Prediction and Optimization of Surface Roughness in Ball Burnishing Process Using Response Surface Methodology

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dc.authoridTR105386en_US
dc.authoridTR16418en_US
dc.contributor.authorSagbas, Aysun
dc.contributor.authorKahraman, Funda
dc.date.accessioned2015-04-07T13:41:09Z
dc.date.available2015-04-07T13:41:09Z
dc.date.issued2009
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractIn this study, a regression model was developed to predict surface roughness in burnishing process of 7178 aluminum alloy by using Response Surface Methodology (RSM). In the development of predictive models, burnishing force, number of passes, feed rate and burnishing speed were considered as model variables, surface roughness were considered as a response variable. The statistical analysis showed that, burnishing force and number of passes have the most significant effect on surface roughness. After building the regression model, a numerical optimization technique using desirability functions was carried out to minimize the surface roughness. The lowest value of surface roughness (0.469 //m) is obtained at a burnishing force of 10 N, a feed rate of 0.30 mm/rev and a burnishing speed of 80 m/min with two passes of the burnishing tool.en_US
dc.identifier.citationJournal of Science and Technology 3 (1), 2009, 140 - 148tr_TR
dc.identifier.issn1307-3818
dc.language.isoenen_US
dc.publisherBeykent Üniversitesitr_TR
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.subjectBurnishing processtr_TR
dc.subjectSurface roughnesstr_TR
dc.subjectOptimizationtr_TR
dc.subjectRSMtr_TR
dc.titlePrediction and Optimization of Surface Roughness in Ball Burnishing Process Using Response Surface Methodologyen_US
dc.typeArticleen_US

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