Yazdan T. Emrani, PE, Director of Public Works, City of Glendale, CA
Increasingly, government agencies and municipalities are looking to streamline their one-to-one GIS operations and move toward enterprise-wide GIS. In today’s world of shrinking budgets and tight labor markets, it is no longer possible to have separate entities within an organization with separate GIS or asset management operations and different. It also makes sense to achieve efficiency and maximize dollars invested by achieving the primary goal for the entire organization and across many departments and group lines.
Experience has shown that a significant number of infrastructure repairs are carried out unplanned. These repairs can cost between 5 and 16 times the normal scheduled repairs. In this time of budget cuts and limited resources, the ability to optimize the use of maintenance dollars by using predictive models in the planning stages is quickly becoming a reality of infrastructure management. Using a predictive performance and asset management GIS model to optimize capital improvement projects (CIPs) and maintenance budgets, identify and prioritize repairs, and create “What…If” scenarios where you can capture different funding levels and determine the optimal repair scenarios for your infrastructure, is critical.
An integrated MIS and asset management system is a methodical approach to optimizing the allocation of scarce resources to achieve a defined goal. This is called the “Goldilocks approach” to operations and maintenance; not too much that you spend money unnecessarily, and not too little that it will cost you more later due to neglect and deferred maintenance, but just the right amount at the right time.
For example, many cities have extensive and aging underground sewer infrastructure. Traditionally, age and hardware have been the only factors used to prioritize inspections. Infrastructure is widely spread over a wide geographic area, making it difficult to track and maintain assets, leading to significant risks to the public and the environment in the event of failure. This traditional approach is not sufficient and does not take into account a deeper understanding of the variables leading to failure, or the impact of failures on the community and the environment. Understanding the factors related to sewer line criticality allows agencies to focus their inspection programs. Each of these criticality factors can be categorized into two broad areas:
1. Consequence of failure (COF): usually location related, and relates the impact of the failure in terms of repair cost, disruption to the public and economy in general, degradation of system operation and damage to the environment
2. Probability of failure (LOF): concerns the probability of failure and depends on the types of pipe materials, the existence of defects observed and the impact of external factors on the rate of deterioration (soil conditions, level of water table, and surcharge frequency)
“An integrated GIS and asset management system is a methodical approach to optimizing the allocation of scarce resources to achieve a defined goal.”
The information can be used for the process of prioritizing inspections and rehabilitation based on the consequences and risk of sewer failure, as described above. The first step in prioritization is to assess the consequence of the failure, usually related to the cost of performing an emergency repair and the associated disruption cost. It is important to note that when there is little data available on the condition of sewers, the consequence of failure based on external factors can be used to prioritize inspections to gather the necessary condition data.
The second step is to assess the probability of failure, taking into account the actual state of the sewer (structural, operational, grease, roots) and other factors that affect the rate of deterioration. These factors include infiltration levels, groundwater level, soil conditions, and frequency of overloading.
Using this system, a heat map can be generated where sewer pipes are color coded according to their COF and LOF scores, respectively. The highest rated sewers would have the highest risk of structural or operational failure. If the pipelines have been inspected and the information is available in the asset management system, the risk of failure can be assessed more accurately. If however, there is little information, general data can be used to make the preliminary assessment and prioritization. Finally, a GIS map showing the combined scores can be generated to produce a final ranking.
In conclusion, municipalities can and should take advantage of technology to maximize their efficiency. However, to do this, GIS and asset management applications must have the following three characteristics:
1. Simple to use – Technology should be simple, logical and foolproof to allow multiple users with different skills to use it successfully.
2. Easy to maintain – A system is a “living document” with constantly changing data. It must be easily adaptable to changes in process, technology or installation requirements.
3. Easy to expand – The capacity of the system should be easily expanded to add new functionality and give the user access to future technological developments.