Uncertainty analysis of cutting parameters during grinding based on RSM optimization and Monte Carlo simulation

Basit Öğe Kaydı
dc.authorid0000-0002-1377-9338
dc.authorid0000-0001-6228-3630
dc.contributor.authorKahraman, Mehmet Fatih
dc.contributor.authorÖztürk, Sabri
dc.date.accessioned2021-06-23T19:50:30Z
dc.date.available2021-06-23T19:50:30Z
dc.date.issued2019
dc.departmentBAİBÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümüen_US
dc.description.abstractDue to the importance of high surface quality of machined parts, regarding its functional requirements, it is necessary to determine an appropriate set of grinding parameters. According to the uncertainty of the machining process, the statistical techniques have recently been used to set up an experimental-based model for estimating the performance of machining parameters and optimizing them. The purpose of this study is to demonstrate the modeling and optimization of the grinding process using three approaches. First, multi non-linear regression (MNLR) based on central composite design (CCD) was used to determine the process model. Then the grinding parameters were optimized considering response surface methodology (RSM). Finally, the probabilistic uncertainty analysis was applied by using Monte Carlo simulation as a function of wheel speed and feed rate.. The surface roughness value, which was named the response variable, was estimated by fitting the MNLR model with a predicted regression coefficient (R-pred(2)) of 84.69 %. Wheel speed of 4205.6 rpm and feed rate of 2.969 mm x min(-1) were calculated as RSM-optimized conditions with a surface roughness of 2.26326 mu m. The verification experiments were performed with three replications to verify the predicted surface roughness value obtained with the derived model, and 2.263 +/- 2 % mu m of surface roughness was calculated using RSM optimized conditions. Monte Carlo simulations were found to be quite effective for identification of the uncertainties in surface roughness that could not be identified by deterministic ways.en_US
dc.identifier.doi10.3139/120.111443
dc.identifier.endpage1219en_US
dc.identifier.issn0025-5300
dc.identifier.issue12en_US
dc.identifier.scopus2-s2.0-85077735667en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1215en_US
dc.identifier.urihttps://doi.org/10.3139/120.111443
dc.identifier.urihttps://hdl.handle.net/20.500.12491/9801
dc.identifier.volume61en_US
dc.identifier.wosWOS:000500588900013en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÖztürk, Sabri
dc.institutionauthorKahraman, Mehmet Fatih
dc.language.isoenen_US
dc.publisherCarl Hanser Verlagen_US
dc.relation.ispartofMaterials Testingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFlat Glassen_US
dc.subjectGrinding Wheelen_US
dc.subjectMulti Non-linear Regressionen_US
dc.subjectResponse Surface Optimizationen_US
dc.subjectMonte Carlo Simulationen_US
dc.titleUncertainty analysis of cutting parameters during grinding based on RSM optimization and Monte Carlo simulationen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Makine Mühendisliği Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu