Health Evaluation Method of CNC Machine Tools Based on Fuzzy Grey Clustering and Combined Weighting Method

Abstract

Health evaluation of Computerized Numerical Control (CNC) Machine Tools is an important step to realize condition-based maintenance. In this paper, the evaluation method that merges fuzzy grey clustering and combined weighting is proposed to determine the health status of CNC machine tools. The evaluation process is: Firstly, weights of relevant parameters of the key components of CNC machine tools are calculated and determined by using the entropy weight method and the analytic hierarchy process (AHP) respectively. Then, the two weights are combined by the combination weighting method, and the combination weights with subjective and objective significance are obtained. Then the grey clustering method is used to evaluate the health status of each key component of CNC machine tools. According to the evaluation results, the fuzzy evaluation matrix of machine tool health evaluation is created by the clustering coefficient of each key component of CNC machine tools. Then based on the matrix, the weights of each key component are calculated by entropy weight method and AHP, and the weights of each key component are obtained by the combination weighting method. Finally, the fuzzy comprehensive evaluation method is used to evaluate the health status of CNC machine tools, and the health status is divided into four grades. Finally, the health status of CNC machine tools is determined based on the principle of maximum degree of membership. At the end of the paper, the evaluation experiment is carried out on machining center, which shows the proposed approach is reasonable and usable.