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The Resource Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management, edited by Lyes Benyoucef, Bernard Grabot, (electronic resource)

Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management, edited by Lyes Benyoucef, Bernard Grabot, (electronic resource)

Editor
Contributor
Summary
Enterprise networks offer a wide range of new business opportunities, especially for small and medium-sized enterprises that are usually more flexible than larger companies. In order to be successful, however, performances and expected benefits have to be carefully evaluated and balanced: enterprises must ensure they become a member of the right network for the right task and must find an efficient, flexible, and sustainable working practice. A promising approach to finding such a practice is to combine analytical methods and knowledge-based approaches, in a distributed context. Artificial intelligence (AI) techniques have been used to refine decision-making in networked enterprise processes, integrating people, information and products across the network boundaries. 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 Springer Series in Advanced Manufacturing publishes the best teaching and reference material to support students, educators and practitioners in manufacturing technology and management. This international series includes advanced textbooks, research monographs, edited works and conference proceedings covering all subjects in advanced manufacturing. The series focuses on new topics of interest, new treatments of more traditional areas and coverage of the applications of information and communication technology (ICT) in manufacturing
Language
  • eng
  • eng
Work
Publication
Edition
1st ed.
Extent
1 online resource (515 p.)
Note
Description based upon print version of record
Contents
  • Intelligent Manufacturing Systems
  • Agent-based System for Knowledge Acquisition and Management Within a Networked Enterprise
  • Multi-agent Simulation-based Decision Support System and Application in Networked Manufacturing Enterprises
  • A Collaborative Decision-making Approach for Supply Chain Based on a Multi-agent System
  • Web-services-based e-Collaborative Framework to Provide Production Control with Effective Outsourcing
  • Isoarchic and Multi-criteria Control of Supply Chain Network
  • Supply Chain Management Under Uncertainties: Lot-sizing and Scheduling Rules
  • Meta-heuristics for Real-time Routing Selection in Flexible Manufacturing Systems
  • Meta-heuristic Approaches for Multi-objective Simulation-based Optimization in Supply Chain Inventory Management
  • Diverse Risk/Cost Balancing Strategies for Flexible Tool Management in a Supply Network
  • Intelligent Integrated Maintenance Policies for Manufacturing Systems
  • Enhancing the Effectiveness of Multi-pass Scheduling Through Optimization via Simulation
  • Intelligent Techniques for Safety Stock Optimization in Networked Manufacturing Systems
  • Real-world Service Interaction with Enterprise Systems in Dynamic Manufacturing Environments
  • Factory of the Future: A Service-oriented System of Modular, Dynamic Reconfigurable and Collaborative Systems
  • A Service-oriented Shop Floor to Support Collaboration in Manufacturing Networks
Isbn
9781282836846
Instance
Label
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management
Title
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management
Statement of responsibility
edited by Lyes Benyoucef, Bernard Grabot
Contributor
Editor
Editor
Subject
Language
  • eng
  • eng
Summary
Enterprise networks offer a wide range of new business opportunities, especially for small and medium-sized enterprises that are usually more flexible than larger companies. In order to be successful, however, performances and expected benefits have to be carefully evaluated and balanced: enterprises must ensure they become a member of the right network for the right task and must find an efficient, flexible, and sustainable working practice. A promising approach to finding such a practice is to combine analytical methods and knowledge-based approaches, in a distributed context. Artificial intelligence (AI) techniques have been used to refine decision-making in networked enterprise processes, integrating people, information and products across the network boundaries. 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 Springer Series in Advanced Manufacturing publishes the best teaching and reference material to support students, educators and practitioners in manufacturing technology and management. This international series includes advanced textbooks, research monographs, edited works and conference proceedings covering all subjects in advanced manufacturing. The series focuses on new topics of interest, new treatments of more traditional areas and coverage of the applications of information and communication technology (ICT) in manufacturing
Member of
Is Subseries of
Dewey number
