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dc.contributor.author강창욱-
dc.date.accessioned2020-04-08T07:50:29Z-
dc.date.available2020-04-08T07:50:29Z-
dc.date.issued2004-06-
dc.identifier.citation산업경영시스템학회지, v. 27, No. 2, Page. 10-16en_US
dc.identifier.issn2005-0461-
dc.identifier.urihttp://scholar.dkyobobook.co.kr/searchDetail.laf?barcode=4010017068146#-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/148397-
dc.description.abstractData mining technique is the exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. This paper uses a data mining technique for the prediction of defect types in manufacturing process. The purpose of this paper is to model the recognition of defect type patterns and prediction of each defect type before it occurs in manufacturing process. The proposed model consists of data handling, defect type analysis, and defect type prediction stages. The performance measurement shows that it is higher in prediction accuracy than logistic regression model.en_US
dc.language.isoko_KRen_US
dc.publisher한국산업경영시스템학회en_US
dc.subjectData mining techniqueen_US
dc.subjectDefect typeen_US
dc.subjectProcess dataen_US
dc.title데이터마이닝 기법을 이용한 제조 공정내의 불량항목별 예측방법en_US
dc.title.alternativeDefect Type Prediction Method in Manufacturing Process Using Data Mining Techniqueen_US
dc.typeArticleen_US
dc.relation.journal한국산업경영시스템학회지-
dc.contributor.googleauthor변성규-
dc.contributor.googleauthor강창욱-
dc.contributor.googleauthor심성보-
dc.relation.code2012211772-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF ENGINEERING SCIENCES[E]-
dc.sector.departmentDEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING-
dc.identifier.pidcwkang57-
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COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > INDUSTRIAL AND MANAGEMENT ENGINEERING(산업경영공학과) > Articles
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