Abstract
This paper integrates an in-process monitoring of tool wear with a quality control of roughness and roundness of machined parts in CNC turning, which are the critical parameters. The Daubechies wavelet transform has been applied to decompose the dynamic cutting forces in order to classify the signals of the tool wear, the average surface roughness, the surface roughness, and the roundness. The decomposed cutting forces are normalized to predict those parameters regardless of cutting conditions by taking the ratio of decomposed cutting forces. Firstly, the ratio of average variance of decomposed feed force to that of decomposed main force is proposed to estimate the tool wear. Secondly, the areas of those decomposed feed force and decomposed main force have been proposed and taken into the ratio to forecast the average surface roughness and the surface roughness concurrently. Lastly, the roundness error is calculated simultaneously by utilizing the ratio of average variance of decomposed redial force to that of decomposed feed force. The exponential function is adopted to represent the relations of the tool wear, the average surface roughness, the surface roughness, the roundness, and all proposed ratios of decomposed cutting forces, respectively. The new cutting tests are conducted to verify all obtained models. The experimentally obtained results showed that the tool wear declines as the ratio of average variance of decomposed feed force to that of decomposed main force increases. The average surface roughness and the surface roughness tend to decrease while the ratio of decomposed feed force to decomposed main force progresses. On the other hand, the roundness error becomes larger when the ratio of average variance of decomposed redial force to that of decomposed feed force escalates. It is concluded that the tool wear, the average surface roughness, the surface roughness, and the roundness can be monitored and controlled at the same time during the in-process CNC turning, which has never been done and developed before. The highest benefit of the proposed system can enhance the quality of machined parts and lead to the higher productivity.