A Bayesian approach to degradation-based burn-in optimization for display products exhibiting two-phase degradation patterns

Tao Yuan, Suk Joo Bae and Xiaoyan Zhu

Reliability Engineering and System Safety, 2016, vol. 155, issue C, 55-63

Abstract: Motivated by the two-phase degradation phenomena observed in light displays (e.g., plasma display panels (PDPs), organic light emitting diodes (OLEDs)), this study proposes a new degradation-based burn-in testing plan for display products exhibiting two-phase degradation patterns. The primary focus of the burn-in test in this study is to eliminate the initial rapid degradation phase, while the major purpose of traditional burn-in tests is to detect and eliminate early failures from weak units. A hierarchical Bayesian bi-exponential model is used to capture two-phase degradation patterns of the burn-in population. Mission reliability and total cost are introduced as planning criteria. The proposed burn-in approach accounts for unit-to-unit variability within the burn-in population, and uncertainty concerning the model parameters, mainly in the hierarchical Bayesian framework. Available pre-burn-in data is conveniently incorporated into the burn-in decision-making procedure. A practical example of PDP degradation data is used to illustrate the proposed methodology. The proposed method is compared to other approaches such as the maximum likelihood method or the change-point regression.

Keywords: Burn-in; Degradation model; Gibbs sampling; Hierarchical Bayesian model; Reliability (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:155:y:2016:i:c:p:55-63

DOI: 10.1016/j.ress.2016.04.019

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