A Cutter Selection Method for 2 1/2-Axis Trochoidal Milling of the Pocket Based on Optimal Skeleton

The trochoidal toolpath is generated based on skeleton. However, several different skeletons can be extracted from one pocket. To improve the efficiency of trochoidal rough milling, a cutter selection method basing the optimal skeleton is proposed. Firstly, for a pocket, preliminary skeleton curves and nodes are extracted according to the principle of medial axis transformation. A skeleton extraction method is given that the skeleton is a combination of skeleton curves generated by randomly connecting the preliminary skeleton curves under nodes constraint. A set of skeletons can be obtained by repeatedly extracting skeleton. Furthermore, an optimization model based on the shortest machining time is established, and then the optimization model is solved by the Genetic Algorithm to determine the optimal tool combination and skeleton. The developed approach is validated in trochoidal milling a pocket for cutter selection. The experimental results show that the method can significantly improve the processing efficiency.

Automated summary

This study proposes a cutter selection method based on the optimal skeleton, extracting skeleton curves and nodes, and solving an optimization model using Genetic Algorithm to determine the optimal tool combination and skeleton. Experimental results in trochoidal milling show significant improvement in processing efficiency.