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Robust modelling and simulationinteg...

Mota, Idalia Flores de la.

Robust modelling and simulationintegration of SIMIO with coloured Petri nets /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Robust modelling and simulationby Idalia Flores De La Mota ... [et al.].
Reminder of title:	integration of SIMIO with coloured Petri nets /
other author:	Mota, Idalia Flores de la.
Published:	Cham :Springer International Publishing :2017.
Description:	xvii, 162 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Petri nets.
Online resource:	http://dx.doi.org/10.1007/978-3-319-53321-6
ISBN:	9783319533216$q(electronic bk.)

Robust modelling and simulationintegration of SIMIO with coloured Petri nets /
Robust modelling and simulationintegration of SIMIO with coloured Petri nets /[electronic resource] :by Idalia Flores De La Mota ... [et al.]. - Cham :Springer International Publishing :2017. - xvii, 162 p. :ill., digital ;24 cm.

Preface -- Introduction -- Chapter 1: Introduction to Digital Simulation -- Chapter 2: Statistics elements for simulation -- Chapter 3: Modelling of Systems using Petri Nets -- Chapter 4: Integrating Coloured Petri Nets with SIMIO -- Chapter 5: Modelling Example -- References -- Annex.

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 systems without 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)

ISBN: 9783319533216$q(electronic bk.)

Standard No.: 10.1007/978-3-319-53321-6doiSubjects--Topical Terms:

278494
Petri nets.

LC Class. No.: TA347.N46

Dewey Class. No.: 511.35

Robust modelling and simulationintegration of SIMIO with coloured Petri nets /
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245 0 0 $a Robust modelling and simulation $h [electronic resource] : $b integration of SIMIO with coloured Petri nets / $c by Idalia Flores De La Mota ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xvii, 162 p. : $b ill., digital ; $c 24 cm.
505 0 $a Preface -- Introduction -- Chapter 1: Introduction to Digital Simulation -- Chapter 2: Statistics elements for simulation -- Chapter 3: Modelling of Systems using Petri Nets -- Chapter 4: Integrating Coloured Petri Nets with SIMIO -- Chapter 5: Modelling Example -- References -- Annex.
520 $a 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 systems without 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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