A hybrid decision making framework for modified failure mode effects and criticality analysis

Abstract

Purpose Assessing the severity of failure modes of critical industrial machinery is often considered as an onerous task and sometimes misinterpreted by shop-floor engineer/maintenance personnel. The purpose of this paper is to develop an improved FMECA method for prioritizing the failure modes as per their risk levels and validating the same through a real case study of induction motors used in a process plant. Design/methodology/approach This paper presents a novel hybrid multi-criteria decision-making (MCDM) approach to prioritize different failure modes according to their risk levels by combining analytical hierarchy process (AHP) with a newly introduced MCDM approach, election based on relative value distance (ERVD). AHP is incorporated in the proposed approach to determine the criteria weights, evaluated in linguistic terms by industrial expert. Furthermore, ERVD, which is based on the concept of prospect theory of human cognitive process, is applied to rank the potential failure modes. Findings It is found that the proposed FMECA approach provides better results in accordance with the actual industrial scenario and helps in effectively prioritizing the failure modes. A comparison is also made to highlight the differences of results between the proposed approach with TOPSIS and conventional FMECA. Research limitations/implications This research paper proposes an improved FMECA method and, thus, provides a deep insight to maintenance managers for effectively prioritizing the failure modes. The correct prioritization of failure modes will help in effective maintenance planning, thus reducing the downtime and improving profit to the organization. Practical implications A real case of process plant induction motor has been introduced in the research paper to show the applicability of this decision-making approach, and the approach is found to be suitable in correct prioritization of the failure modes. Originality/value Severity has been decoupled into various factors affecting it, to make it more relevant as per actual industrial scenario. Then, a novel modified FMECA has been developed using a hybrid MCDM approach (AHP and ERVD). This hybrid method, as well as its application in FMECA, has not been developed by any previous researcher. Moreover, the same has been thoroughly explained by considering a real case of process plant induction motors and validated with cross-functional experts.

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

“…The consistency ratio (CR) of the pairwise comparison matrix is 0.050, which is less than 0.10. Thus, the calculated weights are consistent [31]. Next, we start prioritizing the failure modes by using Eqs.…”

“…Till date, we observe several applications of the AHP method and its variants in the FMEA domain [23,31,34]. The work carried out by Kutlu and Ekmekçioğlu [34] highlighted the application of fuzzy AHP and the use of Chang's extent analysis method [39].…”

“…If 𝐴𝐴 ̃= �𝑎𝑎 � 𝑖𝑖𝑖𝑖 � is a fuzzy positive reciprocal matrix and 𝐴𝐴 = �𝑎𝑎 𝑖𝑖𝑖𝑖 � is the defuzzified positive reciprocal matrix, then 𝐴𝐴 ̃ is said to be consistent 𝑒𝑒𝑖𝑖𝑖𝑖 𝐴𝐴 is consistent [38]. The general procedures for measuring the consistency ratio in AHP is given in [31]. If, in case the result is not consistent, experts need to reevaluate the pairwise comparisons.…”

A novel hybrid multi-criteria group decision making approach for failure mode and effect analysis: An essential requirement for sustainable manufacturing

“…Moreover, they developed a linear programming model capable of determining the RF weight when the prior information available is incomplete. Recently, in [53] a newly developed MCDM method, Election based on Relative Value Distance (ERVD) was coupled with AHP for performing FMEA of an induction motor.…”

A hybrid model integrating FMEA and HFACS to assess the risk of inter-city bus accidents

“…The FMEA model was developed by the Grumman Aircraft Corporation in the 1960s to analyze the flight control systems of naval aircraft [14]. It is a proactive risk assessment technology [7].…”