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Towards Modular Modeling and Simulation of Production Control Systems

Towards Modular Modeling and Simulation of Production Control Systems. Holger Giese und Ulrich A. Nickel AG Softwaretechnik, Universität Paderborn Warburger Str. 100, 33098 Paderborn {hg|duke}@upb.de. Overview. Production Control System Executable UML Class Model & Simulation

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Towards Modular Modeling and Simulation of Production Control Systems

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  1. Towards Modular Modeling and Simulation of Production Control Systems Holger Giese und Ulrich A. Nickel AG Softwaretechnik, Universität Paderborn Warburger Str. 100, 33098 Paderborn {hg|duke}@upb.de

  2. Overview • Production Control System • Executable UML Class Model & Simulation • Modularity & Separation for Executable Models • Requirements & Simulation • Conclusion & Future Work

  3. Flexible distributed control is „complex” to build Frequent adaptation to new requirements or changes in the topology are required Programming languages (Ada, C, …) Test & code corrections in the production environment Design and maintenance Methodology & UML Avoid long downtimes Verification is hard problem Simulation Production Control System (PCS)

  4. PCS: Overview & Elements S ID St M S Sensors/Actors Processor Nodes ID Identification Unit Data Links St Stopper Travel Direction M Motor Signal Direction S Sensor Application SoftwareGate Bus Interface

  5. UML Model describes: possible system topology Reactive overall class behavior (Statecharts, SDL,..) Advantages: OO concepts: e.g., class encapsulation Visual modeling High level view Track Gate Signal Executable UML Class Model

  6. Executable UML Model Simulation Simulation Visuali-zation Production-order Code synthesis Specification Control software Dobs Simulation kernel Java Reflect Hardwareconfiguration Java Virtual Machine Topology

  7. Simulation result: Can detect coordination problems: deadlock, … Provides insight into system dynamics (tinkering style) Limitations: System has to be complete (closed) Observations do only hold for very restricted form of subclass refinement Classes & Simulation

  8. Component Spec.: overall behavior arbitrary structures Abstraction: combine processes build abstract process behavior for layer C depends on (A || B) no abstraction barrier for used layers Limitations: State explosion problem (propability for error detection) Component exchange preserve results only when very restricted conformance realtion holds Modularity: Overall Synchronization A C B Layer C

  9. Reduce class behavior to external visible/relevant contract behavior Multiple contracts (UML-RT ports) Modularity: Contract

  10. Component Spec.: set of contract behavior layered structures Abstraction: specification for layer C is C1 || ... || C4 partial model simulation & analysis arbitrary usage of provided contracts C5 || C6 || C7 assumed for used contracts Limitation: embedding restricted to layered structures Modularity: Partial Contract Border C1 C7 C2 C6 C3 C5 C4 Layer C Contracts are design elements, but the by abstraction steps derived abstract processes are not!!

  11. Factory as open system with in and out contracts (ports): possible Environments? embedding? Modularity: Open PCS

  12. support even for set of contract behavior and implicit dependencies Embedding only restricted by demand to ensure acyclic dependencies Abstraction: specification for C1, …, C4 Advantage: More flexible embedding when independent Modularity: Implicit Component Behavior C1 C7 C2 C6 C3 C5 C4 Component C

  13. Open factory with implicit component behavior: implicit environment embedding rule: “depend has to remain acyclic” Modularity: Implicit Component Behavior

  14. Requirements are described Scenario-oriented: external view system may realize suitable interleaving for multiple parallel requested tasks Factory Simulation: use for checking use for run-time assertions Requirements & Simulation

  15. Conclusion & Future Work Modeling PCS: • strong requirements for control software • methodology & UML-RT • code synthesis and simulation (partial) Validation via simulation: • early failure detection • interactive “testing” Modular simulation • improved separation • modularity & scalability • Future Work • Realize extended concept • Integrate time support

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