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빅데이터 구축을 위한 알루미나 테이프 캐스팅 공정 최적화

Optimization of Alumina Tape Casting Process for Building Big Data

  • 김동하 (한국세라믹기술원 엔지니어링세라믹센터) ;
  • 김시연 (한국세라믹기술원 엔지니어링세라믹센터) ;
  • 이주성 ((주)보부하이테크 연구소) ;
  • 여동훈 (한국세라믹기술원 엔지니어링세라믹센터) ;
  • 신효순 (한국세라믹기술원 엔지니어링세라믹센터) ;
  • 윤상옥 (강릉원주대학교 세라믹신소재공학과)
  • Kim, Dong Ha (Engineering Ceramics Center, Korea Institute of Ceramic Engineering and Technology) ;
  • Kim, Shi Yeon (Engineering Ceramics Center, Korea Institute of Ceramic Engineering and Technology) ;
  • Lee, Joo Sung (R & D Center, Boboo Hitech Co., Ltd.) ;
  • Yeo, Dong-Hun (Engineering Ceramics Center, Korea Institute of Ceramic Engineering and Technology) ;
  • Shin, Hyo-Soon (Engineering Ceramics Center, Korea Institute of Ceramic Engineering and Technology) ;
  • Yoon, Sang-Ok (Department of Ceramic Engineering, Gangneung-Wonju National University)
  • 투고 : 2019.09.17
  • 심사 : 2019.09.23
  • 발행 : 2019.11.01

초록

For machine learning techniques, a large amount of high-quality material property data should be accumulated. In this study, several data for an alumina tape casting process were produced with the variables of slurry viscosity, gap size, and coating speed. The alumina tapes were manufactured in the range of 1,000~6,000 cps for slurry viscosity, $300{\sim}1,000{\mu}m$ for gap size, and 0.5~2.0 m/min for coating speed. As a result, the lower the viscosity, coating speed, and gap size, the more pore-free tapes could be manufactured. The viscosity of the slurry limited the minimum thickness of the tape. Green sheets with high packing density were manufactured from the slurry of 100~6,000 cps slurry viscosity, coating speed of 0.5 m/min, and a $300{\sim}500{\mu}m$ gap size.

키워드

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