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Digital Twin Framework for Reconfigurable Manufacturing Systems: Challenges and Requirements

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Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems (APMS 2021)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 631))

Abstract

Due to the rapid development of new generation information technologies (such as IoT, Big Data analytics, Cyber-Physical Systems, cloud computing and artificial intelligence), Digital twins have become intensively used in smart manufacturing. Despite the fact that their use in industry has attracted the attention of many practitioners and researchers, there is still a need for an integrated and detailed Digital Twin framework for Reconfigurable Manufacturing Systems. To investigate related works, this manuscript reviews the existing Reconfigurable Manufacturing Systems Digital Twin frameworks. It also presents a classification of several studies based on the Digital Twin framework features and properties, the used decision-making tools and techniques as well as on the manufacturing system characteristics. The paper ends with a discussion and future challenges to put forward a structured and an integrated Reconfigurable Manufacturing Systems - Digital Twin framework.

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Authors and Affiliations

  1. University of Picardie Jules Verne, 48 Rue d’Ostende, 02100, Saint-Quentin, France

    Emna Hajjem & Nadia Hamani

  2. IMT Atlantique, LS2N-CNRS, Nantes, France

    Hichem Haddou Benderbal & Alexandre Dolgui

Authors
  1. Emna Hajjem
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  2. Hichem Haddou Benderbal
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  3. Nadia Hamani
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  4. Alexandre Dolgui
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Corresponding author

Correspondence to Hichem Haddou Benderbal .

Editor information

Editors and Affiliations

  1. IMT Atlantique, Nantes, France

    Alexandre Dolgui

  2. Centrale Nantes, Nantes, France

    Alain Bernard

  3. IMT Atlantique, Nantes, France

    David Lemoine

  4. ZF Friedrichshafen AG, Friedrichshafen, Germany

    Gregor von Cieminski

  5. Tecnológico de Monterrey, Mexico City, Mexico

    David Romero

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Hajjem, E., Benderbal, H.H., Hamani, N., Dolgui, A. (2021). Digital Twin Framework for Reconfigurable Manufacturing Systems: Challenges and Requirements. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 631. Springer, Cham. https://doi.org/10.1007/978-3-030-85902-2_59

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  • DOI: https://doi.org/10.1007/978-3-030-85902-2_59

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85901-5

  • Online ISBN: 978-3-030-85902-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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