DocumentCode :
296037
Title :
Artificial neural networks for force and power predictions in oblique cutting
Author :
Karri, V. ; Talhami, H.
Author_Institution :
Dept. Mech. Eng., Tasmania Univ., Hobart, Tas., Australia
Volume :
1
fYear :
1995
fDate :
Nov/Dec 1995
Firstpage :
470
Abstract :
The importance of oblique cutting as a representative for many practical machining operations is discussed. A few of the existing oblique cutting models and their deficiencies are discussed from a predictive point of view. A neural network architecture is developed to predict the forces and power in single edged oblique cutting operation. Experiments are carried out over a comprehensive range of cutting conditions to verify the predictive capability of the neural network model. The force prediction model using neural network is extensively tested and compared with experimental results using statistical routines
Keywords :
backpropagation; cutting; machine tools; machining; multilayer perceptrons; artificial neural networks; force predictions; machining operations; neural network architecture; oblique cutting; power predictions; predictive capability; statistical routines; Artificial neural networks; Computer aided manufacturing; Flexible manufacturing systems; Intelligent networks; Machine tools; Machining; Manufacturing industries; Neural networks; Predictive models; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.488222
Filename :
488222
Link To Document :
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