Surface roughness of Ti6AI4V after heat treatment evaluated by artificial neural networks

dc.contributor.authorAltu?, Mehmet
dc.contributor.authorErdem, Mehmet
dc.contributor.authorOzay, Cetin
dc.contributor.authorBozkir, Oguz
dc.date.accessioned2026-08-12T16:10:14Z
dc.date.issued2016
dc.departmentFırat Üniversitesi
dc.description.abstractThe study examines how, using wire electrical discharge machining (WEDM), the microstructural, mechanical and conductivity characteristics of the titanium alloy T16A14V 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. L18 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. © Carl Hanser Verlag, München.
dc.identifier.doi10.3139/120.110844
dc.identifier.endpage199
dc.identifier.issn0025-5300
dc.identifier.issue3
dc.identifier.scopus2-s2.0-84971639716
dc.identifier.scopusqualityQ2
dc.identifier.startpage189
dc.identifier.urihttps://doi.org/10.3139/120.110844
dc.identifier.urihttps://hdl.handle.net/11508/41831
dc.identifier.volume58
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherCarl Hanser Verlag
dc.relation.ispartofMaterialpruefung/Materials Testing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectArtificial neural network; Heat treatment; Surface roughness; T16A14V; WEDM
dc.titleSurface roughness of Ti6AI4V after heat treatment evaluated by artificial neural networks
dc.typeArticle

Dosyalar