Functional risk-oriented health prognosis approach for intelligent manufacturing systems

• Published in: Reliability engineering & system safety 2020-11, Vol.203, p.107090, Article 107090
• Main Authors: He, Yihai, Zhao, Yixiao, Han, Xiao, Zhou, Di, Wang, Wenzhuo
• Format: Article
• Language: English
• Subjects: Control charts; Cylinder heads; Fault detection; functional fault; functional risk; health prognosis; Health risks; Intelligent manufacturing system; Intelligent manufacturing systems; Manufacturing; Modular systems; Prognosis; Reliability engineering; Risk; Systems health monitoring; TBE control chart; Workpieces
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2020.107090

•Connotations of functional risk and functional fault of intelligent manufacturing systems are defined.•A novel quantitative model of functional risk of intelligent manufacturing systems is established.•A functional fault detection strategy using a TBE control chart is established.•A functional fault detection example of engine cylinder head manufacturing system is implemented. The quality and reliability level of the produced product is the key performance and health state indicator of the running manufacturing system. Hence, the workpiece quality centered operational data originated from the production process should be considered to predict the health state of the intelligent manufacturing system. However, studies of system health prognosis based on the performance of manufacturing function is not gotten the attention it deserved. Therefore, a novel fault detection strategy for intelligent manufacturing systems referring to its functional state is proposed. First, the influencing factors of functional output are explored, and the connotation of functional risk and functional fault is proposed based on system modular hierarchical and output monitoring. Second, the quantitative models of explicit and implicit risks are established as the subsequent functional risk indicators. Third, the Time-between-event control chart is adopted to detect the occurrence of machine functional faults at each step. Finally, the availability and advancement of the proposed fault detection are verified on a cylinder head manufacturing system.