GenAI4FFD

Use of generative AI models to support the planning of factories to increase security of supply in Germany

Project description:

As part of the GenAI4FFD project, an assistance system based on generative artificial intelligence is to be developed that provides support in the elementary phases of the factory planning process - from the beginning of target definition to the completion of detailed planning. The genAI-based assistance system to support factory planning will be developed as a prototype for three central task areas of factory planning as part of the project:

1. recording and analysing requirements: for this purpose, the assistance system is intended to serve knowledge management and as a mediator in communication with the client in order to make fast, high-quality decisions that can be implemented under the given boundary conditions.
2. factory design: Based on the requirements recording and analysis as well as the production and logistics processes derived from this, the assistance system should support the conceptualisation and design of the factory system, for example by generating drafts. In doing so, given boundary conditions from standards and guidelines, e.g. for the workplace, environmental requirements or structural design, should be taken into account.
3. modelling and evaluation: The generated planning results must be subjected to an objective, quantitative evaluation. For this purpose, the assistance system should support the implementation of simulation models that reflect the respective planning status in terms of structure and process design with sufficient accuracy.

Consortium:

Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e. V., Fraunhofer IFF;
IPK - Ingenieurplanungs- und Komplexbaugesellschaft mbH;
METOP Mensch-Technik-Organisation-Planung GmbH;
TragWerk Ingenieure Döking+Purtak GmbH;
Otto von Guericke University Magdeburg;
Schaeffler Technologies AG & Co. KG;
Ingenics AG

Duration:

February 2025 - January 2028

Budget:

Total funding: € 5.5 million
Funding amount: € 3.6 million