Paper Info
Title
Risk prioritization in failure mode and effects analysis under uncertainty
Abstract
Failure mode and effects analysis (FMEA) is a powerful tool for identifying and assessing potential failures. The tool has become increasingly important in new product development, manufacture or engineering applications. Generally, risk assessment in FMEA is carried out by using risk priority numbers (RPNs) which can be determined by evaluating three factors: occurrence (O), severity (S) and detection (D). Due to the vagueness and uncertainty existing in the evaluating process, crisp numbers representing RPNs in the traditional FMEA might be improper or insufficient in contrast to fuzzy numbers. Currently, the fuzzy methods and linear programming method have been proposed as an effective solution for the calculations of fuzzy RPNs. However, considering the fact that fuzzy RPNs are determined on a multidimensional scale spanning O, S and D along with their interactions under a fuzzy environment, several gaps should be bridged in the evaluation, calculation, and ranking of fuzzy RPNs. First, decision makers tend to use multi-granularity linguistic term sets for expressing their assessments because of their different backgrounds and preferences. Second, numerical compensation may be existed among O, S and D that can derive different RPNs in the engineering applications. Third, the complete ranking results for fuzzy RPNs may be easily changed by the effects of uncertain factors. In this study, a fuzzy-RPNs-based method integrating weighted least square method, the method of imprecision and partial ranking method is proposed to generate more accurate fuzzy RPNs and ensure to be robust against the uncertainty. A design example of new horizontal directional drilling machine is used for illustrating the application of the proposed approach.
Year
DOI
Venue
2011
10.1016/j.eswa.2010.06.046
Expert Syst. Appl.
Keywords
Field
DocType
the method of imprecision,fuzzy risk priority numbers,accurate fuzzy rpns,effects analysis,failure mode and effects analysis,engineering application,failure mode,fuzzy rpns,linear programming method,partial ranking method,nonlinear programming model,fuzzy-rpns-based method,risk prioritization,fuzzy environment,fuzzy method,fuzzy number,fuzzy weighted geometric mean,different rpns,linear program,new product development,nonlinear programming,horizontal directional drilling,risk assessment,geometric mean,decision maker,failure mode and effect analysis,multidimensional scaling
Failure mode and effects analysis,Data mining,Vagueness,Ranking,Computer science,Fuzzy logic,Risk assessment,Artificial intelligence,Linear programming,Fuzzy number,Machine learning,New product development
Journal
Volume
Issue
ISSN
38
1
Expert Systems With Applications
Citations 
PageRank 
References 
20
0.99
11
Authors
2
Name
Order
Citations
PageRank
Zaifang Zhang11657.84
Xuening Chu223821.29