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OverviewMax 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. Full Product DetailsAuthor: Max HoffmannPublisher: Springer Fachmedien Wiesbaden Imprint: Springer Vieweg Edition: 1st ed. 2019 Weight: 0.585kg ISBN: 9783658277413ISBN 10: 3658277416 Pages: 318 Publication Date: 26 September 2019 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsAgent OPC UA – Semantic Scalability and Interoperability Architecture for MAS through OPC UA.- Management System Integration of OPC UA Based MAS.- Flexible Manufacturing Based on Autonomous, Decentralized Systems.- Use Cases for Industrial Automation.ReviewsAuthor InformationDr.-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. Tab Content 6Author Website:Countries AvailableAll regions |