Analysis of Variables Effects in 300mm PECVD Chamber Cleaning Process Using NF3

  • Sang-Min Lee (Department of Industrial and Management Engineering, Myongji University) ;
  • Hee-Chan Lee (Department of Electronics Engineering, Myongji University) ;
  • Soon-Oh Kwon (Department of Environmental Engineering and Energy, Myongji University) ;
  • Hyo-Jong Song (Department of Environmental Engineering and Energy, Myongji University)
  • Received : 2024.06.06
  • Accepted : 2024.06.21
  • Published : 2024.06.30

Abstract

NF3, Chamber cleaning gas, has a high Global Warming Potential (GWP) of 17,000, causing significant greenhouse effects. Reducing gas usage during the cleaning process is crucial while increasing the cleaning Rate and reducing cleaning standard deviation (Stdev). In a previous study with a 6-inch PECVD chamber, a multiple linear regression analysis showed that Power and Pressure had no significant effect on the cleaning Rate because of their P-values of 0.42 and 0.68. The weight for Flow is 11.55, and the weights for Power and Pressure are 1.4 and 0.7. Due to the limitations of the research equipment, which differed from those used in actual industrial settings, it was challenging to assess the effects in actual industrial environment. Therefore, to show an actual industrial environment, we conducted the cleaning process on a 12-inch PECVD chamber, which is production-level equipment, and quantitatively analyzed the effects of each variable. Power, Pressure, and NF3 Flow all had P-values close to 0, indicating strong statistical significance. The weight for Flow is 15.68, and the weights for Power and Pressure are 4.45 and 5.24, respectively, showing effects 3 and 7 times greater than those with the 6-inch equipment on the cleaning rate. Additionally, we analyzed the cleaning Stdev and derived that there is a trade-off between increasing the cleaning Rate and reducing the cleaning Stdev.

Keywords

Acknowledgement

This paper presents research conducted as part of the collaborative semiconductor major track project supported by the Korea Industrial Technology Foundation (G02P1 8800005502) in 2024. We would like to express our gratitude to Professor Woo-sig Min and Researcher Eun-beom Lee at the Semiconductor Process Diagnosis Research Institute of Myongji University for their assistance in the experiments

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