Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review

• Published in: Computers & industrial engineering Vol. 135; pp. 881 - 897
• Main Authors: Liu, Hu-Chen, Chen, Xu-Qi, Duan, Chun-Yan, Wang, Ying-Ming
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2019
• Subjects: Failure mode and effect analysis (FMEA); Literature review; Multi-criteria decision making (MCDM); Reliability management; Risk analysis; Literature review; Risk analysis; Reliability management; Failure mode and effect analysis (FMEA); Multi-criteria decision making (MCDM)
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2019.06.055

•This paper provides a comprehensive review of FMEA using MCDM methods.•The 169 articles were found and classified according to the used MCDM methods.•The risk factors, risk factor weighting methods and risk assessment methods are analyzed.•Directions for future research to adopt MCDM methods for FMEA are provided. Failure mode and effect analysis (FMEA) is a proactive reliability management technique extensively utilized in a variety of fields. To enhance the effectiveness of FMEA, a great many multi-criteria decision making (MCDM) methods have been applied for properly evaluating the risk of failure modes over the past two decades. However, there is a lack of study concerning systematic literature review and classification of the researches on this topic. This article aims to provide a comprehensive review of the FMEA studies using MCDM approaches for evaluation and prioritization of failure modes. To do so, a total of 169 journal papers extracted from the online database over the period of 1998–2018 were selected and reviewed. These publications were classified into 10 categories according to the used MCDM methods, and analyzed in regard to the risk factors, risk factor weighting methods, and risk assessment methods in FMEA. Furthermore, a bibliometric analysis was performed based on the frequency of MCDM methods, number of citations, year of publication, appeared journals, country of origin and application areas. This research supports academics and practitioners in effectively adopting MCDM methods to overcome the deficiencies of the traditional FMEA and provides an insight into its state-of-the-art.