Preprint #96-26
Accelerated Degradation Tests: Modeling and Analysis
by
William Q. Meeker, Luis A. Escobar and C. Joseph Lu
Abstract
High reliability systems generally require individual system components
having extremely high reliability over long periods of time. Short product
development times require reliability tests to be conducted with severe
time constraints. Frequently few or no failures occur during such tests,
especially at lower levels of stress. Thus, it is difficult to assess
reliability with traditional life tests that record only time-to-failure.
For some components, degradation measures can be taken over time. A
relationship between component failure and amount of degradation makes
it possible to use degradation models and data to make inferences and
predictions about a time-to-failure distribution.
This paper describes degradation reliability models that correspond to
physical-failure mechanisms. We explain the connection between
degradation reliability models and failure-time reliability models.
Acceleration is modeled by having an accelerating factor (or factors)
that describe the effect of temperature (or other accelerating factor)
on the rate of a failure-causing chemical reaction. Approximate
maximum likelihood estimation is used to estimate model parameters
from the underlying mixed-effect nonlinear regression model.
Simulation-based methods are used to compute confidence intervals for
quantities of interest (e.g., failure probabilities). Finally we use
a numerical example to compare the results of accelerated degradation
analysis and traditional accelerated life test time-to-failure analysis.
Copies of preprints are available from the author upon request. Use
the preprint number (located at the top of the page) and
make the request directly to the author, Iowa State
University,
Department of Statistics, Snedecor Hall, Ames, IA 50011-1210.