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Maintenance optimisation of a parallel-series system with stochastic and economic dependence under limited maintenance capacity

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  • Zhou, Yifan
  • Lin, Tian Ran
  • Sun, Yong
  • Ma, Lin

Abstract

Maintenance optimisation of a parallel-series system considering both stochastic and economic dependence among components as well as limited maintenance capacity is studied in this paper. The maintenance strategies of the components are jointly optimised, and the degradation process of the system is modelled to address the stochastic dependence and limited maintenance capacity issues. To overcome the “curse of dimensionality†problem where the state space of a parallel-series system increases rapidly with the increased number of components in the system, the factored Markov decision process (FMDP) is employed for maintenance optimisation in this work. An improved approximate linear programming (ALP) algorithm is then developed. The selection of the basis functions and the state relevance weights for ALP is also investigated to enhance the performance of the ALP algorithm. Results from the numerical study show that the current approach can handle the decision optimisation problem for multi-component systems of moderate size, and the error of maintenance decision-making induced by the improved ALP is negligible. The outcome from this research provides a useful reference to overcome the “curse of dimensionality†problem during the maintenance optimisation of multi-component systems.

Suggested Citation

  • Zhou, Yifan & Lin, Tian Ran & Sun, Yong & Ma, Lin, 2016. "Maintenance optimisation of a parallel-series system with stochastic and economic dependence under limited maintenance capacity," Reliability Engineering and System Safety, Elsevier, vol. 155(C), pages 137-146.
    • Handle: RePEc:eee:reensy:v:155:y:2016:i:c:p:137-146
    DOI: 10.1016/j.ress.2016.06.012
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    Cited by:

    1. Boardman, Nicholas T. & Sullivan, Kelly M., 2024. "Approximate dynamic programming for condition-based node deployment in a wireless sensor network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. de Jonge, Bram, 2019. "Discretizing continuous-time continuous-state deterioration processes, with an application to condition-based maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 1-5.
    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. Li, Yaohan & Dong, You & Guo, Hongyuan, 2023. "Copula-based multivariate renewal model for life-cycle analysis of civil infrastructure considering multiple dependent deterioration processes," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    5. Lei Zhang & Yifan Zhou & Chuanhui Huang, 2017. "An approximate hybrid approach to maintenance optimisation for a system with multistate components," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 189-196, March.
    6. Chen, Yiming & Liu, Yu & Jiang, Tao, 2021. "Optimal maintenance strategy for multi-state systems with single maintenance capacity and arbitrarily distributed maintenance time," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    7. Zhou, Yifan & Guo, Yiming & Lin, Tian Ran & Ma, Lin, 2018. "Maintenance optimisation of a series production system with intermediate buffers using a multi-agent FMDP," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 39-48.
    8. Barlow, E. & Bedford, T. & Revie, M. & Tan, J. & Walls, L., 2021. "A performance-centred approach to optimising maintenance of complex systems," European Journal of Operational Research, Elsevier, vol. 292(2), pages 579-595.
    9. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    10. Li, Heping & Zhu, Wenjin & Dieulle, Laurence & Deloux, Estelle, 2022. "Condition-based maintenance strategies for stochastically dependent systems using Nested Lévy copulas," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    11. Zhang, Qin & Liu, Yu & Xiahou, Tangfan & Huang, Hong-Zhong, 2023. "A heuristic maintenance scheduling framework for a military aircraft fleet under limited maintenance capacities," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    12. Zhou, Yifan & Li, Bangcheng & Lin, Tian Ran, 2022. "Maintenance optimisation of multicomponent systems using hierarchical coordinated reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    13. Fu, Yuqiang & Zhu, Xiaoyan, 2023. "A joint age-based system replacement and component reallocation maintenance policy: Optimization, analysis and resilience," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    14. Xu, Jianyu & Liu, Bin & Zhao, Xiujie & Wang, Xiao-Lin, 2024. "Online reinforcement learning for condition-based group maintenance using factored Markov decision processes," European Journal of Operational Research, Elsevier, vol. 315(1), pages 176-190.
    15. Shen, Jingyuan & Hu, Jiawen & Ma, Yizhong, 2020. "Two preventive replacement strategies for systems with protective auxiliary parts subject to degradation and economic dependence," Reliability Engineering and System Safety, Elsevier, vol. 204(C).

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