TITLE:
Public Infrastructure Asset Assessment with Limited Data
AUTHORS:
Frederick Bloetscher, Lloyd Wander, Greg Smith, Nihat Dogon
KEYWORDS:
Bayesian, Information Theory, Asset Uncertainty, Infrastructure
JOURNAL NAME:
Open Journal of Civil Engineering,
Vol.7 No.3,
September
26,
2017
ABSTRACT: When creating an asset management plan, missing data is perceived to be a huge problem, especially when the event data (breaks in water distribution pipes as an example) are not tracked. The lack of tracking makes it difficult to determine which factors are the critical ones. Many utilities lack the resources for examining buried infrastructure, so other methods of data collection are needed. The concept for this paper was to develop a means to acquire data on the assets for a condition assessment (buried pipe is not visible and in most cases, cannot really be assessed). What was found was that for buried infrastructure, much more information was known than anticipated. Knowing exact information is not really necessary. However, there was a need to track event-breaks, flooding etc.—what would indicate a “failure”.The latter would be useful for predicting future maintenance needs and the most at-risk assets.