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

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 …

This paper reports the results of an investigative study into the application of perceptron-type
neural networks to tool-state classification during a metal-turning operation. The inputs to the …

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 …

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 …

Tool wear monitoring is the most difficult task in the area of tool condition monitoring for
metal-cutting manufacturing processes. The main objective is to improve the process …

In the paper different approaches are described for applying artificial neural network
techniques for modelling and monitoring of machining processes (turning, milling) by sensor …

Artificial neural networks have been shown to have a lot of potential as a means of
integrating multi-sensor signals for in-process real time monitoring of machining processes …