Journal
NEURAL COMPUTING & APPLICATIONS
Volume 14, Issue 4, Pages 319-324Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-005-0468-x
Keywords
turning; surface roughness; artificial neural network
Categories
Ask authors/readers for more resources
In this work, a back propagation neural network model has been developed for the prediction of surface roughness in turning operation. A large number of experiments were performed on mild steel work-pieces using high speed steel as the cutting tool. Process parametric conditions including speed, feed, depth of cut, and the measured parameters such as feed and the cutting forces are used as inputs to the neural network model. Roughness of the machined surface corresponding to these conditions is the output of the neural network. The convergence of the mean square error both in training and testing came out very well. The performance of the trained neural network has been tested with experimental data, and found to be in good agreement.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available