Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management
(Sprache: Englisch)
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management addresses prominent concepts and applications of AI technologies in the management of networked manufacturing enterprises.
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Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management addresses prominent concepts and applications of AI technologies in the management of networked manufacturing enterprises.
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management addresses prominent concepts and applications of AI technologies in the management of networked manufacturing enterprises.
The aim of this book is to align latest practices, innovation and case studies with academic frameworks and theories, where AI techniques are used efficiently for networked manufacturing enterprises. More specifically, it includes the latest research results and projects at different levels addressing quick-response system, theoretical performance analysis, performance and capability demonstration. The role of emerging AI technologies in the modelling, evaluation and optimisation of networked enterprises' activities at different decision levels is also covered.
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management is a valuable guide for postgraduates and researchers in industrial engineering, computer science, automation and operations research.
The aim of this book is to align latest practices, innovation and case studies with academic frameworks and theories, where AI techniques are used efficiently for networked manufacturing enterprises. More specifically, it includes the latest research results and projects at different levels addressing quick-response system, theoretical performance analysis, performance and capability demonstration. The role of emerging AI technologies in the modelling, evaluation and optimisation of networked enterprises' activities at different decision levels is also covered.
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management is a valuable guide for postgraduates and researchers in industrial engineering, computer science, automation and operations research.
Inhaltsverzeichnis zu „Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management “
- Intelligent Manufacturing Systems- Agent-based System for Knowledge Acquisition and Management
- Multi-agent Simulation-based Decision Support System and Application
- A Collaborative Decision-making Approach for Supply Chain
- Web-Service Based e-Collaborative Framework
- Isoarchic and Multi-criteria Control of Supply Chain Network
- Lot-sizing and Scheduling Rules
- Meta-Heuristics for Real Time Routing Selection
- Meta-heuristic Approaches for Multi-objective Simulation-based Optimization
- Diverse Risk/Cost Balancing Strategies for Flexible Tool Management
- Intelligent Integrated Maintenance Policies for Manufacturing Systems
- Enhancing the Effectiveness of Multi-pass Scheduling
- Intelligent Techniques for Safety-stock Optimization
- Real World Service Interaction with Enterprise Systems in Dynamic Manufacturing Environments
- A Service-oriented System of Modular, Dynamic Reconfigurable and Collaborative Systems
- A Service Oriented Shopfloor to Support Collaboration in Manufacturing Networks
Autoren-Porträt
Dr. Lyes Benyoucef received his PhD in Operations Research at the National Polytechnic Institute of Grenoble, France, in 2000 and his HDR (Research Director Thesis) degree from the University of Metz, France, in 2008. He is a senior researcher (CR1-HDR) at INRIA (the French National Institute for Research in Computer Science and Control). His main research interests include modelling and performance evaluation; and the simulation and optimization of supply chains and e-sourcing technologies.Prof. Bernard Grabot teaches production management, industrial organization and ERP systems at the National Engineering School of Tarbes, France. He is a member of IFAC working groups on knowledge-based enterprise and editor-in-chief of the international journal, Engineering Applications of Artificial Intelligence. His main research interests concern the implementation of ERP systems, supply chain management and knowledge engineering.
Bibliographische Angaben
- 2010, 508 Seiten, Maße: 16,4 x 24,2 cm, Gebunden, Englisch
- Herausgegeben: Lyes Benyoucef, Bernard Grabot
- Verlag: Springer, London
- ISBN-10: 1849961182
- ISBN-13: 9781849961189
Sprache:
Englisch
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