Since the beginning of 2021, we form together the research group TEC | Manufacturing Technology within the Institute for Production Management, Technology and Machine Tools (PTW) at the Technische Universität Darmstadt. Our vision is to conduct trend-setting research for data-driven, adaptable manufacturing technologies in resource-efficient, responsive production. Enthusiasm for our research, a high level of commitment and initiative, as well as openness and curiosity in breaking new ground are essential character attributes of our TEC team.
With the TEC-Lab, the PTW has a technical center with a climate-stable measurement and sample preparation room as well as modern machinery. It provides the perfect environment to quickly develop and test new approaches for data-driven manufacturing using agile methods in a solution-oriented manner. With various demonstrators for data-driven manufacturing technologies and connected production solutions, fun and enthusiasm for data-driven production is also awakened among young scientists.
Our research clusters
In the future, a connected, data-driven production system will enable data-based conclusions to be drawn about plant and process statuses. This requires a continuous digital process chain from data recording to data processing and storage to data evaluation. Reliable quality predictions based on process data can be made in particular by using methods from the field of artificial intelligence. Standardized interfaces and protocols are an essential component of secure communication, not only between different plants but also in production networks. Furthermore, the integration of new types of sensory elements in mechanical engineering components opens up new possibilities for monitoring the condition of machines and plants. In order to achieve this integration, design and process engineering adaptations must be made. Finally, innovative process models are developed based on real process data. These can be based on classical deterministic modeling, but can also be defined via new types of data-driven models. The transferability of the models to other fields of application is a key aspect of our research work, e.g. to implement approaches for process control.
Our trend-setting research results are accompanied by our partners via transfer projects up to industrial application.