Estimation of Wiener Diffusion Parameters Using Process Measurements Subject to Error

  • G. A. Whitmore
Chapter

Abstract

Most materials and components degrade physically before they fail. Engineering degradation tests are designed to measure these degradation processes. Measurements in the tests reflect the inherent randomness of degradation itself as well as measurement errors created by imperfect instruments, procedures and environments. This paper describes a statistical model for measured degradation data that takes both sources of variation into account. The paper presents inference procedures for the model and discusses some practical issues that must be considered in dealing with the statistical problem.

Keywords

Degradation Process Wiener Process Measurement Error Variance Profile Likelihood Function Inverse Gaussian Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Carey, Michèle Boulanger and Koenig, Reed II. (1991), “Reliability Assessment Based on Accelerated Degradation: A Case Study,” IEEE Transactions on Reliability, 40 (5), 499–506.CrossRefGoogle Scholar
  2. Cox, D.R. and Miller, H.D. (1965), The Theory of Stochastic Processes,Chapman and Hall.Google Scholar
  3. Doksum, Kjell A. and Hóyland, Arnljot (1992), “Models for Variable-stress AcceleratedGoogle Scholar
  4. Life Testing Experiments Based on Wiener Processes and the Inverse Gaussian Distribution,“ Technomeirics,34(1), 74–82.Google Scholar
  5. Lu, Jin. (1994), “A Reliability Model Based on Degradation and Lifetime Data,” Ph.D. thesis, McGill University, Montreal, Canada.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1996

Authors and Affiliations

  • G. A. Whitmore
    • 1
    • 2
  1. 1.McGill UniversityMontrealCanada
  2. 2.Faculty of ManagementMontrealCanada

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