Surface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networks

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dc.authoridOZAY, Cetin/0000-0001-9958-519X
dc.authoridOZAY, Cetin/0000-0001-9958-519X
dc.authoridAltuğ, Mehmet/0000-0002-4745-9164
dc.authorwosidOZAY, Cetin/V-7034-2018
dc.authorwosidOZAY, Cetin/ABD-1847-2020
dc.authorwosidAltuğ, Mehmet/ABF-5670-2020
dc.contributor.authorAltug, Mehmet
dc.contributor.authorErdem, Mehmet
dc.contributor.authorOzay, Cetin
dc.contributor.authorBozkir, Oguz
dc.date.accessioned2024-08-04T20:41:47Z
dc.date.available2024-08-04T20:41:47Z
dc.date.issued2016
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe study examines how, using wire electrical discharge machining (WEDM), the microstructural, mechanical and conductivity characteristics of the titanium alloy Ti6Al4V are changed as a result of heat treatment and the effect they have on machinability. Scanning electron microscope (SEM), optical microscope and X-ray diffraction (XRD) examinations were performed to determine various characteristics and additionally related microhardness and conductivity measurements were conducted. L-18 Taquchi test design was performed with three levels and six different parameters to determine the effect of such alterations on its machinability using WEDM and post-processing surface roughness (Ra) values were determined. Micro-changes were ensured successfully by using heat treatments. Results obtained with the optimization technique of artificial neural network (ANN) presented minimum surface roughness. Values obtained by using response surface method along with this equation were completely comparable with those achieved in the experiments. The best surface roughness value was obtained from sample D which had a tempered martensite structure.en_US
dc.description.sponsorshipInonu University Scientific Researches Project [2012/165]; Rectorate of Inonu University, Malatya, Turkeyen_US
dc.description.sponsorshipThis study was supported by Inonu University Scientific Researches Projects with number 2012/165. We thank the Rectorate of Inonu University, Malatya, Turkey for its support.en_US
dc.identifier.doi10.3139/120.110844
dc.identifier.endpage199en_US
dc.identifier.issn0025-5300
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-84971639716en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage189en_US
dc.identifier.urihttps://doi.org/10.3139/120.110844
dc.identifier.urihttps://hdl.handle.net/11616/97354
dc.identifier.volume58en_US
dc.identifier.wosWOS:000371152100003en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherCarl Hanser Verlagen_US
dc.relation.ispartofMaterials Testingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectTi6Al4Ven_US
dc.subjectheat treatmenten_US
dc.subjectWEDMen_US
dc.subjectsurface roughnessen_US
dc.subjectartificial neural networken_US
dc.titleSurface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networksen_US
dc.typeArticleen_US

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