Analysis and Optimization of Milling Deformations of TC4 Alloy Thin-Walled Parts Based on Finite Element Simulations

Abstract

TC4 (DIN3.7164/5) alloy thin-walled parts are widely used in aviation and aerospace industries. However, due to their special structure, shape and poor machinability, large milling forces and milling deformation often occur in the milling process, which cannot guarantee the machining quality and accuracy. The milling processing parameters and milling geometric parameters have a significant impact on the milling force and the deformation, and optimization of the influence factors of milling deformations is important for milling quality. Considering that performing milling experiments under multiple conditions is often costly and time-consuming, this paper provides a finite-element-simulation-based method to study effects of the factors on the forces and deformations during milling thin-walled parts. Firstly, using ABAQUS, a finite element simulation model of the milling process of thin-walled parts is established. Additionally, an orthogonal experimental scheme is designed for optimization of the milling parameters, so as to determine the optimized experimental scheme, and then the optimized experimental scheme is verified to reduce the milling force and deformation by finite element simulations. The optimal parameters for a minimal milling force are a spindle speed of 2000 r/min, a feed rate per tooth of 0.04 mm/z, a milling depth of 1.6 mm, a milling width of 1 mm, a diameter of 6 mm, a rake angle of 20°, a tilt angle of 45°, and two teeth. Similarly, the optimal parameters for minimal node deformations are a spindle speed of 4800 r/min, a feed rate per tooth of 0.18 mm/z, a milling depth of 1 mm, a milling width of 1 mm, a diameter of 16 mm, a rake angle of 20°, a tilt angle of 40°, and four teeth. In addition, this paper uses an optimization algorithm to fit the empirical function with a certain practical value, which can provide a reference for the machining of TC4 titanium alloy. By doing so, we can optimize the milling parameters to obtain the desired machining quality and accuracy, while also saving on time and resources.