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Stephen Kennett presentation

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  • Smoke modelling using salt water.
  • Transcript

    • 1. Dealing Effectively with the data legacy of your organisation Dr Stephen Kennett
    • 2. Defence Science and Technology Organisation (DSTO)
      • Australian Government's lead agency dedicated to providing science and technology support for the country's defence and security needs.
      • DSTO:
      • Seeds and shapes the perceptions and priorities of Defence for the use of science and technology.
      • Provides scientific and technical support to current Defence operations.
      • Investigates future technologies for Defence and national security applications.
      • Ensures Australia is a smart buyer and user of Defence equipment.
      • Enhances existing capabilities by increasing performance and safety, and reducing the cost of ownership of Defence assets.
      • Assists industry to become better at supporting Defence’s capability needs.
    • 3. DSTO
      • DSTO employs around 2300 staff in facilities at
      • Edinburgh (SA), Melbourne,
      • Canberra, Sydney, Brisbane,
      • HMAS Stirling (WA), Scottsdale (TAS), and Innisfail (QLD).
      • DSTO's budget represents
      • approximate 2% of the Defence budget.
    • 4. Legacy Data Replace? Paper based System COTS Solution Reporting needed Legacy Data Manual Effort
    • 5. Legacy Data Replace? Information needed COTS Solution Modification needed Modify Code More Hardware Legacy Data Requirements Change
    • 6. Why keep legacy (Maintenance) data?
        • Parts usage
        • Work area usage
        • Time between jobs – work rate
        • Failure Patterns
        • Usage pattern
        • Comparative histories
        • Life of type information
        • Legal requirement
        • Accountability
    • 7. Legacy Data Choices
      • Import into current database
      • - Missing fields
      • - Duplicate data
      • - Handling exceptions
      • - Audit trail
      • Retain as separate entity
      • - Reporting tool
      • - Database translation
      • - Remove front end?
    • 8. Who needs the data?
      • Engineer
      • problem solving
      • best possible answers
      • Life of asset
      • Auditor
      • Individual records as entered
      • Who altered what? when?
      • Five years
      • Asset Manager
      • Overview of system
      • Two or more asset lifetimes
    • 9. Army Helicopters
      • Aging Aircraft Audit
      • DSTO request to examine Cost of Ownership – CN
      • Cost
            • engineering point of view
            • EE500, EE508
            • accountant point of view
            • ROMAN, SDSS
    • 10.
      • Designed to answer maintenance question on
      • Parts usage
        • Work area usage
        • Time between jobs – work rate
        • Failure Patterns
        • Usage pattern
        • Comparative histories between aircraft
      • In a graphical and intuitive way?
      Army Helicopters
    • 11. Paper based Maintenance Records
    • 12. Data Input
    • 13. Data Trending
    • 14. Maintenance Location
    • 15. MSD Data Quality
      • DSTO was requested to investigate the Quality of Data within the Maritime Systems Division of the Defence Material Organisation (DMO).
      • Limited resources 
      • Focused on the Quality of Maintenance Data in Asset Maintenance planning system (AMPS)
    • 16. Legacy Data
      • AMPS Current State
      • Ingres database with an proprietary user interface running across the defence intranet using Citrix. Separate analysis and reporting program requiring knowledge of both SQL and data table structure.
        • 800+ flat tables
        • No normalisation
      • Preferred state:
      • Intuitive Web interface to multiple databases for both input, analysis and reporting.
        • Normalised database
    • 17.
      • AMPS data quality has been found insufficient for both engineering and costing analyses. MAIT addresses these issues and introduces new features to promote the collection of high quality maintenance data.
      • Analysis capability
      • Web interface to AMPS data
        • Class wide queries
        • System Status
        • Job search
        • Maintenance history
      • Input capability with online feedback
      MAIT
    • 18. MAIT Architecture
    • 19. MAIT
      • Data Quality Reporting
      • RAM Analysis with Quality Indication
      • System Analysis and job tracking
      • Failure Data
      • Readings Trending and Validation
      • System Status Reporting
      • Performance Indicator Reporting
      • Audit and tracking
    • 20. IIS MAIT Ingres DB Ingres DB CITRIX AMPS IIS MAIT MSQL DB Transition
    • 21. Summary
      • Effective Use of Legacy Data.
      • Know who is target audience
      • Suggest
      • Web user interface
      • Integrate old and new data on the fly?
      • Separate application layers and data layer
      • Maintain primary data

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