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Automation and Information Systems
Engineering and operation of intelligent, reconfigurable, distributed cyber-physical production systems
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The increasing demand to produce customer-specific, individual products in shorter innovation
cycles within the machine and plant manufacturing domain require Cyber Physical Production Systems
(CPPS) with higher Overall Equipment Effectiveness (OEE). The main research goals of the AIS are
methods, notations, algorithms and architectures to increase OEE. Research areas are Model-Based
Engineering, self-X-CPPS, human-machine interaction and analysis and aggregation of big data.
To increase the overall equipment effectiveness of
machines, agents and learning approaches have been and
are being developed to improve the operation of CPPS.
In the field of model-based engineering, inconsistencies
management across disciplines and along the life cycle
were investigated to enable a seamless integration of
the data through the engineering workflow. In the field
of human-machine interaction, solutions for information
aggregation and representation for the human were devel-
oped including speech recognition and Augmented Reality
(AR) to support the individual operator according to his/
her skills and requirements. The aggregation and analysis
of big data to gain smart data from big data enables
predictive maintenance and process/product optimization.
Embedded Systems and its software in the mechatronic
industry (products and automated production systems)
are getting more and more important. The AIS adapts
methods and approaches from the computer science
domain with the needs of the machine and plant-man-
ufacturing domain. Therefore, approaches like technical
debt, product lines, family mining and neuronal nets or
Methods applied at the Institute of Automation and Information Systems
Institute of Automation and Information Systems – Main research fields
ontologies are introduced to address the challenges in
automation in real-world scenarios often together with
partners from industry.