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

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Wilson, Kevin and Quigley, John and Bedford, Tim and Walls, Lesley (2013) Bayes linear Bayes graphical models in the design of optimal test strategies. International Journal of Performability Engineering, 9 (6). pp. 715-728. ISSN 0973-1318

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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.

ORCID iDs

Wilson, Kevin, Quigley, John ORCID logoORCID: https://orcid.org/0000-0002-7253-8470, Bedford, Tim ORCID logoORCID: https://orcid.org/0000-0002-3545-2088 and Walls, Lesley ORCID logoORCID: https://orcid.org/0000-0001-7016-9141;
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