This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 679
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Quality and Productivity
Abstract - #306983
Title: Hierarchical Approach to Yield Modeling: Applications of GLMs
Author(s): Christina Mastrangelo*+
Companies: University of Washington
Address: Box 352650, Seattle, WA, 98116, USA
Keywords: Generalized Linear Models ; Hierarchical Modeling ; Yield Modeling
Abstract:

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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