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Maintenance policy for a system with a weighted linear combination of degradation processes

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  • Wu, Shaomin
  • Castro, Inma T.

Abstract

This paper develops maintenance policies for a system under condition monitoring. We assume that a number of defects may develop and the degradation process of each defect follows a gamma process. The system is said failed if a linear combination of the degradation processes exceeds a pre-specified threshold. Preventive maintenance is performed. The system is renewed after several preventive maintenance activities have been performed. The main objective of this paper is to optimise the time between preventive maintenance actions and the number of the preventive maintenance. Numerical examples are given to illustrate the results.

Suggested Citation

  • Wu, Shaomin & Castro, Inma T., 2020. "Maintenance policy for a system with a weighted linear combination of degradation processes," European Journal of Operational Research, Elsevier, vol. 280(1), pages 124-133.
    • Handle: RePEc:eee:ejores:v:280:y:2020:i:1:p:124-133
    DOI: 10.1016/j.ejor.2019.06.048
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    Cited by:

    1. Levitin, Gregory & Xing, Liudong & Xiang, Yanping & Dai, Yuanshun, 2021. "Mixed failure-driven and shock-driven mission aborts in heterogeneous systems with arbitrary structure," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    2. Wang, Xiaofei & Wang, Bing Xing & Hong, Yili & Jiang, Pei Hua, 2021. "Degradation data analysis based on gamma process with random effects," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1200-1208.
    3. Cheng, Yao & Wei, Yian & Liao, Haitao, 2022. "Optimal sampling-based sequential inspection and maintenance plans for a heterogeneous product with competing failure modes," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    4. Shi, Guannan & Zhang, Xiaohong & Zeng, Jianchao & Liao, Haitao & Shi, Hui & Niu, Huifang & Wang, Jinhe, 2024. "A chance-constrained net revenue model for online dynamic predictive maintenance decision-making," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    5. Bautista, Lucía & Castro, Inma T. & Landesa, Luis, 2022. "Condition-based maintenance for a system subject to multiple degradation processes with stochastic arrival intensity," European Journal of Operational Research, Elsevier, vol. 302(2), pages 560-574.
    6. Zhang, Chao & Chen, Rentong & Wang, Shaoping & Dui, Hongyan & Zhang, Yadong, 2022. "Resilience efficiency importance measure for the selection of a component maintenance strategy to improve system performance recovery," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    7. Fang, Guanqi & Pan, Rong & Wang, Yukun, 2022. "Inverse Gaussian processes with correlated random effects for multivariate degradation modeling," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1177-1193.
    8. Shi, Haohao & Zhang, Ji & Zio, Enrico & Zhao, Xufeng, 2023. "Opportunistic maintenance policies for multi-machine production systems with quality and availability improvement," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    9. Mukhopadhyay, Koushiki & Liu, Bin & Bedford, Tim & Finkelstein, Maxim, 2023. "Remaining lifetime of degrading systems continuously monitored by degrading sensors," Reliability Engineering and System Safety, Elsevier, vol. 231(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).
    11. Yan, Rui & Zhu, Xiaoping & Zhu, Xiaoning & Peng, Rui, 2023. "Joint optimisation of task abortions and routes of truck-and-drone systems under random attacks," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    12. Wu, Bin & Zhang, Xiaohong & Shi, Hui & Zeng, Jianchao, 2024. "Failure mode division and remaining useful life prognostics of multi-indicator systems with multi-fault," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    13. Zhang, Nan & Deng, Yingjun & Liu, Bin & Zhang, Jun, 2023. "Condition-based maintenance for a multi-component system in a dynamic operating environment," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    14. Liu, Bin & Pandey, Mahesh D. & Wang, Xiaolin & Zhao, Xiujie, 2021. "A finite-horizon condition-based maintenance policy for a two-unit system with dependent degradation processes," European Journal of Operational Research, Elsevier, vol. 295(2), pages 705-717.
    15. 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).
    16. Chen, Liwei & Gao, Yansan & Dui, Hongyan & Xing, Liudong, 2021. "Importance measure-based maintenance optimization strategy for pod slewing system," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    17. Liu, Xingchen & Sun, Qiuzhuang & Ye, Zhi-Sheng & Yildirim, Murat, 2021. "Optimal multi-type inspection policy for systems with imperfect online monitoring," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    18. Zhang, Xiaohong & Liao, Haitao & Zeng, Jianchao & Shi, Guannan & Zhao, Bing, 2021. "Optimal Condition-based Opportunistic Maintenance and Spare Parts Provisioning for a Two-unit System using a State Space Partitioning Approach," Reliability Engineering and System Safety, Elsevier, vol. 209(C).

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