Project description
Open-source software for digital twins technology
Digital replicas of physical devices – the technology behind this has expanded the realm of manufacturing. The better the digital twin can duplicate the physical object, the more accurate it will be in predicting the performance or failure of the physical device. Digital twin technologies will play an important role in Industry 4.0. The EU-funded Edge Twins HPC project will develop an open-source software tool to produce digital twins that are installed on the physical asset they represent and operate in very constrained compute environments. The aim will be to facilitate a new breed of novel real-time applications – from autonomous vehicles to small devices.
Objective
Digital twins, along with the Internet of Things and Edge computing , are expected to play a decisive role in the next decade’s industrial markets (Industry 4.0) enabling dramatic improvements in complex systems design and operation. However, this technology has not been yet widely implemented, since it requires the collaboration of experts in multiple fields and costly computational tools.
The EdgeTwins HPC project brings a different approach that will extend digital twins to new market segments and users (i.e. SMEs). It aims to develop an open-source software tool (builder) to produce digital twins that run on the Edge. That is, they are installed on the physical asset they represent, and operate in very constrained compute environments. This approach will enable a new breed of novel real-time applications, from autonomous vehicles to small devices.
The main objective of this FET Innovation Launchpad project is to evaluate the business feasibility of an open-source Digital Twin builder software for Edge applications and develop and test a demonstrator (alpha) for one or more use cases identified in the market analysis.
To do so, the participants will leverage on the high-performance computing software stemming of the ExaQute FET Proactive project. These assets will allow, using Reduced Order Modelling techniques, to model complex 4D simulations to later extract the essential features of the solution so that similar results can be obtained at a vastly reduced computational cost.
Fields of science
Programme(s)
Funding Scheme
CSA - Coordination and support actionCoordinator
08034 Barcelona
Spain