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Dynamic resequencing at mixed-model assembly lines

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  • Christian Franz
  • Achim Koberstein
  • Leena Suhl

Abstract

In this paper, we investigate a dynamic resequencing problem covering realistic properties of a mixed-model assembly line. To this end, we present a mathematical model that addresses dynamically supplied blocking information and viable due dates. We developed two different strategies that use a static resequencing algorithm as a subroutine. One strategy integrates each unblocked order immediately into the planned sequence, whereas the other strategy waits for good positions that do not conflict with the due dates. All algorithms construct guaranteed feasible sequences. Using industrial test data, we show that both strategies perform significantly better than a simple method derived from practice. A replanning procedure that tries to improve the current planned sequence whenever computing time suffices yields an additional improvement for both strategies.

Suggested Citation

  • Christian Franz & Achim Koberstein & Leena Suhl, 2015. "Dynamic resequencing at mixed-model assembly lines," International Journal of Production Research, Taylor & Francis Journals, vol. 53(11), pages 3433-3447, June.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:11:p:3433-3447
    DOI: 10.1080/00207543.2014.993046
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    Cited by:

    1. Maximilian Stauder & Niklas Kühl, 2022. "AI for in-line vehicle sequence controlling: development and evaluation of an adaptive machine learning artifact to predict sequence deviations in a mixed-model production line," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 709-747, September.
    2. Elena PUICA, 2023. "Product Personalization and Customization: Proposing a System Architecture that Integrates Self-Transactional Materials with RFID and IoT Shared Database," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 27(3), pages 5-16.

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