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Dr Tom Jackson University of York

DAME: A Distributed Diagnostics Environment for Maintenance The Grid in Engineering Design & Support. Dr Tom Jackson University of York. Overview. Grid Computing What’s new in Grid? The potential benefits The DAME pilot project. Computation. Grid. Data. Communication.

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Dr Tom Jackson University of York

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  1. DAME: A Distributed Diagnostics Environment for MaintenanceThe Grid in Engineering Design & Support Dr Tom Jackson University of York

  2. Overview • Grid Computing • What’s new in Grid? • The potential benefits • The DAME pilot project

  3. Computation Grid Data Communication

  4. What's new in Grid? • Standardisation of interoperability • Open system • Fully exploits the high bandwidth communication and computation now widely avilable. • Provides possibility for management of massive data growth in scientific, engineering and business sectors: • E.g. High Energy Physics LHC will produce 30-40Tbytes data per year, in experiments requiring virtual collaboration of 1000-2000 scientists.

  5. Potential Engineering Benefits • Design • Faster to market • Meet customer needs better • Operation • More effective management of resources • Lower cost • Diagnostics • Distributed sensing and monitoring • Shorter down times

  6. Design • Engineering optimisation • Simulation and Modelling • Needs access to large compute resources • Needs historical information on past designs to guide effective optimisation • Grid provides • Seamless and open access to diverse computational resources • Manageable access to diverse knowledge • Cooperative visualisation

  7. Grid projects in design • GEODISE • Deliver a Design Optimisation Tool demonstrator for Fluid Dynamics problems • G-Yacht - Remote Computing Grid Based Yacht Design • develop a service to give remote access to yacht CFD and analysis tools via a Web Portal • Electromagnetic Scattering by Aircraft • Modelling and analysis of electromagnetic scattering • Grid Enabled Electromagnetic Optimisation • tools for grid-enabled electromagnetic optimisation

  8. Operation • Remote Monitoring • Remote control of facilities • Sets of diverse systems providing information • Timely control of systems required • Grid Provides • Access to remote systems/resources in a standardised way • Access to large data repositories in a timely manner • Central authorisation to distributed resources

  9. Diagnostics • Remote Sensing and Monitoring • Knowledge based diagnostics • Access to large amounts of process information • Combining diverse sources of knowledge to obtain diagnosis. • Grid provides • High bandwidth communication for diverse data types • Virtual organisation for the diagnostics team • Access and management of complex distributed data

  10. DAME EPSRC pilot project • Distributed Aircraft Maintenance Environment. • Develop a Grid enabled diagnostic system • Demonstrate this on the Rolls-Royce Aeroengine diagnostics problem • Develop, and promote understanding of: • Grid middleware and application/services layer integration • The real time issues in Grid computing • The dependability issues • To provide • A Diagnostic Grid • Grid management tools for unstructured data • An application demonstrator to show the way forward

  11. Project Partners • 4 UK universities: • University of York, Dept of Computer Science • University of Sheffield, Dept of Automatic Control and Systems Engineering • University of Oxford, Dept of Engineering Science • University of Leeds, School of Computing and School of Mechanical Engineering • Industrial Partners: • Rolls-Royce Aeroengines • Data Systems and Solutions • Cybula Ltd

  12. Demonstrator Scenario • RR require more timely diagnostics on engine problems • Reduce aircraft ‘down time’ • Real-time engine monitoring data to be used in Ground based diagnostics • Each engine produces up to 1Gb data per flight

  13. Engine flight data London Airport Airline office New York Airport Grid Diagnostics Centre Maintenance Centre American data center European data center

  14. Why Grid Approach? • Diagnosis systems are data centric; • monitoring and analysis of sensor data and domain specific knowledge is critical to the diagnosis process; • Diagnosis systems require complex interactions between multiple stakeholders; • Diagnosis systems are often distributed; • Diagnosis systems need to provide qualifying or supporting evidence for the diagnosis offered; • Diagnosis systems can be safety or business critical, and typically have high dependability requirements.

  15. DAME Grid Challenges • Management of large, distributed and non-homogenous data repositories; • Remote, secure access to flight data and other operational data; • Controlled and secure access to remote resources (experts, computing, simulation models etc); • Rapid datamining and analysis of fault data; • Diagnostic analysis framework, with distributed users and resources; • Communications between key personnel and actors in the system, for collaborative working; • Control of information flow and data quality, and the integration of data from diverse global sources within a strategic decision support system. • 24/7 operation – QoS issues

  16. DAME Architectural Overview

  17. Grid Services Integration

  18. Grid provides • Distributed access to large amounts of data • Data from engine in flight • Engine performance data stored in the data centres • Data on past maintenance • Design data

  19. Grid provides • Distributed diagnostic tools • ‘Plug and Play’ approach for diagnostic analysis toolset • Open, extensible analysis framework • Integration into existing business processes and systems • Search engines for unstructured data (text, images, performance data) • Fast execution of engine models or simulators (processing on demand)

  20. Grid provides • Virtual organisations • Diagnostic team working as one • Maintenance engineers • Engine experts • Operations management

  21. DAME Industrial Steering Group Forming industry liaison group for:Dissemination of core research results, and technology transfer of emerging middleware applications and Grid services;Technical assessment of the wider application and relevance of the DAME technology and diagnostics framework; Dissemination of wider Grid developments and discussion of emerging standards; To monitor and build on opportunities for further funding initiatives, either UK or EC funded. Development and monitoring of PhD studentships aligned with the DAME project.

  22. Conclusion • Middleware and analysis framework have wide applicability (e.g health monitoring) • Better service to customer due to more integrated use of data and resources • Higher product quality due to better simulation, design and operational management • Lower costs due to improved resource managementFurther Information: www.cs.york.ac.uk/dame

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