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Energy Management & Monitoring

Digitalization in the industry is advancing – the amount of data from production control & planning, process monitoring, energy meters and numerous other sensors has been growing exponentially since the beginning of the computer age. Energy data represent an essential basis for the identification and evaluation of efficiency potentials. In addition, control technology measures can raise significant potential for increasing energy efficiency and energy flexibility. The focus of our research is on answering the following questions with high relevance for the industry:

1 | Data Acquisition

What measurements need to be taken in relation to the previously defined objectives in energy management (measuring point concepts for energy & operating data)?

How can low-cost sensors, mobile measurement concepts, simulations or “smart” disaggregation algorithms reduce the investment costs for measuring technology?

What ICT systems can be used to capture and compress large data in real time and high resolution?

Which further data (e.g. production and machine data) should be recorded together with energy data to show possible correlations?

2 | Energy Management & Monitoring

What do intelligent energy management systems look like?

Which key performance indicators are needed and how are they formed?

How can a system support its user with that task?

How can performance indicators and measured values be presented in line with the target group?

3 | Condition Monitoring and Predictive Maintenance

How does the recorded data correlate with the physical states of machines, components and the part quality?

How can complex coherences be revealed by e.g. machine learning?


  • ICT Architecture (Interfaces and Protocols)
  • Measuring Point Concepts for Energy and Operational Data
  • Real-Time Data Acquisition & Data Streaming Analytics
  • Low-Cost-Sensors and Disaggregation
  • Embedded Systems / Smart Monitoring
  • Guided Energy Monitoring
  • Condition Monitoring and Predictive Maintenance