Surface Roughness Prediction in Turning of Free Machining Steel 1215 by Artificial Neural Network

Abstract:

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Surface roughness is a significant aspect of the surface integrity concept. It is efficient to predict the surface roughness in advance by a prediction model. In this study, artificial neural network is used to model the surface roughness in turning of free machining steel 1215. The inputs considered in the prediction ANN model were cutting speed, feed rate and depth of cut, and the output was Ra. Several feed-forward neural networks with different architectures were compared in terms of prediction accuracy, and then the best prediction model, a 3-4-1-1 ANN was capable of predicting Ra with a mean squared error 5.46%, was presented.

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Edited by:

Chengyong Wang, Ning He, Ming Chen and Chuanzhen Huang

Pages:

535-541

DOI:

10.4028/www.scientific.net/AMR.188.535

Citation:

X. J. Cai et al., "Surface Roughness Prediction in Turning of Free Machining Steel 1215 by Artificial Neural Network", Advanced Materials Research, Vol. 188, pp. 535-541, 2011

Online since:

March 2011

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$35.00

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