By E. Oztemel (auth.), Lyes Benyoucef, Bernard Grabot (eds.)
Enterprise networks supply a variety of new enterprise possibilities, particularly for small and medium-sized organisations which are often extra versatile than greater businesses. so as to succeed, in spite of the fact that, performances and anticipated advantages must be conscientiously evaluated and balanced: organizations needs to ascertain they join the perfect community for the correct activity and needs to locate a good, versatile, and sustainable operating perform. A promising method of discovering one of these perform is to mix analytical equipment and knowledge-based techniques, in a allotted context.
Artificial intelligence (AI) recommendations were used to refine decision-making in networked firm strategies, integrating humans, info and items around the community limitations. Artificial Intelligence suggestions for Networked production corporations Management addresses in demand recommendations and functions of AI applied sciences within the administration of networked production businesses.
The goal of this e-book is to align most modern practices, innovation and case experiences with educational frameworks and theories, the place AI recommendations are used successfully for networked production agencies. extra particularly, it comprises the newest examine effects and tasks at diversified degrees addressing quick-response approach, theoretical functionality research, functionality and potential demonstration. The position of rising AI applied sciences within the modelling, review and optimisation of networked businesses’ actions at diverse choice degrees is additionally covered.
Artificial Intelligence recommendations for Networked production companies Management is a helpful consultant for postgraduates and researchers in commercial engineering, laptop technology, automation and operations research.
The Springer sequence in complex Manufacturing publishes the simplest instructing and reference fabric to help scholars, educators and practitioners in production expertise and administration. This overseas sequence contains complex textbooks, examine monographs, edited works and convention complaints overlaying all matters in complicated production. The sequence makes a speciality of new themes of curiosity, new remedies of extra conventional parts and insurance of the functions of data and verbal exchange expertise (ICT) in manufacturing.
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Additional info for Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management
Abouel Nasr and Kamrani (2008) provided an extensive analysis on this issue. Integrating AI and Internet technology for the success of manufacturing design is very popular nowadays. A good example of this is the injection moulding design system developed by Mok et al. (2008). In this study, a Javabased intelligent design system equipped with AI technologies is introduced. It is reported that this system increased the design speed and supported the creation of design standards. Similarly, Balic et al.
Syst. Int. , 1(2):129–156 Shen W, Hao Q, Wang S et al. (2007) An agent-based service-oriented integration architecture for collaborative intelligent manufacturing Rob. Comput. Integr. , 23(3):315–325 Sugimura N, Tanimizu Y, Yoshioka T (1997) A study on object oriented modelling of holonic manufacturing system. In: Proceedings of the 29th CIPR International Seminar on Manufacturing Systems, May 13–14 Smutny L (2003) Intelligent measurement, diagnostic and control systems. Acta Montanistica Slovaca Ročník 8 Tekez E K (2007) A reference model for integrated intelligent manufacturing system.
The operation of the KSs is normally governed by some form of control system, known as a scheduler, which implements the chosen problem-solving strategy (Craig, 1995). The KSs within a BB system are essentially expert systems that are dedicated to solving problems in a specific area. 1). Even though the basic ideas of BB and agent systems are similar, they differ from each other as it can be considered that there is no autonomy within a BB system. This is because of the scheduler, which reviews the KSs and selects the most appropriate KS.