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Modeling and optimization of machining process in discontinuously reinforced aluminium matrix composites

DSpace at IIT Bombay

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Title Modeling and optimization of machining process in discontinuously reinforced aluminium matrix composites
 
Creator PENDSE, DM
JOSHI, SS
 
Subject neural-networks
wear
alloy
art
machining
modeling
composites
surface finish
artificial neural networks (ann)
 
Description This article presents development of an Artificial Neural Networks (ANN) based model for the prediction of surface roughness during machining of composite material using Back Propagation algorithm. Statistically designed experiments based on Taguchi method were carried out on machining of Al/SiCp composite material. The experimentation helped generate a knowledge base for the ANN system and understand the relative importance of process, tool and work material dependent parameters on the roughness of surface generated during machining. The ANN model trained using the experimental data was found to predict the surface roughness with fair accuracy. An optimization approach was also proposed to obtain optimal cutting conditions that yield the desired surface roughness while maximizing the metal removal rate.
 
Publisher MARCEL DEKKER INC
 
Date 2011-08-18T10:43:50Z
2011-12-26T12:55:42Z
2011-12-27T05:42:07Z
2011-08-18T10:43:50Z
2011-12-26T12:55:42Z
2011-12-27T05:42:07Z
2004
 
Type Article
 
Identifier MACHINING SCIENCE AND TECHNOLOGY, 8(1), 85-102
1091-0344
http://dx.doi.org/10.1081/MST-120034242
http://dspace.library.iitb.ac.in/xmlui/handle/10054/9983
http://hdl.handle.net/10054/9983
 
Language en