Water utilities from all around the world have relied on Fracta to improve their water main networks.
Learn How Fracta Helps Improve Water Main Networks
Below are just some of the ways water utilities around the country have used Fracta's machine learning technology to improve their water main network.
East Bay Municipal Utility Department, Ca
EBMUD has worked with Fracta for the past 4 years as an advisor and close utility partner to identify the best ways utilities can leverage machine learning day to day.
City of Topeka, Ks
Topeka wanted to consider both the Likelihood of Failure and the Consequence of Failure in its replacement prioritization program, so Topeka management used the Fracta TotalRisk tool (BRE). Topeka saved ≈$18,000 on repairs for one project alone. With 5-6 such projects annually, Fracta condition assessment on average saves Topeka $80-100k per year, delivering a strong Return on Investment in the first year of usage.
San Francisco Public Works, Ca
By using Fracta’s machine learning algorithm, SFPUC was able to meet and exceed their annual pipe replacement goal of 13 miles by prioritizing the top 1% of riskiest pipes.
Arlington Water Utilities, Tx
Arlington Water Utilities knew its previous water replacement methodology likely had erroneous presumptions and internal bias. Fracta’s likelihood of failure prediction model is an improvement to our old rationale and correlates very well with subsequent break events. Fracta has earned our trust and is now a primary component for prioritizing water main replacements.
We are anticipating that this technology will guide us in prioritizing the replacement of our water infrastructure that is most vulnerable to failure. In addition, this added information will provide valuable information to Public Works staff as they work to repair water main breaks as quickly and efficiently as possible.
— Max Slankard, Director of Public Works, Skokie, Illinois
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