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A study on regression model using response surface methodology

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dc.citedby13
dc.contributor.authorNooraziah A.en_US
dc.contributor.authorTiagrajah V.J.en_US
dc.contributor.authorid55263605500en_US
dc.contributor.authorid35198314400en_US
dc.date.accessioned2023-05-16T02:46:37Z
dc.date.available2023-05-16T02:46:37Z
dc.date.issued2014
dc.description.abstractResponse Surface Methodology (RSM) mostly employs statistical regression method as it is practical, economical and relatively easy to use. The first and second order polynomial equation was developed using RSM. This polynomial model usually refers as a regression model. In this research, the objective is to find the best response surface method to model three factors and three levels parameters in machining. From the study, the Box-Behnken Design can develop a good regression model rather than Central Composite Design or Full Factorial Design. While, the second order regression model has proved to be more effective in predicting the performance of the given data set. © (2014) Trans Tech Publications, Switzerland.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.4028/www.scientific.net/AMM.666.235
dc.identifier.epage239
dc.identifier.scopus2-s2.0-84921637530
dc.identifier.spage235
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84921637530&doi=10.4028%2fwww.scientific.net%2fAMM.666.235&partnerID=40&md5=78c77f5b303629ba072c3c6ca47ace68
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22006
dc.identifier.volume666
dc.publisherTrans Tech Publications Ltden_US
dc.sourceScopus
dc.sourcetitleApplied Mechanics and Materials
dc.titleA study on regression model using response surface methodologyen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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