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

被引：94

作者：

Basheer, Abeesh C. ^{[1
]}

Dabade, Uday A. ^{[1
]}

Joshi, Suhas S. ^{[1
]}

Bhanuprasad, V. V. ^{[3
]}

Gadre, V. M. ^{[2
]}

机构：

[1] Indian Inst Technol, Dept Mech Engn, Bombay 400076, Maharashtra, India

[2] Indian Inst Technol, Dept Elect Engn, Bombay 400076, Maharashtra, India

[3] Def Met Res Lab, Hyderabad 500058, Andhra Pradesh, India

来源：

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY | 2008年 / 197卷 / 1-3期

关键词：

metal matrix composites design of experiments; surface roughness; artificial neural networks;

D O I：

10.1016/j.jmatprotec.2007.04.121

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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 Elsevier B.V. All rights reserved.

引用

页码：439 / 444

页数：6

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