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Smart Agents for the Industry 4.0

Enabling Machine Learning in Industrial Production

Max Hoffmann

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ca. 139,09 €
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Springer Fachmedien Wiesbaden img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

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.

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Schlagwörter

Distributed Artificial Intelligence, Machine Learning, Digital Transformation, Multi-Agent Systems, Factory of the Future, OPC UA, Fieldbus, Autonomous Decision Making, MAS, Digital Factory, Industry 4.0, Industrial Internet of Things (IIoT), Smart Factory, Automation Technology, OPC Unified Architecture