Optimisation of machining parameters of train wheel for shrink-fit application by considering surface roughness and chip morphology parameters

dc.contributor.authorAkay, Mehmet Emin
dc.contributor.authorRidvanogullari, Anil
dc.date.accessioned2021-04-10T16:37:11Z
dc.date.available2021-04-10T16:37:11Z
dc.date.issued2020
dc.departmentMAUNen_US
dc.description.abstractThe train wheel is one of the elements most exposed to static and dynamic loads during the transport. For this reason, it is of great importance for the safety of rail transportation that the wheel-axle assembly is carried out securely through the shrink-fit method. The surface roughness of the inner diameter of the wheel must be within 0.8-3.2 mu m in order to provide the optimum shrink-fit. In this study, different depth-of-cut, feed rate and cutting speed parameters were considered in the turning process of ER8 class train wheel, and optimum machinability parameters were determined. In the experimental study, the Taguchi experimental design method, regression analysis and variance analysis (ANOVA) method were used. Experimental results were examined visually by using chip photographs and SEM images. According to the ANOVA results, it was determined that the most effective parameter is the feed rate with 93.78% on surface roughness in the turning of the train wheel. The SEM images derived from chips proved that the feed rate has strong correlation with surface roughness. Optimum machining parameters were determined as 1.5 mm depth of cut, 0.1 mm/rev feed rate and 250 rpm cutting speed. (c) 2020 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.description.sponsorshipKBU-BAP [KBU-BAP-17-YL-456]en_US
dc.description.sponsorshipThe authors would like to acknowledge the KBU-BAP office. This work was supported by KBU-BAP (Project ID number: KBU-BAP-17-YL-456).en_US
dc.identifier.doi10.1016/j.jestch.2020.06.013
dc.identifier.endpage1207en_US
dc.identifier.issn2215-0986
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-85089298599
dc.identifier.scopusqualityQ1
dc.identifier.startpage1194en_US
dc.identifier.urihttps://doi.org/10.1016/j.jestch.2020.06.013
dc.identifier.urihttps://hdl.handle.net/20.500.12639/2179
dc.identifier.volume23en_US
dc.identifier.wosWOS:000576840300010
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier - Division Reed Elsevier India Pvt Ltden_US
dc.relation.ispartofEngineering Science And Technology-An International Journal-Jestechen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectTrain wheelen_US
dc.subjectTaguchi methoden_US
dc.subjectSurface roughnessen_US
dc.subjectANOVAen_US
dc.subjectRegression analysisen_US
dc.titleOptimisation of machining parameters of train wheel for shrink-fit application by considering surface roughness and chip morphology parametersen_US
dc.typeArticle

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