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Joint optimization of production, inspection, and maintenance under finite time for smart manufacturing systems

Author

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  • Lv, Xiaolei
  • Shi, Liangxing
  • He, Yingdong
  • He, Zhen

Abstract

Given the flexible and configurable characteristics of smart manufacturing systems with a limited time per manufacturing task, the assumption of infinite time for prostems is no longer applicable to the joint-control strategy. Consequently, a joint-control model that considers production, inspection, and maintenance within a finite-time scenario for smart manufacturing systems is proposed in this paper. The objective is to optimize overall production and maintenance functions to minimize the total system cost. Comparing the joint strategy under infinite time with the proposed finite-time approach reveals significant differences in unit costs between the two scenarios. To enhance the effectiveness of the model, a discrete iterative algorithm with multiple loops was developed. Through a case study, it was observed that 1) joint strategies implemented within a finite time horizon were more cost-effective than those under infinite time, thus emphasizing the need for business managers to develop strategies within a finite time frame; 2) different production planning and efficiency levels had varying effects on the final joint strategy, necessitating customized strategies based on different production durations. Overall, the research gap regarding joint strategies within a finite-time context was addressed in this research, serving as a methodological foundation for practitioners to develop various strategies that minimize total costs across diverse real-world scenarios.

Suggested Citation

  • Lv, Xiaolei & Shi, Liangxing & He, Yingdong & He, Zhen, 2025. "Joint optimization of production, inspection, and maintenance under finite time for smart manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:reensy:v:253:y:2025:i:c:s0951832024005623
    DOI: 10.1016/j.ress.2024.110490
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