Modeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression method

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dc.contributor.authorAsilturk, Ilhan
dc.contributor.authorCunkas, Mehmet
dc.date.accessioned2020-03-26T18:15:18Z
dc.date.available2020-03-26T18:15:18Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractMachine parts during their useful life are significantly influenced by surface roughness quality. The machining process is more complex, and therefore, it is very hard to develop a comprehensive model involving all cutting parameters. In this study, the surface roughness is measured during turning at different cutting parameters such as speed, feed, and depth of cut. Full factorial experimental design is implemented to increase the confidence limit and reliability of the experimental data. Artificial neural networks (ANN) and multiple regression approaches are used to model the surface roughness of AISI 1040 steel. Multiple regression and neural network-based models are compared using statistical methods. It is clearly seen that the proposed models are capable of prediction of the surface roughness. The ANN model estimates the surface roughness with high accuracy compared to the multiple regression model. (C) 2010 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.eswa.2010.11.041en_US
dc.identifier.endpage5832en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue5en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage5826en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2010.11.041
dc.identifier.urihttps://hdl.handle.net/20.500.12395/26650
dc.identifier.volume38en_US
dc.identifier.wosWOS:000287419900132en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectPredictive modelingen_US
dc.subjectTurning operationsen_US
dc.subjectArtificial neural networksen_US
dc.subjectSurface roughnessen_US
dc.titleModeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression methoden_US
dc.typeArticleen_US

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