Bayesian degradation modeling for reliability prediction of organic light-emitting diodes

Abstract

Simpler degradation models are generally preferred to simplify analytical procedure of failure-time estimation which follows the degradation modeling. However, the luminosity degradation of organic light-emitting diode (OLED) tends to exhibit an initial unstable period followed by stable and more gradual degradation. The degradation mechanisms of OLED luminosity are illustrated via a stochastic two-compartment model. Conjoining the data with prior information accumulated from field testing, we propose two hierarchical Bayesian models to characterize the nonlinear degradation path of OLED: Bayesian change-point regression model and Bayesian bi-exponential model. The hierarchical Bayesian models effectively fit the nonlinear degradation paths of OLEDs. Analytical results of OLED degradation indicate that reliability estimation from the hierarchical Bayesian models can be substantially improved over the log-linear model which has been widely accepted as a degradation model of light displays. (C) 2016 Published by Elsevier B.V.