Bayes linear Bayes graphical models in the design of optimal test strategies

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Abstract

Test and analysis plays a vital role in reducing uncertainty about the true performance of an engineering system. However tests can be expensive and designing an optimal test strategy can be challenging. We propose a Bayesian modelling process, which takes the form of a Bayesian Network, to determine anticipated test efficacy. Such a model supports engineering managers in assessing trade-offs between test resources and uncertainty reduction. Inference based on a full Bayesian model can be computationally demanding to the extent that it can limit practical application. To overcome this constraint, we develop a Bayes linear approximation for inference. This approach is known as a Bayes linear Bayes graphical model. After explaining the key principals of the method, we provide an application to a real industrial test to establish the condition of an ageing engineering system.
Original languageEnglish
Pages (from-to)715-728
Number of pages14
JournalInternational Journal of Performability Engineering
Volume9
Issue number6
Publication statusPublished - Nov 2013

Keywords

  • bayesian network
  • bayes linear kinematics
  • engineering test strategy
  • reliability analysis
  • uncertainty quantification

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