Artificial Intelligence (AI) is now ubiquitous in our daily lives, not only through user-specific recommendations on streaming platforms, online translators, or (autonomous) cars, but also is essential to the transformation of the economy. AI methods enable new levels of transparency and the possibility of discovering new potentials by making the vast quantity of available data usable. As a result, AI is one of the most significant digital future topics and of great importance for maintaining the competitiveness and technological sovereignty of companies, as well as Germany and Europe as a whole.
Due to its adaptability to complex, dynamic environments and the extensive data available, AI is of critical relevance in logistics. Within intralogistics, there are many potentials for AI, which are currently mainly realized through methods of (mathematical) optimization, traditionally utilizing procedures from Operations Research (OR), such as linear programming, or simulation. Decisions that can be supported by these methods include batch processing of orders, allocation of orders to resources, path optimization, and much more. Compared to classical optimization methods, AI algorithms offer new possibilities for these optimization problems, enabling the inclusion of more complex relationships and diverse influencing factors and thus unlocking new potentials. Additionally, they are often more efficient in computation time than classical algorithms, and AI models can flexibly adapt to dynamic boundary conditions.
In recent years, many AI applications for industrial use cases have already been developed at the Fraunhofer IML.
The Intralogistics and IT Planning department is current developing AI applications for optimizing intralogistics in the following research projects:
DATENFABRIK.NRW | AI solutions for Production und logistics
We are happy to discuss with you whether AI methods can provide a solution for your intralogistics problem. Please do not hesitate to contact the person mentioned for further information.