Industrial
Metaverse
The Convergence of Physical and Virtual Space
Your contact person
Heike Wohlfeld
Research Coordinator ARENA2036 e.V.
Generation of Digital Twins for Production Equipment
For many small and medium-sized businesses, the Industrial Metaverse still seems like a distant dream. There is a lack of real-world examples that clearly illustrate the costs and benefits. This is exactly where we come in: Through ARENA2036’s“Reallabor Industrial Metaverse”project, we’re bringing the technology from theory straight to our shop floor.
Our goal: to make the transition to digital technology as easy as possible for the mechanical and plant engineering industry. Our systems demonstrate how digital twins can accelerate planning, reduce errors, and significantly streamline collaboration across company boundaries.
Our four current best-practice cases demonstrate how this works in a production environment. Step by step, we integrate geometry, kinematics, and real machine data in a virtual environment.
Strategy and foundation
Asset Connectivity in the Industrial Metaverse
Real-time data transfer from the shop floor to the cloud. A digital twin is only as good as its data. In this system, we use IoT protocols to mirror the real-time status of three robots directly into the system. The result is autonomous, collision-free process control based on real production data in real time.
Virtual Process Design Using Digital Twins
Interfaces between expert tools and virtual environments Here, we demonstrate how to integrate established tools with platforms such as NVIDIA Omniverse. We show you how to use PLC simulations, dynamic processes, and collision checks directly within the digital twin without having to abandon your existing expert workflows (e.g., with ISG-virtuos).
Humanoid Robots: Interaction and Training in a Virtual Environment
Complex dynamics and physical AI. From simple URDF imports to advanced reinforcement learning: In this scenario, we train humanoid robots in a physically accurate simulation. By precisely modeling factors such as friction and inertia, we prepare the systems for highly dynamic tasks in a realistic and safe manner.
Integration of Geometry and Kinematics
We seamlessly integrate a KUKA robot, along with its specific process animations, into an overarching factory simulation. This case study illustrates the process: from raw design data to a fully functional digital twin.