Real-Time Digital Twins
Description
We live in a world of exploding complexity driven by technical evolution as well as highly volatile socio-economic environments. Managing complexity is a key issue in everyday decision-making such as providing safe, sustainable, and efficient industrial control solutions as well as solving today's global grand challenges such as the climate change. However, the level of complexity has reached our cognitive capability to take informed decisions. Digital Twins, tightly integrating the real and the digital world, are a key enabler to support decision making for complex systems. They allow informing operational as well as strategic decisions upfront through accepted virtual predictions and optimisations of their real-world counter parts.
Digital Twins [6] are specific virtual representations of physical objects. A Digital Twin integrates all data, models, and other information of a physical asset generated along its life cycle for a dedicated purpose. This is typically reproducing the state and behaviour of the corresponding system as well as predicting and optimising its performance. To this purpose, simulation methods and data-based methods are used.
Depending on the specific nature, application, and context a wide variety of nomenclature has been introduced, see e.g. [2,4,7,14]. Here, we focus on real-time Digital Twins for online prediction and optimisation of highly dynamic industrial assets and processes. By their nature, Digital Twins integrate and tightly connect several digital key technologies including mathematical modelling, simulation, and optimisation; data analytics, machine learning, and artificial intelligence; data and compute platforms from edge to cloud computing; cybersecurity; human computer interaction; and many more. Only a coordinated research effort as envisaged by the TransContinuum Initiative will allow the realisation of the full potential of Digital Twins - a key tool for decision making addressing today's industrial as well as global challenges.
Notes
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TCI-WP-Real-time-digital-twins_FINAL.pdf
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Additional details
References
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