A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization
Genetic algorithms; Optimization; Particle swarm optimization (PSO); Process control; Taguchi methods; Turning; Aisi 1045 steels; Cutting parameters; Experimental values; Genetic algorithm and particle swarm optimizations; Manufacturing industries; Optimization approach; Response surface methodology...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-227292023-05-29T14:11:52Z A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization Ahmad N. Janahiraman T.V. 56486827000 35198314400 Genetic algorithms; Optimization; Particle swarm optimization (PSO); Process control; Taguchi methods; Turning; Aisi 1045 steels; Cutting parameters; Experimental values; Genetic algorithm and particle swarm optimizations; Manufacturing industries; Optimization approach; Response surface methodology; Turning operations; Surface roughness AISI 1045 steel is one of the most widely used steel in the manufacturing industry. In order to have the best quality of turned AISI 1045 steel product, surface roughness is being considered as output parameter. The two purposes of this research are to model the surface roughness using response surface methodology and to compare the different types of optimization approaches in order to identify the optimum surface roughness with particular combination of cutting parameters in turning operation. The result obtained from this study showed that the values from RSMs' prediction are 99.3% similar to the experimental values. While, particle swarm optimization give the lowest surface roughness when compared to Taguchi method and genetic algorithm and it can optimize faster than genetic algorithm. � 2015 IEEE. Final 2023-05-29T06:11:52Z 2023-05-29T06:11:52Z 2016 Conference Paper 10.1109/SPC.2015.7473572 2-s2.0-85009069308 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009069308&doi=10.1109%2fSPC.2015.7473572&partnerID=40&md5=60776979124d14e8c4a77a70159ace2a https://irepository.uniten.edu.my/handle/123456789/22729 7473572 129 133 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Genetic algorithms; Optimization; Particle swarm optimization (PSO); Process control; Taguchi methods; Turning; Aisi 1045 steels; Cutting parameters; Experimental values; Genetic algorithm and particle swarm optimizations; Manufacturing industries; Optimization approach; Response surface methodology; Turning operations; Surface roughness |
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56486827000 |
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56486827000 Ahmad N. Janahiraman T.V. |
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Ahmad N. Janahiraman T.V. |
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Ahmad N. Janahiraman T.V. A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization |
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Ahmad N. |
title |
A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization |
title_short |
A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization |
title_full |
A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization |
title_fullStr |
A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization |
title_full_unstemmed |
A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization |
title_sort |
comparison on optimization of surface roughness in machining aisi 1045 steel using taguchi method, genetic algorithm and particle swarm optimization |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2023 |
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1806426171013857280 |
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13.211869 |