Extrusion load prediction of gear-like profile for different die geometries using ANN and FEM with experimental verification

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dc.authoridAYER, ONDER/0000-0001-8970-145X
dc.authoridAYER, ONDER/0000-0001-8970-145X
dc.authorwosidBingöl, Sedat/GSE-0879-2022
dc.authorwosidAYER, ONDER/HGD-5388-2022
dc.authorwosidAYER, ONDER/ABA-3901-2020
dc.contributor.authorBingol, Sedat
dc.contributor.authorAyer, Onder
dc.contributor.authorAltinbalik, Tahir
dc.date.accessioned2024-06-12T11:02:32Z
dc.date.available2024-06-12T11:02:32Z
dc.date.issued2015
dc.departmentTrakya Üniversitesien_US
dc.description.abstractThis paper deals with the extrusion of gear-like profiles and uses of finite element method (FEM) and artificial neural network (ANN) to predict the extrusion load. In the study, gear-like components has been manufactured by forward extrusion for the AA1070 aluminum alloy and the process was simulated by using a DEFORM-3D software package to establish a database in order to provide the data for ANN modeling. Serious experiments were performed for only one die set and four teeth gear profile to obtain data for comparing with DEFORM-3D results. After verifying a highly appropriate FEM simulation with the experiment at the same conditions, Results were enhanced for different die lengths, extrusion ratios, and two extra teeth number as three and six using FEM simulations. Subsequently, the data from the performed FEM simulations were submitted for the best obtained ANN model. Finally, a good agreement between FE-simulated and ANN-predicted results was obtained. The proposed ANN model is found to be useful in predicting the forming load of the different die set variations based on the reliable test data.en_US
dc.description.sponsorshipTrakya University Scientific Research Projects Department [2008-126]en_US
dc.description.sponsorshipThis study is funded by Trakya University Scientific Research Projects Department with project number 2008-126. A commercial FEM code DEFORM-3D v10.2 which developed by Scientific Forming Technology Corporation (SFTC)(R) was used for simulations. Authors wish to thank Trakya University for the support of DEFORM-3D simulations under the license of SFTC (R).en_US
dc.identifier.doi10.1007/s00170-014-6328-z
dc.identifier.endpage992en_US
dc.identifier.issn0268-3768
dc.identifier.issn1433-3015
dc.identifier.issue5-8en_US
dc.identifier.scopus2-s2.0-84921985152en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage983en_US
dc.identifier.urihttps://doi.org/10.1007/s00170-014-6328-z
dc.identifier.urihttps://hdl.handle.net/20.500.14551/21311
dc.identifier.volume76en_US
dc.identifier.wosWOS:000348307500020en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofInternational Journal Of Advanced Manufacturing Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGear Formingen_US
dc.subjectFinite Element Methoden_US
dc.subjectArtificial Neural Networken_US
dc.subjectExtrusionen_US
dc.subjectAluminumen_US
dc.subjectArtificial Neural-Networksen_US
dc.subjectUpper-Bound Solutionsen_US
dc.subjectDeformation-Behavioren_US
dc.subjectCold-Extrusionen_US
dc.subjectFinite-Elementen_US
dc.subjectStrainen_US
dc.subjectTemperatureen_US
dc.subjectAluminumen_US
dc.subjectEvaluateen_US
dc.subjectBilletsen_US
dc.titleExtrusion load prediction of gear-like profile for different die geometries using ANN and FEM with experimental verificationen_US
dc.typeArticleen_US

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