Machining state monitoring in end milling based on comparison of monitored and predicted cutting torques

Abstract

To improve machining efficiency, it is necessary to know the machining status and optimize cutting conditions. Cutting force prediction is one method of determining the machining status. The instantaneous rigid force model is widely used and can be easily applied to cutting force prediction. However, this model requires six parameters called cutting coefficients, which have to be determined in advance through a preliminary experimental cutting test. Therefore, in this study, a new cutting force prediction method that does not require a cutting test is proposed to enable the practical understanding of the milling process in a factory setting. For this purpose, the conventional instantaneous rigid force model was revised based on the oblique cutting model and the orthogonal cutting theory to reduce the number of cutting parameters required for cutting force prediction. In the proposed model, only the shear angle is required for cutting force prediction. In practical situations, the shear angle can be identified immediately from the measured spindle motor torque, which can be monitored without any additional sensors at the start of milling operation, and the milling forces can then be predicted. In the proposed force model, the effect of tool runout can be expressed by considering the rotational radius deviation at each cutting edge. In addition, tool chipping can be detected by comparing the monitored and predicted torques. To validate the effectiveness of the proposed model, cutting experiments were conducted. The predicted force showed good agreement with the measured one. The similarity between the monitored and predicted torques was decreased by tool chipping. These results indicate that the in-process machining status can be understood and tool chipping can be detected practically without any experimental milling to determine the required parameters for prediction or any additional force sensors.

Keywords

• cutting force prediction
• instantaneous rigid force model
• oblique cutting model
• spindle motor torque
• tool runout
• sensorless
• tool chipping detection