Cutting trouble detection system based on quantitative comparison between predicted and measured cutting torques (1st report Cutting trouble detection for tool wear)

Abstract

This study aims to develop a monitoring system, which can automatically detect tool wear in end-milling operation. A feature of this system is the utilization of the predicted cutting torque for detecting the difference between normal and cutting trouble. The cutting torque predicted by a cutting force simulator is compared with the cutting torque measured and evaluated from the driving torque of a spindle motor. Because the dynamic change of the cutting torque can be predicted by the cutting force simulator as the reference cutting torque, it is possible to detect cutting trouble correctly without disturbance arise from the changes of the cutting conditions and the machining form at every moment. In the cutting simulator, this study uses the workpiece voxel model in order to calculate the uncut chip thickness for the estimation of the cutting force. For the tool wear detection, 200 % increase of the average cutting torque is set as the threshold to detect 300 μm flank wear. In an experimental milling of a workpiece with holes using a worn square end mill, it is confirmed that the increase of the average cutting torque can be identified clearly in both of stationary and transient milling situations. It was verified that the tool flank wear could be detected correctly even in the dynamic change of milling operation.

Keywords

• cutting trouble detection
• end milling
• cutting torque
• simulation
• monitoring