A novel failure mode effect and criticality analysis (FMECA) using fuzzy rule-based method: A case study of industrial centrifugal pump. (May 2021)

• Record Type: Journal Article
• Authors: Gupta, Gajanand; Ghasemian, Hamed; Janvekar, Ayub Ahmed
• Is Part Of: Engineering failure analysis. Volume 123(2021)
• Publication Date: 2021-05
• Subjects: FMEA -- Fuzzy logic -- Dempster-Shafer theory -- Decision making -- Failure mode; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2021.105305
• Languages: English
• ISSNs: 1350-6307

Abstract

Highlights: A novel development of membership functions in Fuzzy Risk Priority Number. Implementation of FMECA model using Fuzzy rule-based and Dempster-Shafer theory. Enabling fuzzified linear equation to faciality easier calculations in Reliability. Introduction of hybrid Multi Criteria Decision Making field by FMEA team members. Abstract: FMECA is the name of a widely utilized tool in diverse areas which based on the assessed potential failures, provides a foundation of remedial measures. Due to utilization of an expert team for evaluation of system failures, numerous methods for aggregating of opinions were proposed; which confronting with uncertainty and incomplete analysis of system have been two continual problems. In this paper, a new FMECA model based on fuzzy logic and Dempster-Shafer theory (D-S theory) is proposed to evaluate the risk in FMEA. The proposed model is development of a recent fuzzy rule-based model with 100 membership functions, which a novel linear equation (Gupta-Ghasemian formula) is discovered through it. By contributing of the generated formula to FMEA, a more useful method which provides a unique result for any combination of risk factors aiming at capturing of uncertainties is presented. As the case study, an industrial centrifugal pump is assessed by a FMEA team comprised of ten experts who were experienced in industrial components. Finally, according to the results, failure modes are ranked and critical components are recognized.