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
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/55357/ http://irep.iium.edu.my/55357/ http://irep.iium.edu.my/55357/ 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

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recordtype	eprints
spelling	iium-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 PeerReviewed 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
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
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/ http://irep.iium.edu.my/55357/ http://irep.iium.edu.my/55357/ 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
first_indexed	2023-09-18T21:18:15Z
last_indexed	2023-09-18T21:18:15Z
_version_	1777411707580186624

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

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