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

Lookup NU author(s): Professor Kevin Wilson

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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 principles of the method, we provide an application to a real industrial test to establish the condition of an ageing engineering system.

Publication metadata

Author(s): Wilson KJ, Quigley J, Walls L, Bedford T

Publication type: Article

Publication status: Published

Journal: International Journal of Performability Engineering

Year: 2013

Volume: 9

Issue: 6

Pages: 715-728

Print publication date: 01/11/2013

Acceptance date: 11/06/2013

ISSN (print): 0973-1318

Publisher: Totem Publisher, Inc.

URL: http://www.ijpe-online.com/november-2013-p12-bayes-linear-bayes-graphical-models-in-the-design-of-optimal-test-strategies.html#axzz3mSqByKrm

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