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dc.creatorMilivojević, Aleksandar
dc.creatorSedmak, Aleksandar
dc.creatorSedmak, Simon
dc.creatorAranđelović, Mihajlo
dc.date.accessioned2023-03-13T12:38:56Z
dc.date.available2023-03-13T12:38:56Z
dc.date.issued2022
dc.identifier.isbn978-86-6060-119-5
dc.identifier.urihttps://machinery.mas.bg.ac.rs/handle/123456789/5974
dc.description.abstractWelding is analyzed here as an intelligent process in the context of Industry 4.0, with a focus on two aspects: automatization and machine learning. In the case of automatization, starting from the first industrial robots as applied in spot welding in car industry 50 years ago, advances in other welding processes like Gas Shielded Arc Welding (GSAW) and Laser Beam Welding (LBW) are presented. As for the machine learning, starting from the early efforts to use neural networks to correlate input welding parameters with a shape of a welded joint in early nineties, advances in modern machine learning technologies to predict mechanical properties and microstructure are presented.sr
dc.language.isoensr
dc.publisherUNIVERSITY OF BELGRADE Faculty of Mechanical Engineeringsr
dc.relationinfo:eu-repo/grantAgreement/MESTD/Integrated and Interdisciplinary Research (IIR or III)/45014/RS/sr
dc.relationinfo:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/33001/RS//sr
dc.rightsopenAccesssr
dc.source10th International Scientific Conference -IRMES 2022 Research and Development of Mechanical Elements and Systems, Proceedingssr
dc.subjectindustry 4.0sr
dc.subjectmachine learningsr
dc.subjectneural networksr
dc.subjectautomatizationsr
dc.titleINTELLIGENT WELDING IN CONTEXT OF INDUSTRY 4.0sr
dc.typeconferenceObjectsr
dc.rights.licenseARRsr
dc.rights.holderUniversity of Belgrade, Faculty of Mechanical Engineeringsr
dc.citation.epage101
dc.citation.rankM33
dc.identifier.fulltexthttp://machinery.mas.bg.ac.rs/bitstream/id/14845/bitstream_14845.pdf
dc.identifier.rcubhttps://hdl.handle.net/21.15107/rcub_machinery_5974
dc.type.versionpublishedVersionsr


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