Prediction of surface roughness in ball-end milling process by utilizing dynamic cutting force ratio

Abstract

The aim of this research is to propose the practical model to predict the in-process surface roughness during the ball-end milling process by utilizing the dynamic cutting force ratio. The proposed model is developed based on the experimentally obtained results by employing the exponential function with five factors of the spindle speed, the feed rate, the tool diameter, the depth of cut, and the dynamic cutting force ratio. The experimentally obtained results showed that the frequency of the dynamic cutting force corresponds with the frequency of the surface roughness profile in the frequency domain. Hence, the dimensionless dynamic cutting force ratio is proposed regardless of the cutting conditions to predict the in-process surface roughness by taking the ratio of the area of the dynamic cutting force in X axis to that in Z axis. The multiple regression analysis is adopted to calculate the regression coefficients at 95 % confident level. The experimentally obtained model has been verified by using the new cutting conditions. It is understood that the developed surface roughness model can be used to predict the in-process surface roughness with the high accuracy of 92.82 % for the average surface roughness and 91.54 % for the surface roughness.