Sensors 2010, 10(6), 5703-5723; doi:10.3390/s100605703
Article

Real-Time Plasma Process Condition Sensing and Abnormal Process Detection

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Received: 25 April 2010; in revised form: 15 May 2010 / Accepted: 25 May 2010 / Published: 8 June 2010
(This article belongs to the Section Physical Sensors)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: 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.
Keywords: process/equipment fault detection; spectrum; optic emission spectrum
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MDPI and ACS Style

Yang, R.; Chen, R. Real-Time Plasma Process Condition Sensing and Abnormal Process Detection. Sensors 2010, 10, 5703-5723.

AMA Style

Yang R, Chen R. Real-Time Plasma Process Condition Sensing and Abnormal Process Detection. Sensors. 2010; 10(6):5703-5723.

Chicago/Turabian Style

Yang, Ryan; Chen, Rongshun. 2010. "Real-Time Plasma Process Condition Sensing and Abnormal Process Detection." Sensors 10, no. 6: 5703-5723.

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