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Dynamic loading and condition-based maintenance policies for multi-state systems with periodic inspection

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  • Zhao, Xian
  • Chai, Xiaofei
  • Cao, Shuai
  • Qiu, Qingan

Abstract

Many engineering systems suffer gradual deterioration due to both external environmental damage and internal stress caused by working loads. System degradation is directly related to its working load, providing opportunities to control degradation by adjusting the workload. However, most existing research neglects the effect of environmental factors on system failure behavior and maintenance decisions. This paper addresses this research gap by investigating the optimal joint inspection interval, condition-based maintenance, and loading policies for systems operating in a random shock environment. We formulated the problem as a Markov decision process aimed at minimizing the long-run discounted cost, utilizing the value iteration algorithm to find optimal integrated policies while analyzing the corresponding structural properties of the policy. We extended our model by characterizing the shock arrival process with a non-homogeneous Poisson process, conducting comprehensive policy comparison and parameter sensitivity analyses through a numerical example. Our results illustrate that dynamic working load adjustment significantly impacts system degradation and the long-run expected cost. Moreover, the optimal joint policy is highly dependent on the relationship between the working load and system state deterioration. Finally, we derived some managerial implications for the joint development of load regulation and maintenance implementation to support decision-making.

Suggested Citation

  • Zhao, Xian & Chai, Xiaofei & Cao, Shuai & Qiu, Qingan, 2023. "Dynamic loading and condition-based maintenance policies for multi-state systems with periodic inspection," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:reensy:v:240:y:2023:i:c:s0951832023005008
    DOI: 10.1016/j.ress.2023.109586
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    References listed on IDEAS

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    1. Peng, Hao & van Houtum, Geert-Jan, 2016. "Joint optimization of condition-based maintenance and production lot-sizing," European Journal of Operational Research, Elsevier, vol. 253(1), pages 94-107.
    2. Zhao, Xian & Sun, Jinglei & Qiu, Qingan & Chen, Ke, 2021. "Optimal inspection and mission abort policies for systems subject to degradation," European Journal of Operational Research, Elsevier, vol. 292(2), pages 610-621.
    3. Uit Het Broek, Michiel A.J. & Teunter, Ruud H. & de Jonge, Bram & Veldman, Jasper, 2021. "Joint condition-based maintenance and load-sharing optimization for two-unit systems with economic dependency," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1119-1131.
    4. Liu, Yu & Chen, Yiming & Jiang, Tao, 2020. "Dynamic selective maintenance optimization for multi-state systems over a finite horizon: A deep reinforcement learning approach," European Journal of Operational Research, Elsevier, vol. 283(1), pages 166-181.
    5. Zhang, Xiaohong & Zeng, Jianchao, 2017. "Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems," European Journal of Operational Research, Elsevier, vol. 262(2), pages 479-498.
    6. Zhao, Xian & Fan, Yu & Qiu, Qingan & Chen, Ke, 2021. "Multi-criteria mission abort policy for systems subject to two-stage degradation process," European Journal of Operational Research, Elsevier, vol. 295(1), pages 233-245.
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    Cited by:

    1. Ning, Ru & Wang, Xiaoyue & Zhao, Xian & Li, Ziyue, 2024. "Joint optimization of preventive maintenance and triggering mechanism for k-out-of-n: F systems with protective devices based on periodic inspection," Reliability Engineering and System Safety, Elsevier, vol. 251(C).

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