Fraunhofer Institute for Mechanics of Materials IWM
Manufacturing Processes
Our understanding of processes and sophisticated simulation techniques enable us to design efficient and safe manufacturing processes. Our services include investigations into the technological development of manufacturing processes for the production of semi-finished products and components with functional properties. This work ranges from powder technology processes, including complex fluid systems, to microfluids, the forming and processing of ductile materials as well as processing techniques for brittle materials and glass forming.
What we offer
- Innovative manufacturing processes for precision contours and functional components with defined property profiles
- Simulation-assisted optimization of the energy and material efficiency of manufacturing processes
- Modeling and simulation of powder technology and fluid dynamic processing stages, simulation methods for generative manufacturing
- Forming process simulations including microstructure development and thermodynamics
- Forming, processing and damage analyses for brittle materials such as glass and silicon
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STREAM:
Semantic representation, networking and curation of quality-assured material data.
Materials science faces major challenges: linking qualitative research data that is already available in large quantities with new data while at the same time ensuring the reproducibility of the data. [more]
ML4P - Machine Learning for Production:
In the Fraunhofer lighthouse project Machine Learning for Production (ML4P), the scientists at the Fraunhofer Institute for Mechanics of Materials IWM investigate how performance of modern production plants can be optimized using machine learning – for both continuous processes and the batch processing industry.
As one of six institutes in ML4P, the Fraunhofer IWM participates with a demonstrator machine for incremental forming processes. The machine realizes a process for float glass bending that was originally developed at the Fraunhofer IWM. The aim of the subproject is to upgrade the glass bending machine to become a cognitive machine. Therefore, the machine will be digitalized in order to collect process and sensor data. Using the collected data, a machine learning-based process control will be implemented. To increase the amount of information available for the process control, numerical simulations of the process shall be integrated.
Thermodynamic simulation of a continuous furnace with temperature and CO2 distribution
EnEffiSint – Increasing the energy efficiency of sintering furnaces
In powder technology, sintering is an essential process step for ceramic and metallic components. For large series, these usually pass through a sintering furnace, in which the atmosphere and temperature distribution prevailing in the furnace play a decisive role - both for the quality of the product and for the energy efficiency of the process. In the BMBF project EnEffiSint, an increase in energy efficiency of at least 30% is to be achieved for an industrial continuous furnace in cooperation with furnace manufacturers, material suppliers, end users and simulation experts.
The specific objective is twofold: Improving the furnace design will result in a direct increase in efficiency, e.g. by eliminating losses due to unnecessarily long furnaces (so-called wall losses). In addition, precise control of the furnace atmosphere will also make the process itself more efficient and accurate, resulting in higher throughput rates, fewer rejects and shorter process times.
TWIP4EU:
Material modeling of high strength TWIP steels
The properties of high strength TWIP steels differ from those of conventional sheet metals due to their special microstructure. In the »TWIP4EU« project, funded by the EU, the Fraunhofer IWM, together with its project partners, is developing a material model with which to more accurately simulate the TWIP steel forming process.