Affiliations: [a] College of Mechanical and Electrical Engineering, Hainan University, Haikou, China
| [b] Beijing Research Institute of Automation for Machinery Industry Co., LTD, Beijing, China
Correspondence:
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Corresponding author. Shihao Liu, College of Mechanical and Electrical Engineering, Hainan University, Haikou, China. E-mail: [email protected].
Abstract: In order to solve the problem of health evaluation of CNC machine tools, an evaluation method based on grey clustering analysis and fuzzy comprehensive evaluation was proposed. The health status grade of in-service CNC machine tools was divided, and the performance indicator system of CNC machine tools was constructed. On the above basis, the relative importance of each performance and its indicators were combined, and grey clustering analysis and fuzzy comprehensive evaluation was utilized to evaluate the health status of in-service CNC machine tools to determine their health grade. The proposed health status evaluation method was applied to evaluate the health level of an in-service gantry CNC machine that can be used for the machining propellers, and the results shown that the health status of the whole gantry CNC machine tool is healthy. The proposed evaluation method provides useful references for further in-depth research on the health status analysis and optimization of CNC machine tools.
Keywords: CNC machine tools, grey clustering, fuzzy comprehensive evaluation, health evaluation, green performance
