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dc.contributor.authorKittaneh, Omar
dc.contributor.authorMajid, Mohamed
dc.contributor.authorHelal, Sara
dc.date.accessioned2023-06-04T10:00:51Z
dc.date.available2023-06-04T10:00:51Z
dc.date.issued2023
dc.identifier.issn1099-1638en_US
dc.identifier.doihttps://doi.org/10.1002/qre.3378en_US
dc.identifier.urihttp://hdl.handle.net/20.500.14131/881
dc.descriptionThe paper introduces a new model for accelerated life testing analysis with nonthermal accelerating stress, which combines the inverse power law (IPL) with a normal distribution. Typically, lifetime probability distributions with a shape parameter are used in this context, but many distributions without this parameter are excellent fits to experimental lifetime data and have not been considered. For the first time, the paper demonstrates that the coefficient of variation can replace the shape parameter, allowing the use of normal distributions. The IPL-normal model is introduced in a mathematical setup that leads to the least squares estimating equations and maximum likelihood estimates of the parameters. This model uses accelerated experimental data to predict the lifetime of organic light-emitting diodes (OLEDs) at use conditions and is benchmarked against prior works validated by market studies.en_US
dc.description.abstractIn 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.en_US
dc.language.isoen_USen_US
dc.publisherWileyen_US
dc.subjectOLED; ALT; coefficient of variation; inverse power law model; regression analysis; MLE.en_US
dc.titleOn the inverse power law-normal model for life prediction of organic light emitting diodesen_US
dc.source.journalQuality and Reliability Engineering Internationalen_US
dc.contributor.researcherExternal Collaborationen_US
dc.contributor.labNAen_US
dc.subject.KSAENERGYen_US
dc.contributor.ugstudent0en_US
dc.contributor.alumnaeSara Helalen_US
dc.source.indexWoSen_US
dc.contributor.departmentNSMTUen_US
dc.contributor.pgstudent0en_US
dc.contributor.firstauthorMajid, Mohamed


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