Max Hoffmann 
Smart Agents for the Industry 4.0 [PDF ebook] 
Enabling Machine Learning in Industrial Production

Dukung

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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Daftar Isi

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.

Tentang Penulis

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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Bahasa Inggris ● Format PDF ● Halaman 318 ● ISBN 9783658277420 ● Ukuran file 8.8 MB ● Penerbit Springer Fachmedien Wiesbaden ● Kota Wiesbaden ● Negara DE ● Diterbitkan 2019 ● Diunduh 24 bulan ● Mata uang EUR ● ID 7173302 ● Perlindungan salinan DRM sosial

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