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Multi-Agent Systems for Distributed AI in Manufacturing
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Table of contents (9 chapters)
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Front Matter
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Back Matter
About this book
Max Hoffmann describes the realization of a framework that enables autonomous decision-making in industrial manufacturing processes by means of multi-agent systems and the OPC UA meta-modeling standard. The integration of communication patterns and SOA with grown manufacturing systems enables an upgrade of legacy environments in terms of Industry 4.0 related technologies. The added value of the derived solutions are validated through an industrial use case and verified by the development of a demonstrator that includes elements of self-optimization through Machine Learning and communication with high-level planning systems such as ERP.
About the Author:
Dr.-Ing. Max Hoffmann is a scientific researcher at the Institute of Information Management in Mechanical Engineering, RWTH Aachen University, Germany, and leads the group “Industrial Big Data”. His research emphasizes on production optimization by means of data integration through interoperability and communication standards for industrial manufacturing and integrated analysis by using Machine Learning and stream-based information processing.
Keywords
Authors and Affiliations
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Institute of Information Management in Mechanical Engineering, RWTH Aachen University, Aachen, Germany
Max Hoffmann
About the author
Dr.-Ing. Max Hoffmann is a scientific researcher at the Institute of Information Management in Mechanical Engineering, RWTH Aachen University, Germany, and leads the group “Industrial Big Data”. His research emphasizes on production optimization by means of data integration through interoperability and communication standards for industrial manufacturing and integrated analysis by using Machine Learning and stream-based information processing.
Bibliographic Information
Book Title: Smart Agents for the Industry 4.0
Book Subtitle: Enabling Machine Learning in Industrial Production
Authors: Max Hoffmann
DOI: https://doi.org/10.1007/978-3-658-27742-0
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019
Hardcover ISBN: 978-3-658-27741-3Published: 26 September 2019
Softcover ISBN: 978-3-658-27744-4Published: 27 September 2020
eBook ISBN: 978-3-658-27742-0Published: 11 September 2019
Edition Number: 1
Number of Pages: XXXIV, 318
Number of Illustrations: 111 b/w illustrations
Topics: Artificial Intelligence, Industrial and Production Engineering, Communications Engineering, Networks