Modeling of surface roughness in precision machining of metal matrix composites using ANN

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 qua...

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Bibliographic Details
Published in:Journal of materials processing technology 2008-02, Vol.197 (1), p.439-444
Main Authors: Basheer, Abeesh C., Dabade, Uday A., Joshi, Suhas S., Bhanuprasad, V.V., Gadre, V.M.
Format: Article
Language:English
Subjects:
Artificial neural networks
Metal matrix composites design of experiments
Surface roughness
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Summary: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.
ISSN:0924-0136
DOI:10.1016/j.jmatprotec.2007.04.121