rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management
  name:
    name part: Benyoucef, Lyes.
    role:
      role term: editor.
  name:
    name part: Grabot, Bernard.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXII, 508 p. 228 illus. online resource.
  abstract: 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…
  table of 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.
  note: edited by Lyes Benyoucef, Bernard Grabot.
  subject:
    topic: Computer science
  subject:
    topic: Artificial intelligence
  subject:
    topic: Control engineering
  subject:
    topic: Robotics
  subject:
    topic: Mechatronics
  subject:
    topic: Industrial engineering
  subject:
    topic: Production engineering
  subject:
    topic: Manufacturing industries
  subject:
    topic: Machines
  subject:
    topic: Tools
  subject:
    topic: Computer Science
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Manufacturing, Machines, Tools
  subject:
    topic: Control, Robotics, Mechatronics
  subject:
    topic: Industrial and Production Engineering
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Series in Advanced Manufacturing
  identifier: 9781849961196
  identifier: http://dx.doi.org/10.1007/978-1-84996-119-6
  record info:
    record creation date: 100508
    record change date: 20151204153451.0
    record identifier: 978-1-84996-119-6