Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/18290
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dc.contributor.authorPeko, Ivan-
dc.contributor.authorNedic, Bogdan-
dc.contributor.authorDjordjevic, Aleksandar-
dc.contributor.authorDzunic, Dragan-
dc.contributor.authorJanković, M-
dc.contributor.authorVeža, Ivica-
dc.date.accessioned2023-06-12T08:16:30Z-
dc.date.available2023-06-12T08:16:30Z-
dc.date.issued2016-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/18290-
dc.description.abstractToday highly competitive market and demands for obtain high surface finish and machining of complex shape geometries replace conventional machining processes with non-conventional. Plasma jet cutting is one of these non-conventional processes that primary uses a thermal energy of highly ionized gas to cut specified material and blow molten metal away. Main advantages of plasma jet cutting process are high speed of cutting, cutting different types of materials, the quality of cut and moderate to low investment costs. This paper presents experimental results concerning the surface roughness variation at plasma jet cutting of structural steel S235JRG2 plate thickness of 15 mm. Using the experimental data artificial neural network (ANN) model was developed in order to predict the surface roughness in terms of two input parameters, cutting current and cutting speed. After the prediction accuracy of the developed model was validated, the model was used for analyzing influence of input parameters on process response values.en_US
dc.publisherFaculty of Engineering, University of Kragujevac, Serbiaen_US
dc.relation.ispartofTribology in Industryen_US
dc.subjectPlasma jet cuttingen_US
dc.subjectSurface roughnessen_US
dc.titleModeling of Surface Roughness in Plasma Jet Cutting Process of Thick Structural Steelen_US
dc.typearticleen_US
Appears in Collections:Faculty of Engineering, Kragujevac

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