반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

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

Development of Monitoring System Using Residual Gas Analyzer (RGA) and Artificial Intelligence Modeling

  • 이지수 (명지대학교 산업경영공학과) ;
  • 김송훈 (명지대학교 전자공학과) ;
  • 김경수 (명지대학교 환경에너지공학과) ;
  • 송효종 (명지대학교 환경에너지공학과) ;
  • 박상훈 ((재)한국화학융합시험연구원) ;
  • 고득훈 ((재)한국화학융합시험연구원) ;
  • 이봉재 ((재)한국화학융합시험연구원)
  • 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 )
  • 투고 : 2024.06.07
  • 심사 : 2024.06.21
  • 발행 : 2024.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

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.

키워드

과제정보

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.

참고문헌

  1. H.G.Jeong, "Import and Export Structure and Global Phase Analysis of the Korean Semiconductor Industry." World Economy Today 24.2 (2024): 1-30. 
  2. Ministry of Foreign Affairs, "climate change negotiations", https://www.mofa.go.kr/www/wpge/m_20150/contents.do, (2024.04.01.) 
  3. S.H. Han, H.W. Park, T.H. Kim, and D.W. Park, "Large scale treatment of perfluorocompounds using a thermal plasma scrubber." Clean Technology 17, no. 3 (2011): 250-258. 
  4. Intergovernmental Panel on Climate Change (IPCC). "IPCC 6th Evaluation Report Comprehensive Report." Panel's 58th Session held in Interlaken, Switzerland (2023). 
  5. J.Y. Ryu, "A Study on Decomposition of Perfluorocom-pounds (NF3, CF4, SF6) Emitted from Semiconductor Process using Plasma." Journal of Korea Society of Waste Management 35.3 (2018): 250-257. 
  6. C.J. Park, "Operating Principle of Residual Gas Analyzer." Applied Science and Convergence Technology 17.4 (2008): 262-269. 
  7. S.Y. Lee and Y.J. Huh, "A Study on Prediction Model of Scaffold Pore Size Using Machine Learning." Journal of the Semiconductor & Display Technology 18.4 (2019): 49. 
  8. K.H. Kang and H.J. Park, "Study on the Effect of Training Data Sampling Strategy on the Accuracy of the Landslide Susceptibility Analysis Using Random Forest Method." Economic and Environmental Geology 52.2 (2019): 199-212. 
  9. G.W. Cha and W.H. Hong, "Development of an Predictive Model via Decision Tree-Based Algorithms for Forecasting Demolition Waste Generation." Journal of the Architectural Institute of Korea (JAIK) 39.3 (2023): 179-187. 
  10. S.C. Ha. "A Research on the Selection Algorithm in Trading Strategies using Machine Learning Techniques." Kookmin University, Seoul (2016): 1-7. 
  11. D.I. Kim, C.S. Park, J.G. Baek, and S.S. Kim, "Multiobjective Genetic Algorithm for Variable Selection in Linear Regression Model and Application." Journal of the Korea society for simulation 18.4 (2009): 137-148.