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Binary bit weighting. Engine flight data. EU Airport. Airline office. US Airport. Grid. Diagnostics centre. Column Summing unit. Maintenance Centre. integer vector. US data center. EU data center. Thresholding unit. threshold type. threshold level. bit vector.

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Further information

Binary bit


Engine flight data

EU Airport

Airline office

US Airport



Column Summing unit


integer vector

US data center

EU data center

Thresholding unit





bit vector


output vector

input vector

Further Information:

Professor Jim Austin (Project Manager)Department of Computer Science,University of YorkYORK, YO10 5DD, [email protected]

Dr Tom Jackson (Project Co-ordinator)Department of Computer Science,University of YorkYORK, YO10 5DD, [email protected]

Distributed Aircraft Maintenance Environment (DAME)

DAME is an e-Science pilot project, demonstrating the use of the GRID to implement a distributed decision support system for deployment in maintenance applications and environments.

It is funded by the EPSRC under the UK e-Science programme, and is one of six EPSRC projects launched in the first phase of UK e-Science funding. DAME is funded for 3 years commencing Jan 2002, with a budget of £3.5 Million, supporting a research team of over 30 staff.

DAME will demonstrate how the GRID and web services (based on OGSA) can facilitate the design and development of systems for diagnosis and maintenance applications which combine geographically distributed resources and data within a decision support system.

  • Aims

  • The DAME project has the following aims:

  • To develop a Distributed Diagnostic Grid Test-bed.

  • To demonstrate the benefits of the Grid test-bed on a realistic Rolls-Royce Aircraft Engine Maintenance scenario.

  • To design and build a system architecture for distributed diagnostic systems that takes advantage of Grid middleware, focusing particularly on the management of data within a Grid.

  • To study and develop the performance issues associated with data grids, particularly real time and dependability concerns.

  • To design a distributed data store for unstructured, non-indexed data & to facilitate rapid data mining.

  • To develop Grid-enabled fault identification and diagnostic methods.

  • Overview

  • DAME will develop a generic test bed for distributed diagnostics that will be built upon grid-enabled technologies and grid/web services. 

  • The generic framework will be deployed in a proof of concept demonstrator in the context of maintenance applications for civil aerospace engines. The project will draw together a number of advanced core technologies, within an integrated web services system including:

  • AURA: High performance search technology

  • QUOTE: On-engine diagnostics system

  • Case Based Reasoning

  • Modeling techniques

  • Cooperative Working environments

  • Globus: Grid software

  • Resource and Work flow management

  • White Rose Grid: host Grid environment

  • Challenges

  • DAME will exploit emerging open standard web service architectures over a Grid network to demonstrate how the data management aspects of maintenance support systems can be handled within a unified knowledge broker model. Some of the domain specific challenges relating to the project include:

  • Management of large, distributed and non-homogenous data repositories;

  • Controlled and secure access to remote resources (experts, computing, knowledge bases etc);

  • 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.

  • Why Grid Solution?

  • Data Growth:

    • Information is being gathered at growing rates at an international level

    • Demonstrator scenario dealing with the data from thousands of operational engines.

  • This information needs to be fully utilized in business process

  • Technology is needed to integrate and exploit the data

  • Support for on-line diagnostics in real time and with dependability

  • Grid offers potential for scalable solutions for all of the above.

  • AURA-G

  • Support of scalable pattern matching

  • Supports distributed search, across multiple CMM engines at different locations

  • Search technology for multi-media data

  • Parallel pattern match engine based on neural networks, built on Correlation Matrix Memories.

  • High performance Beowulf and dedicated hardware implementations

  • OGSA compliant


The challenge for DAME is to consider the design of a Grid based system that can support of engine diagnostics on a global scale.

Architecture Overview

The architecture will pull together a diverse range of tools and applications, data sources and experts in a system facilitated by Globus Grid standards and Grid service middleware. Much of the middleware will be developed within the project and will contribute to the UK e-Science programme.

Data Mining

Diagnostic station

Engine data

Novelty indication

Local Diagnosis

Data used to identify novelty

Data reduction


Match requests


Data to be searched for

Data stores/

data warehouse



QUOTE System

One of the core technologies within the concept demonstrator will be a neural network based diagnostic system.  The QUOTE system provides real-time monitoring and fault diagnosis for aerospace jet engines.

QUOTE will be adapted so that it is available as a core web service application within the demonstrator environment, demonstrating how the GRID model can be used to exploit specific computing resources within a general maintenance framework.

  • Decision Support

  • Will draw from a broad range of diagnostic tools, including case based reasoning, fault isolation methods, and data visualisation. Case based reasoning will:

  • Emulate the diagnostic skill of an experienced maintenance engineer

  • Provide the user with ‘best practice’ advice when confronted with a set of fault symptoms

  • Provide a confidence measure for each suggested solution

  • Facilitate the processing of logistic data, current fault data and historical fault data to intelligently isolate an engine problem

Grid Model

The DAME project will be based upon an open web services architecture, built upon the Globus GRID models.  One of the research issues to be addressed within the project is the applicability of these web service models for supporting the collaborative working environments required for maintenance decision support systems.  An overview of the DAME architecture model is shown below.

Generic Model

The diagnostic framework developed within DAME is being demonstrated in the context of the engine maintenance problem. However, the techniques being developed will be generalised to other domains, and will be assessed for applicability in areas such as remote health applications, pharmaceuticals, and industrial monitoring systems.

An industry based Steering Group has been set up to facilitate the wider deployment and dissemination of the methods and techniques.


Further details can be found at the DAME web site:

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