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

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  • 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
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    References listed on IDEAS

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    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.
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    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).

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