Intelligent Monitoring of Surface Integrity and Cutter Degradation in High-speed Milling Processes

Abstract

In high-speed milling process, dynamic monitoring and detection of work-piece surface defects and cutter degradation is a very important and also an extremely difficult task. Due to the inconsistency and variability of cutter geometry/dimensions, the uncertainties of machine tool conditions, as well as the complexity of the cutting process itself, the modelling of cutting performance in high-speed milling process has remained a challenging issue for both academia and industry. This paper attempts to exploit a force-based approach to model the cutting performance and detect the surface integrity of high-valued work-pieces in high-speed milling process. Experiments on high-speed dry-milling of Titanium (Ti6Al4V) using ball-nose end mills were conducted to verify the proposed approach. Preliminary findings from the study have shown that the force-based modelling techniques proposed is able to establish the association between cutting force signals and the degradation of cutting performance and so as to eliminate surface defects of work-pieces.