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Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management

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.
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Submitted on : Thursday, June 16, 2011 - 9:30:31 AM
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Lyes Benyoucef, Bernard Grabot. Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management. Lyes Benyoucef and Bernard Grabot. Springer, pp.510, 2010, Springer Series in Advanced Manufacturing, 978-1-84996-118-9. ⟨10.1007/978-1-84996-119-6⟩. ⟨inria-00600894⟩



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