DocumentCode :
958035
Title :
An Unsupervised Diagnosis for Process Tool Fault Detection: The Flexible Golden Pattern
Author :
Lacaille, Jérôme ; Zagrebnov, Maxim
Author_Institution :
PDF Solutions, Montpellier, France
Volume :
20
Issue :
4
fYear :
2007
Firstpage :
355
Lastpage :
363
Abstract :
The flexible golden pattern (FGP) algorithm uses a patented technology of empirical scoring to detect abnormal behavior for semiconductor processing equipment or a specific processing chamber during wafer production. This algorithm does not entirely rely on manual extraction of features from data acquired on each tool. It is able to automatically select good pattern indicators from raw (temporal) signal traces. It is able to diagnose unusual behavior disregarding specificity proper to a recipe or even a chamber or even a tool if the algorithm is calibrated for such a purpose. The algorithm does not need any complicated parameter settings; the diagnosis is established by comparison of the normal process behavior to the abnormal one.
Keywords :
fault location; feature extraction; semiconductor technology; abnormal behavior detection; empirical scoring; feature extraction; flexible golden pattern; process tool fault detection; semiconductor processing equipment; specific processing chamber; unsupervised fault diagnosis; wafer production; Algorithm design and analysis; Control charts; Data mining; Degradation; Fault detection; Fault diagnosis; Feature extraction; Pattern analysis; Process control; Production; Adaptive algorithm; compression; diagnostic; reconstruction; score; tube envelopes;
fLanguage :
English
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
Publisher :
ieee
ISSN :
0894-6507
Type :
jour
DOI :
10.1109/TSM.2007.907608
Filename :
4369342
Link To Document :
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