Development of a fuzzy-logic-based Occurrence updating model for process FMEA

Risk priority number (RPN) ranking system is used to evaluate the risk level of failures, to rank failures, and to prioritize actions in traditional failure mode and effect analysis (FMEA). The RPN score is determined by multiplication of three input scores estimated by users, i.e., severity, occurrence, and detect. Even through this approach is simple, one of the problems is the difficulty in obtaining a good estimate of the severity, occurrence and detect ratings. Besides, it is a tedious job to update the ratings from time to time. In this paper, FMEA system with a proposed framework equipped with a fuzzy inference system based occurrence model to predict the occurrence score is proposed, and the fuzzy occurrence model is devised. In here, we propose a property for the fuzzy occurrence model, i.e., monotone output property. We try to derive the condition for the fuzzy occurrence model to be monotone such as that the derivative in non negative. From the derivation, a guideline on how input membership functions should be tuned is also provided. Simulation results are analyzed using real information collected from a semiconductor manufacturing environment.