Multiple regression and ANN models for surface quality of cryogenically-treated AISI 52100 bearing steel

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dc.contributor.authorKara, Fuat
dc.contributor.authorÇiçek, Adem
dc.contributor.authorDemir, Halil
dc.date.accessioned2020-04-30T13:32:50Z
dc.date.available2020-04-30T13:32:50Z
dc.date.issued2013
dc.departmentDÜ, Teknoloji Fakültesi, Makine ve İmalat Mühendisliği Bölümüen_US
dc.description.abstractThis paper focuses on 2 different models, the multiple regression method and the artificial neural network (ANN), for predicting surface roughness (Ra). Experiments were conducted to measure surface roughness in the cylindrical grinding of AISI 52100 bearing steel which had been conventionally heat-treated and deep cryogenically treated (-145°C). In order to compare the effects of holding time at the deep cryogenic temperatures, 5 different holding times (12, 24, 36, 48 and 60 h) were employed to obtain the optimum Ra. The cylindrical grinding test results showed that optimum R a values were obtained on specimens cryogenically treated for 36 h. In addition, the prediction results showed that the ANN was superior to the multiple regression method in terms of prediction capability. Moreover, due to a higher determination coefficient (R2) and lower root-mean-square error (RMSE) and mean error percentage (MEP), the ANN was notably successful in predicting the Ra.en_US
dc.identifier.endpage584en_US
dc.identifier.issn1310-4772
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage570en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12684/451
dc.identifier.volume19en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofJournal of the Balkan Tribological Associationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectANN; Bearing steel; DCT; Surface qualityen_US
dc.titleMultiple regression and ANN models for surface quality of cryogenically-treated AISI 52100 bearing steelen_US
dc.typeArticleen_US

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