Please use this identifier to cite or link to this item: https://doi.org/10.1002/qre.1151
DC FieldValue
dc.titleA Bayesian optimal design for accelerated degradation tests
dc.contributor.authorLiu, X.
dc.contributor.authorTang, L.-C.
dc.date.accessioned2014-06-16T09:23:24Z
dc.date.available2014-06-16T09:23:24Z
dc.date.issued2010-12
dc.identifier.citationLiu, X., Tang, L.-C. (2010-12). A Bayesian optimal design for accelerated degradation tests. Quality and Reliability Engineering International 26 (8) : 863-875. ScholarBank@NUS Repository. https://doi.org/10.1002/qre.1151
dc.identifier.issn07488017
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/53895
dc.description.abstractThis paper proposes a Bayesian design approach to planning a pre-production accelerated design test (ADT) with physically based statistical models. To motivate the study, we consider the hot-carrier-induced degradation of modern MOS field effect transistors. A single-path power-law statistical degradation model with nonlinear stress-life relationships is first developed. Based on this model, we formulate a Bayesian optimal design problem that minimizes the expected pre-posterior variance of the quantity of interest at use environment. To solve the problem, a simulation-based stochastic optimization method, which yields a consistent estimate of the optimal design, is utilized. As demonstrated by the numerical example, such an algorithm is of great practical importance in planning an ADT because it is considerably faster than the commonly used Monte Carlo simulation for evaluating the expected pre-posterior variance. Finally, we perform a comparison study between the proposed Bayesian plan and the locally optimal plan, which is based on the maximum likelihood theory. Results strongly suggest that the robustness of the proposed plan against the uncertainty associated with planning inputs can be significantly enhanced. © 2010 John Wiley & Sons, Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/qre.1151
dc.sourceScopus
dc.subjectAccelerated degradation test
dc.subjectBayesian optimal design
dc.subjectGibbs sampler
dc.subjectHot-carrier-induced degradation
dc.subjectMonte Carlo simulation
dc.subjectPhysically based statistical model
dc.typeArticle
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.description.doi10.1002/qre.1151
dc.description.sourcetitleQuality and Reliability Engineering International
dc.description.volume26
dc.description.issue8
dc.description.page863-875
dc.description.codenQREIE
dc.identifier.isiut000285849100009
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

36
checked on Apr 16, 2021

WEB OF SCIENCETM
Citations

36
checked on Apr 8, 2021

Page view(s)

113
checked on Apr 13, 2021

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.