204 Prediction of Cutting Force by Genetic Programming in Ball-end Milling
Koichiro NAKAZAWA, Koichi KIKKAWA, Yoshio Mizugaki
Abstract
Open-access reader
Koichiro NAKAZAWA, Koichi KIKKAWA, Yoshio Mizugaki
Abstract
Open-access reader
This paper describes the prediction of cutting force by Genetic Programming (GP) method in ball-nosed end milling. In recent years, the prediction methods of cutting force in flat end milling have been proposed. However, it is difficult to predict cutting force in ball-nosed end mill, because the shape of cutting edge is more complicated than Flat end mill, and it is need to take tool attitude into consideration. In this study, modeling of cutting force by GP in ball-nosed end milling is tried on the basis of in-process measurement data.
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This paper describes the prediction of cutting force by Genetic Programming (GP) method in ball-nosed end milling. In recent years, the prediction methods of cutting force in flat end milling have been proposed. However, it is difficult to predict cutting force in ball-nosed end mill, because the shape of cutting edge is more complicated than Flat end mill, and it is need to take tool attitude into consideration. In this study, modeling of cutting force by GP in ball-nosed end milling is tried on the basis of in-process measurement data.
Key concepts: End mill, End milling, Ball (mathematics), Genetic programming, Mechanical engineering, Ball mill, Mill, Enhanced Data Rates for GSM Evolution