Title :
OES structural feature based fault detection method for plasma etching
Author :
Zhao, Lihui ; Wang, Huangang ; Xu, Wenli
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
Optical Emission Spectra (OES) is a widely used signal in plasm etching. In this paper, an OES structural feature based fault detection method is proposed. Firstly, a template of normal OES curves is extracted via non-negative matrix factorization. Then singular points of the curves are detected by local matching based on the template. The magnitude and occurrence time of these singular points form a structural feature vector, which is a quantitative and simplified description of the curve´s shape. Lastly, one-class SVM is introduced for generate a fault detection model based on structural feature vectors from normal OES curves. Experiments on an industrial benchmark dataset show that the proposed method is effective.
Keywords :
fault diagnosis; infrared spectra; sputter etching; support vector machines; ultraviolet spectra; visible spectra; OES structural feature based fault detection method; curve shape; fault detection model; industrial benchmark dataset; nonnegative matrix factorization; normal OES curve; optical emission spectra; plasma etching; singular point; structural feature vector; Benchmark testing; Etching; Fault detection; Feature extraction; Plasmas; Support vector machines; Vectors; OES; Singular Point; Structural Feature; Template Matching; one-class SVM;
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
DOI :
10.1109/ICSAI.2012.6223171