The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
Activity Number:
|
420
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Quality and Productivity Section
|
Abstract - #305004 |
Title:
|
Application of Generalized Linear Models to Predict Semiconductor Yield
|
Author(s):
|
Wenjun Ke*+
|
Companies:
|
Arizona State University
|
Address:
|
1710 S Jentilly Ln, Tempe, AZ, 85281, United States
|
Keywords:
|
Generalized linear models ;
Logistic regression ;
Semiconductor yield ;
Effect size
|
Abstract:
|
This paper presents a methodology to forecast semiconductor manufacturing yield loss using generalized linear mixed models based on defect metrolgy data. This technique yields results at both the die and the wafer levels. The process to be modeled is product failure. We consider manufacturing lot as a random effect, with wafer and die observations correlated within lot. An example of 23296 die (observation unit) are used in the model building and 11445 die are used for model validation. The purpose of this paper is to discuss these approaches. In addition, we calculate power estimates and sample size requirements for fixed effects corresponding to wafer location, die quadrant, radial distance and manufacturing layer, depending on magnitude of the random effect. We focus on power calculations for the GLIMMIX model with correlated binary outcomes to detect the change of effect size.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.