|
Activity Number:
|
118
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Monday, August 7, 2006 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Quality and Productivity
|
| Abstract - #306637 |
|
Title:
|
Profile Monitoring via Linear Mixed Models
|
|
Author(s):
|
Willis Jensen*+ and Jeffrey B. Birch and William H. Woodall
|
|
Companies:
|
W. L. Gore & Associates, Inc. and Virginia Polytechnic Institute and State University and Virginia Polytechnic Institute and State University
|
|
Address:
|
303 Piedmont 7, Blacksburg, VA, 24060,
|
|
Keywords:
|
correlated data ; linear mixed model ; multivariate statistical process control ; phase I ; profile monitoring
|
|
Abstract:
|
Profile monitoring is a relatively new set of techniques in quality control used when the product or process quality is best represented by a function (or a curve) at each time period. The idea is often to model the profile via some parametric method and then monitor the estimated parameters over time to determine if there have been changes in the profiles. Previous modeling methods have not incorporated the correlation structure within the profiles. We propose the use of linear mixed models to monitor the profiles to account for the correlation structure within a profile. When the data are balanced the simple analysis that ignores the correlation structure will perform just as well as a more complicated analysis that takes into account the correlation structure. When the data are unbalanced or when there are missing data, we find that linear mixed model approach is preferable.
|
