Advanced Analytics | Custom Analytics + Software Solutions | Data Visualisation + Reporting Solutions
Harmonic was selected as the Data Science squad within the Waters Services Reform National Transition Unit (NTU). During this time, the squad developed a suite of data science solutions centred around the identification and reduction of water leakage. These solutions are now available for the benefit of all councils.
Water distribution networks across the country are approaching end-of-life, leading to increased maintenance costs and deteriorating service. Prioritising assets for maintenance and renewal correctly is key to maintaining acceptable levels of service within budget, and reducing leakage and water service disruptions.
Current industry-standard methods call for replacing pipes near estimated end-of-life based on their material alone. By using statistically-driven models, additional asset information can be incorporated so that pipes with useful life remaining are less likely to be replaced and rapidly deteriorating pipes are better targeted.
Harmonic developed AssetPulse to forecast maintenance budgets and probable unexpected expenditure. Combined with tweakable renewal policy parameters, water industry experts can very quickly compare and adjust different policies and see their effects decades down the line. This facilitates balancing investment into asset maintenance in the present and incurred costs in fixing pipe failures in the future.
AssetPulse implements two types of policy: an age-based approach as a baseline, and a data-driven policy based on asset data and prior failure history. As the user adjusts the policy parameters by the criticality of the pipe assets, the solution dynamically produces forecasts for:
It also produces the expected cost of pipe failures, produced by analysing hundreds of potential future scenarios.
The tool helps asset planners’ large-scale strategic decision-making by including geospatial visualisations at whole-network scales, allowing rapid identification of problematic network sections, locations of interest, or regions of cost intensification due to urban development. To help identify and incorporate risks, these visualisations also support overlays of areas prone to liquefaction or floods, fault lines, and others.
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