The health status of CNC machining tools plays a critical role in ensuring enterprise production safety and efficient equipment operation. Timely evaluation of equipment health status facilitates early fault detection and response. This paper proposes a comprehensive evaluation method: first, CNC machine tools is divided into eight major systems based on their characteristics; second, the importance of each system is analyzed through a judgment matrix to clarify the mapping relationships among equipment, systems, and factors, as well as the information sources of these factors; third, a whitening weight function is constructed using grey fuzzy clustering theory to establish an equipment evaluation system based on grey clustering; finally, the universality and effectiveness of this method are verified through a case study on CNC machine tools.

CNC Machine Tools,health condition evaluation,Grey theory