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Joint optimization of condition-based maintenance policy and buffer capacity for a two-unit series system

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  • Zhang, Ning
  • Qi, Faqun
  • Zhang, Chengjie
  • Zhou, Hongming

Abstract

The purpose of this paper is to address a joint optimization problem of condition-based maintenance policy and buffer capacity for a two-unit series system. The system consists of two machines and an intermediate buffer, both upstream and downstream machines suffer from soft failure, and maintenance actions are taken according to the deterioration state of the system. Different from previous studies that the maintenance strategy and buffer capacity were always be optimized separately, this paper optimizes the maintenance strategy as well as the buffer capacity. All system states and transition probabilities between them are analyzed based on semi-Markov process, and then the expected cost and sojourn time of the system are constructed. By minimizing the average operation and maintenance cost per unit time of the system, joint optimization decision (i.e., optimal maintenance thresholds of upstream and downstream machines and buffer size) were determined. A practical simulation example of production-buffer-assembly system is used to illustrate the superiority of the proposed joint optimization strategy.

Suggested Citation

  • Zhang, Ning & Qi, Faqun & Zhang, Chengjie & Zhou, Hongming, 2022. "Joint optimization of condition-based maintenance policy and buffer capacity for a two-unit series system," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021007109
    DOI: 10.1016/j.ress.2021.108232
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    Cited by:

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    3. Zhu, Xiaojun & Balakrishnan, N., 2023. "Non-parametric inference based on reliability life-test of non-identical coherent systems with application to warranty time," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    4. Zheng, Meimei & Su, Zhiyun & Wang, Dong & Pan, Ershun, 2024. "Joint maintenance and spare part ordering from multiple suppliers for multicomponent systems using a deep reinforcement learning algorithm," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Li, Yaping & Xia, Tangbin & Chen, Zhen & Pan, Ershun, 2023. "Multiple degradation-driven preventive maintenance policy for serial-parallel multi-station manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    6. Gan, Shuyuan & Hu, Hengheng & Coit, David W., 2023. "Maintenance optimization considering the mutual dependence of the environment and system with decreasing effects of imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Rasay, Hasan & Taghipour, Sharareh & Sharifi, Mani, 2022. "An integrated Maintenance and Statistical Process Control Model for a Deteriorating Production Process," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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