Title :
Monitoring of tool wear using artificial neural networks
Author :
Venkatesh, Kurapati ; Zhou, MengChu ; Caudill, Reggie
Author_Institution :
Center for Manuf. Syst., New Jersey Inst. of Technol., Newark, NJ, USA
fDate :
29 June-1 July 1994
Abstract :
An online scheme for tool wear monitoring using artificial neural networks (ANNs) has been proposed. Motivated by the fact that the tool wear at a given instance of time depends on the tool wear value at previous instance of time, memory was included in ANN. With this aim, an ANN without memory, an ANN with one phase memory, and an ANN with two are investigated in this study. The advantages and unique characteristics of the proposed tool wear modeling scheme with earlier methods of tool wear estimation are discussed.
Keywords :
computerised monitoring; machine tools; manufacturing data processing; neural nets; real-time systems; wear; machine tools; neural networks; online scheme; tool wear monitoring; Adaptive control; Artificial neural networks; Condition monitoring; Machine tools; Machining; Manufacturing systems; Surface finishing; Switches; Training data; Wearable sensors;
Conference_Titel :
American Control Conference, 1994
Print_ISBN :
0-7803-1783-1
DOI :
10.1109/ACC.1994.735022