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Multi-objective maintenance strategy for complex systems considering the maintenance uncertain impact by adaptive multi-strategy particle swarm optimization

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  • Zhang, Yadong
  • Wang, Shaoping
  • Zio, Enrico
  • Zhang, Chao
  • Dui, Hongyan
  • Chen, Rentong

Abstract

Effective maintenance optimization strategies are crucial for improving the complex equipment reliability and reducing the maintenance costs. However, the effectiveness of the maintenance procedures applied to industrial equipment is affected by uncertainty, e.g. due to the professional skills of maintenance personnel, the actual condition of the equipment being maintained. The quantification of the uncertainty on the effect of maintenance has practical significance and must be accounted in the development of maintenance strategies for reducing equipment probability of failure. This paper proposes a multi-objective maintenance strategy considering the uncertain impact of the maintenance actions. The impact of maintenance actions on the reliability of components is first studied and a reliability assessment model is developed, which considers the skill of maintenance personnel and the actual condition of the equipment. To optimize the multi-objective maintenance strategy, a multi-strategy particle swarm optimization (MS-PSO) algorithm is proposed. Two case studies are considered to verify the effectiveness of the proposed approach for multi-objective maintenance strategy optimization. In the case studies considered, it turns out that the maintenance cost rate (MCR) is reduced throughout the system life cycle and the cumulative availability is improved.

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  • Zhang, Yadong & Wang, Shaoping & Zio, Enrico & Zhang, Chao & Dui, Hongyan & Chen, Rentong, 2025. "Multi-objective maintenance strategy for complex systems considering the maintenance uncertain impact by adaptive multi-strategy particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:reensy:v:256:y:2025:i:c:s0951832024007427
    DOI: 10.1016/j.ress.2024.110671
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    References listed on IDEAS

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