The massive number of infrastructure intervention activities occurring in cities leads to detrimental social, environmental, and economic impacts on the community. Municipalities are experiencing high inefficiency and financial burdens imposed by their underperforming infrastructure. One-third of Canada’s municipal infrastructure is in fair, poor, and failing condition states. Consequently, the risk of service disruption dramatically increases, which forces decision-makers to take immediate corrective action to maintain them. Furthermore, aging infrastructure systems worldwide are placing tremendous pressure on governments through steeply growing budget deficits and urgent need for replacement. This study advocates for the coordination of infrastructure maintenance of the right-of-way assets (i.e. roads, water, and sewer) to minimize the service disruption along with considerable time and cost savings. Those savings are a result of the common activities that can be done once instead of ns times as well as parallel activities that can be merged to save time.
Canada’s municipal infrastructure deficit was estimated at $123 billion for the existing infrastructure, growing by $2 billion annually, with $115 billion needed for constructing new infrastructure to satisfy the growing population, which increased from 17.9 million in 1960 to 35.1 million in 2013 and is expected to be 42.5 million by 2056.
To visualize the potential savings that can result from coordinating infrastructure maintenance versus the no coordination scenario; where the maintenance of each asset is separately undertaken, four key performance indicators were modelled and analyzed:
(1) physical state, (2) life-cycle costs, (3) user costs, and (4) replacement value. Those specific indicators were selected after thoroughly investigating various reports throughout North America (i.e. America’s infrastructure report card, Canada’s infrastructure report). The system considers roads and water networks and has the potential to add up other infrastructure systems such as; sewer system, bridges, telecommunication, etc. It comprises of a database that contains different datasets such as; asset inventory, maintenance, financial, and key performance indicators. The asset inventory includes all the relevant information about the assets under investigation (i.e. physical, geographical/spatial, etc.)
This information is prone to change from one case to another. The maintenance and financial datasets include information about the maintenance strategies, which varies from one municipality to another (i.e. applicability, physical state improvement, unit cost, etc..). The key performance indicators dataset includes information about the selected indicators such as; description, category, unit of measurement, threshold, etc. Hence after, the modeling takes place in two parallel directions: (1) conventional/no coordination, and (2) coordination. In the conventional case, the assets’ maintenance is assumed to be undertaken solely with no coordination potential. However, in the coordination case, the assets’ maintenance is assumed to be undertaken either separately or with coordination, depending on the optimal case. Future prediction and deterioration models were built to compute the aging-based deterioration of the asset as well as the physical state enhancement resulting from the application of an intervention on a section basis. Markov chain deterioration was used to represent the deterioration of the road from one condition state to the other. Wiebull deterioration was used to represent the water pipes deterioration.
Furthermore, financial models were developed to compute the life-cycle costs associated with undertaking an intervention as well as the assets’ replacement value on an annual basis. Life-cycle costs include the direct and indirect costs of undertaking an intervention. User costs indicate the lost time caused by several factors including detours and rerouting that add to travel time, reduced roadway capacity that slows the travel speed and increases the travel time, and delays of opening new or improved facilities that prevent users from gaining travel-time benefits. Replacement value represents the dollar value of replacing the asset at a certain time, based on the deteriorated performance (i.e. economic loss at the time of replacement, not the full cost of replacement).
Towards the end, a powerful optimization engine, genetic algorithms, associated with some pre-applied meta heuristic rules, integer and dynamic programming were utilized to simulate thousands of solutions and find the assets’ optimal intervention schedule throughout the planning horizon. Due to the existence of multiple conflicting objectives, goal optimization (goal programming) was utilized where; deferential weights of importance among the conflicting goals as well as the assets were placed, and the objective was minimizing the sum of the positive and negative deviations from the key performance indicators’ thresholds. As highlighted earlier, the study comprises two different optimization modes for the conventional and coordination cases respectively.
To demonstrate the functionality of the coordination framework, the developed systems were applied to a 9-km stretch of the road and water networks of Kelowna, located in the southern interior of British Columbia, Canada. The network includes 20 road sections covering water pipes of different materials. The data set scales/sizes in terms of the number of collocated road sections and water pipes were scaled down several times to enable the use of the optimization techniques.
Furthermore, the study considered the sections where the road and water mains coexist and have the same length. The data was obtained from the open source City of Kelowna GIS maps. The main findings of the study, displayed in figures 1 to 4 (above), showed huge financial savings, represented through 33 percent in the lifecycle costs and 50 percent in the user costs, as well as temporal savings resulting from coordinating the maintenance actions of the collocated assets.
In simple words, let us assume you are repairing the road this year, the water network next year, and the sewer network the third year. In the conventional case, you will reconstruct the road three times, you will do the excavation two times, etc… This causes extra disruption because the same corridor is visited three times in three consecutive years. Not only is the disruption an issue, but the municipality will also end up paying extra money due to the duplicated activities. In the coordinated scenario, this corridor will be repaired once, and the municipality will end up paying less money with less disruption. Further to financial savings, specific conclusions were drawn through analyzing the section-based results of the coordination versus the conventional maintenance in terms of the frequency of carrying out interventions in the same section along the planning horizon, as displayed in figure 5. The coordinated maintenance showed to be much more efficient compared to the conventional maintenance in 90 percent of the sections, resulting in fewer number of maintenance actions and accordingly causing less service disruption as well as less user costs.
In summary, coordinating the maintenance of the collocated assets revealed enormous temporal and financial savings, which could act as a long-term solution to re-pay the debt of the growing infrastructure deficit.
SOLIMAN ABU-SAMRA is a professional civil engineer with professional and academic experience in project and infrastructure asset management. Soliman pursued his bachelor’s and master’s degrees in construction and infrastructure management and is currently working towards his doctoral degree in Civil Engineering at Concordia University. Throughout his academic career, he published seven books and more than 20 journal and conference articles about establishing proper management systems for multiple infrastructure assets and construction operations. He has conducted research on asset management, life cycle costing analysis, asset performance, budget allocation, and funding optimization for different infrastructure systems including but not limited to; water mains and stations, sewer networks, pipelines, highways, bridges, district cooling plants, coastal structures, and buildings.
PROF. TAREK ZAYED has his Ph.D., M.Sc., and B.Sc. in Construction Engineering and Management. He has 30 years of professional experience working in the construction industry and in academic posts in USA, Canada, Hong Kong, and abroad. He is a professor in the building and real estate department at the Hong Kong Polytechnic University. He conducted research on infrastructure management, simulation and artificial intelligent applications in construction, asset performance, scheduling, life cycle cost analysis, budget allocation, and risk assessment for construction and rehabilitation of highways, oil and gas pipelines, water and sewer systems, and bridges. His research interests are centered in simulation and IT-based modeling, productivity assessment and analysis of construction operations, construction, infrastructure and asset management, performance assessment and rehabilitation of municipal infrastructure systems, optimized capital investment plan for assets, and integrated decision support system.
