Functional risk-oriented health prognosis approach for intelligent manufacturing systems

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.