Prediction of cutting forces and surface roughness using artificial neural network (ANN) and support vector regression (SVR) in turning 4140 steel

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dc.contributor.authorAsilturk, I.
dc.contributor.authorKahramanli, H.
dc.contributor.authorEl Mounayri, H.
dc.date.accessioned2020-03-26T18:31:05Z
dc.date.available2020-03-26T18:31:05Z
dc.date.issued2012
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn the present study, the prediction of cutting forces and surface roughness was carried out using neural networks and support vector regression (SVR) with six inputs, namely, three axis vibrations of the tool holder and cutting speed, feedrate and depth of cut. The data obtained by experimentation are used to construct predictive models. A feedforward backpropagation neural network and SVR have been selected for modelling. The coefficient of determination (R-2), mean absolute prediction error and root mean square error were calculated for each method, and these values served as a measure of prediction precision. We carried out comparison of the prediction accuracy of artificial neural networks and SVR. Comparison of the two models indicates that both models have successful performance. Experimental results are provided to confirm the effectiveness of this approach.en_US
dc.description.sponsorshipSelcuk UniversitySelcuk University; IUPUI; TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)en_US
dc.description.sponsorshipThe present study was supported by Scientific Research Projects Coordinators (BAP) of Selcuk University, IUPUI and TUBITAK.en_US
dc.identifier.doi10.1179/1743284712Y.0000000043en_US
dc.identifier.endpage986en_US
dc.identifier.issn0267-0836en_US
dc.identifier.issn1743-2847en_US
dc.identifier.issue8en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage980en_US
dc.identifier.urihttps://dx.doi.org/10.1179/1743284712Y.0000000043
dc.identifier.urihttps://hdl.handle.net/20.500.12395/28322
dc.identifier.volume28en_US
dc.identifier.wosWOS:000306070400014en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCIS LTDen_US
dc.relation.ispartofMATERIALS SCIENCE AND TECHNOLOGYen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectNeural networken_US
dc.subjectCNC turningen_US
dc.subjectSurface roughnessen_US
dc.subjectSVR prediction modelen_US
dc.titlePrediction of cutting forces and surface roughness using artificial neural network (ANN) and support vector regression (SVR) in turning 4140 steelen_US
dc.typeArticleen_US

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