Responsible KEG Investigator:
Professor Ian Nabney
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Type of Project: Case Award
Funder: Rolls-Royce and EPSRC
Date Commissioned: 01/2007
Date Completed:
12/2009
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Project SummaryThe aim of the project is to
provide new tools for design-risk analysis of complex systems allowing early
design decisions to be informed by their reliability impact (and in certain
cases, by implication, their safety impact). Additionally, maintenance and fault
diagnosis could be based on a deep understanding of the system components and
their interactions. Bayesian belief networks (BBNs) will be used to represent
entire engineering systems in a probabilistic way (latest generation gas
turbines will be used for proof-of-concept) in order to analyse the interactions
at both module and component level and perform a design-risk analysis. We shall
investigate how uncertainty in probabilities can be represented, inferred with,
and used to help designers assess the impact of component and design choices.
The techniques will be validated using historical information (including service
histories) from existing aeroengines.
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