Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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A Study on Real-Time Defect Detection System Using CNN Algorithm During Scaffold 3D Printing

CNN 알고리즘을 이용한 인공지지체의 3D프린터 출력 시 실시간 출력 불량 탐지 시스템에 관한 연구

  • Lee, Song Yeon (Mechatronics Engineering, Graduate School of Korea University of Technology and Education) ;
  • Huh, Yong Jeong (School of Mechatronics Engineering, Korea University of Technology and Education)
  • 이송연 (한국기술교육대학교 대학원 메카트로닉스공학과) ;
  • 허용정 (한국기술교육대학교 메카트로닉스공학부)
  • Received : 2021.09.03
  • Accepted : 2021.09.16
  • Published : 2021.09.30
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Abstract

Scaffold is used to produce bio sensor. Scaffold is required high dimensional accuracy. 3D printer is used to manufacture scaffold. 3D printer can't detect defect during printing. Defect detection is very important in scaffold printing. Real-time defect detection is very necessary on industry. In this paper, we proposed the method for real-time scaffold defect detection. Real-time defect detection model is produced using CNN(Convolution Neural Network) algorithm. Performance of the proposed model has been verified through evaluation. Real-time defect detection system are manufactured on hardware. Experiments were conducted to detect scaffold defects in real-time. As result of verification, the defect detection system detected scaffold defect well in real-time.

Keywords

References

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