|
QICID: 29848
Title: Statistical Process Monitoring of Nonlinear Profiles Using Wavelets
Copyright: ASQ
Author: Chicken, Eric; Pignatiello, Jr., Joseph; Simpson, James R.
Organization: Florida State University; 53rd Test Management Group
Subject: Average run length (ARL); Control charts; Likelihood methods; Nonlinear models; Parametric models; Statistical process control (SPC); Thresholds;
Series: Journal of Quality Technology, Vol. 41, No. 2, April 2009, pp. 198-212
This ARTICLE is available for FREE
to ASQ members
with the appropriate membership type and/or magazine subscriptions. If you are signed-in you should be able to download articles you are entitled to receive. If you have questions about your membership please contact Customer Care at 800-248-1946 or help@asq.org
Abstract: [This abstract is based on the authors' abstract.]
The complex data records collected by many modern industrial processes do not readily allow the use of traditional statistical process-control techniques. An observation from a process might consist of n pairs of x and y data. Such data structures or relationships between x and y are called profiles. This study presents a semiparametric wavelet method for monitoring changes in sequence of nonlinear profiles. The method uses the spatial-adaptive properties of wavelets to detect profile changes. The method is used to differentiate between different radar profiles. Results indicate the method can quickly detect a variety of changes from a given in-control profile.
Number of pages: 15
Price for ASQ Members: $5.00
Price for List/Forum/Division: $10.00
All electronic articles are sent as PDFs via e-mail. To view the documents, you will need Adobe
Reader (free download).
Orders placed during business hours are usually filled within one business day.
If you have questions please e-mail our Customer Care center at help@asq.org.
Browse QIC articles chronologically
previous next
|
