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Genetic Algorithm for optimizing cutting conditions of uncoated carbide (WC-Co) in milling machining operation

Mohd. Zain, Azlan and Haron, Habibollah and Sharif, Safian (2009) Genetic Algorithm for optimizing cutting conditions of uncoated carbide (WC-Co) in milling machining operation. In: 2009 Innovative Technologies in Intelligent Systems and Industrial Applications. IEEE, pp. 214-218. ISBN 978-1-4244-2886-1

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Official URL: http://dx.doi.org/10.1109/CITISIA.2009.5224209

Abstract

This paper presents the capability of Genetic Algorithm (GA) technique in obtaining the optimal machining parameters for uncoated carbide (WC-Co) tool to minimize the surface roughness (Re) value in milling process. The optimal machining parameters are generated using MATLAB Optimization toolbox. Regression technique is applied to create the surface roughness predicted equation to be taken as a fitness function of the GA. Result of this study indicated that the GA technique capable to estimate the optimal cutting conditions that yields to the minimum R(a) value. With high speed, low feed and high radial rake angle of the cutting conditions rate, GA technique recommended 0.17533 mu m as the best minimum predicted surface roughness value. Consequently, the GA technique has decreased the minimum surface roughness value of the experimental data by about 25.7%.

Item Type:Book Section
Additional Information:Conference: Conference on Innovative Technologies in Intelligent Systems and Industrial Applications Location: Kuala Lumpur, MALAYSIA Date: JUL 25-26, 2009
Uncontrolled Keywords:surface-roughness, prediction, optimization
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:14631
Deposited By: Ms Zalinda Shuratman
Deposited On:30 Sep 2011 15:16
Last Modified:30 Sep 2011 15:16

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