Direct Prediction Methods on Lifetime Distribution of Organic Light-Emitting Diodes From Accelerated Degradation Tests
- Authors
- Park, Jong In; Bae, Suk Joo
- Issue Date
- Mar-2010
- Publisher
- Institute of Electrical and Electronics Engineers
- Keywords
- Accelerated degradation test; delta approximation; lifetime distribution-based procedure; multiple imputation; nonlinear random-coefficients model; organic light-emitting diode
- Citation
- IEEE Transactions on Reliability, v.59, no.1, pp 74 - 90
- Pages
- 17
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE Transactions on Reliability
- Volume
- 59
- Number
- 1
- Start Page
- 74
- End Page
- 90
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/175355
- DOI
- 10.1109/TR.2010.2040761
- ISSN
- 0018-9529
1558-1721
- 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.
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