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Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA

In this study, Simulated Annealing (SA) and Genetic Algorithm (GA) soft computing techniques are integrated to estimate optimal process parameters that lead to a minimum value of machining performance. Two integration systems are proposed, labeled as integrated SA-GA-type1 and integrated SA-GA-type2...

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Main Authors: Mohd. Zain, Azlan, Haron, Habibollah, Sharif, Safian
Format: Article
Published: Elsevier B.V. 2011
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/29551/
http://dx.doi.org/10.1016/j.asoc.2011.05.024
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spelling my.utm.295512019-04-25T01:15:24Z http://eprints.utm.my/id/eprint/29551/ Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA Mohd. Zain, Azlan Haron, Habibollah Sharif, Safian QA75 Electronic computers. Computer science In this study, Simulated Annealing (SA) and Genetic Algorithm (GA) soft computing techniques are integrated to estimate optimal process parameters that lead to a minimum value of machining performance. Two integration systems are proposed, labeled as integrated SA-GA-type1 and integrated SA-GA-type2. The approaches proposed in this study involve six modules, which are experimental data, regression modeling, SA optimization, GA optimization, integrated SA-GA-type1 optimization, and integrated SA-GA-type2 optimization. The objectives of the proposed integrated SA-GA-type1 and integrated SA-GA-type2 are to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, to estimate the optimal process parameters values that has to be within the range of the minimum and maximum process parameter values of experimental design, and to estimate the optimal solution of process parameters with a small number of iteration compared to the optimal solution of process parameters with SA and GA optimization. The process parameters and machining performance considered in this work deal with the real experimental data in the abrasive waterjet machining (AWJ) process. The results of this study showed that both of the proposed integration systems managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data. Elsevier B.V. 2011-12 Article PeerReviewed Mohd. Zain, Azlan and Haron, Habibollah and Sharif, Safian (2011) Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA. Applied Soft Computing Journal, 11 (8). pp. 5350-5359. ISSN 1568-4946 http://dx.doi.org/10.1016/j.asoc.2011.05.024 DOI:10.1016/j.asoc.2011.05.024
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mohd. Zain, Azlan
Haron, Habibollah
Sharif, Safian
Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA
description In this study, Simulated Annealing (SA) and Genetic Algorithm (GA) soft computing techniques are integrated to estimate optimal process parameters that lead to a minimum value of machining performance. Two integration systems are proposed, labeled as integrated SA-GA-type1 and integrated SA-GA-type2. The approaches proposed in this study involve six modules, which are experimental data, regression modeling, SA optimization, GA optimization, integrated SA-GA-type1 optimization, and integrated SA-GA-type2 optimization. The objectives of the proposed integrated SA-GA-type1 and integrated SA-GA-type2 are to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, to estimate the optimal process parameters values that has to be within the range of the minimum and maximum process parameter values of experimental design, and to estimate the optimal solution of process parameters with a small number of iteration compared to the optimal solution of process parameters with SA and GA optimization. The process parameters and machining performance considered in this work deal with the real experimental data in the abrasive waterjet machining (AWJ) process. The results of this study showed that both of the proposed integration systems managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data.
format Article
author Mohd. Zain, Azlan
Haron, Habibollah
Sharif, Safian
author_facet Mohd. Zain, Azlan
Haron, Habibollah
Sharif, Safian
author_sort Mohd. Zain, Azlan
title Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA
title_short Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA
title_full Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA
title_fullStr Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA
title_full_unstemmed Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA
title_sort optimization of process parameters in the abrasive waterjet machining using integrated sa-ga
publisher Elsevier B.V.
publishDate 2011
url http://eprints.utm.my/id/eprint/29551/
http://dx.doi.org/10.1016/j.asoc.2011.05.024
_version_ 1643648324831543296
score 13.211869

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