Bivariate constant stress degradation model: LED lighting system reliability estimation with two‐stage modelling

Abstract

Light-emitting diode (LED) lamp has received great attention as a potential replacement for the more commercially available lighting technology, such as incandescence and fluorescence lamps. LED which is the main component of LED lamp has a very long lifetime. This means that no or very few failures are expected during LED lamp testing. Therefore, degradation testing and modelling are needed. Because the complexity of modern lighting system is increasing, it is possible that more than one degradation failures dominate the system reliability. If degradation paths of the system's performance characteristics (PCs) tend to be comonotone there is a likely dependence between the PCs because of the system's common usage history. In this paper, a bivariate constant stress degradation data model is proposed. The model accommodates assumptions of dependency between PCs and allows the use of different marginal degradation distribution functions. Consequently, a better system reliability estimation can be expected from this model than from a model with independent PCs assumption. The proposed model is applied to an actual LED lamps experiment data.

A Bayesian optimal design for accelerated degradation tests

“…Similarly, a gamma distribution is used as the prior distribution for 2 , with mean 89.84 and standard deviation chosen such that a central 90% probability interval for 2 is approximately between 89 and 90.5. A gamma distribution is used as the prior distribution for 3 , with mean 0.5204 and standard deviation chosen such that a central 90% probability interval for 3 is approximately between 0.48 and 0.56. Finally, a gamma distribution is used as the prior distribution for , with mean 10 000 and standard deviation chosen such that a central 90% probability interval for is approximately between 9900 and 10 100.…”

“…), accelerated degradation tests (ADT) are commonly used to quickly obtain products' reliability information, provided there is (1) a measurable quality characteristic whose time-dependent degradation is associated with products' reliability, and (2) a relationship that links the accelerated testing environment to the use condition. Readers might refer to Sari et al 3 and Pan and Crispin 4 for recent successful applications of ADT in the reliability assessment of LED lighting systems.…”

Lifetime prediction based on Gamma processes from accelerated degradation data

“…An effective ADT must guarantee that the failure mechanism of products under different accelerated stresses remains consistent, so the lifetime characteristics at the normal use stress level can be extrapolated from accelerated degradation data. The applications of ADT can be referred by light bars, 1 integrated logic family, 2 light-emitting diodes 3,4 and carbon-film resistors, 5 …”

Lifetime Distribution and Associated Inference of Systems with Multiple Degradation Measurements Based on Gamma Processes

“…First, they considered the correlation between the degradation measure and the failure event by introducing a probabilistic measure, and then proposed a state-space model to describe the evolution of the degradation process by incorporating both the degradation dynamics and random stress effects. Sari et al [11] proposed a two-stage reliability model for bivariate degradation data. With the proposed model, not only the marginal reliability but also the system reliability can be assessed.…”