A Review of Accelerated Test Models

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dc.contributor.author Escobar, Luis
dc.contributor.author Meeker, William
dc.contributor.author Meeker, William
dc.contributor.department Statistics
dc.date 2018-02-16T05:14:01.000
dc.date.accessioned 2020-07-02T06:55:57Z
dc.date.available 2020-07-02T06:55:57Z
dc.date.issued 2006-06-21
dc.description.abstract <p>Engineers in the manufacturing industries have used accelerated test (AT) experiments for many decades. The purpose of AT experiments is to acquire reliability information quickly. Test units of a material, component, subsystem, or entire systems are subjected to higher-than-usual levels of one or more accelerating variables such as temperature or stress. Then the AT results are used to predict life of the units at use conditions. The extrapolation is typically justified (correctly or incorrectly) on the basis of physically motivated models or a combination of empirical model fitting with a sufficient amount of previous experience in testing similar units. The need to extrapolate in both time and the accelerating variables generally necessitates the use of fully parametric models. Statisticians have made important contributions in the development of appropriate stochastic models for AT data (typically a distribution for the response and regression relationships between the parameters of this distribution and the accelerating variable(s)), statistical methods for AT planning (choice of accelerating variable levels and allocation of available test units to those levels), and methods of estimation of suitable reliability metrics. This paper provides a review of many of the AT models that have been use successfully in this area</p>
dc.description.comments <p>This preprint was published in <em>Statistical Science</em> 21 (2006): 552–577, doi:1<a href="http://dx.doi.org/10.1214/088342306000000321" target="_blank">0.1214/088342306000000321</a>.</p>
dc.identifier archive/lib.dr.iastate.edu/stat_las_preprints/13/
dc.identifier.articleid 1027
dc.identifier.contextkey 6997418
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_preprints/13
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90290
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_preprints/13/2006_06.pdf|||Fri Jan 14 19:37:14 UTC 2022
dc.source.uri 10.1214/088342306000000321
dc.subject.disciplines Statistics and Probability
dc.subject.keywords Reliability
dc.subject.keywords regression model
dc.subject.keywords lifetime data
dc.subject.keywords degradation data
dc.subject.keywords extrapolation
dc.subject.keywords acceleration factor
dc.subject.keywords Arrhenius relationship
dc.subject.keywords Eyring relationship
dc.subject.keywords inverse power relationship
dc.subject.keywords voltage-stress acceleration
dc.subject.keywords photodegradation
dc.title A Review of Accelerated Test Models
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication a1ae45d5-fca5-4709-bed9-3dd8efdba54e
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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