Prediction of Surface Roughness on CNC Turning based on Monitoring of Cutting Force and Cutting Temperature

This paper presents the surface roughness model which is proposed and developed to predict the surface roughness in the CNC turning of the carbon steel with the coated carbide tool under various cutting conditions by using the response surface analysis with the Box-Behnken design based on the experimental results. The in-process monitoring of the cutting force and the cutting temperature is utilized to analyze the relation between the surface roughness and the cutting condition. The tool dynamometer and the infrared pyrometer are employed and installed on the turret of CNC turning machine to measure the in-process cutting force and cutting temperature. The models of cutting force ratio and cutting temperature are also developed based on the experimental data. The optimum cutting condition is determined referring to the minimum surface roughness of the surface plot, which is obtained from the developed surface roughness model. The experimental results show that the higher cutting speed gives the better surface roughness due to the higher cutting temperature, however the tool life becomes shorter. The feed rate is the most significant factor which affects the surface roughness, while a small depth of cut helps to improve the surface roughness. The effectiveness of the surface roughness prediction model has been proved by utilizing an analysis of variance (ANOVA) at 95% confident level. Hence, the surface roughness can be predicted and obtained easily referring to the developed surface roughness model.