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Challenges in Data Life Cycle Management for Sustainable Cyber-Physical Production Systems

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Advances in Production Management Systems. Towards Smart and Digital Manufacturing (APMS 2020)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 592))

Abstract

Rapid technological advances present new opportunities to use industrial Big Data to monitor and improve performance more systematically and more holistically. The on-going fourth industrial revolution, aka Industrie 4.0, holds the promise to support the implementation of sustainability principles in manufacturing. However, much of these opportunities are missed as social and environmental performance are still largely considered as an afterthought or add-on to business as usual. This paper reviews existing data life cycle models and discusses their usefulness for sustainable manufacturing performance management. Finally, we suggest possible directions for further research to promote more sustainable cyber-physical production systems.

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Authors and Affiliations

  1. Chalmers University of Technology, Gothenburg, Sweden

    Mélanie Despeisse & Ebru Turanoglu Bekar

Authors
  1. Mélanie Despeisse
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  2. Ebru Turanoglu Bekar
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Corresponding author

Correspondence to Mélanie Despeisse .

Editor information

Editors and Affiliations

  1. University of Novi Sad, Novi Sad, Serbia

    Bojan Lalic

  2. University of Belgrade, Belgrade, Serbia

    Vidosav Majstorovic

  3. University of Novi Sad, Novi Sad, Serbia

    Ugljesa Marjanovic

  4. ZF Hungária Kft., Eger, Hungary

    Gregor von Cieminski

  5. Tecnológico de Monterrey, Mexico City, Mexico

    David Romero

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Despeisse, M., Bekar, E.T. (2020). Challenges in Data Life Cycle Management for Sustainable Cyber-Physical Production Systems. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Towards Smart and Digital Manufacturing. APMS 2020. IFIP Advances in Information and Communication Technology, vol 592. Springer, Cham. https://doi.org/10.1007/978-3-030-57997-5_7

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  • DOI: https://doi.org/10.1007/978-3-030-57997-5_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57996-8

  • Online ISBN: 978-3-030-57997-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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