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Development of Predictive Maintenance Models for a Packaging Robot Based on Machine Learning

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Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures (APMS 2023)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 690))

Abstract

This study presents the development of a predictive model for the health monitoring of power transmitters in a packaging robot using machine learning techniques. The model is based on a Discrete Bayesian Filter (DBF) and is compared to a model based on a Naïve Bayes Filter (NBF). Data preprocessing techniques are applied to select suitable descriptors for the predictive model. The results show that the DBF model outperforms the NBF model in terms of predictive power. The model can be used to estimate the current state of the power transmitter and predict its degradation over time. This can lead to improved maintenance planning and cost savings in the context of Industry 4.0.

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Author information

Authors and Affiliations

  1. Laboratoire de Génie Informatique, de Production et de Maintenance, Université de Lorraine, Nancy, France

    Ayoub Chakroun, Sadok Turki & Nidhal Rezg

  2. Laboratory QUARTZ EA 7393, University Paris VIII Vincennes, University Institute of Technology, 93100, Montreuil, France

    Yasmina Hani & Abderrahmane Elmhamedi

Authors
  1. Ayoub Chakroun
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  2. Yasmina Hani
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  3. Sadok Turki
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  4. Nidhal Rezg
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  5. Abderrahmane Elmhamedi
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Corresponding author

Correspondence to Ayoub Chakroun .

Editor information

Editors and Affiliations

  1. Norwegian University of Science and Technology, Trondheim, Norway

    Erlend Alfnes

  2. Norwegian University of Science and Technology, Trondheim, Norway

    Anita Romsdal

  3. Norwegian University of Science and Technology, Trondheim, Norway

    Jan Ola Strandhagen

  4. ZF Friedrichshafen AG, Friedrichshafen, Germany

    Gregor von Cieminski

  5. Tecnológico de Monterrey, Mexico City, Mexico

    David Romero

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Chakroun, A., Hani, Y., Turki, S., Rezg, N., Elmhamedi, A. (2023). Development of Predictive Maintenance Models for a Packaging Robot Based on Machine Learning. In: Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. APMS 2023. IFIP Advances in Information and Communication Technology, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-031-43666-6_46

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  • DOI: https://doi.org/10.1007/978-3-031-43666-6_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43665-9

  • Online ISBN: 978-3-031-43666-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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