Asset Management Framework for Integrated Municipal Infrastructure
Publication: Journal of Infrastructure Systems
Volume 26, Issue 4
Abstract
Municipalities are experiencing high inefficiency and financial burden imposed by their underperforming aging infrastructure. One-third of Canada’s municipal infrastructure is in fair, poor, and failing condition states, increasing the risk of service disruption and leaving decision-makers with no choice but to undertake immediate intervention. Furthermore, the massive number of intervention activities occurring in cities leads to detrimental social, environmental, and economic impacts on the community. Thus, coordinating municipal infrastructure maintenance is progressively becoming of paramount importance to cope with those tough challenges and reduce service disruptions, repair cost, and time. This research presents an asset management solution to ensure proper expenditure utilization while maintaining infrastructure performance. The framework revolves around three core models: (1) a central database that contains detailed asset inventory for the infrastructure systems; (2) multidimensional computational models to assess the performance of the intervention plan through the duration and cost savings as well as the asset condition state; and (3) a trilevel multiobjective goal optimization model that relies on a combination of metaheuristic rules, goal optimization, and genetic algorithms to plan the corridor interventions across the planning horizon. To demonstrate the functionality of the framework, the system was applied to a stretch of roads, water, and sewer networks from the city of Montreal. The preliminary results of the coordinated intervention scenario displayed an overall improvement of 8%, broken down to 11% improvement in the network condition state, 7% financial savings, and 6% temporal savings, as opposed to the conventional (uncoordinated) intervention scenario. Furthermore, the coordinated intervention scenario proved to be more efficient in more than 70% of the corridors under study, revealing less number of visits to the same corridor and causing less service disruption to the surrounding community, as opposed to the conventional intervention scenario.
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Data Availability Statement
All data generated or analyzed during the study are included in the published article.
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© 2020 American Society of Civil Engineers.
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Received: Apr 22, 2018
Accepted: Jul 13, 2020
Published online: Sep 19, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 19, 2021
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