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Digital twins

 

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Ceit develops digital twins as state-of-the-art tools to optimise operations in a range of industrial sectors. These precise virtual replicas enable systems to be simulated, monitored and analysed in real time, thus improving efficiency, minimising inactivity and facilitating more informed decision-making.

 
 

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Solutions

 

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Digital twins for manufacturing

We design digital twins using precise modelling of manufacturing processes, thus creating virtual replicas that enable operations to be simulated, monitored and analysed in real time. These solutions improve efficiency, reduce inactivity and facilitate decision-making in industrial environments.

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Digital twins for the circular economy

We develop digital twins as key tools in promoting the circular economy in water and waste management. These technologies enable infrastructure operations to be simulated, monitored and optimised in real time, thus identifying opportunities with a view to reducing the consumption of resources, improving operational efficiency and minimising environmental impact.

Further information

 
 

Digital twins for transport (Alphon concept)

Digital twins for transport are key tools in improving security, operational efficiency and infrastructure planning. At Ceit we develop state-of-the-art models that integrate perception, simulation and control models, thus enabling complex systems to be analysed and optimised in rail, sea and land transport. These solutions compile data in real time, simulate the evolution of assets and control the courses of action required to ensure optimum performance, prolong lifespan and reduce operating costs.

Further information

 

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Technologies

Mathematical modeling
Advanced simulation algorithms
Real-time sensor systems
ROM and hybrid models
Synthetic data generation through digital twins
Use of synthetic data for Reduced Order Model (ROM) generation

Integration with smart grids
Perception and predictive analysis
Model-based optimization
Real-time data analysis
Process automation through AI
Digital twins for predictive maintenance

 
 

Sectors of application

 

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