Self-optimizing Production Systems
The research area of Self-optimizing Production Systems deals with the development of self-optimizing systems as a part of a socio-technical production network. The object of research covers all levels of a production system from supply-chain-level through order processing to process control and machine control level. The ability of self-optimizing systems to autonomously adapt to changing environmental conditions, allows a flexible automation, which enables both a cost-effective production and a dynamic adaptation to changing situations. Thereby, a better performance can be achieved than initially planned and forecasted.
Research targets include data mining and information retrieval by adequate sensors, preparation and disposition of information, and simulation of alternative solutions and their visualization to enable a faster decision-making and adaption. At supply-chain and production control level research focuses on developing decision support for employees. That requires the design of suitable interfaces between the human and the machine and/or the system. For automated but flexible and robust manufacturing and assembly the control of the system needs to be enlarged by intelligence and cognition. Thus, not only controlled variables but also control structures can be adopted during the process without the intervention of employees. Essential are on the one hand sensors that perceive and detect environmental conditions. On the other hand mechanisms that enable self-control and learning need to be established. Application areas range from automated micro-assembly up to large components as well as milling, over weaving, welding up to injection molding.
Dr. Dr. Alexander Mertens
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