Prediction model and experimental study of surface roughness in micro-milling based on RSM

The influence of parameters used in micro-milling process on roughness of aluminum surface machined by a micro turn-milling NC machine developed by authors was analyzed based on RSM. The cutting parameters included cutting speed, feed per tooth, and depth of cut in the orthogonal design experiments central composite. A predictive model for surface roughness in micro-milling was established by RSM and the significances of the regression equation and regression factor coefficients were proved herein. It appears that the cutting speed has a significant effect on surface roughness and the next one is feed per tooth, the depth of cut has a little effect under the current experimental conditions. Analysis of variance was performed to evaluate the significance of regression. The fitting degree of the model is high. The parameters used in micro-milling can be selected to improve the quality of the surface based on the model of the paper.