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Computational inteligence in optimization of machining operation parameters of ST-37 steel

Optimal selection of cutting parameters is one of the significant issues in achieving high quality machining. In this study, a method for the selection of optimal cutting parameters during lathe operation is presented. The present study focuses on multiple-performance optimization on machining chara...

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Main Authors: Golshan, Abolfazl, Ghodsiyeh, Danial, Gohari, Soheil, Ayob, Amran, Baharudin, B. T. Hang Tuah
Format: Article
Language:English
Published: Trans Tech Publications 2013
Online Access:http://psasir.upm.edu.my/id/eprint/28735/1/Computational%20inteligence%20in%20optimization%20of%20machining%20operation%20parameters%20of%20ST-37%20steel.pdf
http://psasir.upm.edu.my/id/eprint/28735/
http://www.scientific.net/AMM.248.456
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spelling my.upm.eprints.287352016-02-12T02:21:59Z http://psasir.upm.edu.my/id/eprint/28735/ Computational inteligence in optimization of machining operation parameters of ST-37 steel Golshan, Abolfazl Ghodsiyeh, Danial Gohari, Soheil Ayob, Amran Baharudin, B. T. Hang Tuah Optimal selection of cutting parameters is one of the significant issues in achieving high quality machining. In this study, a method for the selection of optimal cutting parameters during lathe operation is presented. The present study focuses on multiple-performance optimization on machining characteristics of St-37 steel. The cutting parameters used in this experimental study include cutting speed, feed rate, depth of cut and rake angle. Two output parameters, namely, surface roughness and tool life are considered as process performance. A statistical model based on linear polynomial equations is developed to describe different responses. For optimal conditions, the Non-dominated Sorting Genetic Algorithm (NSGA) is employed in achieving appropriate models. The optimization procedure shows that the proposed method has a high performance in problem-solving. Trans Tech Publications 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/28735/1/Computational%20inteligence%20in%20optimization%20of%20machining%20operation%20parameters%20of%20ST-37%20steel.pdf Golshan, Abolfazl and Ghodsiyeh, Danial and Gohari, Soheil and Ayob, Amran and Baharudin, B. T. Hang Tuah (2013) Computational inteligence in optimization of machining operation parameters of ST-37 steel. Applied Mechanics and Materials, 248. pp. 456-461. ISSN 1660-9336; ESSN: 1662-7482 http://www.scientific.net/AMM.248.456 10.4028/www.scientific.net/AMM.248.456
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Optimal selection of cutting parameters is one of the significant issues in achieving high quality machining. In this study, a method for the selection of optimal cutting parameters during lathe operation is presented. The present study focuses on multiple-performance optimization on machining characteristics of St-37 steel. The cutting parameters used in this experimental study include cutting speed, feed rate, depth of cut and rake angle. Two output parameters, namely, surface roughness and tool life are considered as process performance. A statistical model based on linear polynomial equations is developed to describe different responses. For optimal conditions, the Non-dominated Sorting Genetic Algorithm (NSGA) is employed in achieving appropriate models. The optimization procedure shows that the proposed method has a high performance in problem-solving.
format Article
author Golshan, Abolfazl
Ghodsiyeh, Danial
Gohari, Soheil
Ayob, Amran
Baharudin, B. T. Hang Tuah
spellingShingle Golshan, Abolfazl
Ghodsiyeh, Danial
Gohari, Soheil
Ayob, Amran
Baharudin, B. T. Hang Tuah
Computational inteligence in optimization of machining operation parameters of ST-37 steel
author_facet Golshan, Abolfazl
Ghodsiyeh, Danial
Gohari, Soheil
Ayob, Amran
Baharudin, B. T. Hang Tuah
author_sort Golshan, Abolfazl
title Computational inteligence in optimization of machining operation parameters of ST-37 steel
title_short Computational inteligence in optimization of machining operation parameters of ST-37 steel
title_full Computational inteligence in optimization of machining operation parameters of ST-37 steel
title_fullStr Computational inteligence in optimization of machining operation parameters of ST-37 steel
title_full_unstemmed Computational inteligence in optimization of machining operation parameters of ST-37 steel
title_sort computational inteligence in optimization of machining operation parameters of st-37 steel
publisher Trans Tech Publications
publishDate 2013
url http://psasir.upm.edu.my/id/eprint/28735/1/Computational%20inteligence%20in%20optimization%20of%20machining%20operation%20parameters%20of%20ST-37%20steel.pdf
http://psasir.upm.edu.my/id/eprint/28735/
http://www.scientific.net/AMM.248.456
_version_ 1643829552952115200
score 13.211869

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