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Autor(en): 
  • Antoni Guasch
  • Miquel Angel Piera
  • Miguel Mujica Mota
  • Idalia Flores de la Mota
  • Robust Modelling and Simulation: Integration of SIMIO with Coloured Petri Nets 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2018  
    Genre:  Naturwissensch., Medizin, Technik 
     
    B / Computational Science and Engineering / Computer mathematics / Computer modelling & simulation / computer science / Computer simulation / engineering / Industrial and Production Engineering
    ISBN:  9783319851266 
    EAN-Code: 
    9783319851266 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  2818 gr 
    Seiten:  162 
    Illustration:  XVII, 162 p. 112 illus., 70 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book presents for the first time a methodology that combines the power of a modelling formalism such as colored petri nets with the flexibility of a discrete event program such as SIMIO. Industrial practitioners have seen the growth of simulation as a methodology for tacking problems in which variability is the common denominator. Practically all industrial systems, from manufacturing to aviation are considered stochastic systems. Different modelling techniques have been developed as well as mathematical techniques for formalizing the cause-effect relationships in industrial and complex systems. The methodology in this book illustrates how complexity in modelling can be tackled by the use of coloured petri nets, while at the same time the variability present in systems is integrated in a robust fashion. The book can be used as a concise guide for developing robust models, which are able to efficiently simulate the cause-effect relationships present in complex industrial systemswithout losing the simulation power of discrete-event simulation. In addition SIMIO's capabilities allows integration of features that are becoming more and more important for the success of projects such as animation, virtual reality, and geographical information systems (GIS).

      



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