670.427028563
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsedt
  • MPeBySgWsoo
  • cdjPF4zMlhc
Language note
English
LC call number
Q334-342
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Benyoucef, Lyes.
  • Grabot, Bernard.
Series statement
Springer Series in Advanced Manufacturing,
http://library.link/vocab/subjectName
  • Artificial intelligence
  • Manufactures
  • Industrial engineering
  • Artificial Intelligence
  • Manufacturing, Machines, Tools, Processes
  • Control, Robotics, Mechatronics
  • Industrial and Production Engineering
Label
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management, edited by Lyes Benyoucef, Bernard Grabot, (electronic resource)
Instantiates
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Content category
text
Content type code
  • txt
Contents
Intelligent Manufacturing Systems -- Agent-based System for Knowledge Acquisition and Management Within a Networked Enterprise -- Multi-agent Simulation-based Decision Support System and Application in Networked Manufacturing Enterprises -- A Collaborative Decision-making Approach for Supply Chain Based on a Multi-agent System -- Web-services-based e-Collaborative Framework to Provide Production Control with Effective Outsourcing -- Isoarchic and Multi-criteria Control of Supply Chain Network -- Supply Chain Management Under Uncertainties: Lot-sizing and Scheduling Rules -- Meta-heuristics for Real-time Routing Selection in Flexible Manufacturing Systems -- Meta-heuristic Approaches for Multi-objective Simulation-based Optimization in Supply Chain Inventory Management -- Diverse Risk/Cost Balancing Strategies for Flexible Tool Management in a Supply Network -- Intelligent Integrated Maintenance Policies for Manufacturing Systems -- Enhancing the Effectiveness of Multi-pass Scheduling Through Optimization via Simulation -- Intelligent Techniques for Safety Stock Optimization in Networked Manufacturing Systems -- Real-world Service Interaction with Enterprise Systems in Dynamic Manufacturing Environments -- Factory of the Future: A Service-oriented System of Modular, Dynamic Reconfigurable and Collaborative Systems -- A Service-oriented Shop Floor to Support Collaboration in Manufacturing Networks
Dimensions
unknown
Edition
1st ed.
Extent
1 online resource (515 p.)
Form of item
online
Isbn
9781282836846
Media category
computer
Media type code
  • c
Other control number
10.1007/978-1-84996-119-6
Specific material designation
remote
System control number
  • (CKB)2670000000027864
  • (EBL)992971
  • (OCoLC)663093973
  • (SSID)ssj0000412161
  • (PQKBManifestationID)11268345
  • (PQKBTitleCode)TC0000412161
  • (PQKBWorkID)10366121
  • (PQKB)11774936
  • (DE-He213)978-1-84996-119-6
  • (MiAaPQ)EBC992971
  • (EXLCZ)992670000000027864
Label
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management, edited by Lyes Benyoucef, Bernard Grabot, (electronic resource)
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Content category
text
Content type code
  • txt
Contents
Intelligent Manufacturing Systems -- Agent-based System for Knowledge Acquisition and Management Within a Networked Enterprise -- Multi-agent Simulation-based Decision Support System and Application in Networked Manufacturing Enterprises -- A Collaborative Decision-making Approach for Supply Chain Based on a Multi-agent System -- Web-services-based e-Collaborative Framework to Provide Production Control with Effective Outsourcing -- Isoarchic and Multi-criteria Control of Supply Chain Network -- Supply Chain Management Under Uncertainties: Lot-sizing and Scheduling Rules -- Meta-heuristics for Real-time Routing Selection in Flexible Manufacturing Systems -- Meta-heuristic Approaches for Multi-objective Simulation-based Optimization in Supply Chain Inventory Management -- Diverse Risk/Cost Balancing Strategies for Flexible Tool Management in a Supply Network -- Intelligent Integrated Maintenance Policies for Manufacturing Systems -- Enhancing the Effectiveness of Multi-pass Scheduling Through Optimization via Simulation -- Intelligent Techniques for Safety Stock Optimization in Networked Manufacturing Systems -- Real-world Service Interaction with Enterprise Systems in Dynamic Manufacturing Environments -- Factory of the Future: A Service-oriented System of Modular, Dynamic Reconfigurable and Collaborative Systems -- A Service-oriented Shop Floor to Support Collaboration in Manufacturing Networks
Dimensions
unknown
Edition
1st ed.
Extent
1 online resource (515 p.)
Form of item
online
Isbn
9781282836846
Media category
computer
Media type code
  • c
Other control number
10.1007/978-1-84996-119-6
Specific material designation
remote
System control number
  • (CKB)2670000000027864
  • (EBL)992971
  • (OCoLC)663093973
  • (SSID)ssj0000412161
  • (PQKBManifestationID)11268345
  • (PQKBTitleCode)TC0000412161
  • (PQKBWorkID)10366121
  • (PQKB)11774936
  • (DE-He213)978-1-84996-119-6
  • (MiAaPQ)EBC992971
  • (EXLCZ)992670000000027864

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