Journal
SOFT COMPUTING
Volume 23, Issue 18, Pages 8801-8814Publisher
SPRINGER
DOI: 10.1007/s00500-018-3480-7
Keywords
Failure mode and effect analysis; Two-dimensional uncertain linguistic variable; GRA-TOPSIS; Healthcare risk analysis
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Funding
- National Natural Science Foundation of China [61773250, 71671125, 71402090]
- Program for Shanghai Youth Top-Notch Talent
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This paper provides a novel risk priority approach for failure mode and effect analysis (FMEA), which can overcome some inherent drawbacks of the traditional risk priority number (RPN) method in imprecise risk evaluation, risk factor weighting and questionable RPN computation. Considering FMEA team members' vagueness and uncertainty in their evaluations on failure modes, two-dimensional uncertain linguistic variables are advised to describe the risk evaluation result of a failure mode and the reliability of the evaluation result. The grey relation analysis-technique for order preference by similarity to ideal solution (GRA-TOPSIS) is applied for determining the risk ranking of the identified failure modes. In particular, a maximizing deviation method is employed for calculating the optimal weights of risk factors in an objective way. Via a practical healthcare risk analysis case, the new FMEA is proved to be appropriate and effective in coping with the risk evaluation problems with uncertain linguistic information. Furthermore, by comparing with existing methods, it is shown that the proposed integrated approach excels in the risk evaluation and prioritization of failure modes in FMEA.
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