Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/11532
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dc.contributor.authorÜnver, H.-
dc.contributor.authorÖzbayoğlu, A.M.-
dc.contributor.authorSöyleyici, C.-
dc.contributor.authorÇelik, B.B.-
dc.date.accessioned2024-04-20T13:36:29Z-
dc.date.available2024-04-20T13:36:29Z-
dc.date.issued2024-
dc.identifier.isbn9780323991346-
dc.identifier.isbn9780323996723-
dc.identifier.urihttps://doi.org/10.1016/B978-0-323-99134-6.00010-4-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/11532-
dc.description.abstractSince the early 1980s, implementation of artificial intelligence (AI)-based intelligent machining process monitoring (MPM) has been advancing, parallel to the new AI models and machining technologies. These systems are critical for balancing the tradeoffs among productivity, quality, cost, and sustainability measures of machine tool shops and the broader manufacturing industry. Furthermore, increased demand for high-level process automation, pressure to use less workforce, and data explosion by widely used low-cost sensory equipment have increased the expectation from MPM to become an enabler of the dark factory. This chapter covers a broad range of AI models and techniques used in MPM by providing both algorithmic fundamentals and architectural examples from recent studies. © 2024 Elsevier Inc. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofArtificial Intelligence in Manufacturing: Concepts and Methodsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial intelligenceen_US
dc.subjectChatteren_US
dc.subjectDeep learningen_US
dc.subjectFeature engineeringen_US
dc.subjectMachine learningen_US
dc.subjectMachiningen_US
dc.subjectProcess monitoringen_US
dc.subjectTool wearen_US
dc.subjectTransfer learningen_US
dc.titleArtificial Intelligence for Machining Process Monitoringen_US
dc.typeBook Parten_US
dc.departmentTOBB ETÜen_US
dc.identifier.startpage307en_US
dc.identifier.endpage350en_US
dc.identifier.scopus2-s2.0-85189573543en_US
dc.institutionauthor-
dc.identifier.doi10.1016/B978-0-323-99134-6.00010-4-
dc.authorscopusid6603873269-
dc.authorscopusid57947593100-
dc.authorscopusid58109448700-
dc.authorscopusid58973250800-
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
item.openairetypeBook Part-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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