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Job shop planning and scheduling of reconfigurable manufacturing systems

Author

Listed:
  • Jad Imsetif

    (Oakland University)

  • Nasim Nezamoddini

    (Oakland University)

  • Faisal Aqlan

    (The University of Louisville)

Abstract

The fourth industrial revolution (Industry 4.0) has enabled rapid product variations and technological developments such as reconfigurable manufacturing systems (RMSs). Planning and scheduling in RMS differ from traditional systems; therefore, the manufacturing industry has faced implementation barriers. This research proposes a new mixed-integer linear programming (MILP) formulation for process planning and scheduling in RMSs. The formulation, considers new aspects such as number of products, their quantity and complexity, calibration rate, work-in-process (WIP), and inventory management. Moreover, this research promotes RMS effectiveness for business and provides new insights on the effects of different factors on the overall performance. The applicability of the proposed formulation is illustrated with a case study. The results showed that RMS outperforms a traditional system with 30% savings in cost and up to a 25% increase in demand fulfillment. Sensitivity analyses are conducted to investigate the effect of different parameters on the cost-effectiveness of RMS compared to traditional manufacturing systems. Analysis of variance (ANOVA) highlighted the importance of the reconfigurability of the machines compared to other settings

Suggested Citation

  • Jad Imsetif & Nasim Nezamoddini & Faisal Aqlan, 2025. "Job shop planning and scheduling of reconfigurable manufacturing systems," Operations Management Research, Springer, vol. 18(3), pages 891-912, September.
    • Handle: RePEc:spr:opmare:v:18:y:2025:i:3:d:10.1007_s12063-025-00551-2
    DOI: 10.1007/s12063-025-00551-2
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    References listed on IDEAS

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    1. Hichem Haddou Benderbal & Mohammed Dahane & Lyes Benyoucef, 2017. "Flexibility-based multi-objective approach for machines selection in reconfigurable manufacturing system (RMS) design under unavailability constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6033-6051, October.
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