Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment
To minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/2/253 |
| _version_ | 1797494447486795776 |
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| author | Hyukjoon Kwon Sang Jeen Hong |
| author_facet | Hyukjoon Kwon Sang Jeen Hong |
| author_sort | Hyukjoon Kwon |
| collection | DOAJ |
| description | To minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or components of complicated semiconductor fabrication equipment are some of the most unnoticed factors that eventually change the plasma conditions. In this work, we propose improved stability and accuracy of process fault detection using optical emission spectroscopy (OES) data. Under a controlled experimental setup of arbitrarily induced fault scenarios, the extended isolation forest (EIF) approach was used to detect anomalies in OES data compared with the conventional isolation forest method in terms of accuracy and speed. We also used the OES data to generate features related to electron temperature and found that using the electron temperature features together with equipment status variable identification data (SVID) and OES data improved the prediction accuracy of process/equipment fault detection by a maximum of 0.84%. |
| first_indexed | 2024-03-10T01:34:25Z |
| format | Article |
| id | doaj.art-44ed1c7188824a75a62ecaf40d365641 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T01:34:25Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-44ed1c7188824a75a62ecaf40d3656412023-11-23T13:34:46ZengMDPI AGElectronics2079-92922022-01-0111225310.3390/electronics11020253Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch EquipmentHyukjoon Kwon0Sang Jeen Hong1Department of Electronics Engineering, Myongji University, 116 Myongji-ro, Yongin-si 17058, KoreaDepartment of Electronics Engineering, Myongji University, 116 Myongji-ro, Yongin-si 17058, KoreaTo minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or components of complicated semiconductor fabrication equipment are some of the most unnoticed factors that eventually change the plasma conditions. In this work, we propose improved stability and accuracy of process fault detection using optical emission spectroscopy (OES) data. Under a controlled experimental setup of arbitrarily induced fault scenarios, the extended isolation forest (EIF) approach was used to detect anomalies in OES data compared with the conventional isolation forest method in terms of accuracy and speed. We also used the OES data to generate features related to electron temperature and found that using the electron temperature features together with equipment status variable identification data (SVID) and OES data improved the prediction accuracy of process/equipment fault detection by a maximum of 0.84%.https://www.mdpi.com/2079-9292/11/2/253fault detectionoptical emission spectroscopy (OES)silicon etchplasmaextended isolation forest (EIF)electron temperature |
| spellingShingle | Hyukjoon Kwon Sang Jeen Hong Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment Electronics fault detection optical emission spectroscopy (OES) silicon etch plasma extended isolation forest (EIF) electron temperature |
| title | Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment |
| title_full | Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment |
| title_fullStr | Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment |
| title_full_unstemmed | Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment |
| title_short | Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment |
| title_sort | use of optical emission spectroscopy data for fault detection of mass flow controller in plasma etch equipment |
| topic | fault detection optical emission spectroscopy (OES) silicon etch plasma extended isolation forest (EIF) electron temperature |
| url | https://www.mdpi.com/2079-9292/11/2/253 |
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