A generalized Wiener process with dependent degradation rate and volatility and time-varying mean-to-variance ratio

Shirong Zhou, Yincai Tang*, Ancha Xu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

In degradation analysis, there exist two natural features for the degradation data. The first is the dependence of degradation rate and degradation volatility, and the other is the time-varying mean-to-variance ratio. Ignoring them may lead to a significant bias in assessing lifetime information of materials. This paper proposes a generalized Wiener degradation model, which puts these two characteristics and unit-to-unit variation into consideration simultaneously. The proposed model includes many existing Wiener degradation models as special cases. Then, a generalized closed-form approximated residual lifetime distribution is given for the proposed model. Statistical inference for the model parameters is conducted based on the expectation maximizing (EM) method, and two simple auxiliary frameworks are developed for the determination of initial values and the forms of the time-scaled functions. The developed methodologies are then illustrated and verified in a simulation study and two real data analysis.

Original languageEnglish
Article number107895
JournalReliability Engineering and System Safety
Volume216
DOIs
StatePublished - Dec 2021

Keywords

  • EM algorithm
  • Inverse Gaussian distribution
  • Random effect
  • Volatility
  • Wiener process

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