Structural optimization design and application of variable helix angle end mill based on improved genetic algorithm

Cutting tools are the teeth of industry, and the cutting performance and manufacturing quality of cutting tools are directly related to the dimensional accuracy, surface smoothness and machining efficiency of the workpiece. In this study, the evolution and optimization ability of the basic genetic algorithm is improved by using the penalty function and improved tournament selection method, etc., and the best plan for the optimal design of variable helix angle end mill structure is analyzed by combining the objective function and constraints of the structural optimal design of the end mill. An effective meta-analysis model has also been established to perform simulation analysis of the variable helix angle end mill structure. It is found that the optimal scheme proposed in this paper reduces the standard deviation values of the milling force spectral distribution of the end milling cutter in Al7075-T6 material and TC4 material by 17.21% and 19.09%. It was also found that the tool life of the optimized structure variable helix angle end mill was increased by 25.82%-44.56% compared to the original tool life, which achieved good application results. The method proposed in this paper has an important role to play in improving the precision of industrial product machining and manufacturing, and improving the machining efficiency.