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Optimal selective maintenance for multi-state systems in variable loading conditions

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  • Dao, Cuong D.
  • Zuo, Ming J.

Abstract

This paper studies the selective maintenance problem for multi-state series systems working in variable loading conditions in the next mission. In the mission, a component's degradation depends on its current state and the load applied on it. A load-dependent degradation model is proposed for multi-state components operating in variable loading conditions. This model is inspired by the load-sharing model where many components share a common workload and the failure rate of a component depends on the state of other components. A Monte-Carlo simulation method is presented to simulate the multi-state component's degradation and to evaluate the system reliability. The final objective is to determine the best selective maintenance strategy to maximize the expected system reliability in the next mission within available resources. An illustrative example, reliability estimation results, and analysis of optimal selective maintenance scenarios for different levels of budget limitation are provided.

Suggested Citation

  • Dao, Cuong D. & Zuo, Ming J., 2017. "Optimal selective maintenance for multi-state systems in variable loading conditions," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 171-180.
    • Handle: RePEc:eee:reensy:v:166:y:2017:i:c:p:171-180
    DOI: 10.1016/j.ress.2016.11.006
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    Cited by:

    1. Liu, Lujie & Yang, Jun & Kong, Xuefeng & Xiao, Yiyong, 2022. "Multi-mission selective maintenance and repairpersons assignment problem with stochastic durations," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    2. 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.
    3. Diallo, Claver & Venkatadri, Uday & Khatab, Abdelhakim & Liu, Zhuojun, 2018. "Optimal selective maintenance decisions for large serial k-out-of-n: G systems under imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 234-245.
    4. Ghorbani, Milad & Nourelfath, Mustapha & Gendreau, Michel, 2022. "A two-stage stochastic programming model for selective maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    5. Tommaso Ortalli & Andrea Di Martino & Michela Longo & Dario Zaninelli, 2024. "Make-or-Buy Policy Decision in Maintenance Planning for Mobility: A Multi-Criteria Approach," Logistics, MDPI, vol. 8(2), pages 1-18, May.
    6. Wenbin Cao & Xisheng Jia & Yu Liu & Qiwei Hu & Jianmin Zhao, 2019. "Selective maintenance optimisation considering random common cause failures and imperfect maintenance," Journal of Risk and Reliability, , vol. 233(3), pages 427-443, June.
    7. Noppada Teera-achariyakul & Dulpichet Rerkpreedapong, 2022. "Optimal Preventive Maintenance Planning for Electric Power Distribution Systems Using Failure Rates and Game Theory," Energies, MDPI, vol. 15(14), pages 1-19, July.
    8. Jiang, Tao & Liu, Yu, 2020. "Selective maintenance strategy for systems executing multiple consecutive missions with uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    9. Tang Tang & Lijuan Jia & Jin Hu & Yue Wang & Cheng Ma, 2022. "Reliability analysis and selective maintenance for multistate queueing system," Journal of Risk and Reliability, , vol. 236(1), pages 3-17, February.
    10. Shahraki, Ameneh Forouzandeh & Yadav, Om Prakash & Vogiatzis, Chrysafis, 2020. "Selective maintenance optimization for multi-state systems considering stochastically dependent components and stochastic imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    11. A. Khatab & C. Diallo & E.-H. Aghezzaf & U. Venkatadri, 2022. "Optimization of the integrated fleet-level imperfect selective maintenance and repairpersons assignment problem," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 703-718, March.
    12. Zhong, Jilong & Sanhedrai, Hillel & Zhang, FengMing & Yang, Yi & Guo, Shu & Yang, Shunkun & Li, Daqing, 2020. "Network endurance against cascading overload failure," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    13. Chaabane, K. & Khatab, A. & Diallo, C. & Aghezzaf, E.-H. & Venkatadri, U., 2020. "Integrated imperfect multimission selective maintenance and repairpersons assignment problem," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    14. Xisheng Jia & Wenbin Cao & Qiwei Hu, 2019. "Selective maintenance optimization for random phased-mission systems subject to random common cause failures," Journal of Risk and Reliability, , vol. 233(3), pages 379-400, June.
    15. Ji Hwan Cha & Maxim Finkelstein, 2019. "Optimal preventive maintenance for systems having a continuous output and operating in a random environment," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 327-350, July.
    16. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    17. Levitin, Gregory & Finkelstein, Maxim & Xiang, Yanping, 2021. "Optimal mission abort policies for repairable multistate systems performing multi-attempt mission," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    18. Zhou, Kai-Li & Cheng, De-Jun & Zhang, Han-Bing & Hu, Zhong-tai & Zhang, Chun-Yan, 2023. "Deep learning-based intelligent multilevel predictive maintenance framework considering comprehensive cost," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

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