Journal ArticleDOI
An analysis of accelerated performance degradation tests assuming the arrhenius stress-relationship
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An analytical model is developed for accelerated performance degradation tests and the method of maximum likelihood estimation is used to estimate the parameters involved, using two real examples for estimating the failure-time distribution.Abstract:
An analytical model is developed for accelerated performance degradation tests. The performance degradations of products at a specified exposure time are assumed to follow a normal distribution. It is assumed that the relationship between the location parameter of normal distribution and the exposure time is a linear function of the exposure time that the slope coefficient of the linear relationship has an Arrhenius dependence on temperature, and that the scale parameter of the normal distribution is constant and independent of temperature or exposure time. The method of maximum likelihood estimation is used to estimate the parameters involved. The likelihood function for the accelerated performance degradation data is derived. The approximated variance-covariance matrix is also derived for calculating approximated confidence intervals of maximum likelihood estimates. Finally we use two real examples for estimating the failure-time distribution, technically defined as the time when performance degrades below a specified level.read more
Citations
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Journal ArticleDOI
Identifying the failure mechanism in accelerated life tests by two-parameter lognormal distributions
TL;DR: In this article, the relation between the Arrhenius equation and the lognormal distribution in the degradation process was studied, and it was shown that the ratio of the differences between logarithmic standard deviations must be equivalent at different temperature levels.
Proceedings ArticleDOI
Rubber lifetime prediction for ADT data considering non-arrhenius behavior
Hongyu Wang,Yu Zhao,Xiaobing Ma +2 more
TL;DR: In this paper, a non-Arrhenius ADT model was used to estimate the lifetime distribution of the rubber under normal conditions. And the degradation path model was extended to similar degradation path models as well as stochastic process models.
References
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Journal ArticleDOI
An efficient method for finding the minimum of a function of several variables without calculating derivatives
Book
Statistical Methods for Reliability Data
TL;DR: In this paper, the use of Bayesian methods for reliability data is discussed and a detailed discussion of the application of these methods in the context of automated life test planning is presented.
Book
Accelerated Testing: Statistical Models, Test Plans, and Data Analyses
TL;DR: Accelerated Testing: Statistical Models, Test Plans, and Data Analyses, by W. Nelson.
Journal ArticleDOI
Accelerated Testing: Statistical Models, Test Plans, and Data Analyses
TL;DR: In this article, Accelerated Testing: Statistical Models, Test Plans, and Data Analyses Technometrics: Vol 33, No 2, pp 236-238 and this article.
Journal ArticleDOI
Using Degradation Measures to Estimate a Time-to-Failure Distribution
C. Joseph Lu,William O. Meeker +1 more
TL;DR: In this article, the authors developed statistical methods for using degradation measures to estimate a time-to-failure distribution for a broad class of degradation models, using a nonlinear mixed-effects model and developing methods based on Monte Carlo simulation to obtain point estimates and confidence intervals for reliability assessment.