Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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Development of Monitoring System Using Residual Gas Analyzer (RGA) and Artificial Intelligence Modeling

잔류가스 분석기(RGA)와 인공지능 모델링을 이용한 모니터링 시스템 개발

  • Ji Soo Lee (Department of Industrial Management of Engineering, Myongji University) ;
  • Song Hun Kim (Department of Electronic Engineering, Myongji University) ;
  • Gyeong Su Kim (Department of Environmental Energy and Engineering, Myongji University) ;
  • Hyo Jong Song (Department of Environmental Energy and Engineering, Myongji University) ;
  • Sang-Hoon Park (Korea Testing & Research Institute ) ;
  • Deuk-Hoon Goh (Korea Testing & Research Institute ) ;
  • Bong-Jae Lee (Korea Testing & Research Institute )
  • 이지수 (명지대학교 산업경영공학과) ;
  • 김송훈 (명지대학교 전자공학과) ;
  • 김경수 (명지대학교 환경에너지공학과) ;
  • 송효종 (명지대학교 환경에너지공학과) ;
  • 박상훈 ((재)한국화학융합시험연구원) ;
  • 고득훈 ((재)한국화학융합시험연구원) ;
  • 이봉재 ((재)한국화학융합시험연구원)
  • Received : 2024.06.07
  • Accepted : 2024.06.21
  • Published : 2024.06.30
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Abstract

This study aims to talk about the necessity of solving the PFC gas emission problem raised by the recent development of the semiconductor industry and the remote plasma source method monitoring system used in the semiconductor industry. The 'monitoring system' means that the researchers applied machine learning to the existing monitoring technology and modeled it. In the process of this study, Residual Gas Analyzer monitoring technology and linear regression model were used. Through this model, the researchers identified emissions of at least 12700mg CO2 to 75800mg CO2 with values ranging from ion current 0.6A to 1.7A, and expect that the 'monitoring system' will contribute to the effective calculation of greenhouse gas emissions in the semiconductor industry in the future.

Keywords

Acknowledgement

이 연구는 2023년도 산업통상자원부 및 한국산업기술기획평가원(KEIT) 연구비 지원에 의한 연구(RS-2023-00267529) 및 2024년도 부처협업형 반도체전공트랙 사업을 통해 한국산업기술진흥원(G02P18800005502)의 지원을 받아 수행된 연구임.

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