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Selective maintenance optimization for multi-state systems considering stochastically dependent components and stochastic imperfect maintenance actions

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  • Shahraki, Ameneh Forouzandeh
  • Yadav, Om Prakash
  • Vogiatzis, Chrysafis

Abstract

This paper presents a selective maintenance optimization problem for complex systems composed of stochastically dependent components. The components of a complex system degrade during mission time, and their degradation states vary from perfect functioning to complete failure states. The degradation rate of each component not only depends on its intrinsic degradation but also on the state of other dependent components of the system. The proposed approach captures the two-way interactions between components through system performance rates and uses Monte Carlo simulation to compute the reliability of the system in the next operational mission. Different maintenance actions such as do-nothing, perfect, and stochastic imperfect maintenance are considered during the maintenance break to improve the reliability of the system. The selective maintenance bi-objective optimization problem is modelled considering both the expected value and variance of the system reliability as objective functions. Time and budget are considered as constraints for finding the optimal maintenance strategy. Two illustrative examples are provided for a better understanding of the proposed approach and for demonstrating its effectiveness.

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  • 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).
    • Handle: RePEc:eee:reensy:v:196:y:2020:i:c:s0951832019303126
    DOI: 10.1016/j.ress.2019.106738
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    Cited by:

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    3. Zhang, Nailong & Si, Wujun, 2020. "Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. 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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    6. Azizi, Fariba & Salari, Nooshin, 2023. "A novel condition-based maintenance framework for parallel manufacturing systems based on bivariate birth/birth–death processes," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    7. Zhao, Yunfei & Smidts, Carol, 2022. "Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    8. uit het Broek, Michiel A.J. & Teunter, Ruud H. & de Jonge, Bram & Veldman, Jasper, 2021. "Joint condition-based maintenance and condition-based production optimization," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    9. Cavalcante, Cristiano A.V. & Lopes, Rodrigo S. & Scarf, Philip A., 2021. "Inspection and replacement policy with a fixed periodic schedule," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    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. Yin, Mingang & Liu, Yu & Liu, Shuntao & Chen, Yiming & Yan, Yutao, 2023. "Scheduling heterogeneous repair channels in selective maintenance of multi-state systems with maintenance duration uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    12. Chadha, Mayank & Ramancha, Mukesh K. & Vega, Manuel A. & Conte, Joel P. & Todd, Michael D., 2023. "The modeling of risk perception in the use of structural health monitoring information for optimal maintenance decisions," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    13. Hamzea Al-Jabouri & Ahmed Saif & Claver Diallo, 2023. "Robust selective maintenance optimization of series–parallel mission-critical systems subject to maintenance quality uncertainty," Computational Management Science, Springer, vol. 20(1), pages 1-31, December.
    14. Liu, Gehui & Chen, Shaokuan & Ho, Tinkin & Ran, Xinchen & Mao, Baohua & Lan, Zhen, 2022. "Optimum opportunistic maintenance schedule over variable horizons considering multi-stage degradation and dynamic strategy," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    15. 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).
    16. Zhang, Nan & Cai, Kaiquan & Zhang, Jun & Wang, Tian, 2022. "A condition-based maintenance policy considering failure dependence and imperfect inspection for a two-component system," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    17. 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).
    18. Wakiru, James & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K. & Mburu, Stanley, 2020. "Towards an innovative lubricant condition monitoring strategy for maintenance of ageing multi-unit systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    19. Rasay, Hasan & Taghipour, Sharareh & Sharifi, Mani, 2022. "An integrated Maintenance and Statistical Process Control Model for a Deteriorating Production Process," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    20. 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).
    21. 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).
    22. Mosayebi Omshi, E. & Grall, A., 2021. "Replacement and imperfect repair of deteriorating system: Study of a CBM policy and impact of repair efficiency," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    23. 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).
    24. Ait Mokhtar, El Hassene & Laggoune, Radouane & Chateauneuf, Alaa, 2023. "Imperfect maintenance modeling and assessment of repairable multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    25. Dui, Hongyan & Liu, Meng & Song, Jiaying & Wu, Shaomin, 2023. "Importance measure-based resilience management: Review, methodology and perspectives on maintenance," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

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