Technische Universität Dresden

TUD is one of the oldest and largest technical universities in Germany (37,000 students) and member of the group of the 9 leading technical universities in Germany.

TUD has its roots in the Royal Saxon Technical School, which was founded in 1828. Today, it is a university that coalesces natural and engineering sciences with humanities and social sciences, as well as medicine. This wide range of disciplines, unique in Germany, obligates the university to promote interdisciplinarity and to contribute to the integration of science into society. A stable diversity in research and teaching forms the basis for the further successful development of TUD. As part of its core competencies, it promotes and develops its fields of excellence. All disciplines represented at the university, have their foundation in the expertise, initiative spirit, creative curiosity, dedication to performance, communication and the ability to cope with criticism. All members participate in the continuous process of researching by learning and learning by researching.

Logo of this consortium partner

Technische Universität Dresden
Mommsenstraße 13
01062 Dresden
Germany
www.tu-dresden.de

‘Knowledge builds bridges – education unites people’ - TUD is one of eleven German universities that were recently identified as ‘Universities of Excellence’.

Role

The role of TUD in the iDev40 project is diverse. It will mainly contribute to the virtualization of the ECS value chain in establishing value chain wide tools and methods based on virtualization and harmonization of essential processes between R&D and manufacturing within the high tech industry. This will be achieved by optimizing the whole value chain using today`s capabilities of the internet of things, computer integrated manufacturing and artificial intelligence. In particular, TUD will be the work package leader for ‘Virtualization in Smart Production and Development’ and further contribute to four individual tasks.

Key Contribution

TUD will develop an approach to automate repetitive activities in offices in order to shift the working efforts of the employees towards more innovative working time. Additionally, TUD will develop a cross-site standard process for production planning and controlling which comprises for example a network-oriented lead time scheduling. TUD will investigate smart concepts and techniques to visualize data properly. It addresses the questions which specific data in which form and which aggregation should be shown in order to extract the desired information in accordance to the needs of the different stakeholders. Furthermore, efforts will be made to visualize data with both dynamic and spatial character in a compressed way intuitively to interpret. TUD will contribute to perform a better short-term prediction and scheduling respectively. This will be accomplished by substituting static transportation times with more realistic ones within the fab-simulation. TUD will enable the simulation-based forecast for development lots by extending the method for the automated generation of fab capacity models to support the inclusion of development and engineering lots. To support the creation and analysis of simulation experiments, TUD will develop a knowledge-based, holistic framework for the coupling of interoperable, compound simulation and analysis modules.

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