期刊
SOFT COMPUTING
卷 21, 期 18, 页码 5355-5367出版社
SPRINGER
DOI: 10.1007/s00500-016-2118-x
关键词
Failure mode and effect analysis; MULTIMOORA; Continuous weighted entropy; Interval-valued intuitionistic fuzzy set
资金
- National Natural Science Foundation of China [71402090]
- NSFC key program [71432007]
- China Postdoctoral Science Foundation [2015T80456]
- Program for Young of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning [QD2015019]
- Chen Guang project - Shanghai Municipal Education Commission
- Shanghai Education Development Foundation
Failure mode and effect analysis (FMEA) is a prospective risk assessment tool used to identify, assess and eliminate potential failure modes in various industries to improve security and reliability. However, the conventional risk priority number (RPN) method has been widely criticized for the deficiencies in risk factor weights, calculation of RPN, evaluation of failure modes, etc. In this paper, we present a novel approach for FMEA based on interval-valued intuitionistic fuzzy sets (IVIFSs) and MULTIMOORA method to handle the uncertainty and vagueness from FMEA team members' subjective assessments and to get a more accurate ranking of failure modes identified in FMEA. In this proposed model, interval-valued intuitionistic fuzzy (IVIF) continuous weighted entropy is applied for risk factor weighting and the IVIF-MULTIMOORA method is used to determine the risk priority order of failure modes. Finally, an illustrative case is provided to demonstrate the effectiveness and practicality of the proposed FMEA and a comparison analysis with other relevant methods is conducted to show its merits.
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