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AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07
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AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07

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  • 1. AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07 OKLAHOMA CITY AIR LOGISTICS CENTER I n t e g r i t y - S e r v i c e - E x c e l l e n c e TEAM TINKER Mr. Bob Wright OC-ALC/ENFO [email_address]
  • 2. Problem
    • Many USAF airframe’s average age are at or beyond design limits and experiencing growing unpredicted component failures
    • Current damage analyses for structural components do not consider extensive maintenance activity accomplished on these airframes
    • Much relevant maintenance data (description of defects found, or repair accomplished) is either captured on paper only, or not captured at all; and not related to a specific a/c
  • 3. Mil-Std-1530 Requirement 5.4.3.1 Structural maintenance database development. The structural maintenance database shall be developed to capture adequate, detailed information on the aging processes (fatigue, corrosion, delaminations, etc.) which occur in the aircraft and thus support the ongoing evaluation of structural integrity during sustainment. The database shall be developed to record all significant damage findings such as cracks , corrosion , and/or delaminations discovered during program depot maintenance, analytical condition inspections, time compliance technical order (TCTO) structural inspections, teardown inspections, and normal operational maintenance . The database shall also be able to record a description of the damage types , damage sizes , damage locations , inspection techniques (including POD information), aircraft configuration, pertinent aircraft usage history including basing information, and corrosion preventive methods (e.g., wash cycles, coatings, etc.). The database shall also be able to record all significant repairs and/or modifications so as to maintain configuration control. These records shall include a description of the repair/modification and when it was incorporated. Additional considerations for data to be recorded shall facilitate the analysis update described in 5.5.6. MIL-STD-1530C (Aircraft Structural Integrity Program)
  • 4. What is Needed
    • Provide quantitative information for decisions related to individual aircraft and fleet system health.
      • Acquire, consolidate, and evaluate maintenance data to provide a continual update of the health of operational aircraft.
        • Significant damage findings during PDM
        • Analytical Condition Inspections/results
        • TCTO structural Inspections/results
        • Field -3 repairs
    • Identify/use existing Air Force systems when possible
        • Depot and Field level (i.e. CAMS, PDMSS, G081, etc.)
    • Provide alternative solutions for data short falls.
        • Damage size, type, and location.
        • Pictures/Diagrams
        • Basing information,
        • Modification and repair actions.
  • 5. Functional Requirements for Maintenance Data Analysis
    • 327 th ASW ASIP managers need trending analysis relating actual defects found to aircraft usage
    • 76 MXW needs to anticipate incoming non predicted defects based on aircraft usage and PDM history ASIMIS / G050
    • ASC and Fleet Viability Board need to view current fleet status and future repair requirements to determine best course of action for airframes
  • 6. Using usage data and mx information to anticipate Structural Failures Reporting Actual Fleet Condition Structural Models Usage Monitoring Inspection Fidelity Assessment Damage Findings ASIMIS 76 MXW G050 New Mil-Std 1530C Task V (sustainment) goal Proposed Vision
  • 7. ASIMIS Aircraft Usage Reporting
    • Usage data available via web-based tool called DART
    • Flight loads recorder data can be accessed via web system called ADADS
  • 8.
    • Consolidates the following data
        • NDI Log
        • AFMC 202’s (Technical Assistance Requests)
        • T.O. 00-25-107 (Tech Manual for Requesting Maintenance Assistance)
        • AFTO 349
        • AFTO 95 Corrosion Data
        • AFTO 427 Integral Fuel Cell Repairs
        • Structural Audit Findings
    • Graphical User Interface (GUI)
        • Data retrieval & Analysis
        • Eventually data input
    Maintenance Data Collection
  • 9. 76 AMXG/QIQ Proposed Projects
    • Automated Process Guide – Automates inspection processes utilizing mobile data collection devices
      • Ensures standardization and complete inspections
      • More accurate tie to WUC and HMC technical data codes
    • Labor Analysis – Provides visibility into work flow including back shops and support processes
      • Flags labor problem areas for individual analysis
    • Low Percent Analysis – Anticipates incoming non predicted defects based on aircraft usage and PDM history (not a reliability study!!)
    • Quality Data Analysis – Analyzes aircraft defects to provide root cause and trend analysis
  • 10. Support Requirements for Maintenance Data Analysis
    • ASIMIS collects usage history per tail number
      • Flight hours, landings, fuel offloads, time @ mach/alt
    • 76 MXW will collect defect/repair information per tail number
    • We still need tools to query defect information captured during maintenance and display against usage data to enable trending analysis
  • 11. Point of Contacts
        • Randel Bowman, 76 AMXG/QIQ
          • E-mail: [email_address]
        • Bob Wright, OC-ALC/ENFO
          • E-mail: [email_address]
        • Ken Simmons, OC-ALC/ENET
          • E-mail: [email_address]

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