Fuzzy FMECA risk evaluation and its applications in Chinese train control systems based on cloud model

Abstract

In view of defects that traditional Fuzzy Analytical Hierarchy Process (FAHP) cannot accurately describe the ambiguity and randomness of the assessment, and as well as inconsistency existed in judgment process, in this paper a novel risk evaluation method is proposed using Fuzzy Failure Modes Effects and Criticality Analysis (FMECA) based on could model. The method firstly applies FMECA to identify the risk, and then uses FAHP to determine the subjection degree function with cloud model based. In the end, the group decision can be conducted with the synthetically aggregated cloud model, which can be directly observed through the distribution of the cloud pictures. Compared with traditional FAHP, the relevant practical examples in Chinese train control (CTC) systems show that the results of the two possess difference due to their original data coming from different 20-expert questionnaires, the reason is found that there exists inconsistence in 20-expert questionnaires on FAHP via t-examination method. Hence, though another 20-expert questionnaires and after inconsistence test, we obtain consistent result in both methods, but the Fuzzy-FMECA with cloud model based could implement the transformation between exact value and quantized one by incorporating the ambiguity and randomness, and provide more abundant information than subjection degree function of the conventional FAHP method, and possesses better consistency, and is a feasible and more effective decision method. In addition, the correlation coefficient method and center-of-gravity method are also applied to verify the correctness and effectiveness of the proposed method, and such that it can be widely applied to solve real-world practical issues.