Importance Analysis of System Related Fault Based on Improved Decision-Making Trial and Evaluation Laboratory

The existence of related faults between components brings great difficulties to the analysis of the importance of system components. How to quantify the influence of related faults and evaluate the importance of components is one of the hot issues in current research. In this paper, under the assumption that the fault propagation obeys the Markov process, the PageRank algorithm is integrated into the decision-making trial and evaluation laboratory (DEMATEL). On the basis, the calculation of influencing degree and influenced degree between components is studied to quantify the influence of related faults, and the problem of subjective evaluation of weight coefficient in traditional DEMATEL is solved. The rationality is verified through the method of combining the Interpretative Structural Modeling Method (ISM) and direct relation matrix. The importance of system related faults is identified accurately based on the calculation of center degree and cause degree, and the central-related faults of CNC machine tools are analyzed as an example to verify the effectiveness of the proposed method.