An efficient method to predict the chatter stability of titanium alloy thin-walled workpieces during high-speed milling by considering varying dynamic parameters.
Regeneration chatter in the vertical milling process of titanium alloy thin-walled workpieces seriously affects the material's machining surface quality and efficiency. Therefore, the prediction of stable cutting depths is a critical requirement for this milling process. However, the dynamic parameters of thin-walled workpieces change with material removal, which makes the prediction of milling stability to be very complicated. To solve this problem, this study firstly proposes a combination method of Kriging surrogate models and finite element simulations to construct the relationship between dynamic parameters and different milling positions. Secondly, the combination method uses both the prediction theory of regenerative chatter and Kriging models to calculate the minimum stable cutting depths in the milling process of titanium alloy thin-walled workpieces. At last, comparisons of the regenerative chatter theory results with experiment results indicate that the presented methods for the prediction of chatter stability are practical in avoiding chatter and improving manufacturing efficiency.