Referenced Items are not available for this document.
During a semiconductor manufacturing process a large amount of data is stored in databases. These data can be used to model the semiconductor manufacturing yield. A model of the yield according to process measurements is useful to predict the yield before final tests. It is also an help to do sensitivity analysis of the yield to process variations. This paper compares three methods to model the manufacturing yield from test data. Principal components analysis, independent component analysis and partial least squares regression are reviewed. A methodology is then exposed to achieve, efficient manufacturing yield modeling
Published in:
Advanced Semiconductor Manufacturing Conference and Workshop, 2005 IEEE/SEMI
Date of Conference: 11-12 April 2005
- Page(s):
- 118 - 123
- Print ISBN:
- 0-7803-8997-2
- INSPEC Accession Number:
- 8521779
- Conference Location :
- Munich
- Digital Object Identifier :
- 10.1109/ASMC.2005.1438778
- Product Type:
- Conference Publications
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