Abstract

Accelerated degradation testing (ADT) is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.

Highlights

  • Due to the highly competitive market, nowadays many products are requested to have long lifespans and high reliability

  • In consideration of the unit-to-unit variation, Tang, et al [18] incorporated a random variable into the acceleration model to capture the random effect and used the time-scale transformation Wiener process model for nonlinear light emitting diodes (LEDs) constant stress ADT (CSADT) data analysis under electric current stress

  • In our previous work [21], we introduced this model into accelerated degradation testing (ADT) analysis, but without the consideration of unit-to-unit variation

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Summary

Introduction

Due to the highly competitive market, nowadays many products are requested to have long lifespans and high reliability. In consideration of the unit-to-unit variation, Tang, et al [18] incorporated a random variable into the acceleration model to capture the random effect and used the time-scale transformation Wiener process model for nonlinear LED CSADT data analysis under electric current stress.

Models
Derivation of the Failure Time Distribution under the Given Stress Level
Statistical
Estimation of Ω1 for CSADT
K ni m
Estimation of Ω2 for CSADT
Estimation of Ω1 and Ω2 for SSADT
Case Study
Simulation Example
Model Comparison
Sensitivity Analysis
Ns 1 Nt k
LED Application
It is clear that thefollow degradation atThe first stress level in Figure
Resistor
Compared results
Conclusions
Full Text
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