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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/7411

Title: Modeling of surface roughness in precision machining of metal matrix composites using ANN
Authors: BASHEER, AC
DABADE, UA
JOSHI, SS
BHANUPRASAD, VV
GADRE, VM
Issue Date: 2008
Publisher: ELSEVIER SCIENCE SA
Citation: JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 197(1-3), 439-444
Abstract: Characteristics of machined surfaces are known to influence the product performance significantly since they are directly linked to the ability of the material to withstand stresses, temperature, friction and corrosion. This paper presents an experimental work on the analysis of machined surface quality on Al/SiCp composites leading to an artificial neural network-based (ANN) model to predict the surface roughness. The predicted roughness of machined surfaces based on the ANN model was found to be in very good agreement with the unexposed experimental data set. (c) 2007
URI: http://dx.doi.org/10.1016/j.jmatprotec.2007.04.121
http://dspace.library.iitb.ac.in/xmlui/handle/10054/7411
http://hdl.handle.net/10054/7411
ISSN: 0924-0136
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