Nowadays, simulation is used for design space exploration, virtual testing or predictive maintenance for supporting early stage product decisions. Most importantly, real testing is ultimately used to assure product quality and certification. The aim of UPSIM is to enable companies to safely collaborate on simulations in a repeatable, reliable and robust manner and to implement simulations in a Credible Digital Twin setting as a strategic capability in order for them to become an important factor in quality, cost, time-to-market and overall competitiveness.
The UPSIM project funded by the Innovation Foundation Denmark in the ITEA3 framework to work towards reduction of physical tests by providing credible digital twins. In close collaboration with Agro Intelligence ApS, Aarhus University works towards credible digital twins able to incorporate sensory data at runtime in order to improve continuously.. The project has a full budget of 18M€ (~134MDKK) and is supported with 500k€ (~3.7MDKK) by the Danish Innovation Foundation. The project brings together expertise from 31 one partners from Austria, Germany, Denmark, the Netherlands, Romania and the United Kingdom.
UPSIM is divided into 5 interrelated work packages to enable credible digital twins for production. The core problems addressed by UPSIM are:
Aarhus University is specifically involved in the use case of developing credible digital twins for agricultural robots. In the process of moving towards autonomous robotic agricultural operations, several tasks rise to ensure continuous product reliability and performance without human interaction during operation. A common challenge when developing agricultural machinery is the ability to comply with the varying physical conditions across Europe, e.g. soil type and texture, topography, etc. Furthermore, the robots need to be compatible with a wide range of equipment and tools to be an integrated part of future farming. The agricultural robots consist of multiple sensors, software, electronics and mechanics. Tests is a crucial but time-consuming. By obtaining a validated digital twin of the system, the time to market can be reduced by performing tests in a virtual setting rather than performing physical tests that are often constrained by the availability of a test field, weather conditions and fully functional subsystems. By increasing the physics-based modelling, simulation and digital twin capabilities will provide valuable insights about the overall machine performance in the design phase as well as during field operation – the Figure below illustrates the realization and work panned by the involved partners