3SC 실용트리즈와 머신러닝을 이용한 기공을 가진 인공지지체 제조문제 해결에 관한 연구

A Study on Manufacturing Problem Solving of Scaffold with Pore Using 3SC Practical TRIZ and Machine Learning

  • 이송연 (한국기술교육대학교대학원 메카트로닉스공학과) ;
  • 허용정 (한국기술교육대학교 메카트로닉스공학부)
  • Lee, Song-Yeon (Mechatronics Engineering, Graduate School of Korea University of Technology and Education) ;
  • Huh, Yong Jeong (Department of Mechatronics Engineering Korea University of Technology and Education)
  • 투고 : 2019.08.09
  • 심사 : 2019.09.23
  • 발행 : 2019.09.30

초록

In this paper, we have analyzed manufacturing problems of the scaffold with pores using FDM 3D printer and PLGA. We suggested the solutions using 3SC practical TRIZ. We selected the final solution used machine learning. We reduced number of experiments using most influential factor after analysis print factors. We printed the scaffold and measured pore size. We created the regression model using python tensorflow. The print condition data of measured pore size was used as training data. We predicted the pore size of printed condition using regression model. We printed the scaffold using the predicted the print condition data. We quantitatively compare the predicted scaffold pore size data and the measured scaffold pore size data. We got satisfactory result.

키워드

참고문헌

  1. Song-Yeon Lee and Yong-Jeong Huh, "A Study on Manufacturing Condition of PLGA Scaffold Using 3SC Practical TRIZ and Design of Experiment", J. of The Korean Society of Semiconductor & Display Technology, Vol.17, pp. 70-75, 2018.
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  6. Yeon-Ho Chu and Young-Kyu Choi, "A Deep Learning based IOT Device Recognition System", J. of The Korean Society of Semiconductor & Display Technology, Vol.18, pp. 01-05, 2019.