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

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dc.contributor.author Altuğ, Mehmet
dc.contributor.author Erdem, Mehmet
dc.contributor.author Özay, Çetin
dc.contributor.author Bozkır, Oğuz
dc.date.accessioned 2019-10-03T06:39:05Z
dc.date.available 2019-10-03T06:39:05Z
dc.date.issued 2016
dc.identifier.citation Altug, M. Erdem, M. Ozay, C . Bozkir, O. (2016). Surface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networks. Cilt:58.Sayı:3. 189- 199 ss. tr_TR
dc.identifier.uri http://hdl.handle.net/11616/14459
dc.description.abstract The 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. tr_TR
dc.language.iso eng tr_TR
dc.publisher Carl hanser verlag, kolbergerstrasse 22, postfach 86 04 20, d-81679 munıch, germany tr_TR
dc.relation.isversionof 10.3139/120.110844 tr_TR
dc.rights info:eu-repo/semantics/restrictedAccess tr_TR
dc.subject Dıscharge machınıng wedm tr_TR
dc.subject multıobjectıve optımızatıon tr_TR
dc.subject mıcrostructural evolutıon tr_TR
dc.subject parametrıc optımızatıon tr_TR
dc.subject cuttıng parameters tr_TR
dc.subject tı-6al-4v alloy tr_TR
dc.subject edm parameters tr_TR
dc.subject tool steel tr_TR
dc.subject wıre tr_TR
dc.subject machınabılıty tr_TR
dc.title Surface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networks tr_TR
dc.type article tr_TR
dc.relation.journal Materıals testıng tr_TR
dc.contributor.department İnönü Üniversitesi tr_TR
dc.identifier.volume 58 tr_TR
dc.identifier.issue 3 tr_TR
dc.identifier.startpage 189 tr_TR
dc.identifier.endpage 199 tr_TR

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