Direct Prediction Methods on Lifetime Distribution of Organic Light-Emitting Diodes From Accelerated Degradation Tests

Abstract

Abstract-Accelerated degradation testing (ADT) expedites product degradation by stressing the product beyond its normal use. To extrapolate the product's reliability at use condition, the ADT requires a known functional link relating the harsh testing environment to the usual use environment. Practitioners are often faced with a great challenge to designate an explicit form of the stress-degradation relationship a priori in accelerated degradation models. In this paper, we propose three methods to make direct inference on the lifetime distribution itself without invoking arbitrary assumptions on the degradation model: delta approximation, multiple imputation of failure-times, and the lifetime distribution-based (LDB) method. The methods are easy to implement without computational difficulty, hence they have potential in a wide range of applications for estimating lifetime distributions from ADT data. We applied the methods to two ADT data sets including a real application of commercial organic light-emitting diodes (OLED). The analysis of the examples and simulation results suggests parametric LDB and multiple imputation method as more potential alternatives to traditional failure-time approaches, especially for the case where there is neither enough physical background, nor historical evidence supporting presumed relationships between stress and the parameters of the degradation model.

Utilizing Accelerated Degradation and Field Data for Life Prediction of Highly Reliable Products

“…The mean values of the computational results are treated as the parameters' estimation. Then, reliability evaluation for ADT and the prior information for field life prediction can be obtained by (8), (10), and (11).…”

“…Thus, ADT can effectively overcome the life evaluation problem of high reliability and long-life products. 8 Wang et al 9 used ADT for life evaluation of light-emitting diode (LED)-based light bars and concluded that the failure time at normal use condition is 11 571 h. Park et al 10 used organic LED as a motivation example and provided three failure time distribution inference methods from ADT data. Bae et al 11 analyzed the ADT data of membrane electrode assembly and concluded the median failure time is 669.78 h. In addition, some researchers are concerned with the situation that both failure and degradation data exist in accelerated testing.…”

Reliability analysis based on the Wiener process integrated with historical degradation data

“…In reliability engineering, it is oftentimes infeasible to analyze reliability based on the exact lifetimes of devices or systems due to their high reliability 1–3 . Some models based on accelerated degradation testing (ADT) data have been proposed in the literature to overcome this challenge, including nonstochastic and stochastic processes 2,4–9 . Compared with nonstochastic processes, the degradation models based on stochastic processes have better application prospects.…”

A General Accelerated Degradation Model Based on the Wiener Process

“…In addition, the uncertainties from the temporal variation of the degradation process and unit-to-unit variation from the inherent heterogeneity of the tested products should be properly considered when analyzing ADT data. In the literature, two classes of models are widely used for degradation modeling, i.e., degradation path models [8,9] and stochastic process models [10,11,12], with examples for acceleration models including the Arrhenius model for temperature stress and the Eyring model for voltage stress [3,8,13]. With different combinations of degradation and acceleration models from these two directions, extensive work has been given to the statistical analysis of ADT data.…”