This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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679
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Quality and Productivity
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Abstract - #306983 |
Title:
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Hierarchical Approach to Yield Modeling: Applications of GLMs
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Author(s):
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Christina Mastrangelo*+
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Companies:
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University of Washington
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Address:
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Box 352650, Seattle, WA, 98116, USA
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Keywords:
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Generalized Linear Models ;
Hierarchical Modeling ;
Yield Modeling
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Abstract:
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In this talk, we summarize a hierarchical approach to model semiconductor yield. This domain is well-known for its complexity, the enormous amounts of data generated, and for a complicated sampling strategy within each process. A two-stage modeling technique can facilitate the analysis of this problem. The first stage modeling is called "sub-process modeling", which is used to identify the key sub-processes for intermediate variables. The second stage modeling is called "meta-modeling", which is used to establish the relationship between intermediate variables and the yield. This approach allows us to analyze the relationship between intermediate variables and all key sub-processes independently, and then combine all effects to predict yield by some of these key sub-processes. Generalized linear models are used for sub-process and meta-modeling due to their ability to tackle categorical
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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