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Milling surface roughness prediction using evolutionary programming methods

Authors :
Çolak, Oğuz
Kurbanoğlu, Cahit
Kayacan, M. Cengiz
Source :
Materials & Design. Feb2007, Vol. 28 Issue 2, p657-666. 10p.
Publication Year :
2007

Abstract

Abstract: CNC milling has become one of the most competent, productive and flexible manufacturing methods, for complicated or sculptured surfaces. In order to design, optimize, built up to sophisticated, multi-axis milling centers, their expected manufacturing output is at least beneficial. Therefore data, such as the surface roughness, cutting parameters and dynamic cutting behavior are very helpful, especially when they are computationally produced, by artificial intelligent techniques. Predicting of surface roughness is very difficult using mathematical equations. In this study gene expression programming method is used for predicting surface roughness of milling surface with related to cutting parameters. Cutting speed, feed and depth of cut of end milling operations are collected for predicting surface roughness. End of the study a linear equation is predicted for surface roughness related to experimental study. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
02641275
Volume :
28
Issue :
2
Database :
Academic Search Index
Journal :
Materials & Design
Publication Type :
Academic Journal
Accession number :
22967529
Full Text :
https://doi.org/10.1016/j.matdes.2005.07.004