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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
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.
Cox, D.R. and Miller, H.D. (1965), The Theory of Stochastic Processes,Chapman and Hall.
Doksum, Kjell A. and Hóyland, Arnljot (1992), “Models for Variable-stress Accelerated
Life Testing Experiments Based on Wiener Processes and the Inverse Gaussian Distribution,“ Technomeirics,34(1), 74–82.
Lu, Jin. (1994), “A Reliability Model Based on Degradation and Lifetime Data,” Ph.D. thesis, McGill University, Montreal, Canada.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1996 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Whitmore, G.A. (1996). Estimation of Wiener Diffusion Parameters Using Process Measurements Subject to Error. In: Jewell, N.P., Kimber, A.C., Lee, ML.T., Whitmore, G.A. (eds) Lifetime Data: Models in Reliability and Survival Analysis. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-5654-8_47
Download citation
DOI: https://doi.org/10.1007/978-1-4757-5654-8_47
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4753-6
Online ISBN: 978-1-4757-5654-8
eBook Packages: Springer Book Archive