Increasing networking and standardization in industry are opening up new opportunities for the uniform mapping and control of production systems. In this position, you will have the opportunity to help design a forward-looking digital twin framework based on industry standards that combines machine control, simulation, and monitoring. You will work at the interface between research and practice and develop solutions that can be transferred to a wide range of production machines.

Rising product complexity, shorter development cycles, and sustainability demands are driving automation in product development. AI-based generative design, especially in topology optimization, offers efficient ways to explore complex design spaces and enable largely automated processes.

The efficient assessment of a component’s structural integrity using deep learning enables the joint optimization of material selection and distribution. This allows for a more flexible and exploratory design space exploration, fostering the development of more holistic design solutions.

Revoltech is a young start-up at TU Darmstadt that develops sustainable leather alternatives. In order to substantiate the sustainability of one of their products, MATTR, with facts and figures, a Life Cycle Assessment (LCA) is now to be carried out. The scientific challenge here is dealing with missing data on a product in the development stage and formulating sustainability requirements.