Department of Cutting Technology (T²F)
Head of Department: Dr.-Ing. M. Erler
The department's research and work is at the interface between manufacturing technology, digitalization and artificial intelligence. Our goal is to make the manufacturing of the future more sustainable, flexible and efficient. We focus on the development of innovative technologies that meet both the ecological and economic requirements of modern production processes.
Autonomous production planning is at the heart of our department. Our goal is to develop intelligent systems that can independently analyze, optimize, and adapt production processes. The focus is on the automation of process planning, starting with the generation of tool paths and extending to the control of complex process chains. In addition, we are focusing on the integration of modern technologies such as artificial intelligence (AI) and machine learning (ML) to enable data-driven decisions and to realize adaptive manufacturing processes. A particular challenge is flexibility in production, which is to be achieved by dynamically adapting manufacturing and logistics systems to changing requirements.
Sustainability is a central concern of our work. We develop innovative methods and technologies that optimize the use of materials and energy and minimize waste. We place a high value on combining machining and additive processes in order to exploit the advantages of both approaches. Process optimization to reduce emissions and material losses is just as much a focus as life cycle-oriented manufacturing concepts that promote sustainability in production through innovative process chains.
Another focus of our research is on flexible manufacturing process chains. The aim is to design production processes that are robust and adaptable to varying requirements. This includes hybrid manufacturing processes that seamlessly combine additive and subtractive technologies. In addition, we are working on automated systems for planning and optimizing process chains that enable dynamic adaptation to different production scenarios. This is complemented by simulation-based approaches that provide a precise prediction of process behavior and thus a sound basis for decision-making.
Further information and overviews are also available in the TU Dresden Research Information System.
Contact
© Erler
Head of the working group Cutting Technology
NameDr.-Ing. Martin Erler
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Besucheradresse:
Zeuner-Bau, room 327C George-Bähr-Straße 3c
01069 Dresden
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