Mobile Applications. Journal of Systems and Software, 123, 1-32.

Van Eck, N., & Waltman, L. (2010). Software Survey: Vosviewer, a Computer Program for Bibliometric Mapping. Scientometrics, 84(2), 523-538.

Vještica, M., Dimitrieski, V., Pisarić, M., Kordić, S., Ristić, S., & Luković, I. (2019). Towards a Formal Description and Automatic Execution of Production Processes. 2019 IEEE 15th International Scientific Conference on Informatics, 463-468.

Vještica, M., Dimitrieski, V., Pisarić, M., Kordić, S., Ristić, S., & Luković, I. (2021). Towards a Formal Specification of Production Processes Suitable for Automatic Execution. Open Computer Science, 11(1), 161-179. https://doi.org/10.1515/comp-2020-0200

Wallin, J. A. (2005). Bibliometric Methods: Pitfalls and Possibilities. Basic & Clinical Pharmacology & Toxicology, 97(5), 261-275.

Waltman, L., Van Eck, N. J., & Noyons, E. C. M. (2010). A Unified Approach to Mapping and Clustering of Bibliometric Networks. Journal of Informetrics, 4(4), 629-635.

Whittle, J., Hutchinson, J., & Rouncefield, M. (2013). The State of Practice in Model-Driven Engineering. IEEE Software, 31(3), 79-85.

Wortmann, A., Barais, O., Combemale, B., & Wimmer, M. (2020). Modeling Languages in Industry 4.0: An Extended Systematic Mapping Study. Software and Systems Modeling, 19(1), 67-94. https://doi.org/10.1007/s10270-019-00757-6

Wortmann, A., Combemale, B., & Barais, O. (2017). A Systematic Mapping Study on Modeling for Industry 4.0. 2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems (MODELS), 281-291.

Ziaei, M., Zamani, B., & Bohlooli, A. (2020). A Model-Driven Approach for IoT-Based Monitoring Systems in Industry 4.0. 99-105. https://doi.org/10.1109/SCIOT50840.2020.9250202

Published

2022-12-01

How to Cite

Ruiz-de la Peña, J., Pérez-Campdesuñer, R., & Andrade-Molina, P. G. (2022). Production Management from Intelligent Models-Driven for Industry 4.0: Challenges and Opportunities. Economía Y Negocios, 13(2), 1–15. https://doi.org/10.29019/eyn.v13i2.1084