The research activities of the chair "Hybrid Materials" (Prof. Weidenmann), and the research unit "Mechanical Engineering" (Prof. Sause) and the junior professorship "Data-driven Materials Processing" (Prof. Lechner) are closely interlinked in the institute division "Sustainable Technologies and Systems" of the MRM and cover the entire materials science spectrum for the elucidation of process-structure-property relationships of different structural materials.

The Research Group „Processes“ is working on the development and characterization of manufacturing processes for the sustainable production of composite materials and material composites. Special attention is paid to the presentation of thermoplastic and thermoset-based composites as well as hybrid material composites with high lightweight construction potential, such as sandwich structures or fiber-metal laminates, using production-ready processes.

Within the Research Group „Materials and Mechanics“ a large number of test procedures for material characterization are used and methodically developed further. The main focus of the investigations is on the material class of fibre composites, but other hybrid materials are also being investigated. Furthermore, all test methods are also applied to all conventional materials, such as metals, ceramics or polymers. In the field of numerical modeling, the focus is on the representation of materials with a pronounced hierarchical order. For this purpose, multiscale and multiphysics as well as homogenization approaches are further developed. Especially for the representation of damage processes and dynamic phenomena in these materials such approaches are necessary to achieve a better representation of the processes.

The main focus of the Research Group „Condition Monitoring“ is the use of sensor data to monitor the condition of processes and components. For this purpose, measurement techniques are to be further developed on the one hand. On the other hand the investigation of data streams with self-optimizing and adaptive algorithms is to be a research focus. Especially the use of non-destructive testing methods and process monitoring generates large amounts of data, the analysis of which requires the use of artificial intelligence tools.