E.ON monitors and analyses deep-learning algorithms and mission critical systems on the fly using Tableau


Real-time analysis of Combined Heat and Power systems ensures reliable customer experience
70,000 energy network components visualised in one easy-to-use map
Hundreds of critical sensors turned into one unified, interactive dashboard

E.ON is one of the leading energy groups in Europe with around 75,000 employees, headquartered in Essen, Germany. The company uses Tableau to help business units throughout the organisation gain deep insights from their data – all in compliance with stringent data protection regulations.

In addition to supporting other areas, E.ON uses Tableau to monitor the status of hundreds of sensors on each Combined Heat and Power (CHP) system, by visualising and analysing deep learning algorithms that determine their health and state. Similarly, their Grid system monitors tens of thousands of network components within one single map. These visual, unified insights into critical energy systems underpins the company’s predictive maintenance strategy and ensures they operate at optimal performance.

We can now visualise and prioritise 70,000 assets on one easy-to-use map.

Real-time, map-based analysis of hundreds of critical sensors ensures reliable customer experience

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 Previously, a reliance on outdated reporting processes was making it increasingly difficult for E.ON to efficiently plan and manage predictive maintenance across these networks.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.

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.