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Advances in Petri Net Theory and Applications edited by Dr. Tauseef Aized Advances in Petri Net Theory and Applications edited by Dr. Tauseef Aized Advances in Petri Net Theory and Applications Edited by Dr. Tauseef Aized Published by Sciyo Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2010 Sciyo All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited. After this work has been published by Sciyo, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Iva Lipovic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright Fedorov Oleksiy, 2010. Used under license from Shutterstock.com First published October 2010 Printed in India A free online edition of this book is available at www.sciyo.com Additional hard copies can be obtained from [email protected] Advances in Petri Net Theory and Applications, Edited by Dr. Tauseef Aized p. cm. ISBN-10 953-307-108-7 ISBN-13 978-953-307-108-4 Contents Preface IX Chapter 1 Production Process Object Model Research Based on Petri Net Techniques 1 Chen You-ling Sun Ya-nan Yang Qing-qing Xie Shu-hong Chapter 2 Synthesis of Coloured Petri Nets from Natural-like Language Descriptions 21 Enrique Arjona, Graciela Bueno and Ernesto López-Mellado Chapter 3 Petri Net as a Manufacturing System Scheduling Tool 43 Dr. Tauseef Aized, Professor and Chair Chapter 4 Petri Net Model Based Implementation of Hierarchical and Distributed Control for Discrete Event Robotic Manufacturing Cells 59 Gen’ichi Yasuda Chapter 5 Intelligent Production Systems Reconfi guration by Means of Petri Nets and the Supervisory Control Theory 75 Zapata M. Germán, Chacón R. Edgar and Palacio B. Juan Chapter 6 Parameter Perturbation Analysis through Stochastic Petri Nets: Application to an Inventory System 103 Labadi Karim, Darcherif Moumen, Haoxun Chen Chapter 7 Modelling Multimedia Synchronization using a Time Petri Net Based Approach 123 Abdelghani Ghomari and Chabane Djeraba Chapter 8 Hybrid Petri Nets and Metaheuristic Approach to Farm Work Scheduling 137 Senlin Guan, Morikazu Nakamura and Takeshi Shikanai Chapter 9 Parallel Application Scheduling Model Based on Petri Net with Changeable Structure 153 Xiangang Zhao, Caiying Wei, Manyun Lin, Xiaohu Feng and Wei Lan VI Chapter 10 Petri Nets Hierarchical Modelling Framework of Active Products’ Community 175 Ahmed Zouinkhi, Eddy Bajic, Eric Rondeau and Mohamed Naceur Abdelkrim Chapter 11 Assessment Method of Business Process Model of EKD 197 Sílvia Inês Dallavalle de Pádua and Ricardo Yassushi Inamasu Preface Time-driven systems such as living organisms, ecological systems and world population have long been modeled and analyzed through differential equations. Man-made technological environments such as computer, transportation and telecommunication networks or manufacturing and logistics systems represent systems whose behaviors are governed by events occurring asynchronously over time. Events may be controlled or uncontrolled. Event-driven systems are of increasing importance in today’s world because they are growing in number, size and sophistication. It is therefore imperative to have systematic design methodologies in order to achieve desirable performance and to avoid catastrophic failures. These systems may be asynchronous and sequential, exhibiting many characteristics: concurrency, confl ict, mutual exclusion and non-determinism. These characteristics are diffi cult to describe using traditional control theory which deals with systems of continuous or synchronous discrete variables modelled by differential or difference equations. In addition, inappropriate control of the occurrence of events may lead to system deadlock, capacity overfl ows or may otherwise degrade system performance. These systems are typically referred to as discrete event dynamical systems (DEDS). In order to capture the properties of DEDS, several mechanisms have been proposed and developed for modelling such systems. These are state machines, Petri nets, communicating sequential processes and fi nitely recursive processes. In order to conduct performance analysis of these kinds of systems, methods such as perturbation analysis, queuing network theory and Markov processes have been formulated and applied. Petri net as a graphical tool provides a unifi ed method for design of discrete event systems from hierarchical systems description to physical realizations. This reading is a selection of articles authored by distinguished researchers and academics working in Petri net fi eld and gives an in-depth treatment on selected topics. In order to fully comprehend the material presented, the readers are expected to have background knowledge in the fi eld. This collection of articles attempts to give a state-of-the-art implementation of Petri net theory which may encourage the readers to apply Petri net in their own way. July 31, 2010. Editor Dr. Tauseef Aized, Professor and Chair Department of Mechanical, Mechatronics and Manufacturing Engineering, KSK Campus, University of Engineering and Technology, Lahore, Pakistan 1 Production Process Object Model Research Based on Petri Net Techniques Chen You-ling Sun Ya-nan Yang Qing-qing Xie Shu-hong Chongqing University China 1. Introduction A bottleneck in production process is a link which hindered business process to increase effective output greater or reduce inventory and cost [1]. Solve the bottleneck of the traditional method of production is usually through improved technology, increased scale of production [2], increasing capital investment, etc. to achieve. However, this method is usually the bottleneck occurs in quite a long time before they can be discovered and resolved, often resulting in wasted production capacity. In recent years, with a variety of simulation techniques become more sophisticated, people started to recognize the use of simulation technology to address bottleneck in business results are quite remarkable [3]. Such as the use of SIMOGRAMS method to determine the production process bottleneck workshop and improve the bottleneck cell [4]; use Em-plant to build production line simulation model and optimize production line configuration and layout [5] [6];the use of WITNESS studied the production efficiency of the system issues to improve the initiative and creativity of workers [7]. To some extent the use of simulation technology can solve production bottleneck problem, but the simulation model building takes longer, is not strong universal and the need of trained professional model talent, so it is not conducive for the production process widely used in various sectors. Through research, the production process conduct the dynamic system model Petri net techniques [8], combined with simulation software, and put forward the production process object model (referred to as PPOM) method. 2. Production Process Object Model (PPOM) 2.1 PPOM thought PPOM is a production process object model method, which combines object-oriented thought (Object Oriented, OO) and Petri net techniques, make each processing site in the production process, production cell or working procedure to a high degree of abstraction [9],then abstract entity place sub-module, combined with the actual situation of production, optimize the abstract entity place sub-module, establish an PPOM abstract model of production system and form an organic production system, build production capacity analysis objective function model, using simulation annealing algorithm to find out the minimum production cell and detect the bottleneck cell of the production system.