Digital twins for ENERGY 4.0

Digital twin ENERGY 4.0 –
increasing the energy efficiency of industrial plants and systems

  • simulation of industrial plants and systems along the entire life cycle - design, operation, maintenance
  • increases benefits, reliability, and productivity
  • combination of physical and data-driven modelling with artificial intelligence algorithms
  • reduces costly sensor technology
  • enables remote diagnostics, fault prediction and predictive maintenance
  • considers different energy sources (electricity, heat, fuels)
  • enables optimal coupling of the sectors (industry, buildings, mobility, energy sector)
  • cuts primary energy consumption, costs, emissions, and climate impact

Level of innovation

  • combines the energy-intensive industry to Energy 4.0 via AI and offers interfaces to digital B2B market platforms
  • implementations in industry at state of the art in research & development
  • HM 2020: first broad public presentation of this competence of the TU Wien

Applications & target groups

  • retrofit possibility for increasing the efficiency of existing plants and systems
  • energy-intensive processes in the manufacturing industry, such as paper and pulp, chemicals and petrochemicals, cement, steel and non-ferrous metals, metal processing, oil and gas, food and beverages
  • energy and heat suppliers and their supply networks

 

 

Schematic illustration of how the digital twin ENERGIE 4.0 works

Digital Twins for ENERGY 4.0

Digital twins for ENERGY 4.0 – optimal design, operation, and predictive maintenance to increase overall energy efficiency, flexibility, and sustainability

Contact

Univ.Prof. Dr. René Hofmann and Peter Heimerl