Asset Condition Data Strategy
Chris Goodhand, Innovation Manager (01977 605641)
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Innovation Funding Incentive
Comms & IT
A rigorous mathematical analysis of asset condition data sets,
specifically, quantifying their robustness, making the best use of the
information contained in them, and setting recommendations for
sampling strategy. This will inform both the continued use and ongoing
development of investment modelling tools such as health indices for
improved network management and design.
Specifically the research solves the problem of the best way to estimate
the health index frequencies for a whole population of assets, when a
sample of only some of the assets has been inspected. The delivered
methodology, the “regression for proportions approach” has the
flexibility to cope with a number of situations, for example where the
inspections have occurred over a number of years. It gives good results
and is straightforward to implement.