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    On the inverse power law-normal model for life prediction of organic light emitting diodes

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    Author
    Kittaneh, Omar
    Majid, Mohamed
    Helal, Sara
    Subject
    OLED; ALT; coefficient of variation; inverse power law model; regression analysis; MLE.
    Date
    2023
    
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    Abstract
    In accelerated life testing analysis with nonthermal accelerating stress, the inverse power law (IPL) is often solely merged with a particular lifetime probability distribution with a shape parameter. Although many fundamental lifetime distributions, such as the normal distribution, are excellent fits to the experimental lifetime data, they have not been considered as they lack the shape parameter. As such, this paper, for the first time, demonstrates that the shape parameter can be replaced by the coefficient of variation, allowing the use of normal distributions in this context. The work further introduces the IPL-normal model in a rigorous mathematical setup that precisely leads to the least squares estimating equations and maximum likelihood estimates of the IPL-normal accelerating parameters and the general coefficient of variation. The proposed model uses accelerated experimental data to successfully predict the lifetime of organic light-emitting diodes (OLEDs) at use conditions. Based on these fundamentals, the predictions are benchmarked with prior works that were validated by market studies.
    Department
    NSMTU
    Publisher
    Wiley
    Journal title
    Quality and Reliability Engineering International
    DOI
    https://doi.org/10.1002/qre.3378
    ae974a485f413a2113503eed53cd6c53
    https://doi.org/10.1002/qre.3378
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