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170406 ||| eng |
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|a 9783319533216
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| 100 |
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|a De La Mota, Idalia Flores
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| 245 |
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|a Robust Modelling and Simulation
|h Elektronische Ressource
|b Integration of SIMIO with Coloured Petri Nets
|c by Idalia Flores De La Mota, Antoni Guasch, Miguel Mujica Mota, Miquel Angel Piera
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a XVII, 162 p. 112 illus., 70 illus. in color
|b online resource
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| 505 |
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|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
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| 653 |
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|a Operations Research, Management Science
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| 653 |
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|a Operations research
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| 653 |
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|a Industrial engineering
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| 653 |
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|a Management science
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| 653 |
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|a Computer simulation
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| 653 |
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|a Computer Modelling
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| 653 |
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|a Mathematics / Data processing
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| 653 |
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|a Computational Science and Engineering
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| 653 |
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|a Industrial and Production Engineering
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| 653 |
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|a Production engineering
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| 700 |
1 |
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|a Guasch, Antoni
|e [author]
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| 700 |
1 |
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|a Mujica Mota, Miguel
|e [author]
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| 700 |
1 |
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|a Angel Piera, Miquel
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-53321-6
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-319-53321-6?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 670
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| 520 |
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|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 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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