Model-based Tool Condition Monitoring for Ball-nose End Milling

Abstract

The primary aim of this study is to investigate model-based tool condition monitoring methods for ball-nose end milling targeting for sculptured surface machining applications. The approach is based on a proposed tool wear modelling framework comprising of three parts: cutting force simulation, discrete wavelet analysis of cutting force sensor signal, and feature-based tool wear estimation model. In sculptured surface machining, the cutting engagement is not fixed. Most reported or conventional tool condition monitoring methods are based on thresholds or features derived from sensor signals captured from end milling with constant cutting engagement, which are therefore not suitable to be used directly for monitoring sculptured surface machining. There is a potential to apply the conventional tool condition monitoring methods in sculptured surface machining by accounting for the varying cutting engagement through the use of developed machining models. The experimental results showed that the model-based approach is feasible and effective.