Standard Article

Accelerated Life Models

  1. Mikhail Nikulin

Published Online: 15 JUN 2010

DOI: 10.1002/9780470400531.eorms0004

Wiley Encyclopedia of Operations Research and Management Science

Wiley Encyclopedia of Operations Research and Management Science

How to Cite

Nikulin, M. 2010. Accelerated Life Models. Wiley Encyclopedia of Operations Research and Management Science. .

Author Information

  1. Université Victor Segalen, IMB, Bordeaux, France

Publication History

  1. Published Online: 15 JUN 2010

Abstract

Failures of highly reliable units are rare. One way of obtaining complementary reliability information is to do accelerated life testing (ALT), that is, to use higher level of experimental factors, hence to obtain failures quickly. Another way of obtaining complementary reliability information is to measure some parameters which characterize the aging or wear of the product in time. Statistical inference from ALT is possible if failure time regression models relating failure time distribution with external explanatory variables (covariates, stresses) influencing the reliability are well chosen. Statistical inference from failure time-degradation data with covariates needs even more complicated models relating failure time distribution, not only with external but also with internal explanatory variables (degradation, wear) which explain the state of units before the failures. In the last case models, for degradation process distribution are needed too. We discuss the most-used failure time regression models used in statistics of accelerated trials for analysis of failure time and failure time-degradation data with covariates.

Keywords:

  • accelerated experiment;
  • AFT model;
  • accelerated life testing;
  • covariate;
  • changing shape and scale model;
  • degradation model;
  • Meeker's path model;
  • nonparametric model;
  • parametric model;
  • power generalized Weibull family;
  • redundant system;
  • Sedyakin's model;
  • semiparametric model;
  • shock process;
  • time-varying stress;
  • time-scaled γ process