Artificial Intelligence and Machine Learning for Every Application

Artificial Intelligence (AI) and Machine Learning (ML) have long been incorporated into many products and processes – but their potential is far from exhausted. Numerous applications are still waiting to be developed.

Our strengths:

• We have a deep mathematical understanding of AI algorithms.
• We combine AI with expert knowledge.
• We optimally integrate AI into modeling, simulation, and optimization applications.

Artificial Intelligence Meets Deep Mathematical Expertise

At Fraunhofer ITWM, we support the development of innovative AI products and services with our in-depth mathematical understanding and expertise in transferring ideas into marketable products.

In particular, we excel in the optimal application and integration of AI models. The intelligent and skillful coupling of AI with mathematical-physical simulation and modeling allows us to incorporate knowledge from experts in your own organization into the models, thus gaining a clear advantage over purely data-driven models. We know the limits and possibilities of different AI methods and combine them precisely – always with the goal of achieving the optimal result as quickly, accurately, and reliably as possible. Our methodological repertoire also includes neural networks and Deep Learning, which we use specifically in suitable applications – for example, in pattern recognition, image analysis, or the prediction of complex relationships.

Modelling – Digital Twins Represent Reality

A precise digital model forms the basis for informed decisions in development and production. Digital Twins enable products or processes to be tested and further developed without risk – provided they accurately reflect reality. This is exactly where we come in: with our physical and mathematical expertise, we overcome the so-called »Sim2Real Problem« and create models that are not only realistic but also robust and resilient.

Simulation – Hybrid Models for Greater Reliability

The real world contains uncertainties that are difficult to predict or model. Pure AI models often reach their limits here. We combine data-driven approaches with physical simulation to create hybrid models. The result: greater accuracy, greater robustness – and thus better predictions and lower operational risks.

Optimization – Intelligent and Efficient

Many processes can be improved – but finding the optimal solution is often a complex task. AI-supported methods can significantly shorten this process. By combining AI with prior knowledge, we accelerate optimization processes and increase efficiency in a targeted manner. This allows us to reduce production costs, improve plant utilization, and make processes more flexible.