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Flexible scheduling of diagnostic tests in automotive manufacturing

Author

Listed:
  • Simone König

    (Institute of Automation and Information Systems, Technical University of Munich
    Mercedes-Benz AG)

  • Maximilian Reihn

    (Mercedes-Benz AG)

  • Felipe Gelinski Abujamra

    (Mercedes-Benz AG)

  • Alexander Novy

    (Mercedes-Benz AG)

  • Birgit Vogel-Heuser

    (Institute of Automation and Information Systems, Technical University of Munich)

Abstract

The car of the future will be driven by software and offer a variety of customisation options. Enabling these customisation options forces modern automotive manufacturers to update their standardised scheduling concepts for testing and commissioning cars. A flexible scheduling concept means that every chosen customer configuration code must have its own testing procedure. This concept is essential to provide individual testing workflows where the time and resources are optimised for every car. Manual scheduling is complicated due to constraints on time, predecessor-successor relationships, mutual exclusion criteria, resources and status conditions on the car engineering and assembly line. Applied methods to handle the mathematical formulation for the corresponding industrial optimisation problem and its implementation are not yet available. This paper presents a procedure for automated and non-preemptive scheduling in the testing and commissioning of cars, which is built on a Boolean satisfiability problem on parallel and identical machines with temporal and resource constraints. The presented method is successfully implemented and evaluated on a variant assembly line of an automotive Original Equipment Manufacturer. This paper is the starting point for an automated workflow planning and scheduling process in automotive manufacturing.

Suggested Citation

  • Simone König & Maximilian Reihn & Felipe Gelinski Abujamra & Alexander Novy & Birgit Vogel-Heuser, 2023. "Flexible scheduling of diagnostic tests in automotive manufacturing," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 320-342, June.
    • Handle: RePEc:spr:flsman:v:35:y:2023:i:2:d:10.1007_s10696-021-09438-3
    DOI: 10.1007/s10696-021-09438-3
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    References listed on IDEAS

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    1. Shi, Yuhui & Reich, Daniel & Epelman, Marina & Klampfl, Erica & Cohn, Amy, 2017. "An analytical approach to prototype vehicle test scheduling," Omega, Elsevier, vol. 67(C), pages 168-176.
    2. Bartels, J.-H. & Zimmermann, J., 2009. "Scheduling tests in automotive R&D projects," European Journal of Operational Research, Elsevier, vol. 193(3), pages 805-819, March.
    3. Alain Quilliot & Antoine Sarbinowski & Hélène Toussaint, 2021. "Vehicle driven approaches for non preemptive vehicle relocation with integrated quality criterion in a vehicle sharing system," Annals of Operations Research, Springer, vol. 298(1), pages 445-468, March.
    4. Christian Weckenborg & Karsten Kieckhäfer & Thomas S. Spengler & Patricia Bernstein, 2020. "The Volkswagen Pre-Production Center Applies Operations Research to Optimize Capacity Scheduling," Interfaces, INFORMS, vol. 50(2), pages 119-136, March.
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