Distributed Aircraft Maintenance Environment

Distributed Aircraft Maintenance Environment

Grid-based on-line aeroengine diagnostics Jim Austin, University of York Aims To build a distributed, Grid based, diagnostic maintenance system To prove the technology on a Rolls Royce Aeroengine diagnostic maintenance problem Demonstrate the process of building a Grid based system To deliver grid-enabled technologies that underpin the application 2

The Application The support of engine diagnostics on a global scale. 3 Engine flight data London Airport Airline office New York Airport Grid

Maintenance Centre American data center European data center 4 Aircraft Engine Outline architecture Quote Systems Diagnostic

operator Engine data Engine data log AURA data search Operational Report Model-based Interpretation

Maintenance operator Database of Operational data Case-based Reasoning Decisionsupport 5 Example use case

Local Environment Perform Extended Analysis <> Diagnosis / Prognosis <

Engine Decision Support Perform Analysis <> Pattern Match <> Status /

Parameters Modeller Update Operation Provide Domain Expert Assessment Update Local Diagnostics

Diagnosis Assessment Inform Domain Expert of Undetected Problem Domain Expert / Maintenance Planner Results Reports

Results Store Result of Diagnosis and Operation Provide Statistics Report Maintenance Team 6

Challenges Support on-line diagnostics in real time Deal with the data from 100,000 engines in operation Prove pattern matching methodology Prove the business case for the technology 7 Technologies AURA: High performance search technology QUOTE: On-engine diagnostics system Globus: Grid software WR Grid: Demonstrator hardware

8 AURA High performance search engine Based on neural networks Develop for distributed operation 9 QUOTE

On-engine health assessment Under trials on Trent 500 now Will identify novelty Some diagnostics 10 11 White Rose Computational Infrastructure Oxford Super Janet

Leeds Cluster Leeds Shared Memory White Rose Computational Grid Sheffield Distributed Memory York Shared Memory 12

Our developing architecture 13 Industry Collaborators DS&S : Rolls Royce data services providers Rolls Royce : Data and problem WRCG: Esteem, Sun and Streamline: Demonstrator Grid Cybula: AURA technology support 14 Academic team

Austin project management, data management Tarassenko, Austin algorithms for fault identification Dew, Djemame system architecture Fleming, Thompson decision support McKay data modeling 15 Academic Team McDermid Dependability Wellings Real time issues Researchers - 15, including... Tom Jackson - Coordinator Martyn Fletcher - Software Manager

16 End 17

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