An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA

Abstract Failure mode and effect analysis (FMEA) is a proactive risk assessment technique, which has been widely used by engineers to meet the safety and reliability requirements of processes, products, structures, services, and systems. The major aim of the FMEA technique is to rank the failure modes according to their risk levels and subsequent actions are performed to eliminate/mitigate their consequences. In a typical FMEA, for each failure mode, three risk factors, namely severity (S), occurrence (O) and detection (D) are evaluated and a risk priority number (RPN) is estimated by multiplying these risk factors. In recent years a significant effort has been underway and different approaches have been proposed to improve FMEA, to overcome its several drawbacks. We notice that there is a significant amount of literature based on multi-criteria decision making (MCDM) methods, which have been solely aimed to improve the risk estimation process in FMEA by overcoming the drawbacks of the traditional FMEA technique. In this work, we propose a novel integrated MCDM approach by combining Fuzzy Analytical Hierarchy Process (FAHP) with the modified Fuzzy Multi-Attribute Ideal Real Comparative Analysis (modified FMAIRCA). At first, we calculate the fuzzy relative importance between the risk factors by using the FAHP method and then we use those importance values in our proposed modified FMAIRCA to rank the failure modes according to their risk level. Our modified FMAIRCA method is computationally inexpensive and is able to provide more viable decisions. We consider a benchmark example in FMEA domain to validate the ability of our integrated approach and highlight the usefulness of the same. Further, we compare the ranking result with other MCDM methods - FVIKOR, FCOPRAS, FMOORA, FMABAC, FTOPSIS and sensitivity analysis is also performed to highlight the robustness of the proposed approach.