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

Mohammed Abdul Majid, Sara Helal*, Omar Kittaneh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish
Pages (from-to)2677-2685
Number of pages9
JournalQuality and Reliability Engineering International
Volume39
Issue number7
DOIs
StatePublished - Nov 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 John Wiley & Sons Ltd.

Keywords

  • ALT
  • MLE
  • OLED
  • coefficient of variation
  • inverse power law model
  • regression analysis

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research

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