Plasma information-based virtual metrology (PI-VM) and mass production process control

In this paper, we review the development of plasma engineering technology that improves dramatically the production efficiency of OLED (organic light-emitting diode) displays and semiconductor manufacturing by utilizing a process monitoring methodology based on the physical domain knowledge. The dom...

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Published in:	Journal of the Korean Physical Society Vol. 80; no. 8; pp. 647 - 669
Main Authors:	Park, Seolhye, Seong, Jaegu, Jang, Yunchang, Roh, Hyun-Joon, Kwon, Ji-Won, Lee, Jinyoung, Ryu, Sangwon, Song, Jaemin, Roh, Ki-Baek, Noh, Yeongil, Park, Yoona, Jang, Yongsuk, Cho, Taeyoung, Yang, Jae-Ho, Kim, Gon-Ho
Format:	Journal Article
Language:	English
Published:	Seoul The Korean Physical Society 01.04.2022 Springer Nature B.V
Subjects:	Algorithms Domains Fault detection Mass production Mathematical and Computational Physics Metrology Organic light emitting diodes Particle and Nuclear Physics Physical properties Physics Physics and Astronomy Plasma Plasma and Phenomenology Plasma chemistry Plasma diagnostics Plasmas (physics) Process controls Reaction kinetics Review - Fluids Sheaths Surface reactions Theoretical Virtual metrology Mass production CVD (chemical vapor deposition) FDC (fault detection and classification) APC (advanced process control) PI (plasma information) parameter Etching OLED (organic light-emitting diode)
ISSN:	0374-4884, 1976-8524
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Abstract	In this paper, we review the development of plasma engineering technology that improves dramatically the production efficiency of OLED (organic light-emitting diode) displays and semiconductor manufacturing by utilizing a process monitoring methodology based on the physical domain knowledge. The domain knowledge consists of plasma-heating and sheath physics, plasma chemistry and plasma-material surface reaction kinetics, and plasma diagnostics. Based on this, a plasma information-based virtual metrology (PI-VM) algorithm was developed drastically enhanced process prediction performance by parameterizing plasma information (PI) which can trace the states of processing plasmas. PI-VM has superior process prediction accuracy compared to the classical statistics-based virtual metrologies. The developed PI-VM algorithms adopted for practical processing issues such as the control and management of the OLED-display mass production demonstrated savings of approximately 25% of the yield loss over the past 5 years. This improvement was achieved with the development of FDC (fault detection and classification) and APC (advanced process control) logic, which can be developed through the analysis of the physical characteristics of the feature parameters used in PI-VM with the evaluation of their contributions and their correlations to the processing results. PI-VM provides leverage that can be applied in the development of process equipment and factory automation technologies.
AbstractList	In this paper, we review the development of plasma engineering technology that improves dramatically the production efficiency of OLED (organic light-emitting diode) displays and semiconductor manufacturing by utilizing a process monitoring methodology based on the physical domain knowledge. The domain knowledge consists of plasma-heating and sheath physics, plasma chemistry and plasma-material surface reaction kinetics, and plasma diagnostics. Based on this, a plasma information-based virtual metrology (PI-VM) algorithm was developed drastically enhanced process prediction performance by parameterizing plasma information (PI) which can trace the states of processing plasmas. PI-VM has superior process prediction accuracy compared to the classical statistics-based virtual metrologies. The developed PI-VM algorithms adopted for practical processing issues such as the control and management of the OLED-display mass production demonstrated savings of approximately 25% of the yield loss over the past 5 years. This improvement was achieved with the development of FDC (fault detection and classification) and APC (advanced process control) logic, which can be developed through the analysis of the physical characteristics of the feature parameters used in PI-VM with the evaluation of their contributions and their correlations to the processing results. PI-VM provides leverage that can be applied in the development of process equipment and factory automation technologies. In this paper, we review the development of plasma engineering technology that improves dramatically the production efficiency of OLED (organic light-emitting diode) displays and semiconductor manufacturing by utilizing a process monitoring methodology based on the physical domain knowledge. The domain knowledge consists of plasma-heating and sheath physics, plasma chemistry and plasma-material surface reaction kinetics, and plasma diagnostics. Based on this, a plasma information-based virtual metrology (PI-VM) algorithm was developed drastically enhanced process prediction performance by parameterizing plasma information (PI) which can trace the states of processing plasmas. PI-VM has superior process prediction accuracy compared to the classical statistics-based virtual metrologies. The developed PI-VM algorithms adopted for practical processing issues such as the control and management of the OLED-display mass production demonstrated savings of approximately 25% of the yield loss over the past 5 years. This improvement was achieved with the development of FDC (fault detection and classification) and APC (advanced process control) logic, which can be developed through the analysis of the physical characteristics of the feature parameters used in PI-VM with the evaluation of their contributions and their correlations to the processing results. PI-VM provides leverage that can be applied in the development of process equipment and factory automation technologies.
