Currently, it is hard to estimate the reliability parameters of organic light emitting diode (OLED) when conducting life test at normal stress, due to the remarkably improved life of OLED to thousands hours. This work adopted three constant stress accelerated life tests (CSALT) to predict the life of white OLED in a short time. Weibull function was applied to describe the life distribution, and shape parameters and scale parameters were estimated by least square method (LSM). Experimental test data were statistically analyzed by using self-developed software. The life of white OLED predicted via this software is well agreement with those reported from customers. Numerical results indicated that the assumptions of CSALT are correct and the CSALT is feasible to predict the life of white OLED. Our work confirms that the life of white OLED meets Weibull distribution and that the accelerated life equation conforms to inverse power law. Furthermore, the precise accelerated parameters are shown to be particularly useful to enable a rapid estimation of the white OLED life.
In order to accurately acquire the life time information for the organic light emitting diode (OLED), an experiment based on the normal stress life test was carried out to gain the data for the luminance degradation tests. The luminance degradation model of OLED was established based on the Weibull function and the least square method. Combined with luminance degradation data, Weibull parameters were estimated, the qualitative and the quantitative relationship between the initial luminance and the OLED life was obtained, and the life estimation of the product was achieved. Numerical results show that the test scheme is feasible, the luminance degradation model proves to be reliable for the OLED life estimation, and the fitting accuracy is very high by comparison with the test data fluctuation. Moreover, the real life time of the OLED is measured, which can verify the validity of the assumptions used in accelerated life test methods and provide manufacturers and customers with significant guidelines.
In order to obtain reliability information for a white organic light-emitting diode (OLED), two constant and one step stress tests were conducted with its working current increased. The Weibull function was applied to describe the OLED life distribution, and the maximum likelihood estimation (MLE) and its iterative flow chart were used to calculate shape and scale parameters. Furthermore, the accelerated life equation was determined using the least squares method, a Kolmogorov-Smirnov test was performed to assess if the white OLED life follows a Weibull distribution, and self-developed software was used to predict the average and the median lifetimes of the OLED. The numerical results indicate that white OLED life conforms to a Weibull distribution, and that the accelerated life equation completely satisfies the inverse power law. The estimated life of a white OLED may provide significant guidelines for its manufacturers and customers.
Focusing on improving the accuracy of existing life prediction models for optoelectronic products, the three‐parameter Weibull right approximation method (TPWRAM) was employed to substitute exponential function based on the least square method in the analysis and two‐staged methods. Two optimized models were established (Model I and Model II), based on maximum likelihood estimation and the Monte Carlo method, respectively. One group of conventional life tests (CLTs) of vacuum fluorescent display (VFD) were conducted to collect luminance degradation data for each sample, and the two optimized models were applied to achieve VFD life prediction and obtain mean time to failure, median life, and confidence intervals. The results indicate that the CLT test design is correct and feasible, the amount of data on luminance degradation is large, and the test data selection method is reasonable. Model I and Model II optimized by TPWRAM both reflect the VFD luminance variation law well, and the predicted life approaches VFD service life from user feedback, proving that the two models are precise, and thus, can provide technical references for researchers and engineers regarding aspects of life prediction.
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