Health diagnosis of NC machine tool from user’s perspective

Article type: Research Article

Authors: Guan, Wei^{a; b; *} | Liu, Changjie^a

Affiliations: [a] School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, China | [b] Hudong Heavy Machinery Co., Ltd, Shanghai, China

Correspondence: [*] Corresponding author: Wei Guan, School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China. E-mail: 18601763242@163.com.

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.

Keywords: NC machine tool, PCA, fault detection, equipment management

DOI: 10.3233/JCM-226184

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 5, pp. 1477-1491, 2022