Smart Agents for the Industry 4.0 Enabling Machine Learning in Industrial Production /

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 upg...

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Κύριος συγγραφέας: Hoffmann, Max (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg, 2019.
Έκδοση:1st ed. 2019.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Hoffmann, Max.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Smart Agents for the Industry 4.0  |h [electronic resource] :  |b Enabling Machine Learning in Industrial Production /  |c by Max Hoffmann. 
250 |a 1st ed. 2019. 
264 1 |a Wiesbaden :  |b Springer Fachmedien Wiesbaden :  |b Imprint: Springer Vieweg,  |c 2019. 
300 |a XXXIV, 318 p. 111 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a Agent 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. 
520 |a 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. Contents Agent 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 Target Groups Scientists and students in automation technology, production technology, mechanical engineering, process control, factory planning Practitioners in these fields 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. 
650 0 |a Artificial intelligence. 
650 0 |a Industrial engineering. 
650 0 |a Production engineering. 
650 0 |a Electrical engineering. 
650 1 4 |a Artificial Intelligence.  |0 http://scigraph.springernature.com/things/product-market-codes/I21000 
650 2 4 |a Industrial and Production Engineering.  |0 http://scigraph.springernature.com/things/product-market-codes/T22008 
650 2 4 |a Communications Engineering, Networks.  |0 http://scigraph.springernature.com/things/product-market-codes/T24035 
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950 |a Computer Science (Springer-11645)