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An optimizing maintenance policy for airborne redundant systems operating with faults by using Markov process and NSGA-II

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  • Cheng, Dawei
  • Lu, Zhong
  • Zhou, Jia
  • Liang, Xihui

Abstract

Redundancy is widely applied in modern airborne systems. Operation with faults in redundant airborne systems can improve the dispatch reliability of aircraft and reduce operational losses due to flight delays or cancellations. In this paper, a Markov model of redundant airborne systems operating with faults is developed, and an analytical method for state frequency calculation is proposed based on the Markov process. On this basis, the multiobjective optimization model is built by taking the time intervals of systems operating with faults as the decision variables, the average safety requirement as the constraint, and the operation cost and dispatch reliability as objectives. Then an algorithm based on NSGA-II is proposed to solve the multiobjective optimization model. Finally, a case study is given to illustrate the application of our proposed method. The results and discussions show that our method has advantages in both accuracy and efficiency compared with some present approaches. Additionally, the loss caused by flight delays and cancellations can be controlled by selecting the proper time intervals optimized by our method. In this way, the operating cost and dispatch reliability can be optimized by airlines, and aircraft safety can be ensured.

Suggested Citation

  • Cheng, Dawei & Lu, Zhong & Zhou, Jia & Liang, Xihui, 2023. "An optimizing maintenance policy for airborne redundant systems operating with faults by using Markov process and NSGA-II," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:reensy:v:236:y:2023:i:c:s0951832023001722
    DOI: 10.1016/j.ress.2023.109257
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    References listed on IDEAS

    as
    1. Wang, Wei & Wu, Zhiying & Xiong, Junlin & Xu, Yaofeng, 2018. "Redundancy optimization of cold-standby systems under periodic inspection and maintenance," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 394-402.
    2. Zhang, Jian-Xun & Du, Dang-Bo & Si, Xiao-Sheng & Hu, Chang-Hua & Zhang, Han-Wen, 2021. "Joint optimization of preventive maintenance and inventory management for standby systems with hybrid-deteriorating spare parts," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    3. Shekhar, Chandra & Kumar, Amit & Varshney, Shreekant, 2020. "Load sharing redundant repairable systems with switching and reboot delay," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    4. Hamdan, K. & Tavangar, M. & Asadi, M., 2021. "Optimal preventive maintenance for repairable weighted k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    5. Yang, Ao & Qiu, Qingan & Zhu, Mingren & Cui, Lirong & Chen, Weilin & Chen, Jianhui, 2022. "Condition-based maintenance strategy for redundant systems with arbitrary structures using improved reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    6. 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.
    7. Vu, Hai Canh & Do, Phuc & Fouladirad, Mitra & Grall, Antoine, 2020. "Dynamic opportunistic maintenance planning for multi-component redundant systems with various types of opportunities," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    8. Adjoul, Oussama & Benfriha, Khaled & Zant, Chawki El & Aoussat, Améziane, 2021. "Algorithmic Strategy for Simultaneous Optimization of Design and Maintenance of Multi-Component Industrial Systems," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    9. Shen, Jingyuan & Cui, Lirong & Ma, Yizhong, 2019. "Availability and optimal maintenance policy for systems degrading in dynamic environments," European Journal of Operational Research, Elsevier, vol. 276(1), pages 133-143.
    10. Kumar, Pankaj & Jain, Madhu, 2020. "Reliability analysis of a multi-component machining system with service interruption, imperfect coverage, and reboot," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    11. Wu, Hui & Li, Yan-Fu & Bérenguer, Christophe, 2020. "Optimal inspection and maintenance for a repairable k-out-of-n: G warm standby system," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    12. Zhang, Fengxia & Shen, Jingyuan & Liao, Haitao & Ma, Yizhong, 2021. "Optimal preventive maintenance policy for a system subject to two-phase imperfect inspections," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    13. Gao, Shan & Wang, Jinting, 2021. "Reliability and availability analysis of a retrial system with mixed standbys and an unreliable repair facility," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    14. Andrés Cacereño & David Greiner & Blas J. Galván, 2021. "Multi-Objective Optimum Design and Maintenance of Safety Systems: An In-Depth Comparison Study Including Encoding and Scheduling Aspects with NSGA-II," Mathematics, MDPI, vol. 9(15), pages 1-39, July.
    15. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2022. "Optimal preventive switching of components in degrading systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    16. Ma, Xiaoyang & Liu, Bin & Yang, Li & Peng, Rui & Zhang, Xiaodong, 2020. "Reliability analysis and condition-based maintenance optimization for a warm standby cooling system," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    17. Ruiz-Castro, Juan Eloy, 2020. "A complex multi-state k-out-of-n: G system with preventive maintenance and loss of units," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    18. Zhang, Fengxia & Shen, Jingyuan & Ma, Yizhong, 2020. "Optimal maintenance policy considering imperfect repairs and non-constant probabilities of inspection errors," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    19. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2021. "Optimal operation and maintenance scheduling in m-out-of-n standby systems with reusable elements," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    20. Zhao, Qian Qian & Yun, Won Young, 2018. "Determining the inspection intervals for one-shot systems with support equipment," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 63-75.
    21. Xu, Jun & Liang, Zhenglin & Li, Yan-Fu & Wang, Kaibo, 2021. "Generalized condition-based maintenance optimization for multi-component systems considering stochastic dependency and imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    22. Sharifi, Mani & Taghipour, Sharareh & Abhari, Abdolreza, 2021. "Inspection interval optimization for a k-out-of-n load sharing system under a hybrid mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    23. Levitin, Gregory & Xing, Liudong & Dai, Yanshun, 2022. "Minimum cost replacement and maintenance scheduling in dual-dissimilar-unit standby systems," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
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