IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v237y2023i5p966-979.html
   My bibliography  Save this article

Joint optimization of inspection and maintenance strategy for complex multi-component systems using a quantum-inspired genetic algorithm

Author

Listed:
  • Diyin Tang
  • Xuan Wang
  • Junwei Di
  • Guofeng Zheng
  • Jinsong Yu

Abstract

Advances in sensor and data technology enable real-time condition monitoring, thus extending the opportunities for condition-based maintenance (CBM) to be applied in practice. In this paper, a joint inspection and maintenance strategy for multi-component systems is proposed. The objective of this strategy is to minimize the long-run expected operational cost by jointly considering the inspection frequency of each health monitor in the system and the threshold for the maintenance initialization. To find the optimal strategy, a dynamic Bayesian network-based maintenance model is developed at first to provide reasoning of the dynamic reliability of degrading components in the multi-component system, in which complex relationship among inspections by different health monitors, different failure modes in the system, and different maintenance actions to system components are considered and quantified. Then, a quantum-inspired genetic algorithm (QGA) is proposed to optimize the strategy. With quantum encoding method, improved rotation gate, and specially designed crossover and mutation operators, the QGA is able to find the optimal strategy for multi-component systems with a general system structure. An example simplified from real practice is presented to demonstrate the effectiveness and advantages of the proposed strategy and the optimization algorithm, with comparison to similar strategies and traditional intelligent optimization algorithms.

Suggested Citation

  • Diyin Tang & Xuan Wang & Junwei Di & Guofeng Zheng & Jinsong Yu, 2023. "Joint optimization of inspection and maintenance strategy for complex multi-component systems using a quantum-inspired genetic algorithm," Journal of Risk and Reliability, , vol. 237(5), pages 966-979, October.
    • Handle: RePEc:sae:risrel:v:237:y:2023:i:5:p:966-979
    DOI: 10.1177/1748006X221102992
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X221102992
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X221102992?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hu, Jiawen & Chen, Piao, 2020. "Predictive maintenance of systems subject to hard failure based on proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    2. Wang, Ling & Chu, Jian & Mao, Weijie, 2009. "A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure," European Journal of Operational Research, Elsevier, vol. 194(1), pages 184-205, April.
    3. Alessandro Niccolai & Francesco Grimaccia & Marco Mussetta & Riccardo Zich, 2019. "Optimal Task Allocation in Wireless Sensor Networks by Means of Social Network Optimization," Mathematics, MDPI, vol. 7(4), pages 1-15, March.
    4. Liao, Haitao & Elsayed, Elsayed A. & Chan, Ling-Yau, 2006. "Maintenance of continuously monitored degrading systems," European Journal of Operational Research, Elsevier, vol. 175(2), pages 821-835, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiang, Weixin & Cui, Lirong & Liang, Xiaojun, 2024. "Optimal maintenance policies for three-unit parallel production systems considering yields," Reliability Engineering and System Safety, Elsevier, vol. 248(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Naichao & Hu, Jiawen & Ma, Lin & Xiao, Boping & Liao, Haitao, 2020. "Availability Analysis and Preventive Maintenance Planning for Systems with General Time Distributions," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    2. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    3. Hamza Boudhar & Mohammed Dahane & Nidhal Rezg, 2017. "New dynamic heuristic for the optimization of opportunities to use new and remanufactured spare part in stochastic degradation context," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 437-454, February.
    4. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2023. "Improving classical optimal age-replacement policies for degrading items," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    5. Hu, Qiwei & Chakhar, Salem & Siraj, Sajid & Labib, Ashraf, 2017. "Spare parts classification in industrial manufacturing using the dominance-based rough set approach," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1136-1163.
    6. Zhang, Jian-Xun & Si, Xiao-Sheng & Du, Dang-Bo & Hu, Chang-Hua & Hu, Chen, 2020. "A novel iterative approach of lifetime estimation for standby systems with deteriorating spare parts," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    7. Liu, Xinbao & Yang, Tianji & Pei, Jun & Liao, Haitao & Pohl, Edward A., 2019. "Replacement and inventory control for a multi-customer product service system with decreasing replacement costs," European Journal of Operational Research, Elsevier, vol. 273(2), pages 561-574.
    8. Dilaver, Halit Metehan & Akçay, Alp & van Houtum, Geert-Jan, 2023. "Integrated planning of asset-use and dry-docking for a fleet of maritime assets," International Journal of Production Economics, Elsevier, vol. 256(C).
    9. Rassoul Noorossana & Kamyar Sabri-Laghaie, 2015. "Reliability and maintenance models for a dependent competing-risk system with multiple time-scales," Journal of Risk and Reliability, , vol. 229(2), pages 131-142, April.
    10. Zhou, Shirong & Tang, Yincai & Xu, Ancha, 2021. "A generalized Wiener process with dependent degradation rate and volatility and time-varying mean-to-variance ratio," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    11. Cheng, Guoqing & Li, Ling, 2020. "Joint optimization of production, quality control and maintenance for serial-parallel multistage production systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    12. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    13. Song, Sanling & Coit, David W. & Feng, Qianmei, 2014. "Reliability for systems of degrading components with distinct component shock sets," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 115-124.
    14. Guo, Chiming & Wang, Wenbin & Guo, Bo & Si, Xiaosheng, 2013. "A maintenance optimization model for mission-oriented systems based on Wiener degradation," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 183-194.
    15. Wang, Liying & Song, Yushuang & Zhang, Wenhua & Ling, Xiaoliang, 2023. "Condition-based inspection, component reallocation and replacement optimization of two-component interchangeable series system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    16. 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).
    17. Yonit Barron & Chananel Benshimol, 2024. "Emergency Supply Alternatives for a Storage Facility of a Repairable Multi-Component System," Mathematics, MDPI, vol. 12(17), pages 1-33, August.
    18. Yousefi, Nooshin & Coit, David W. & Song, Sanling, 2020. "Reliability analysis of systems considering clusters of dependent degrading components," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    19. Xinlong Li & Yan Ran & Fangming Wan & Hui Yu & Genbao Zhang & Yan He, 2022. "Condition-based maintenance strategy optimization of meta-action unit considering imperfect preventive maintenance based on Wiener process," Flexible Services and Manufacturing Journal, Springer, vol. 34(1), pages 204-233, March.
    20. Fritzsche, R., 2012. "Cost adjustment for single item pooling models using a dynamic failure rate: A calculation for the aircraft industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1065-1079.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:risrel:v:237:y:2023:i:5:p:966-979. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.