Job shop planning and scheduling of reconfigurable manufacturing systems

Jad Imsetif (), Nasim Nezamoddini () and Faisal Aqlan ()
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Jad Imsetif: Oakland University
Nasim Nezamoddini: Oakland University
Faisal Aqlan: The University of Louisville

Operations Management Research, 2025, vol. 18, issue 3, No 3, 912 pages

Abstract: 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

Keywords: Reconfigurable manufacturing systems; Mixed integer linear programming; Optimization; Sensitivity analyses; Cost effectiveness (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12063-025-00551-2

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