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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 628Modeling Milling Process Using Artificial Neural...

Modeling Milling Process Using Artificial Neural Network

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Abstract:

Machining processes, such as milling, are considered to be too complex to be modeled accurately by using analytical or even numeric means due to involvement of various control parameters, some of them highly vague and imprecise. Such situation calls for application of nonconventional methods for modeling the responses of interest with acceptable degree of accuracy. In this work, a computational intelligence tool, possessing quick learning ability, has been used for modeling and predicting tool’s flank wear and workpiece surface roughness in milling of cold work tool steel. Six numeric and two categorical input parameters were used in the artificial neural network model. 116 data sets were used for training the network, while 13 were used for testing. Both the responses were modeled with acceptable degree of accuracy.

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Periodical:

Advanced Materials Research (Volume 628)

Pages:

128-134

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.628.128

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Online since:

December 2012

Authors:

Asif Iqbal

Keywords:

AISI D2, Back-Propagation, End Mill, Surface Roughness (SR), Tool Wear, Training

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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