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