Failure Mode and Effects Analysis (FMEA) using interval number based BWM—MCDM approach: Risk Expected Value (REV) method

One of the most popular structured approaches in risk assessment is Failure Mode and Effects Analysis (FMEA) that helps in discovering potential failures existing within the design of a product or process. But numerous inadequacies are conjoined with it, for example, Risk Priority Number (RPN) used in FMEA fails to consider the individual effects of the risk factors, thereby neglecting the priority importance of each potential failure modes (PFMs). In this paper, a novel approach, namely, REV method is proposed, where subjective weights of risk factors are determined by using Interval number based Best Worst Method (BWM) to evaluate the weights of risk factors and determine their importance. REV is proposed as an alternative to RPN and aims to improve FMEA that could efficiently handle the vagueness and uncertainty of real-life situations. It is benefitted from decisions of both probability of risk of failure, for assessing the individual influence of the risk factors, as well as priority weights of PFMs from the preference decisions making ability of the MCDM methods with conflicting criteria. It is a user-friendly, flexible approach where suitable MCDM method of choice can be used for obtaining REVs. Here, MCDM techniques of TOPSIS, VIKOR, PROMETHEE and EDAS are used for reviewing individual impacts of PFMs. Furthermore, the proposed approach is endorsed with a case study involving failures in components of submersible pumps used in a power plant. The model is validated using Kendall Tau coefficient computed for different REVs and results are found to be satisfactory (0.849 for TOPSIS-VIKOR, 0.832 for PROMETHEE-EDAS, 0.851 for VIKOR- EDAS and 0.934 for TOPSIS- EDAS).