• DocumentCode
    1557604
  • Title

    Inference From Lumen Degradation Data Under Wiener Diffusion Process

  • Author

    Tsai, Tzong-Ru ; Lin, Chin-Wei ; Sung, Yi-Ling ; Chou, Pei-Ting ; Chen, Chiu-Ling ; Lio, Yuhlong

  • Author_Institution
    Dept. of Stat., Tamkang Univ., Tamsui, Taiwan
  • Volume
    61
  • Issue
    3
  • fYear
    2012
  • Firstpage
    710
  • Lastpage
    718
  • Abstract
    The lumen degradation of light emitting diodes subject to increasing stress loading is investigated by using a cumulative damage model. The cumulative damage process is taken as a Wiener diffusion process with a drift which depends on two stress loadings. General statistical inferences on the parameters and percentiles of the light emitting diode lifetime distribution are presented based on the cumulative damage measurements, collected from a two-variable constant-stress loading accelerated degradation test. Approximate lower s-confidence bounds of the light emitting diode lighting lifetime percentiles are given using the Fisher information of the maximum-likelihood estimators, and Bonferroni´s inequality. The application of the proposed method is illustrated by a lumen cumulative damage data set of high power light emitting diodes.
  • Keywords
    diffusion; life testing; light emitting diodes; maximum likelihood estimation; stochastic processes; Bonferroni inequality; Fisher information; Wiener diffusion process; accelerated degradation test; cumulative damage model; light emitting diode lifetime distribution; lumen degradation data; maximum likelihood estimators; s-confidence bounds; statistical inferences; stress loading; Degradation; Light emitting diodes; Load modeling; Loading; Maximum likelihood estimation; Reliability; Stress; Arrhenius law model; draft parameter; exponential law model; power law model; step-stress loading method;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/TR.2012.2207533
  • Filename
    6239641