Scheduling inspection and renewal of large infrastructure assets

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Journal titleJournal of Infrastructure Systems
IssueDecember 4
Pages136143; # of pages: 8
SubjectPipes and pipelines
AbstractA decision framework is introduced to assist municipal engineers and planners to optimise decisions regarding the renewal of large infrastructure assets, such as water transmission pipes, trunk sewers or other assets with high costs of failure, inspection and condition assessment. The proposed decision framework identifies a need for immediate intervention or alternatively, enables to optimise the scheduling of the next inspection and condition assessment. The deterioration of the asset is modelled as a semi-Markov process, thereby discretised into condition states. The waiting times in each state are assumed to be random variables with ?known' probability distributions. If pertinent data are scarce (as is typical in most municipalities) these probability distributions can be initially derived based on expert opinion. These distributions will then be continually updated as observed deterioration data are collected over time. Monte-Carlo simulation is used to calculate the distributions of the cumulative waiting times. Conditional survival probabilities are used to compile age-dependent transition probability matrices in the various states. The expected discounted total cost associated with an asset (including cost of intervention, inspection and failure) is computed as a function of time. The time to schedule the next inspection/condition assessment is when the total expected discounted cost is minimum. Immediate intervention should be planned if the time of minimum cost is less than a threshold period (2 to 3 years) away. A computer program was prepared for demonstration and proof of concept. The decision framework lends itself to a computer application fairly easily. Although usable in its current form, this paper identifies some issues that require as yet unavailable data as well as more research in order to develop the framework into a comprehensive application tool.
Publication date
AffiliationNRC Institute for Research in Construction; National Research Council Canada
Peer reviewedYes
NRC number44298
NPARC number20378982
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Record identifier930af743-370a-436c-bc75-a56072bd471a
Record created2012-07-24
Record modified2016-05-09
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