Gaussian Process Modeling and Optimization of Profile Response Experiments

Experiments where the response of interest is a curve or ‘profile’ arise in a variety of applications in engineering practice. In a recent paper (Journal of Quality Technology, 44, 2, pp. 117–135, 2012), a mixed‐effects Bayesian approach was proposed for the Bayesian optimization of profile response...

Full description

Saved in:
Bibliographic Details
Published in:Quality and reliability engineering international 2014-06, Vol.30 (4), p.449-462
Main Authors: Alshraideh, Hussam, del Castillo, Enrique
Format: Article
Language:English
Subjects:
Bayesian analysis
Correlation
Diagnostic systems
functional responses
Gaussian
Gaussian random function processes
Mathematical models
Optimization
Reliability engineering
robust parameter design
separability
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Experiments where the response of interest is a curve or ‘profile’ arise in a variety of applications in engineering practice. In a recent paper (Journal of Quality Technology, 44, 2, pp. 117–135, 2012), a mixed‐effects Bayesian approach was proposed for the Bayesian optimization of profile response systems, where a particular shape of the profile response defines desired properties of the product or process. This paper proposes an alternative spatio‐temporal Gaussian random function process model for such profile response systems, which is more flexible with respect to the types of desired profile shapes that can be modeled and allows us to model profile‐to‐profile correlation, if this exists. The method is illustrated with real examples taken from the literature, and practical aspects related to model building and diagnostics are discussed. Copyright © 2013 John Wiley & Sons, Ltd.
ISSN:0748-8017
1099-1638
DOI:10.1002/qre.1497