Robust Modelling and Simulation [electronic resource] : Integration of SIMIO with Coloured Petri Nets /
De La Mota, Idalia Flores.author.
Guasch, Antoni.author.
Mujica Mota, Miguel.author.
Angel Piera, Miquel.author.
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).
Includes bibliographical references at the end of each chapters.
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).
Industrial engineering.
Production engineering.
Operations research.
Management science.
Computer simulation.
Computer mathematics.
Industrial and Production Engineering.
Operations Research, Management Science.
Simulation and Modeling.
Computational Science and Engineering.