Mission reliability evaluation and selective maintenance approach for manufacturing systems considering epistemic uncertainty

For manufacturing systems, the states of operational performance and functional output are essential indicators of their reliability evaluation, operational health state monitoring, and maintenance decision. However, due to the instability of the 5M1E factors, that is, Man, Machine, Method, Material, Measurement, and Environment, in the manufacturing process, certain components within these systems could introduce epistemic uncertainty factors and thus interfere with the results of evaluation and decision. Consequently, a novel integrated mission reliability evaluation and selective maintenance approach considering epistemic uncertainty is proposed. First, an uncertain-random operational model for manufacturing systems, in which the uncertain operational mechanisms are specified, is established as the foundation. Second, a mission reliability evaluation method for uncertain-random manufacturing systems that fuses the conformity and fitness quality data is proposed to cope with the challenge of epistemic uncertainty. Third, a selective maintenance decision model that maximizes the system's mission reliability is developed in consideration of the uncertain factors within the operation process. Finally, a case study of a ferrite phase shifting unit manufacturing system is conducted to validate the proposed approach.