Failure modes and effects analysis using integrated weight-based fuzzy TOPSIS

Failure mode and effect analysis (FMEA) technique has been extensively used as a powerful tool for identifying and assessing potential failures in different phases of the product life cycle. However, the conventional FMEA has been criticised much for its deficiencies in measurement scale, computation of risk priority numbers (RPN), risk factors’ weights, etc. In this work, the authors propose a more reasonable failure evaluation structure using fuzzy weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). To fully reflect the importance of risk factors severity (S), occurrence (O) and detection (D), the authors consider integrating both subjective weights and objective weights, which is not presented in literature before, avoid failure modes from being underestimated or overestimated. For ranking fuzzy TOPSIS is adopted to get the closeness coefficient for each failure mode. Then, all failure modes can be ranked according to the closeness coefficients. A case of nuclear reheat valve system is provided to illustrate the applications and benefits of proposed FMEA method.