A failure mode and risk assessment method based on cloud model

Abstract

Failure mode and effects analysis (FMEA) is a predictive reliability analysis technique, which is widely used to improve the reliability and safety of products in products design, manufacture and service phases. However, traditional FMEA has many shortcomings in practical application, resulting in poor accuracy of analysis results. In this paper, based on meta-action failure modes, a risk assessment and ranking method based on cloud model is proposed. First, the domain expert’s assessment of failure modes’ attributes is transformed into a cloud model. Then, the best–worst method (BWM) and cloud model are combined to calculate the cloud weight of each attribute, and the weight of each expert to risk factors of each failure mode is evaluated by cloud distance. Finally, the comprehensive cloud expression of each failure mode is synthesized and compared. The proposed evaluation method not only has the advantages of cloud model in dealing with fuzziness and randomness, but also integrates the advantages of BWM, and fully takes into account the differences of experts in assigning weights to different failure modes’ attributes. Finally, the effectiveness of the proposed method is verified by comparing the risk assessment results of the CNC machine tool’s rotation-meta-action failure modes with different risk assessment methods.