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Simulation of Smart Factory Processes Applying Multi-Agent-Systems—A Knowledge Management Perspective

Electrical Engineering & Computer Science, Knowledge Based Systems & Knowledge Management, University of Siegen, 57076 Siegen, Germany
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J. Manuf. Mater. Process. 2020, 4(3), 89; https://doi.org/10.3390/jmmp4030089
Received: 24 July 2020 / Revised: 27 August 2020 / Accepted: 5 September 2020 / Published: 9 September 2020
(This article belongs to the Special Issue Cyber Physical Production Systems)
The implementation of Industry 4.0 and smart factory concepts changes the ways of manufacturing and production and requires the combination and interaction of different technologies and systems. The need for rapid implementation is steadily increasing as customers demand individualized products which are only possible if the production unit is smart and flexible. However, an existing factory cannot be transformed easily into a smart factory, especially not during operational mode. Therefore, designers and engineers require solutions which help to simulate the aspired change beforehand, thus running realistic pre-tests without disturbing operations and production. New product lines may also be tested beforehand. Data and the deduced knowledge are key factors of the said transformation. One idea for simulation is applying artificial intelligence, in this case the method of multi-agent-systems (MAS), to simulate the inter-dependencies of different production units based on individually configured orders. Once the smart factory is running additional machine learning methods for feedback data of the different machine units may be applied for generating knowledge for improvement of processes and decision making. This paper describes the necessary interaction of manufacturing and knowledge-based solutions before showing an MAS use case implementation of a production line using Anylogic. View Full-Text
Keywords: multi-agent-systems; smart factory; cyber–physical production systems; knowledge management multi-agent-systems; smart factory; cyber–physical production systems; knowledge management
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Dornhöfer, M.; Sack, S.; Zenkert, J.; Fathi, M. Simulation of Smart Factory Processes Applying Multi-Agent-Systems—A Knowledge Management Perspective. J. Manuf. Mater. Process. 2020, 4, 89.

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