Modified failure mode and effects analysis under uncertainty: A rough cloud theory-based approach

Failure mode and effect analysis (FMEA) has been commonly utilized for recognition of failures, causes and influences in a system/process. However, the traditional FMEA method has been subjected to a lot of criticisms, e.g., equal importance of risk factor, lack of mechanism in manipulating imprecise information; Although the traditional FMEA is improved by various approaches based on fuzzy set theory, it still suffers from several limitations, such as requirement of prior information, construction of many fuzzy rules, and ignoring randomness in risk evaluation. Therefore, this study integrates the advantage of rough set theory in flexibly and objectively expressing vagueness without extra information and the merit of cloud model theory in taking randomness of experts' risk assessments into account. Meanwhile, an integrated weighting method considering both subjective and objective aspects is employed to estimate risk factor weights. Then, the failure modes are ranked by an extended TOPSIS (technique for order performance by similarity to ideal solution) method. To finish, a case study about risk evaluation of failure modes in a steam valve system is analyzed to show the effectiveness of the proposed method. (C) 2019 Elsevier B.V. All rights reserved.