Analysis of Cutter Wear Conditions in CNC Machine Tools with Wavelet Packet Transform - Göllü, Mehmet; Yılmaz, Alper; Bayrak, Gökay (Institute of Electrical and Electronics Engineers Inc., 2023)
Cutter wear and breakages in CNC machines lead to financial losses ranging from 5% to 10% of annual revenue for companies. Especially in the production of automotive and defense industry products, there are high expectations for precision and uninterrupted production within the scope of industry 4.0. Therefore, minimizing cutter breakages and monitoring their conditions in CNC machines is of great importance. In recent years, research using smart methods to solve these problems has increased. In this study, the current of the servo motor operating in a CNC machine is measured during its operation. The obtained current signals are decomposed using the wavelet packet transform (WPT), and an attempt is made to determine the status of the cutter on the relevant axis. The use of WPT is proposed to ensure high noise immunity. The developed system aims to provide operators with real-time notifications about the condition of cutters, enabling rapid intervention. Thus, the goal is to reduce additional costs resulting from cutter breakages and minimize downtime that negatively affects production continuity. The results obtained using WPT are expected to make a significant contribution to increasing efficiency and minimizing errors in the metalworking industry. © 2023 IEEE.
14th International Conference on Electrical and Electronics Engineering, ELECO 2023 -- 2023-11-30 through 2023-12-02 -- Virtual, Bursa -- 197135
Keywords: Computer control systems; Cutting tools; Losses; Machine tools; Metal working; Wavelet analysis; Wavelet transforms; Annual revenue; Automotives; CNC machine; CNC machine tools; Condition; Cutter wears; Defense Industry; Financial loss; Wavelet packet transforms; Wear condition; Wear of materials