Tool path regeneration in five-axis flank milling for ruled surface based on error distribution

Abstract

Five-axis flank milling is widely used in the field of aerospace and automotive industry. However, the accurate model between variety conditions of machining and the errors is difficult to establish directly. It is urgent to obtain a tool path for reducing the errors of the parts. Herein, a tool path regeneration method is proposed for five-axis flank milling of ruled surface according to the actual error distribution. The method contains three steps: First, the errors at the middle of the straight generatrix on the machined surface are calculated according to error distribution, and the corresponding normal vectors are obtained by geometric calculation. Second, multi-peaks Gaussian fitting method is utilized to make connections between parameters in the original tool path and error distribution. Finally, the regenerative tool path is obtained by offsetting original tool path. Machining experiments are performed to test the effectiveness of the proposed tool path regeneration method. The error distribution after tool path regeneration shows that the average error reduces 92.32%, with the surface roughness staying constant. Results show that the proposed tool path regeneration method is effective to improve the accuracy for five-axis flank milling.