The adaptability of a tool wear monitoring system under changing cutting conditions

The process of metal cutting is a complex phenomenon that has been research ed for many years but the aim of practical cutting tool condition monitorin g has yet to be achieved. Previous work by the current authors using two ne ural networks (to classify acquired data) moderated by an Expert System (ba sed on Taylor's tool life equation) has shown that it is possible to accura tely monitor tool wear with a single machine/tool/material/cutting conditio n combination and to identify any inconsistencies between the predictions o f the neural networks and engineering practice. This paper investigates the effects that minor inconsistencies in cutting conditions might have on suc h a system by determining the 'zone of influence' of this working system by systematically varying the cutting conditions whilst keeping all other var iables fixed. The investigation has found that the zone of influence is sma ll but usable, and an approach to the utilisation of the system in a machin e shop is suggested. (C) 2000 Academic Press.