Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이성환 | - |
dc.date.accessioned | 2020-12-23T07:03:17Z | - |
dc.date.available | 2020-12-23T07:03:17Z | - |
dc.date.issued | 2003-11 | - |
dc.identifier.citation | 한국정밀공학회지, v. 20, no. 11, page. 71-78 | en_US |
dc.identifier.issn | 1225-9071 | - |
dc.identifier.uri | http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE00854266 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/156468 | - |
dc.description.abstract | The exit burrs in the micro-drilling of precision miniature holes are of interest, especially for ductile materials. As burrs from this process can be difficult to remove, it is important to acquire the way of prediction burr types as well as optimal cutting conditions which minimize the burrs. In this paper, an artificial neural network was used for the prediction of burr formation in micro-drilling. First, the influence of cutting conditions including cutting speed, feed and drill diameter on the exit burr characteristics, such as burr size and type, were observed and analyzed. Then, the burr types were classified by using the influential experimental data as input parameters to the neural nets. | en_US |
dc.language.iso | ko_KR | en_US |
dc.publisher | 한국정밀공학회 | en_US |
dc.subject | Micro-drilling | en_US |
dc.subject | exit burr | en_US |
dc.subject | deburring | en_US |
dc.subject | burr type | en_US |
dc.subject | cutting condition | en_US |
dc.subject | artificial neural network | en_US |
dc.subject | 마이크로드릴링 | en_US |
dc.subject | 출구 버 | en_US |
dc.subject | 버 제거 | en_US |
dc.subject | 버 형태 | en_US |
dc.subject | 절삭 조건 | en_US |
dc.subject | 인공지능신경망 | en_US |
dc.title | 마이크로 드릴 가공 시 버 크기의 예측 | en_US |
dc.title.alternative | Prediction of Burr Size in Micro-drilling | en_US |
dc.type | Article | en_US |
dc.relation.journal | 한국정밀공학회지 | - |
dc.contributor.googleauthor | 이성환 | - |
dc.contributor.googleauthor | 권성용 | - |
dc.relation.code | 2012101691 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | DEPARTMENT OF MECHANICAL ENGINEERING | - |
dc.identifier.pid | sunglee | - |
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