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Cited 35 time in webofscience Cited 36 time in scopus
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dc.contributor.authorKIM, SUNGWOOK-
dc.contributor.authorKong, Jun Ho-
dc.contributor.authorLee, Sang Won-
dc.contributor.authorLEE, SEUNGCHUL-
dc.date.accessioned2022-02-09T04:40:07Z-
dc.date.available2022-02-09T04:40:07Z-
dc.date.created2022-02-08-
dc.date.issued2022-01-
dc.identifier.issn2234-7593-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/109264-
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>The recent advances in artificial intelligence have already begun to penetrate our daily lives. Even though the development is still in its infancy, it has been shown that it can outperform human beings even in terms of intelligence (e.g., AlphaGo by DeepMind), implying a massive potential for its broader application in various industrial sectors. In particular, the growing public interest in industry 4.0, which focuses on revolutionizing the traditional manufacturing scene, has stimulated a deeper investigation of its possible applications in the related industries. Since it has several limitations that hinder its direct usage, research on the convergence of artificial intelligence with other engineering fields, including precision engineering and manufacturing, is ongoing. This overview looks to summarize some of the important achievements made using artificial intelligence in some of the most influential and lucrative manufacturing industries in hopes of transforming the manufacturing sites.</jats:p>-
dc.languageEnglish-
dc.publisher한국정밀공학회-
dc.relation.isPartOfInternational Journal of Precision Engineering and Manufacturing-
dc.titleRecent Advances of Artificial Intelligence in Manufacturing Industrial Sectors: A Review-
dc.typeArticle-
dc.identifier.doi10.1007/s12541-021-00600-3-
dc.type.rimsART-
dc.identifier.bibliographicCitationInternational Journal of Precision Engineering and Manufacturing, v.23, no.1, pp.111 - 129-
dc.identifier.wosid000714326100001-
dc.citation.endPage129-
dc.citation.number1-
dc.citation.startPage111-
dc.citation.titleInternational Journal of Precision Engineering and Manufacturing-
dc.citation.volume23-
dc.contributor.affiliatedAuthorKIM, SUNGWOOK-
dc.contributor.affiliatedAuthorLee, Sang Won-
dc.contributor.affiliatedAuthorLEE, SEUNGCHUL-
dc.identifier.scopusid2-s2.0-85118505989-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessY-
dc.type.docTypeReview-
dc.subject.keywordPlusCONVOLUTIONAL NEURAL-NETWORKS-
dc.subject.keywordPlusOF-CHARGE ESTIMATION-
dc.subject.keywordPlusDEFECT PATTERNS-
dc.subject.keywordPlusFAULT-DETECTION-
dc.subject.keywordPlusCLASSIFICATION-
dc.subject.keywordPlusDIAGNOSIS-
dc.subject.keywordPlusMACHINE-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusSTATE-
dc.subject.keywordPlusCNN-
dc.subject.keywordAuthorArtificial intelligence-
dc.subject.keywordAuthorDeep learning-
dc.subject.keywordAuthorFault detection and diagnosis-
dc.subject.keywordAuthorCondition monitoring-
dc.subject.keywordAuthorManufacturing process-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.relation.journalWebOfScienceCategoryEngineering, Mechanical-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClasskci-

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이승철LEE, SEUNGCHUL
Dept of Mechanical Enginrg
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