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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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dc.citedby6
dc.contributor.authorAhmad N.en_US
dc.contributor.authorJanahiraman T.V.en_US
dc.contributor.authorid56486827000en_US
dc.contributor.authorid35198314400en_US
dc.date.accessioned2023-05-29T06:11:52Z
dc.date.available2023-05-29T06:11:52Z
dc.date.issued2016
dc.descriptionGenetic 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 roughnessen_US
dc.description.abstractAISI 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7473572
dc.identifier.doi10.1109/SPC.2015.7473572
dc.identifier.epage133
dc.identifier.scopus2-s2.0-85009069308
dc.identifier.spage129
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85009069308&doi=10.1109%2fSPC.2015.7473572&partnerID=40&md5=60776979124d14e8c4a77a70159ace2a
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22729
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015
dc.titleA comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimizationen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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