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Optimal selective renewal policy for systems subject to propagated failures with global effect and failure isolation phenomena

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  • Maaroufi, Ghofrane
  • Chelbi, Anis
  • Rezg, Nidhal

Abstract

This paper considers a selective maintenance policy for multi-component systems for which a minimum level of reliability is required for each mission. Such systems need to be maintained between consecutive missions. The proposed strategy aims at selecting the components to be maintained (renewed) after the completion of each mission such that a required reliability level is warranted up to the next stop with the minimum cost, taking into account the time period allotted for maintenance between missions and the possibility to extend it while paying a penalty cost. This strategy is applied to binary-state systems subject to propagated failures with global effect, and failure isolation phenomena. A set of rules to reduce the solutions space for such complex systems is developed. A numerical example is presented to illustrate the modeling approach and the use of the reduction rules. Finally, the Monte-Carlo simulation is used in combination with the selective maintenance optimization model to deal with a number of successive missions.

Suggested Citation

  • Maaroufi, Ghofrane & Chelbi, Anis & Rezg, Nidhal, 2013. "Optimal selective renewal policy for systems subject to propagated failures with global effect and failure isolation phenomena," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 61-70.
    • Handle: RePEc:eee:reensy:v:114:y:2013:i:c:p:61-70
    DOI: 10.1016/j.ress.2012.12.019
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    References listed on IDEAS

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    Cited by:

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    4. Dao, Cuong D. & Zuo, Ming J. & Pandey, Mayank, 2014. "Selective maintenance for multi-state series–parallel systems under economic dependence," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 240-249.
    5. Zhao, Guilin & Xing, Liudong, 2020. "Reliability analysis of IoT systems with competitions from cascading probabilistic function dependence," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    6. Liu, Yu & Chen, Yiming & Jiang, Tao, 2018. "On sequence planning for selective maintenance of multi-state systems under stochastic maintenance durations," European Journal of Operational Research, Elsevier, vol. 268(1), pages 113-127.
    7. 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.
    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. Khatab, A. & Aghezzaf, E.-H., 2016. "Selective maintenance optimization when quality of imperfect maintenance actions are stochastic," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 182-189.
    10. 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).
    11. 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.
    12. Xia, Tangbin & Si, Guojin & Shi, Guo & Zhang, Kaigan & Xi, Lifeng, 2022. "Optimal selective maintenance scheduling for series–parallel systems based on energy efficiency optimization," Applied Energy, Elsevier, vol. 314(C).
    13. Wang, Yujie & Xing, Liudong & Levitin, Gregory & Huang, Ning, 2018. "Probabilistic competing failure analysis in phased-mission systems," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 37-51.
    14. Ghorbani, Milad & Nourelfath, Mustapha & Gendreau, Michel, 2024. "Stochastic programming for selective maintenance optimization with uncertainty in the next mission conditions," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    15. Xiaosheng Zhang & Jianqiao Chen & Ben Han & Junxiang Li, 2019. "Multi-mission selective maintenance modelling for multistate systems over a finite time horizon," Journal of Risk and Reliability, , vol. 233(6), pages 1040-1059, December.
    16. Shafiee, Mahmood & Finkelstein, Maxim, 2015. "An optimal age-based group maintenance policy for multi-unit degrading systems," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 230-238.
    17. Zhao, Guilin & Xing, Liudong, 2021. "Reliability analysis of body sensor networks subject to random isolation time," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    18. Peng Su & Guanjun Wang, 2022. "Reliability analysis of network systems subject to probabilistic propagation failures and failure isolation effects," Journal of Risk and Reliability, , vol. 236(2), pages 290-306, April.
    19. 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).
    20. Mahmood Shafiee & Maxim Finkelstein, 2015. "A proactive group maintenance policy for continuously monitored deteriorating systems: Application to offshore wind turbines," Journal of Risk and Reliability, , vol. 229(5), pages 373-384, October.
    21. Wang, Yujie & Xing, Liudong & Wang, Honggang & Levitin, Gregory, 2015. "Combinatorial analysis of body sensor networks subject to probabilistic competing failures," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 388-398.

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