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마이크로 드릴 가공 시 버 크기의 예측

Title
마이크로 드릴 가공 시 버 크기의 예측
Other Titles
Prediction of Burr Size in Micro-drilling
Author
이성환
Keywords
Micro-drilling; exit burr; deburring; burr type; cutting condition; artificial neural network; 마이크로드릴링; 출구 버; 버 제거; 버 형태; 절삭 조건; 인공지능신경망
Issue Date
2003-11
Publisher
한국정밀공학회
Citation
한국정밀공학회지, v. 20, no. 11, page. 71-78
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.
URI
http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE00854266https://repository.hanyang.ac.kr/handle/20.500.11754/156468
ISSN
1225-9071
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > MECHANICAL ENGINEERING(기계공학과) > Articles
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