Integrating Risk Estimates into the Planning of Preventive Maintenance for Large Portfolios of Bridges

Road managers must anticipate preventive maintenance intervention needs for all bridges in their network. This must be done years ahead of time, so that there is sufficient time to perform the appropriate detailed investigations of the structures by engineering offices, to combine with the interventions on other objects and schedule them, to obtain financing, and to prepare projects. Preventive maintenance interventions are, however, not always executed at the optimal time due to multiple factors, including variability in early overviews of upcoming intervention needs, lack of resources to conduct detailed investigations and lack of resources to carry out the interventions. Consequently, some interventions are executed earlier than required and some later, leading to either higher than necessary expenditures or higher than necessary risks. While existing bridge management systems do an admirable job in predicting when future interventions are required, there is potential to improve how they can help determine which investigations or interventions are to be postponed if necessary.
The work presented in this paper meets this challenge by demonstrating how standardized overviews of bridge related risks could be integrated into these systems, where the risk estimates are made using fault trees and standardized estimates of probabilities and consequences of base events. The top events of the fault trees are servicerelated events associated with the detection of situations related to bridges that would cause interruptions to service, e.g., the discovery of an excessively large crack that would cause a manager to reduce traffic loads on the bridge until at least detailed engineering investigations could be conducted. The consequences for each top event are approximated using parameters that enable quick estimation for all bridges in a network, e.g., the expected user costs because of increased travel time due to traffic deviations. The method is demonstrated on four highway bridges in Switzerland.

Keywords: Bridge, Preventive maintenance, Emergency interventions, Risk estimates, Service risk.