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Lookup NU author(s): Dr Kevin Wilson
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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 principles of the method, we provide an application to a real industrial test to establish the condition of an ageing engineering system.
Author(s): Wilson KJ, Quigley J, Walls L, Bedford T
Publication type: Article
Publication status: Published
Journal: International Journal of Performability Engineering
Print publication date: 01/11/2013
Acceptance date: 11/06/2013
ISSN (print): 0973-1318
Publisher: Totem Publisher, Inc.