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Digital Twin: An Added Value for Digital CONWIP in the Context of Industry 4.0

Author

Listed:
  • Latifa Benhamou

    (Laboratory of Automation, Mechanics, and Industrial and Human Computer Science, National Center for Scientific Research, Arts et Métiers Institute of Technology, 75013 Paris, France)

  • Samir Lamouri

    (Laboratory of Automation, Mechanics, and Industrial and Human Computer Science, National Center for Scientific Research, Arts et Métiers Institute of Technology, 75013 Paris, France)

  • Patrick Burlat

    (WIPSIM, Systems and Software Consulting Firm, 42000 Saint-Étienne, France)

  • Vincent Giard

    (Laboratory of Analysis and Modeling of Decision Support Systems, Université Paris-Dauphine, PSL Research University, 75006 Paris, France)

Abstract

Despite technological progress and a large amount of research on Industry 4.0, digital transformation remains a complex process that most manufacturers are hesitant to invest in. Interest in digital Kanban, for example, remains low compared with traditional Kanban, which is widely used. This applies to the other card-based production control systems, including CONstant Work-In-Process (CONWIP), which is the focus of this paper. In an industrial context where digitization and Industry 4.0 are the main trends, one may wonder why traditional CONWIP is preferred to digital CONWIP. Following a praxeological approach (i.e., study of practice and instrumentation), this article explores the strengths and weaknesses of the CONWIP practice, in both its paper and electronic versions, while taking into account the human dimension. The aim is to motivate potential CONWIP users to implement it in its digital mode and to show them how a Digital Twin-based solution can overcome the managerial problems that arise with digitization while enabling improved performance. As an illustration, experience feedback from several companies using Digital Twin with CONWIP is provided.

Suggested Citation

  • Latifa Benhamou & Samir Lamouri & Patrick Burlat & Vincent Giard, 2023. "Digital Twin: An Added Value for Digital CONWIP in the Context of Industry 4.0," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9874-:d:1176050
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    References listed on IDEAS

    as
    1. Yann Jaegler & Anicia Jaegler & Patrick Burlat & Samir Lamouri & Damien Trentesaux, 2018. "The ConWip production control system: a systematic review and classification," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5736-5757, September.
    2. Samayita Guha & Subodha Kumar, 2018. "Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap," Production and Operations Management, Production and Operations Management Society, vol. 27(9), pages 1724-1735, September.
    3. Kessler, Melanie & Arlinghaus, Julia C. & Rosca, Eugenia & Zimmermann, Manuel, 2022. "Curse or Blessing? Exploring risk factors of digital technologies in industrial operations," International Journal of Production Economics, Elsevier, vol. 243(C).
    4. Huang, Min & Wang, Dingwei & Ip, W. H., 1998. "Simulation study of CONWIP for a cold rolling plant," International Journal of Production Economics, Elsevier, vol. 54(3), pages 257-266, May.
    5. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
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