In this study, we proposed a methodology for predicting tool wear in the turning process using the SVR model. This model maintains stable performance even in small-scale data environments and demonstrates robust characteristics against outliers. We detected changes in machining performance caused by tool wear through an AE sensor and accelerometer. Features were extracted from the acquired sensor signals and utilized in the machine learning model. Prior to training, the extracted features underwent a preliminary screening process based on distance correlation. By optimizing the feature combination using the RFECV algorithm, we achieved a prediction accuracy of R² = 0.95. The analysis revealed that key features influencing the tool wear prediction model included several significant variables. Additionally, we found that evaluating feature importance allowed for more efficient model improvement. Overall, when developing a tool wear prediction model for cutting, it is crucial to utilize various sensor signals, extract features in both the time and frequency domains, and optimize the combination of those features.

Ultra precision grinding technology has been developed from the refinement of the abrasive, the development of high stiffness equipment and grinding skill. The conventional wafering process which consists of lapping, etching, 1st, 2nd and 3rd polishing has been changed to the new process which consists of precision surface grinding, final polishing and post cleaning. Especially, the ultra precision grinding of wafer improves the flatness of wafer and the efficiency of production. Furthermore, it has been not only used in bare wafer grinding, but also applied to wafer back grinding and SOI wafer grinding. This paper focuses on the flatness of the ground wafer. Generally, the ground wafer has concave profile because of the difference of wheel path density, grinding temperature and elastic deformation of the equipment. Wafer tilting is applied to avoid non-uniform material removal. Through the geometric analysis of wafer grinding process, the profile of the ground wafer is predicted by the development of profile simulator.