Technische Universität München - Lehrstuhl für Automatisierung und Informationssysteme (AIS)

The AIS chair is concerned with innovative methods, notations, algorithms and architectures to increase the overall plant effectiveness of machines and plants in the context of cyberphysical production systems and over the complete plant lifecycle.

Interdisciplinary, industry-focused research

In addition to model-based development, agent-driven cyber-physical systems and human-machine interaction, the field of Big Data and Machine Learning is a core competence of the AIS. In 2017, the chair was able to develop and test a system architecture on demonstrators that integrates heterogeneous data sources and enables efficient data analysis. In addition, data-driven methods for predictive maintenance (BMWi research project: SIDAP) or prediction of product quality (EU research project: IMPROVE) were developed. The successful mastering of innovation processes in product-service systems is the goal of the DFG-funded Collaborative Research Center 768 "Cycle Management of Innovation Processes". In order to strengthen the exchange between industry and research, an industry colloquium was successfully organized in 2017 under the auspices of the AIS. The focus was on interactive sessions with the topics of inconsistency, change and knowledge management, as well as user integration.