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

被引:26
作者
Liao, Ruoyu [1 ]
He, Yihai [1 ]
Feng, Tianyu [1 ]
Yang, Xiuzhen [1 ]
Dai, Wei [1 ]
Zhang, Weifang [1 ]
机构
[1] Beihang Univ, Sch Reliabil & Syst Engn, Beijing, Peoples R China
关键词
Mission reliability; Operational risk; Multistate manufacturing system; Risk-based maintenance; Predictive maintenance; STRATEGY SELECTION; OPTIMIZATION; NETWORK; MODEL;
D O I
10.1016/j.ress.2023.109273
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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 corre-sponding requirements, leading to operational risk improvement continuously. However, few existing mainte-nance 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 pre-dictive 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.
引用
收藏
页数:13
相关论文
共 38 条
[1]   A review on condition-based maintenance optimization models for stochastically deteriorating system [J].
Alaswad, Suzan ;
Xiang, Yisha .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2017, 157 :54-63
[2]   A systematic literature review of machine learning methods applied to predictive maintenance [J].
Carvalho, Thyago P. ;
Soares, Fabrizzio A. A. M. N. ;
Vita, Roberto ;
Francisco, Robert da P. ;
Basto, Joao P. ;
Alcala, Symone G. S. .
COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 137
[3]   System reliability for a multi-state manufacturing network with joint buffer stations [J].
Chang, Ping-Chen ;
Lin, Yi-Kuei ;
Chen, James C. .
JOURNAL OF MANUFACTURING SYSTEMS, 2017, 42 :170-178
[4]   A data-driven predictive maintenance strategy based on accurate failure prognostics [J].
Chen, Chuang ;
Wang, Cunsong ;
Lu, Ningyun ;
Jiang, Bin ;
Xing, Yin .
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2021, 23 (02) :387-394
[5]   Reliability evaluation for multi-state manufacturing systems with quality-reliability dependency [J].
Chen, Zhaoxiang ;
Chen, Zhen ;
Zhou, Di ;
Xia, Tangbin ;
Pan, Ershun .
COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 154
[6]   Mission Reliability-Oriented Selective Maintenance Optimization for Intelligent Multistate Manufacturing Systems With Uncertain Maintenance Quality [J].
Chen, Zhaoxiang ;
He, Yihai ;
Zhao, Yixiao ;
Han, Xiao ;
Liu, Fengdi ;
Zhou, Di ;
Wang, Wenzhuo .
IEEE ACCESS, 2019, 7 :109804-109816
[7]   A cost-informed component maintenance index and its applications [J].
Dui, Hongyan ;
Tian, Tianzi ;
Wu, Shaomin ;
Xie, Min .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2023, 230
[8]   Different costs-informed component preventive maintenance with system lifetime changes [J].
Dui, Hongyan ;
Zhang, Chi ;
Tian, Tianzi ;
Wu, Shaomin .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, 228
[9]   Joint production and preventive maintenance controls for unreliable and imperfect manufacturing systems [J].
El Cadi, Abdessamad Ait ;
Gharbi, Ali ;
Dhouib, Karem ;
Artiba, Abdelhakim .
JOURNAL OF MANUFACTURING SYSTEMS, 2021, 58 :263-279
[10]   An Intelligent Health diagnosis and Maintenance Decision-making approach in Smart Manufacturing [J].
Gao, Guibing ;
Zhou, Dengming ;
Tang, Hao ;
Hu, Xin .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 216