Ontology-Based Feedback to Improve Runtime Control for Multi-Agent Manufacturing Systems
Improving the overall equipment effectiveness (OEE) of machines on the shop floor is crucial to ensure the productivity and efficiency of manufacturing systems. To achieve the goal of increased OEE, there is a need to develop flexible runtime control strategies for the system. Decentralized strategi...
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Main Authors | , , , , |
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Format | Journal Article |
Language | English |
Published |
18.09.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Improving the overall equipment effectiveness (OEE) of machines on the shop
floor is crucial to ensure the productivity and efficiency of manufacturing
systems. To achieve the goal of increased OEE, there is a need to develop
flexible runtime control strategies for the system. Decentralized strategies,
such as multi-agent systems, have proven effective in improving system
flexibility. However, runtime multi-agent control of complex manufacturing
systems can be challenging as the agents require extensive communication and
computational efforts to coordinate agent activities. One way to improve
communication speed and cooperation capabilities between system agents is by
providing a common language between these agents to represent knowledge about
system behavior. The integration of ontology into multi-agent systems in
manufacturing provides agents with the capability to continuously update and
refine their knowledge in a global context. This paper contributes to the
design of an ontology for multi-agent systems in manufacturing, introducing an
extendable knowledge base and a methodology for continuously updating the
production data by agents during runtime. To demonstrate the effectiveness of
the proposed framework, a case study is conducted in a simulated environment,
which shows improvements in OEE during runtime. |
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DOI: | 10.48550/arxiv.2309.10132 |