Robust Modelling and Simulation

Integration of SIMIO with Coloured Petri Nets

Business & Finance, Management & Leadership, Operations Research, Nonfiction, Science & Nature, Technology, Engineering, Industrial
Cover of the book Robust Modelling and Simulation by Idalia Flores De La Mota, Antoni Guasch, Miguel Mujica Mota, Miquel Angel Piera, Springer International Publishing
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Author: Idalia Flores De La Mota, Antoni Guasch, Miguel Mujica Mota, Miquel Angel Piera ISBN: 9783319533216
Publisher: Springer International Publishing Publication: March 28, 2017
Imprint: Springer Language: English
Author: Idalia Flores De La Mota, Antoni Guasch, Miguel Mujica Mota, Miquel Angel Piera
ISBN: 9783319533216
Publisher: Springer International Publishing
Publication: March 28, 2017
Imprint: Springer
Language: English

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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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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