Health diagnosis of NC machine tool from user’s perspective

Abstract

NC machines’ health monitoring is important for manufacturing enterprises. In this paper, we propose a scheme to do the monitoring and diagnosis mainly via collecting the internal data generated by the inside sensors of NC machine tool. Then these data are analyzed by Principal Component Analysis (PCA) method to determine the health status. The experimental results show that this method has certain applicability and effectiveness for the health diagnosis of NC machine tools, and is of good value for large manufacturing enterprises, of which core competitiveness resides on the sufficient operation of these machines.