Unleash Potentials in Simulation
Increasing trust in system modelling and simulation is essential for enabling Digital Twin enriched system development, production, and operation. The ITEA3 UPSIM project aims for system simulation credibility via introducing a formal simulation quality management approach, encompassing collaboration and continuous integration for complex systems.
Testing Advanced Driver Assistance Systems (ADAS) is challenging, as the environmental conditions that appear in reality are manifold and complex …
Virtual Design and Testing of medical imaging catheters by means of creating interacting device/human Digital Twins. To decrease the time to …
In the process of moving towards autonomous robotic agricultural operations, several tasks rise to ensure continuous product reliability and …
The pan-European ITEA3 Project UPSIM aims for Unleashing Potentials in Simulation by introducing quality management to modelling and simulation. Credible Digital Twins will be the game changer for accelerating innovation and reducing development costs in different industries. UPSIM will boost virtual system development and will introduce collaboration processes that will ensure data availability in distributed development environments. Broad automation via continuous testing and AI supported simulation is focused in the combination with blockchain-based traceability and quality measures, which finally leads to credible Digital Twins for various applications – from smart engineering, virtual commissioning to predictive maintenance in system operation.
Collaboration with the INTO-CPS Association will push for applications of UPSIM results within the context of Cyber-Physical Systems (CPS) for aligning approaches and bringing together interested partners. With the large number of components and their inherent...
The UPSIM Consortium with its cross-domain partners identified the need for a project-specific Digital Twin (DT) definition as no perfect match exists so far. A working group developed a first UPSIM DT definition announced today. “The Credible Digital Twin is a...
Bridging the Gap Between Industrial Use Cases, Methods and Algorithms The simulation ecosystem of the Julia programming language is rapidly growing. In order to bridge the gap between industrial use cases and methods and algorithms available in Julia, FMI.jl is...
Digital Twin is one of the emerging technologies in discussion in almost all industrial sectors and directly refers to the physical asset and allows it to be simulated, controlled and improved. A recent market study outlines that less than 1 % of physical machines and components “are modelled such that the models capture and mimic behaviour” today! This fact directly indicates the missed exploitation potential of modelling and simulation.
UPSIM is aiming for Credible Digital Twins and will change this situation significantly with predictive capabilities, leading to an opening and the accessibility of multi-billion markets prospected like for virtual commissioning and predictive maintenance.
Modelling and Simulation is used in many industries for supporting classical system design, early-stage testing, or virtual commissioning. All these current applications of modelling and simulation have one thing in common – finally, expensive real testing is mandatory. Taking the related CAX costs (education, tool license fees, IT infrastructure, etc.) into account someone could reasonably ask for a positive and timely return of invest in modelling and simulation.
The essential value of modelling and simulation is seen twofold: by the support in early-stage decisions making and the replacement of a significant number of real tests. But as long as simulation possess unclear modelling and approximation gaps to the corresponding real-world system at hand, these potentials will not be accessible, and the current situation will not change.
Therefore, the UPSIM consortium identified credibility and trust in system modelling and simulation as the key enabler for return of invest, where compared to software development modelling and simulation quality is ensured by processes and evaluation models.