An intelligent system approach for surface roughness and vibrations prediction in cylindrical grinding

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dc.contributor.authorAsilturk, Ilhan
dc.contributor.authorTinkir, Mustafa
dc.contributor.authorEl Monuayri, Hazim
dc.contributor.authorCelik, Levent
dc.date.accessioned2024-02-23T14:20:18Z
dc.date.available2024-02-23T14:20:18Z
dc.date.issued2012
dc.departmentNEÜen_US
dc.description.abstractThis work aims to develop an adaptive network-based fuzzy inference system (ANFIS) for surface roughness and vibration prediction in cylindrical grinding. The system uses a piezoelectric accelerometer to generate a signal related to grinding features and surface roughness. To accomplish such a goal, an experimental study was carried out and consisted of 27 runs in a cylindrical grinding machine operating with an aluminium oxide grinding wheel and AISI 8620 steel workpiece. The workpiece speed, feed rate and depth of cut were used as an input to ANFIS, which in turn outputs surface roughness (Ra) and vibration (a(z)). Different neuro-fuzzy parameters were adopted during the training process of the system in order to improve online monitoring and prediction. Experimental validation runs were conducted to compare the measured surface roughness values with the values predicted online. The comparison shows that the gauss-shaped membership function achieved an online prediction accuracy of 99%.en_US
dc.description.sponsorshipTUBITAKen_US
dc.description.sponsorshipThis study is supported by Scientific Research Projects Coordinators (BAP) of Selcuk University and TUBITAK. This support is greatly appreciated.en_US
dc.identifier.doi10.1080/0951192X.2012.665185
dc.identifier.endpage759en_US
dc.identifier.issn0951-192X
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-84864055450en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage750en_US
dc.identifier.urihttps://doi.org/10.1080/0951192X.2012.665185
dc.identifier.urihttps://hdl.handle.net/20.500.12452/13114
dc.identifier.volume25en_US
dc.identifier.wosWOS:000306528400006en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofInternational Journal Of Computer Integrated Manufacturingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAnfisen_US
dc.subjectCnc Grindingen_US
dc.subjectSurface Roughnessen_US
dc.subjectVibration Monitoringen_US
dc.subjectPrediction Modelen_US
dc.titleAn intelligent system approach for surface roughness and vibrations prediction in cylindrical grindingen_US
dc.typeArticleen_US

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