A Stochastic Approach for Failure Mode and Effect Analysis

Abstract

This study presents a novel approach combining Failure Mode and Effect Analysis (FMEA) and Multi-Attributive Border Approximation Area Comparison (MABAC) method based on a stochastic evaluation process to prioritize potential failure modes (FMs) in an assembly line. The aim of the proposed approach is to improve the performance of FMEA by eliminating its shortcomings addressed in the study. In this context, firstly the risk factor (RF) importance weights and the performance values of the FMs for the RFs are determined by generating random numbers having uniform distribution in a range of minimum and maximum value of a limited number of expert evaluations. In this wise, the number of experts are increased to improve effectiveness of the risk evaluation process. Diverse opinions of experts are also assessed more precisely. Secondly, the priorities of the FMs are identified by implementing MABAC method. MABAC is a practical and reliable tool which provides stability for solutions. Finally, a comparative analysis is implemented to confirm the effectiveness of Stochastic FMEA-MABAC approach.