Using Machine Learning and GIS to Reduce the Business Risk and Cost of Maintaining Aging Drinking Water Mains

Originally Aired April 9, 2019

Asset management is a planning process that ensures a utility gets the most value from its assets and has the financial resources to rehabilitate and replace them when necessary. This also includes developing a plan to reduce costs while increasing the efficiency and the reliability of your assets. Asset management planning and latest condition assessment tools using Artificial Intelligence, specifically Machine Learning, provide a new method for aligning maintenance, repair and replacement strategies to better allocate limited resources. Machine Learning has emerged as a technology to make a significant impact in buried water infrastructure asset management.

Fracta’s cloud-based software solution uses Machine Learning to determine a pipe segment’s, Likelihood of Failure (LOF) and Consequence of Failure (COF) to assess a utility’s Business Risk Exposure (BRE). This approach gives an objective criticality score, an assessment for the entire water distribution system. This score translates the results into financial terms water engineers, planners and finance professionals can use to make fast, accurate and capital-efficient risk mitigation decisions about buried water main infrastructure, including allocation of direct inspection for leak and repair/replacement assessments. This, in turn leads to improved asset management planning for the utility.

Presenter
Doug Hatler
Chief Revenue Officer
Fracta
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Presenter
Greg Baird
President
The Water Finance Research Foundation/Group
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Presenter
Paul Carpenter
Senior Technical Sales Engineer
Fracta
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Presenter
Chad Atcheson
Pipe Rehabilitation Product Manager
Suez
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