As one of the largest energy supply companies in Germany, E.ON manages a vast network of Combined Heat and Power plant sensors, cables and grid components. Regular, proactive monitoring and maintenance of this complex network plays a vital role in improving performance – and ensuring customers continue to receive a reliable and rewarding service experience. Previously, a reliance on outdated reporting processes was making it increasingly difficult for E.ON to efficiently plan and manage predictive maintenance across these networks.
E.ON introduced Tableau to help the organisation take system monitoring and predictive maintenance into the future.
Alexander Schaaf, Visual Analytics Engineer at E.ON, says: “One of my first tasks was to help colleagues visualise the grid system of cables and substations, using shapes and colour to help them see at a glance which assets required priority maintenance,” he explains. “We can now visualise and prioritise 70,000 assets on one easy-to-use map.”
To simplify the complex monitoring of the many sensors, Alexander’s advanced analytics and artificial intelligence (AI) team developed an algorithm that maps the value of the sensors to a single ‘health index’ that is very easy to monitor. Alexander explains: “We are using this with Tableau, combined and embedded into a web page. Operators no longer sit in a control room staring at 20 screens – they can monitor everything in a unified, live visual environment. Colleagues outside of the power plant can also monitor the turbines by picking up their iPad and examining the health index.”
Other areas at E.ON are also already using Tableau; around 15 business units use the Tableau Server, while hundreds of employees use Tableau Desktop to create new dashboards and analyses.