
Adding up the numbers in effective asset life-cycle management
Mathematical optimization has long been used in forestry to determine appropriate harvesting and planting, relative to the life spans of trees. The New Brunswick Department of Transportation is using similar methods to plan the long-term treatment of roads and bridges.
Anyone working in the transportation or civil infrastructure industries is most likely quite familiar with the management practice commonly known as "fix the worst first." It's a practice necessitated by aging infrastructure, insufficient funding and complex, competing priorities. With life-cycles that can stretch hundreds of years, these factors make informed decision-making and effective resource allocation daunting challenges.
Consider the complexities of monitoring deterioration: of roads, bridges, signs, sewers, etc. Then factor in their increasing use due to expanding populations and heavier volumes of traffic. Consider the boom-bust cycles that result in periods of significant expansion followed by periods of maintenance. Bear in mind adjacency issues: the proximity of pavements, culverts, sewers, curbs, sidewalks, pipes and signs to one another.

To put all of this into perspective, New Brunswick's Department of Transportation (NBT), for example, maintains approximately 3,000 bridges across the province: some old, some new, all built to last a long time, and consequently with long treatment cycles. Which ones do you treat, how, and how often? Add to these considerations 18,000km of highways, 18 ferries, and 240,000 driveways and basins. The mathematical calculations become truly mind-boggling.
In 2002, NBT began looking for an alternative to this ongoing operational dilemma, one that would take into account the complexities of the province's transportation network, and that would systematically deliver optimal treatment plans for all assets at the least cost. In conducting their research, officials looked at other transportation agencies, studying the successes and challenges of an array of asset management initiatives.
What they found was that while these engineering-centric transportation organizations were very good at making detailed operational judgments, they had yet to produce a model enabling optimal decision support at the strategic level.
A shift in culture
NBT recognized that a revolutionary asset management system would not come about without considerable change management and, in turn, a business framework within which to support that cultural shift. Drawing from best practices both in and outside the transportation industry, the team approached the system's development with the following principles in mind:
- The 80-20 rule: Eighty per cent of decisions can be made with 20 per cent of the data.
- Performance-based measures: Monitor the long-term performance of assets using strategic, quantifiable measures and targets.
- Least life-cycle cost: Evaluate treatment alternatives, enabling the network of assets to function at the lowest cost over a predetermined period.
- Asset-centric data gathering: Establish sources of information related to design material, inspection, treatment and cost.
- Continuous improvement: Incorporate mechanisms to accommodate updates to deterioration models and asset inventory.
- Evolutionary implementation: Implement and evolve the system using prototype technology and pilot districts.
Continued: Infrastructure Management Maturity Model
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