scholarly journals APC Technique and Fault Detection and Classification System in Semiconductor Manufacturing Process

2015 ◽  
Vol 21 (9) ◽  
pp. 875-880
Author(s):  
Dae-Geun Ha ◽  
Jun-Mo Koo ◽  
Dam-Dae Park ◽  
Chong-Hun Han
Keyword(s):  
Fault Detection ◽  
Classification System ◽  
Manufacturing Process ◽  
Semiconductor Manufacturing ◽  
Fault Detection And Classification

Computational Intelligence Techniques to Fault Detection in the Semiconductor Manufacturing Process

2011 ◽  
Vol 52-54 ◽  
pp. 1171-1176 ◽  
Author(s):  
Kittisak Kerdprasop ◽  
Nittaya Kerdprasop
Keyword(s):  
Fault Detection ◽  
Process Control ◽  
High Precision ◽  
Computational Intelligence ◽  
Manufacturing Process ◽  
Semiconductor Manufacturing ◽  
Semiconductor Industry ◽  
Classification Model ◽  
Minimal Set ◽  
Margin Of Error

The semiconductor industry deals with the production at a scale of nanometer, thus resulting in the process control with little margin of error. Timely detection of faults during the manufacturing process is critical to the improvement in product yields. Difficulty of detecting accurately faulty processes and products is due to the abundant of data obtained from hundreds of tool-state and process-state sensors. We thus analyze this problem through the computational intelligence techniques. The analysis results reveal the minimal set of features for fault detection as well as the high precision classification model of faults.

Simultaneous Fault Detection and Classification for Semiconductor Manufacturing Tools

2003 ◽  
Vol 150 (12) ◽  
pp. G778 ◽  
Author(s):  
Brian E. Goodlin ◽  
Duane S. Boning ◽  
Herbert H. Sawin ◽  
Barry M. Wise
Keyword(s):  
Fault Detection ◽  
Semiconductor Manufacturing ◽  
Fault Detection And Classification
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