Surface roughness optimization in end milling using the multi objective genetic algorithm approach

In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Therefore, determining the optimum cutting levels to achieve the minimum surface roughness is important for it is economical and mechanical issues. This paper presents the optimization of machining para...

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Main Authors: Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Riza, Muhammad, Mohammad Yuhan, Suprianto
Format: Article
Language:English
English
Published: Trans Tech Publications Inc. 2012
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Online Access:http://irep.iium.edu.my/55357/1/10.1.1.971.7225.pdf
http://irep.iium.edu.my/55357/7/55357_Surface%20Roughness%20Optimization_SCOPUS.pdf
http://irep.iium.edu.my/55357/
https://www.scientific.net/AMR.576.103
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
English
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spelling my.iium.irep.553572017-04-04T02:06:46Z http://irep.iium.edu.my/55357/ Surface roughness optimization in end milling using the multi objective genetic algorithm approach Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Riza, Muhammad Mohammad Yuhan, Suprianto T Technology (General) In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Therefore, determining the optimum cutting levels to achieve the minimum surface roughness is important for it is economical and mechanical issues. This paper presents the optimization of machining parameters in end milling processes by integrating the genetic algorithm (GA) with the statistical approach. Two objectives have been considered, minimum arithmetic mean roughness (Ra) and minimum Root-mean-square roughness (Rq). The mathematical models for the surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed. Trans Tech Publications Inc. 2012 Article REM application/pdf en http://irep.iium.edu.my/55357/1/10.1.1.971.7225.pdf application/pdf en http://irep.iium.edu.my/55357/7/55357_Surface%20Roughness%20Optimization_SCOPUS.pdf Al Hazza, Muataz Hazza Faizi and Adesta, Erry Yulian Triblas and Riza, Muhammad and Mohammad Yuhan, Suprianto (2012) Surface roughness optimization in end milling using the multi objective genetic algorithm approach. Advanced Materials Research, 576. pp. 103-106. ISSN 1022-6680 https://www.scientific.net/AMR.576.103 10.4028/www.scientific.net/AMR.576.103
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic T Technology (General)
spellingShingle T Technology (General)
Al Hazza, Muataz Hazza Faizi
Adesta, Erry Yulian Triblas
Riza, Muhammad
Mohammad Yuhan, Suprianto
Surface roughness optimization in end milling using the multi objective genetic algorithm approach
description In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Therefore, determining the optimum cutting levels to achieve the minimum surface roughness is important for it is economical and mechanical issues. This paper presents the optimization of machining parameters in end milling processes by integrating the genetic algorithm (GA) with the statistical approach. Two objectives have been considered, minimum arithmetic mean roughness (Ra) and minimum Root-mean-square roughness (Rq). The mathematical models for the surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed.
format Article
author Al Hazza, Muataz Hazza Faizi
Adesta, Erry Yulian Triblas
Riza, Muhammad
Mohammad Yuhan, Suprianto
author_facet Al Hazza, Muataz Hazza Faizi
Adesta, Erry Yulian Triblas
Riza, Muhammad
Mohammad Yuhan, Suprianto
author_sort Al Hazza, Muataz Hazza Faizi
title Surface roughness optimization in end milling using the multi objective genetic algorithm approach
title_short Surface roughness optimization in end milling using the multi objective genetic algorithm approach
title_full Surface roughness optimization in end milling using the multi objective genetic algorithm approach
title_fullStr Surface roughness optimization in end milling using the multi objective genetic algorithm approach
title_full_unstemmed Surface roughness optimization in end milling using the multi objective genetic algorithm approach
title_sort surface roughness optimization in end milling using the multi objective genetic algorithm approach
publisher Trans Tech Publications Inc.
publishDate 2012
url http://irep.iium.edu.my/55357/1/10.1.1.971.7225.pdf
http://irep.iium.edu.my/55357/7/55357_Surface%20Roughness%20Optimization_SCOPUS.pdf
http://irep.iium.edu.my/55357/
https://www.scientific.net/AMR.576.103
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