Real time predictive analysis of Environment Agency MEICA flood risk management assets
Keith Solts - Environment Agency
Ability to predict asset failure before failure actually occurs is an aspiration driving the move toward real-time or near real-time monitoring of asset condition and performance. Advances in analytical techniques are enabling the integration of real-time data with data on past condition to provide performance information for the asset manager. This allows proactive decisions to repair or replace to be taken. Such technology is becoming increasingly routine. The rapid take up of new technology is driven by the need for companies to understand performance of a complex network of assets which are loaded continuously or at least a high frequency, e.g., buried pipes, tunnels, pumps.
Our MEICA assets are easy to inspect, but only loaded to capacity during flood events. This poses challenges and opportunities. A key challenge is understanding likely future performance given little actual performance history. An opportunity is associated with accessibility i.e., sensors for monitoring performance can be easily be deployed. Given the lack of past performance information, capturing as much data as possible when the asset is being loaded is important. Such performance information is required to help with pro-active maintenance and to optimise operations.
Our research seeks to clarify new and emerging sensor technologies for monitoring real time MEICA asset performance. The research will test the market in terms of availability and applicability to our assets and inform the adoption of new technology. It will ultimately demonstrate how data can be brought into an analytic environment to improve decision making.
