Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London
Springer London
2010
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| Schriftenreihe: | Springer Series in Advanced Manufacturing
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| Schlagworte: | |
| Online-Zugang: | BTU01 FHI01 FHN01 FHR01 Volltext |
| Beschreibung: | 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 |
| Beschreibung: | 1 Online-Ressource (XXVI, 510p. 228 illus) |
| ISBN: | 9781849961196 |
| DOI: | 10.1007/978-1-84996-119-6 |
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| 500 | |a 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. | ||
| 500 | |a 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. | ||
| 500 | |a 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 | ||
| 505 | 0 | |a 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 | |
| 650 | 4 | |a Engineering | |
| 650 | 4 | |a Industrial engineering | |
| 650 | 4 | |a Machinery | |
| 650 | 4 | |a Manufacturing, Machines, Tools | |
| 650 | 4 | |a Industrial and Production Engineering | |
| 650 | 4 | |a Ingenieurwissenschaften | |
| 700 | 1 | |a Grabot, Bernard |e Sonstige |4 oth | |
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Datensatz im Suchindex
| _version_ | 1804152238680047616 |
|---|---|
| any_adam_object | |
| author | Benyoucef, Lyes |
| author_facet | Benyoucef, Lyes |
| author_role | aut |
| author_sort | Benyoucef, Lyes |
| author_variant | l b lb |
| building | Verbundindex |
| bvnumber | BV041889629 |
| collection | ZDB-2-ENG |
| 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 |
| ctrlnum | (OCoLC)699999842 (DE-599)BVBBV041889629 |
| dewey-full | 670 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 670 - Manufacturing |
| dewey-raw | 670 |
| dewey-search | 670 |
| dewey-sort | 3670 |
| dewey-tens | 670 - Manufacturing |
| discipline | Werkstoffwissenschaften / Fertigungstechnik |
| doi_str_mv | 10.1007/978-1-84996-119-6 |
| format | Electronic eBook |
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| id | DE-604.BV041889629 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:07:32Z |
| institution | BVB |
| isbn | 9781849961196 |
| language | English |
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| physical | 1 Online-Ressource (XXVI, 510p. 228 illus) |
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| publishDate | 2010 |
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| publisher | Springer London |
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| series2 | Springer Series in Advanced Manufacturing |
| spelling | Benyoucef, Lyes Verfasser aut Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management edited by Lyes Benyoucef, Bernard Grabot London Springer London 2010 1 Online-Ressource (XXVI, 510p. 228 illus) txt rdacontent c rdamedia cr rdacarrier Springer Series in Advanced Manufacturing 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 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 Engineering Industrial engineering Machinery Manufacturing, Machines, Tools Industrial and Production Engineering Ingenieurwissenschaften Grabot, Bernard Sonstige oth Erscheint auch als Druckausgabe 978-1-84996-118-9 https://doi.org/10.1007/978-1-84996-119-6 Verlag Volltext |
| spellingShingle | Benyoucef, Lyes Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management 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 Engineering Industrial engineering Machinery Manufacturing, Machines, Tools Industrial and Production Engineering Ingenieurwissenschaften |
| title | Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management |
| title_auth | Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management |
| title_exact_search | Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management |
| title_full | Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management edited by Lyes Benyoucef, Bernard Grabot |
| title_fullStr | Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management edited by Lyes Benyoucef, Bernard Grabot |
| title_full_unstemmed | Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management edited by Lyes Benyoucef, Bernard Grabot |
| title_short | Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management |
| title_sort | artificial intelligence techniques for networked manufacturing enterprises management |
| topic | Engineering Industrial engineering Machinery Manufacturing, Machines, Tools Industrial and Production Engineering Ingenieurwissenschaften |
| topic_facet | Engineering Industrial engineering Machinery Manufacturing, Machines, Tools Industrial and Production Engineering Ingenieurwissenschaften |
| url | https://doi.org/10.1007/978-1-84996-119-6 |
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