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Run-to-Run Fault Detection of Reactive Ion Etching Using Support Vector Machine  

Park Young-Kook (차세대전력기술연구센터)
Hong Sang-Jeen (명지대학교 전자공학과)
Han Seung-Soo (차세대전력기술연구센터)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.10, no.5, 2006 , pp. 962-969 More about this Journal
Abstract
To address the importance of the process fault detection for productivity, support vector machines (SVMs) is employed to assist the decision to determine process faults in real-time. The reactive ion etching (RIE) tool data acquired from a production line consist of 59 variables, and each of them consists of 10 data points per second. Principal component analysis (PCA) is first performed to accommodate for real-time data processing by reducing the dimensionality or the data. SVMs for eleven steps or etching m are established with data acquired from baseline runs, and they are further verified with the data from controlled (acceptable) and perturbed (unacceptable) runs. Then, each SVM is further utilized for the fault detection purpose utilizing control limits which is well understood in statistical process control chart. Utilizing SVMs, fault detection of reactive ion etching process is demonstrated with zero false alarm rate of the controlled runs on a run to run basis.
Keywords
SVM; RIE; PCA; Fault detection;
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Times Cited By KSCI : 1  (Citation Analysis)
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