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INTRODUCCIÓN

This architecture enables intelligent distributed monitoring by a society of cognitive agents in a flexible manufacturing system. It promotes adaptability, efficiency, and dynamic monitoring through multi-agent systems.

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INTRODUCCIÓN

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  1. INTRODUCCIÓN Multi-agent Paradigm Based on Co-operate to achieve Heterogeneous resources FMS Monitoring Functions Intelligent distributed monitoring Architecture for Flexible Manufacturing Systems Society of cognitive agents Modeled as FMS Monitoring Sufficient Knowledge for the decision-making

  2. INTRODUCCIÓN Need adaptability in production structures Continuosly increasing -Increase in competition -Decrease product life cycle Cycle, due date inventory level Efectiveness of a production Flexibility and reacticity to integrate the evolution of the market

  3. INTRODUCCIÓN - More Suitable for dynamic monitoring - Build Complex and flexible advanced intelligent systems Multi Agents Systems (MAS) Monitoring Systems More - decentralized - emergent - concurrent Than - centralized - planned - sequential

  4. Diagnosis Error handling Detection Adquisition of sensors information Execution RESOURCES Sensors Effectors Multi-agent Architecture for Distributed and Real Time Monitoring Functions - Error detection - Error diagnosis - Error handling Monitoring systems

  5. Multi-agent Architecture for Distributed and Real Time Monitoring Under the responsability a RMA handle: Local rules and enviromental information to perform the monitoring functions Network of cognitive agents “RESOURCE MONITORING AGENTS” (RMA) Replace a Centralised monitoring Each resource MAADM Dynamic interaction of the agents in real-time Overall system perfomance EMERGE It is not globally planned CONTRACT NET PROTOCOL The architecture receives the tasks to execute in the FMS INTERFACE Task Manager Agent

  6. MAA- The monitoring of the FMS is distribuited over the RMAs- Global Monitoring is achieved by passing appropiate messages between the RMAs- The Contract Net Protocol is used to co-ordinate and co- operate the RMAs, and ro reshedule the operations in failure

  7. Resource Monitoring Agent Model - Knowledge - Control ( Reasoning ) - Co-operation - Communication Distinguishes Cognitive Agent Model TYPES - Self-Knowledge: own information for monitoring its resource (resource state database, diagnosis production rules and error hendling production rules) - Other Knowledge: information about other RMAs, wich can operate whit him Knowledge (internal and external activities)

  8. Resource Monitoring Agent Model

  9. Resource Monitoring Agent Model TYPES OF MESSAGES - Information request messages: part dimensions, part weight,presence or no presence of the part, resource status, tools status, etc - Failure Alert Messages: resource in failure, tool in failure, etc - Cooperation and co-ordination messages: contracts, bids, acknowledgements, etc Communication (synchronous and is done by sending messages)

  10. Resource Monitoring Agent Model SET OF METHODS - Detection: It interacts with the resources status database to detect the abnormal situations ocurring on each resource. - Diagnosis: It identifies and recognises faults, using a rule-based expert system. The knowledge bse is a set of production rules. If event1 and eventnthen fault1,........,faultm - Error Handling: It determinate the corrective actions that handle the faults. They are:resheduling, urgent halt, transit to degradaded mode, operator call and actionleap - Contract Net Protocol Control (RMAs decision-making capability to acomplish the monitoring functions and to co-operate with others agents)

  11. Resource Monitoring Agent Model RESCHEDULING It reschedules locally operations that couldn´t be executed by the resource in failure using the Contract Net Protocol, developed to resolve the problem of dynamic scheduling in FMS. - Detection: It interacts with the resources status database to detect the abnormal situations ocurring on each resource. - Diagnosis: It identifies and recognises faults, using a rule-based expert system. The knowledge bse is a set of production rules. If event1 and eventnthen fault1,........,faultm - Error Handling: It determinate the corrective actions that handle the faults. They are:resheduling, urgent halt, transit to degradaded mode, operator call and actionleap - Contract Net Protocol

  12. Contract Net Protocol

  13. Propagación de Requisito RA12 RA11 RA31 RA32 RA21 RA22 RA51 RA52 RA41 RA42 Agente Recurso Manager Requisito (OP0) Requisito (OP0) Requisito (OP2) Requisito (OP1) Requisito (OP1) Requisito (OP2) Requisito (OP4) Requisito (OP3)

  14. Realimentación de Petición RA12 RA11 RA31 RA32 RA21 RA22 RA51 RA52 RA41 RA52 Agente Recurso Manager Petición (OP0) Petición (OP0) Petición (OP2) Petición (OP1) Petición (OP1) Petición (OP2) Petición (OP4) Petición (OP3)

  15. Propagación de Contrato Contrato (OP0) Contrato (OP1) Contrato (OP2) Contrato (OP3) Contrato (OP4) Agente Recurso Manager RA11 RA21 RA31 RA41 RA51

  16. Realimentación de Aceptación y Cancelación de petición Admisión (OP0) Cancelación (OP0) Admisión (OP2) Cancelación (OP1) RA12 Admisión (OP1) Cancelación (OP2) Cancelación (OP1) RA31 RA22 Cancelación (OP4) Admisión (OP3) Admisión (OP4) Cancelación (OP3) RA51 RA41 Agente Recurso Manager RA11 RA32 RA21 RA52 RA42

  17. Resolución de conflictos e incertidumbres RA1 RA1 RA1 RA1 RA2 RA2 RA2 RA2 P2 P2 P2 C2 P1 A1 C1 P1 RA3 RA3 RA3 RA3 Tiempo Actual Tiempo Actual Tiempo Actual Tiempo Actual Ventana reservada para contratos anteriores Ventana reservada para contratos anteriores P1 P1 Reparo Temporal Reparo Temporal Reparo Temporal Reparo Temporal C1 Ventana reservada para contratos anteriores Ventana reservada para contratos anteriores P1 = P2 P2 P2 P2

  18. Conclusiones Las principales ventajas de la arquitectura propuesta son flexibilidad en un ambiente variable, reconfiguración y adaptibilidad inherente, tolerancia a fallos rápida y eficiente, desarrollo modular y autonomía operacional. Los resultados experimentales obtenidos en la simulación, demostraron que la arquitectura multiagente is una plataforma de trabajo bastante apropiada para monitorización distribuida y en tiempo real de FMS. La implementación de la arquitectura multiagente fue llevada a cabo en Java por ser orientada a objetos, distribuida, segura, dinámica y programación de alto desempeño. El Java Expert System Shell fue integrado en el software, para el desarrollo del sistema experto basado en reglas, usado en el diagnóstico y manejo de error.

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