Service oriented, holonic and multi-agent manufacturingsystems for industry of the future : proceedings of SOHOMA 2019
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Bibliographic Information
Service oriented, holonic and multi-agent manufacturingsystems for industry of the future : proceedings of SOHOMA 2019
（Studies in computational intelligence, v. 853）
Springer Nature, c2020
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Other editors: Damien Trentesaux, Paulo Leitão, Adriana Giret Boggino, Vincent Botti
Includes bibliographical references and author index
Description and Table of Contents
Description
This proceedings book presents selected peer-reviewed papers from the 9th International Workshop on 'Service Oriented, Holonic and Multi-agent Manufacturing Systems for the Industry of the Future' organized by Universitat Politecnica de Valencia, Spain, and held on October 3-4, 2019. The SOHOMA 2019 Workshop aimed to foster innovation in the digital transformation of manufacturing and logistics by promoting new concepts and methods and solutions through service orientation in holonic and agent-based control with distributed intelligence.
The book provides insights into the theme of the SOHOMA'19 Workshop - 'Smart anything everywhere - the vertical and horizontal manufacturing integration, ' addressing 'Industry of the Future' (IoF), a term used to describe the 4th industrial revolution initiated by a new generation of adaptive, fully connected, analytical and highly efficient robotized manufacturing systems. This global IoF model describes a new stage of manufacturing, that is fully automatized and uses advanced information, communication and control technologies such as industrial IoT, cyber-physical production systems, cloud manufacturing, resource virtualization, product intelligence, and digital twin, edge and fog computing.
It presents the IoF interconnection of distributed manufacturing entities using a 'system-of-systems' approach, discussing new types of highly interconnected and self-organizing production resources in the entire value chain; and new types of intelligent decision-making support based on from real-time production data collected from resources, products and machine learning processing.
This book is intended for researchers and engineers working in the manufacturing value chain, and specialists developing computer-based control and robotics solutions for the 'Industry of the Future'. It is also a valuable resource for master's and Ph.D. students in engineering sciences programs.
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