Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 강창욱 | - |
dc.date.accessioned | 2020-04-08T07:50:29Z | - |
dc.date.available | 2020-04-08T07:50:29Z | - |
dc.date.issued | 2004-06 | - |
dc.identifier.citation | 산업경영시스템학회지, v. 27, No. 2, Page. 10-16 | en_US |
dc.identifier.issn | 2005-0461 | - |
dc.identifier.uri | http://scholar.dkyobobook.co.kr/searchDetail.laf?barcode=4010017068146# | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/148397 | - |
dc.description.abstract | Data 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.iso | ko_KR | en_US |
dc.publisher | 한국산업경영시스템학회 | en_US |
dc.subject | Data mining technique | en_US |
dc.subject | Defect type | en_US |
dc.subject | Process data | en_US |
dc.title | 데이터마이닝 기법을 이용한 제조 공정내의 불량항목별 예측방법 | en_US |
dc.title.alternative | Defect Type Prediction Method in Manufacturing Process Using Data Mining Technique | en_US |
dc.type | Article | en_US |
dc.relation.journal | 한국산업경영시스템학회지 | - |
dc.contributor.googleauthor | 변성규 | - |
dc.contributor.googleauthor | 강창욱 | - |
dc.contributor.googleauthor | 심성보 | - |
dc.relation.code | 2012211772 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | DEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING | - |
dc.identifier.pid | cwkang57 | - |
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