실험계획법과 뉴럴 네트워크를 이용한 버 형상 예측
- Title
- 실험계획법과 뉴럴 네트워크를 이용한 버 형상 예측
- Other Titles
- Prediction of Burr Type using the Taguchi Method and Neural Network
- Author
- 이성환
- Issue Date
- 2005-10
- Publisher
- 한양대학교 공학기술연구소
- Citation
- 공학기술논문집, v. 14, Page. 33-42
- Abstract
- Burrs formed during face milling operations can be very difficult to characterize since there exist
several parameters which have complex combined effects that affect the cutting process. Many
researchers have attempted to predict burr characteristics including burr size and shape, using
various experimental parameters such as cutting speed, feed rate, in-plane exit angle, and number
of inserts. However, the results of these studies tend to be limited to a specific process parameter
range and to certain materials. In this paper, the Taguchi method, a systematic optimization method
for design and analysis of experiments, is introduced to acquire optimum cutting conditions for burr
minimization. In addition, an in process monitoring scheme using an artificial neural network is
presented for the prediction of burr types.
- URI
- http://riet.hanyang.ac.kr/journal/172https://repository.hanyang.ac.kr/handle/20.500.11754/111673
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > MECHANICAL ENGINEERING(기계공학과) > Articles
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