System Modeling and Control with Resource-Oriented Petri Nets

Petri nets are widely used in modeling, analysis, and control of discrete event systems arising from manufacturing, transportation, computer and communication networks, and web service systems. However, Petri net models for practical systems can be very large, making it difficult to apply such models to real-life problems. System Modeling and Control with Resource-Oriented Petri Nets introduces a new resource-oriented Petri net (ROPN) model that was developed by the authors. Not only does it successfully reduce model size, but it also offers improvements that facilitate effective modeling, analysis, and control of automated and reconfigurable manufacturing systems. Presenting the latest research in this novel approach, this cutting-edge volume provides proven theories and methodologies for implementing cost and time-saving improvements to contemporary manufacturing systems. It provides effective tools for deadlock avoidance—deadlock-free routing and deadlock-free scheduling. The authors supply simple and complex industrial manufacturing system examples to illustrate time-tested concepts, theories, and approaches for solving real-life application problems. Written in a clear and concise manner, the text covers applications to automated and reconfigurable manufacturing systems, automated guided vehicle (AGV) systems, semiconductor manufacturing systems, and flexible assembly systems. Explaining complex concepts in a manner that is easy to understand, the authors provide the understanding and tools needed for more effective modeling, analysis, performance evaluation, control, and scheduling of engineering processes that will lead to more flexible and efficient manufacturing systems.

Preface Acknowledgments The Authors List of Abbreviations Introduction to Petri Net ModelingThe Modeling Process Automated Manufacturing Systems Historical Perspective of Petri Nets in Automation Scope and Objectives Summary References Petri Nets: Basic Concept Basic ConceptsSubclass of PN Properties Timed PN PN with Inhibitor ArcsSummary References Colored Petri Net A Simple Example Definitions of CPN Transition Enabling and Firing Rules P-Invariant in CPN SummaryReferences Process-Oriented Petri Net Modeling IntroductionModeling Method Resource Sharing in POPN Characteristics of POPN Summary References Resource-Oriented Petri Net Modeling Introduction Steps of ROPN Modeling Modeling Part Production Processes Modeling Material Handling Processes Resource Sharing in ROPN Characteristics of ROPN Summary References Process- vs. Resource-Oriented Petri NetsModeling Power and Model Size Conservativeness Structure for LivenesExampleSummaryReferences Control of Flexible and Reconfigurable Manufacturing SystemsIntroduction Deadlock in FMS System Modeling by CROPN Existence of Deadlock Deadlock Avoidance Policy Liveness of Overall System Illustrative Example Implementation Deadlock Avoidance with Shared Material Handling SystemSummaryReferences Avoiding Deadlock and Reducing Starvation and BlockingIntroductionA Simple Example Relaxed Control Policy Dependent PPCs in Interactive Subnets Complexity in Applying the Control LawPerformance Improvement through Examples Summary ReferencesControl and Routing of Automated Guided Vehicle SystemsIntroduction Control of AGV Systems with Unidirectional Paths Control of AGV Systems with Bidirectional Paths Routing of AGV Systems Based on CROPNSummaryReferences Control of FMS with Multiple AGVs Introduction System Modeling with CROPN Deadlock Avoidance PolicyIllustrative Example Summary References Control of FMS with Multiple Robots Introduction Motivation through ExampleDeadlock Control Policy Illustrative Example Summary References Control of Semiconductor Manufacturing Systems Modeling, Analysis, and Control of Cluster ToolsDeadlock Avoidance in Track System Deadlock-Free Scheduling of a Track System Summary References Modeling and Control of Assembly/Disassembly SystemsIntroduction A Flexible Assembly System R-Policy Modeling FAS by CROPN Realizable Resource Requirement Deadlock Avoidance Control Policy Illustrative Example Industrial Case Study Summary References Bibliography Index

Naiqi Wu is a professor of industrial and systems engineering in the Department of Industrial Engineering at Guangdong University of Technology, People’s Republic of China. MengChu Zhou is a professor of electrical and computer engineering and the director of the Discrete-Event Systems Laboratory at the New Jersey Institute of Technology, Newark, USA.