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dc.contributor.authorŠvéda J.
dc.contributor.authorKolář P.
dc.contributor.authorRytíř M.
dc.contributor.authorFojtů P.
dc.contributor.authorFiala Š.
dc.contributor.authorChládek Š.
dc.contributor.authorKozlok T.
dc.contributor.authorMachálka M.
dc.date.accessioned2022-10-06T09:26:59Z
dc.date.available2022-10-06T09:26:59Z
dc.date.issued2022
dc.identifierV3S-359888
dc.identifier.citationŠVÉDA, J., et al. Framework for milling process monitoring. MM Science Journal. 2022, 2022(3), 5969-5978. ISSN 1803-1269. DOI 10.17973/MMSJ.2022_10_2022123.
dc.identifier.issn1803-1269 (print)
dc.identifier.issn1805-0476 (online)
dc.identifier.urihttp://hdl.handle.net/10467/104318
dc.description.abstractModern machining systems use horizontal and vertical data integration for the automatic monitoring and quality control of the machining operations. There are currently available some comprehensive papers focused on high-level system integration. Independently of that, there are also multiple publications focused on the automatic monitoring of specific machining operations. There is lack of presented connections between the high-level proposals and the operation-level methods. This paper proposes a framework for milling process monitoring that covers both mentioned levels, i.e., the system complexity as well as particular operation details. The data model consisting of five key objects (cutting tool management; machine tool; workpiece; machining operation and user) is presented within the framework.eng
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherMM Science Journal
dc.relation.ispartofMM Science Journal
dc.subjectmachining data frameworkeng
dc.subjectmachine tooleng
dc.subjectmillingeng
dc.subjectcutting tooleng
dc.subjecttool wear monitoringeng
dc.subjectcyber-physical production systemseng
dc.titleFramework for milling process monitoringeng
dc.typečlánek v časopisecze
dc.typejournal articleeng
dc.identifier.doi10.17973/MMSJ.2022_10_2022123
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/OPVVV/CZ.02.1.01%2F0.0%2F0.0%2F16_026%2F0008432/CZ/Cluster 4.0 - Methodology of System Integration/
dc.rights.accessopenAccess
dc.identifier.wos000860191200001
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion


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