An improved time-varying stability analysis of micro milling considering tool wear

Micro-milling is widely used to process micro-parts and structures, which has the advantages of high material removal rate, high precision and high flexibility of applicable materials. The chatter in micro-milling process seriously reduces the machining efficiency and surface quality. The existing researches are focusing on a se-lection of appropriate process parameters to suppress the occurrence of chatter, while the influence of tool wear has rarely been considered. In this work, an improved time-varying stability analysis of micro milling considering tool wear was studied. A modified force model taking tool wear, bottom edge milling force, tool runout, and size effect into consideration was established. The dynamic forces due to regenerative undeformed chip thickness in both the shearing region and the transition region were investigated. A dynamic equation which combined the modified force model and the dynamic forces was developed and solved for stability analysis. Experiments on micro-milling of Ti-6Al-4 V titanium alloy with coated micro-milling tools, were carried out to verify the improved time-varying stability analysis model. The results showed that the modified force model had relatively high prediction accuracy, and the calculated stability lobe diagram (SLD) of micro-milling considering tool wear was verified. This work offers theoretical and technical guidance toward the improvement of chatter stability and the development of process online monitoring in micro-milling.

Automated summary

Micro-milling is widely used in processing micro-parts and structures, but the existence of chatter reduces efficiency and surface quality. This study focuses on the influence of tool wear on chatter stability using an improved time-varying stability analysis model. Experimental results validate the accuracy of the modified force model and the stability analysis considering tool wear, providing theoretical and technical guidance for improving chatter stability and developing online monitoring in micro-milling processes.