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Real-Time Plasma Process Condition Sensing and Abnormal Process Detection
The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a tim...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3247728/ https://www.ncbi.nlm.nih.gov/pubmed/22219683 http://dx.doi.org/10.3390/s100605703 |
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author | Yang, Ryan Chen, Rongshun |
author_facet | Yang, Ryan Chen, Rongshun |
author_sort | Yang, Ryan |
collection | PubMed |
description | The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a timely and accurately process fault or abnormal detection in a plasma reactor is needed. Optical emission spectroscopy (OES) is one of the most frequently used metrologies in in-situ process monitoring. Even though OES has the advantage of non-invasiveness, it is required to provide a huge amount of information. As a result, the data analysis of OES becomes a big challenge. To accomplish real-time detection, this work employed the sigma matching method technique, which is the time series of OES full spectrum intensity. First, the response model of a healthy plasma spectrum was developed. Then, we defined a matching rate as an indictor for comparing the difference between the tested wafers response and the health sigma model. The experimental results showed that this proposal method can detect process faults in real-time, even in plasma etching tools. |
format | Online Article Text |
id | pubmed-3247728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-32477282012-01-04 Real-Time Plasma Process Condition Sensing and Abnormal Process Detection Yang, Ryan Chen, Rongshun Sensors (Basel) Article The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a timely and accurately process fault or abnormal detection in a plasma reactor is needed. Optical emission spectroscopy (OES) is one of the most frequently used metrologies in in-situ process monitoring. Even though OES has the advantage of non-invasiveness, it is required to provide a huge amount of information. As a result, the data analysis of OES becomes a big challenge. To accomplish real-time detection, this work employed the sigma matching method technique, which is the time series of OES full spectrum intensity. First, the response model of a healthy plasma spectrum was developed. Then, we defined a matching rate as an indictor for comparing the difference between the tested wafers response and the health sigma model. The experimental results showed that this proposal method can detect process faults in real-time, even in plasma etching tools. Molecular Diversity Preservation International (MDPI) 2010-06-08 /pmc/articles/PMC3247728/ /pubmed/22219683 http://dx.doi.org/10.3390/s100605703 Text en © 2010 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Yang, Ryan Chen, Rongshun Real-Time Plasma Process Condition Sensing and Abnormal Process Detection |
title | Real-Time Plasma Process Condition Sensing and Abnormal Process Detection |
title_full | Real-Time Plasma Process Condition Sensing and Abnormal Process Detection |
title_fullStr | Real-Time Plasma Process Condition Sensing and Abnormal Process Detection |
title_full_unstemmed | Real-Time Plasma Process Condition Sensing and Abnormal Process Detection |
title_short | Real-Time Plasma Process Condition Sensing and Abnormal Process Detection |
title_sort | real-time plasma process condition sensing and abnormal process detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3247728/ https://www.ncbi.nlm.nih.gov/pubmed/22219683 http://dx.doi.org/10.3390/s100605703 |
work_keys_str_mv | AT yangryan realtimeplasmaprocessconditionsensingandabnormalprocessdetection AT chenrongshun realtimeplasmaprocessconditionsensingandabnormalprocessdetection |