Prof. Sanja LAzarova-Molnar

Manuel Götz

This Master's thesis deals with the development of data requirements and architecture for a digital twin of manufacturing systems with collaborative robots (cobots). To give a foundation for the following discussions, the thesis starts with a comprehensive overview of basic terms related to digital twins and collaborative robots. Subsequently, it discusses the current state of knowledge in the area of data requirements and architecture for a digital twin of manufacturing systems featuring cobots and highlights the academic and practical relevance of the topic. The specific goals for manufacturing systems with cobots are identified, including improving work and production effectiveness, promoting sustainable development, and ensuring ergonomics and safety. To monitor and simulate these goals, key performance indicators (KPIs) are proposed, such as throughput, mean time to failure, energy consumption, scrap ratio or number of human-cobot-contacts. By addressing these challenges and exploiting the potential of digital twins, this thesis aims to contribute to the optimization of manufacturing systems involving cobots. The proposed data requirements and architecture provide a framework for implementing digital twins in manufacturing systems with cobots, enabling monitoring, analysis, simulation, and optimization. This research provides valuable insights and practical guidance for researchers and practitioners in the field of manufacturing systems, digital twins and collaborative robotics.