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Model-based Analysis & Simulation, Digital Twins

Model-based Analysis & Simulation, Digital Twins

By means of model-based analyses and digital twins, we enable you to optimize the production process and energy use off-line, to identify possible measures and to evaluate their effect in terms of product quality and production costs.

Thanks to the AIT's many years of experience and expertise in the mathematical modelling and simulation of complex dynamic processes, we are your ideal partner for detailed analyses at component, plant and factory level.

Our spectrum ranges from

  • Energy technology for the economic use of waste heat, through high-performance heat exchangers, high-temperature storage tanks and industrial heat pumps, via which
  • Use of new energy sources and economic exploitation of fluctuating energy prices,
  • Process engineering, such as product drying or reactors, up to
  • Sequence control and application optimization in discontinuous production and energy supply systems.

We are also happy to help quickly and competently with unique questions.


Our services

  • Development of new plant concepts using simulation techniques
  • Reproduction of existing plant concepts
  • Tailor-made operational optimization
  • Optimal design and model-based characterization of components
  • Technical and economic feasibility studies, potential analyses and derivation of catalogs of measures
  • Creation of digital twins for production by interaction of physical models and neural networks

Your benefit

  • Product and production optimization
  • Cost optimization of production processes through model-based sensitivity analyses
  • Investment decision support
  • Improvement of the process understanding
  • Faster training of new staff on digital twins

Our methods

  • Computational Fluid Dynamics (CFD) for detailed analysis of heat and mass transfer.
  • Simulation and design of control and regulation concepts for electrical, thermal and mechanical systems.
  • Digitalization, horizontal and vertical networking, data acquisition and visualization
  • Statistical methods for classification, regression analysis, validation, optimization and prediction
  • Digital twins in the form of functional mockup units and neural networks

Reference projects