This thesis gives an account of an investigative study to develop a modular Tool Condition
Monitoring System (TCMS) for metal cutting operations (turning in particular) through the …

Implementation of neural networks to integrate sensor signals in the cutting tool condition
monitoring (TCM) problem has been widely pursued, but most of these methods have either …

This paper outlines a neural networks based modular tool condition monitoring system for
cutting tool-state classification. Test cuts were conducted on EN24 alloy steel using P15 and …

The process of metal cutting is a complex phenomenon that has been researched for many
years but the aim of practical cutting tool condition monitoring has yet to be achieved …

A wide range of cutting tool monitoring techniques have been proposed and developed in
the last decade, but only a few have found industrial applications, and a truly universally …

This paper describes results of the application of feed-forward Multi-Layer Perceptron (MLP)
neural networks for cutting tool state identification in a metal turning operation. Test cuts …

This paper describes preliminary results of the application of feedforward multilayer
perceptron (MLP) neural networks for cutting tool state identification in a metal turning …

The need to monitor tool wear is crucial, particularly in advanced manufacturing industries,
as it aims to maximise the lifespan of the cutting tool whilst guaranteeing the quality of …

Multiple sensors are used in this work to provide complementary information about the
process and this helps to improve the confidence factor of the resulting diagnostics. The …

The potential application of neural networks in manufacturing scenarios is increasingly
becoming feasible. Typical of such manufacturing scenario is the integration of metal cutting …