- Generative AI for Design: Specialized support for metamaterials and acoustic structures design to optimize material performance.
- AI-based Surrogate Modeling: Implementation of advanced surrogate models to enable simulation and optimization.
- Physics-informed World Models: Development of dynamic system models that integrate physical laws with AI
- Digital Twins and Safe Learning: Technical assistance in building digital twins and safe learning frameworks
- Edge AI and Intelligent Sensing: Specialized engineering for the deployment of intelligent sensing systems and Edge AI solutions.
Key Value: Enabling rapid exploration of complex design spaces and efficient validation of scalable solutions for real-world manufacturing environments.
Practical example
Advanced manufacturing requires a seamless bridge between digital design and physical deployment.
This service facilitates, among other activities:
- Metamaterial Impact Optimization: Designing 3D-printable structures using graph-based AI to improve the performance of protective equipment while simplifying production.
- Human-to-Robot Skill Transfer: Implementing data-efficient learning from human demonstrations to transition manual assembly lines into automated systems.
- Geometry-aware Adaptation: Utilizing optimization methods that allow robotic manipulators to rapidly adapt to new product geometries during deployment.
Case Study: A company in the protective sports equipment sector seeks to improve chest protector performance. The service supports the design of 3D-printable metamaterials using graph-based AI models, which optimizes impact absorption and enables more efficient manufacturing processes.
