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

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

Reliability Engineering and System Safety, 2023, vol. 236, issue C

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.

Keywords: Mission reliability; Operational risk; Multistate manufacturing system; Risk-based maintenance; Predictive maintenance (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:236:y:2023:i:c:s0951832023001886

DOI: 10.1016/j.ress.2023.109273

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