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Condition-based opportunistic maintenance policies with two-phase inspections for continuous-state systems

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  • Chen, Yuan
  • Qiu, Qingan
  • Zhao, Xian

Abstract

This paper proposes two condition-based opportunistic maintenance policies with two-phase inspections for continuously degraded systems with real-time monitoring and periodic inspections, respectively. The degradation of the components and the system is modeled by a Gamma process. Existing literature finds the optimal maintenance strategies by monitoring the performance of all components in a multi-component system. However, it maybe unrealistic and costly to perform inspections on all components for certain systems. Hence, this study considers a two-phase inspection method, that is, the system-level inspection is conducted first, and then the decision for component-level inspection is made based on the system performance. Maintenance is performed to the component when its degradation reaches the preventive maintenance (PM) threshold or the corrective maintenance (CM) threshold at a component-level inspection. Whenever a maintenance action is implemented, the other components whose degradation exceeds an opportunistic maintenance (OM) threshold will be repaired. Then the long-run expected cost for two-component systems and multi-component systems are derived based on the semi-regenerative properties and simulation method. The combination of the system-level inspection interval, OM, PM and CM thresholds is determined to minimize the long-run expected cost. Finally, this study applies the proposed maintenance policies to the battery pack systems in electrical vehicles.

Suggested Citation

  • Chen, Yuan & Qiu, Qingan & Zhao, Xian, 2022. "Condition-based opportunistic maintenance policies with two-phase inspections for continuous-state systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:reensy:v:228:y:2022:i:c:s0951832022003908
    DOI: 10.1016/j.ress.2022.108767
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    References listed on IDEAS

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    4. Wu, Jing & Qian, Cunhua & Dohi, Tadashi, 2024. "Optimal opportunity-based age replacement policies in discrete time," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Ma, Weining & Zhang, Qin & Xiahou, Tangfan & Liu, Yu & Jia, Xisheng, 2023. "Integrated selective maintenance and task assignment optimization for multi-state systems executing multiple missions," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
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    7. Lijun Shang & Baoliang Liu & Kaiye Gao & Li Yang, 2023. "Random Warranty and Replacement Models Customizing from the Perspective of Heterogeneity," Mathematics, MDPI, vol. 11(15), pages 1-22, July.
    8. 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).
    9. Zhao, Xian & Lv, Zuheng & Qiu, Qingan & Wu, Yaguang, 2023. "Designing two-level rescue depot location and dynamic rescue policies for unmanned vehicles," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    10. Zhang, Wenyu & Zhang, Xiaohong & He, Shuguang & Zhao, Xing & He, Zhen, 2024. "Optimal condition-based maintenance policy for multi-component repairable systems with economic dependence in a finite-horizon," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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