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Accelerated life test (ALT) planning in Bayesian framework is studied in this paper with a focus of differentiating competing acceleration models, when there is uncertainty as to whether the relationship between log mean life and the stress variable is linear

Accelerated life test (ALT) planning in Bayesian framework is studied in this paper with a focus of differentiating competing acceleration models, when there is uncertainty as to whether the relationship between log mean life and the stress variable is linear or exhibits some curvature. The proposed criterion is based on the Hellinger distance measure between predictive distributions. The optimal stress-factor setup and unit allocation are determined at three stress levels subject to test-lab equipment and test-duration constraints. Optimal designs are validated by their recovery rates, where the true, data-generating, model is selected under the DIC (Deviance Information Criterion) model selection rule, and by comparing their performance with other test plans. Results show that the proposed optimal design method has the advantage of substantially increasing a test plan׳s ability to distinguish among competing ALT models, thus providing better guidance as to which model is appropriate for the follow-on testing phase in the experiment.

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Title
  • Simulation-Based Bayesian Optimal ALT Designs for Model Discrimination
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Date Created
2015-02-01
Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1016/j.ress.2014.10.002
    • Identifier Type
      International standard serial number
      Identifier Value
      0951-8320
    Note
    • NOTICE: this is the author's version of a work that was accepted for publication in RELIABILITY ENGINEERING & SYSTEM SAFETY. Changes resulting from the publishing process, such as editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in RELIABILITY ENGINEERING & SYSTEM SAFETY, 134, 1-9. DOI: 10.1016/j.ress.2014.10.002

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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Nasir, Ehab A., & Pan, Rong (2015). Simulation-based Bayesian optimal ALT designs for model discrimination. RELIABILITY ENGINEERING & SYSTEM SAFETY, 134, 1-9. http://dx.doi.org/10.1016/j.ress.2014.10.002

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