Publication Date

9-2013

Series Number

Preprint #2013-05

Abstract

Accelerated repeated measures degradation tests can sometimes be used to assess product or component reliability when one would expect few or even no failures during a study. Such tests can be used to estimate the lifetime distributions of highly reliable items. This paper describes methods for selecting a single-variable accelerated repeated measures degradation test plan when the (possibly transformed) degradation is linear in (possibly transformed) time and unit-to-unit variability is described by a random effect. To find optimum test plans, we use a criterion based on a large-sample approximation to the estimation precision of the quantile of the failure-time distribution at use conditions. We also discuss how to find compromise test plans that satisfy practical constraints. We use the general equivalence theorem to verify that a test plan is globally optimum. The resulting optimized plans are also evaluated using simulation and compared with other test plans.

Comments

This preprint was published as Brian P. Weaver and William Q. Meeker, "Methods for Planning Repeated Measures Accelerated Degradation Tests", Applied Stochastic Models in Business and Industry (2014): 658-671, doi: 10.1002/asmb.2061.

Language

en

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