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Mission reliability-driven risk-based predictive maintenance approach of multistate manufacturing system

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  • Liao, Ruoyu
  • He, Yihai
  • Feng, Tianyu
  • Yang, Xiuzhen
  • Dai, Wei
  • Zhang, Weifang

Abstract

With the coupling effect of equipment state, product quality, and task requirements of manufacturing system, physical condition-based maintenance of the manufacturing system has gradually failed to satisfy the corresponding requirements, leading to operational risk improvement continuously. However, few existing maintenance studies consider operational risk, such as product quality decline and production task delay. Therefore, a novel operational risk-based predictive maintenance approach is proposed using mission reliability and adopting the principle of risk-based maintenance. First, according to the operation principle of manufacturing system, the definition of mission reliability-oriented operational risk is expounded, and the mechanism of risk-based maintenance is put forward. Second, the source and types of operational risk are explained: the fundamental risk is obtained from the manufacturing equipment degradation and failures, the explicit risk is characterized by the qualification rate of key quality characteristics of process and products, and the implicit risk is quantified by the realization rate of production tasks. Third, to decrease the three risk types, an operational risk-based predictive maintenance strategy is proposed to minimize the comprehensive production cost. Finally, a case study of subway current receiver manufacturing system is conducted to illustrate the effectiveness and advantages of the proposed approach.

Suggested Citation

  • Liao, Ruoyu & He, Yihai & Feng, Tianyu & Yang, Xiuzhen & Dai, Wei & Zhang, Weifang, 2023. "Mission reliability-driven risk-based predictive maintenance approach of multistate manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:reensy:v:236:y:2023:i:c:s0951832023001886
    DOI: 10.1016/j.ress.2023.109273
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    References listed on IDEAS

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