Author	Park, Yoona Kim, Gon-Ho Jang, Yunchang Park, Seolhye Jang, Yongsuk Seong, Jaegu Song, Jaemin Ryu, Sangwon Lee, Jinyoung Roh, Hyun-Joon Yang, Jae-Ho Noh, Yeongil Cho, Taeyoung Roh, Ki-Baek Kwon, Ji-Won
Author_xml	– sequence: 1 givenname: Seolhye orcidid: 0000-0002-5957-1532 surname: Park fullname: Park, Seolhye email: druyvesteyndf@gmail.com organization: Samsung Display Co., Ltd – sequence: 2 givenname: Jaegu orcidid: 0000-0002-3926-0534 surname: Seong fullname: Seong, Jaegu organization: Samsung Display Co., Ltd – sequence: 3 givenname: Yunchang surname: Jang fullname: Jang, Yunchang organization: Department of Nuclear Engineering, Seoul National University – sequence: 4 givenname: Hyun-Joon surname: Roh fullname: Roh, Hyun-Joon organization: Department of Nuclear Engineering, Seoul National University – sequence: 5 givenname: Ji-Won surname: Kwon fullname: Kwon, Ji-Won organization: Department of Nuclear Engineering, Seoul National University – sequence: 6 givenname: Jinyoung surname: Lee fullname: Lee, Jinyoung organization: Department of Plasma Engineering, Korea Institute of Machinery & Materials (KIMM) – sequence: 7 givenname: Sangwon surname: Ryu fullname: Ryu, Sangwon organization: Department of Nuclear Engineering, Seoul National University – sequence: 8 givenname: Jaemin surname: Song fullname: Song, Jaemin organization: Department of Nuclear Engineering, Seoul National University – sequence: 9 givenname: Ki-Baek surname: Roh fullname: Roh, Ki-Baek organization: Department of Nuclear Engineering, Seoul National University – sequence: 10 givenname: Yeongil surname: Noh fullname: Noh, Yeongil organization: Samsung Display Co., Ltd – sequence: 11 givenname: Yoona surname: Park fullname: Park, Yoona organization: Samsung Display Co., Ltd – sequence: 12 givenname: Yongsuk surname: Jang fullname: Jang, Yongsuk organization: Samsung Display Co., Ltd – sequence: 13 givenname: Taeyoung surname: Cho fullname: Cho, Taeyoung organization: Samsung Display Co., Ltd – sequence: 14 givenname: Jae-Ho surname: Yang fullname: Yang, Jae-Ho organization: Samsung Display Co., Ltd – sequence: 15 givenname: Gon-Ho surname: Kim fullname: Kim, Gon-Ho email: ghkim@snu.ac.kr organization: Department of Nuclear Engineering, Seoul National University
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Keywords	Virtual metrology Mass production CVD (chemical vapor deposition) FDC (fault detection and classification) APC (advanced process control) PI (plasma information) parameter Etching OLED (organic light-emitting diode)
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SubjectTerms	Algorithms Domains Fault detection Mass production Mathematical and Computational Physics Metrology Organic light emitting diodes Particle and Nuclear Physics Physical properties Physics Physics and Astronomy Plasma Plasma and Phenomenology Plasma chemistry Plasma diagnostics Plasmas (physics) Process controls Reaction kinetics Review - Fluids Sheaths Surface reactions Theoretical
Title	Plasma information-based virtual metrology (PI-VM) and mass production process control
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