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Failure Diagnostic and Performance Monitoring, it is a part of CM program for airlines, it is addressing the condition of components of the aircraft, either it is initial , random or wear failures.

Failure Diagnostic and Performance Monitoring, it is a part of CM program for airlines, it is addressing the condition of components of the aircraft, either it is initial , random or wear failures.

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Failure diagnostic Presentation Transcript

  • 1. Failure Diagnostic and Performance Monitoring ACTUARIAL TECHNIQUE An Implemented Approach for Airlines Prepared by Eng. Mohammed Salem Awad Consultant
  • 2. OVERVIEW
    • Maintenance Process
      • Maintenance Process
      • On Condition
      • Condition Monitoring
    Preventive Maintenance Corrective Maintenance
  • 3. PRODUCT LIFE MODEL CYCLES / HOURS Failure Rate Bath –Tub Curve Chance Failure Initial F. Wear out F.
  • 4. THEORETICAL MODEL WEIBULL DISTRIBUTION Define By Three Parameters  Location Parameter   Scale Parameter  Shape Parameter 
  • 5. THEORETICAL MODEL WEIBULL DISTRIBUTION time
  • 6. THEORETICAL MODEL WEIBULL DISTRIBUTION
    • The Parameters can be indicated
    •  Location Parameter  characteristic life
    •  1 Infant mortality. 
    • = 1 Randomly Distributed Failures.
    •  Failure related to TSO 
  • 7. THEORETICAL MODEL WEIBULL DISTRIBUTION Parameters Evaluation Cumulative distribution function Transform to i.e identical to 
  • 8. ACTUARIAL TECHNIQUES The Flow Chart is illustrated the Actuarial Technique Flight Time, Median Rank, No. Of Reading *Decision of Reliability For Component *Characteristic Life of Component. *Time Since Overhaul Selection The Value of   Transform the distribution to the linear form y = mx + c Weibull Distribution R 2 > 80% Evaluation For  and  YES NO Evaluation of R and R 2 
  • 9. ACTUARIAL TECHNIQUES Analysis : Actuarial Techniques is a part of Reliability Control Program. 1- Specify a components for the analysis and indicate its part number, collect number of reading of confirm failure, and define its failure Mode. 2- According to the number of reading select the corresponding values of median rank at desired level of confidence say 95% of two tail regain . 3- Transform the Weibull distribution to linear form y = mx + c and start the analysis by using one tentative value location parameter of Weibull distribution. 4- Calculate coef. of correlation R and coef. of determination R. Flight Time, Median Rank, No. Of Reading *Decision of Reliability For Component *Characteristic Life of Component. *Time Since Overhaul Selection The Value of   Transform the distribution to the linear form y = mx + c Weibull Distribution R 2 > 80% Evaluation For  and  YES NO Evaluation of R and R 2 
  • 10. ACTUARIAL TECHNIQUES 5- If R is less than 80 % select another value of location parameter and repeat the calculation until the value of R is greater than 80%. 6- When the value R is greater than 80 % then evaluate scale parameter and shape parameter. 7- As the three parameters of Weibull distribution are defined, so we can find for the concerned component, its reliability level, characteristic life, and it mean time to failure. Flight Time, Median Rank, No. Of Reading *Decision of Reliability For Component *Characteristic Life of Component. *Time Since Overhaul Selection The Value of   Transform the distribution to the linear form y = mx + c Weibull Distribution R 2 > 80% Evaluation For  and  YES NO Evaluation of R and R 2 
  • 11. DATA COLLECTION Sections/ Divisions -Hangar -Line Maintenance -Technical Record -Material Planning -Engineering Forms Com. Change Form Com. Change Form Hours Run Form Shop Finding Report Review of CM Com.
  • 12. FLOW INFORMATION HANGAR LINE M. TECH. STORES MATERIAL PLANNING TECH. RECORD Engineering Division *Decision of Reliability For Component *Characteristic Life of Component. *Time Since Overhaul C.C.F C.C.F Conform Failures Reliable Components Shop Finding Report Hours Run Hours Run Review of CM Review of CM
  • 13. CYCLE OF CONDITION MONITORING COMPONENTS Data Sampling / Analysis for confirmed Failures Shop Finding Report (Confirmed / Not Confirmed) CM Components Removals Local Repairs / Repair At Station
  • 14. Main Electric Trim Actuator CASE STUDY
  • 15. CASE STUDY DATA SURVEY
  • 16. CASE STUDY Fitting Data To Weibull Distribution
    • Evaluation of Location Parameters
    • The Graph
    • shows the
    • best value is
    • 750
    • Flt Hours
  • 17. CASE STUDY Fitting Data To Weibull Distribution
    • Evaluation of Location Parameters
  • 18. CASE STUDY Fitting Data To Weibull Distribution
    • Evaluation of Weibull Parameters
    • Using Linear
    • Regression
    • Y = M X + C
  • 19. CASE STUDY Fitting Data To Weibull Distribution
    • Evaluation of Weibull Parameters
  • 20. CASE STUDY Fitting Data To Weibull Distribution
    • Weibull Parameters
    • Location Parameter = 750 Flight Hours
    • Scale Parameter = 3305
    • Shape Parameter = 2.209
    • Since the Shape Parameter is Greater Than 1
    • So this item is time related to Overhaul ( TBO)
  • 21. CASE STUDY Weibull Distribution
    • Hazard Function
  • 22. CASE STUDY Weibull Distribution
    • Reliability Function
  • 23. CASE STUDY Weibull Distribution
    • Result : For Main Electric Trim Actuator
    • Hazard Rate
    • The Main Time To
    • Failure
    • Reliability Distribution
    • Reliable Life
  • 24. SUMMARY
    • This paper define clearly two Situation
      • Beta greater than 1
      • This situation will lead to Time related to TBO
      • Beta Less than 1
        • Two decision can be carry out
        • Either the problem is due to improper installation for components by the engineers during maintenance which cause the defects.
        • There is a certain defects in the design of the components which leads to failure
  • 25. SUMMARY cont…
    • If and only if the Airline has a skill and reliable engineers, the approach can indicates the reliable vendors from those suppliers of the components.
  • 26. Contact Contact : Mohammed Salem Awad Consultant Tel : 00967734777518 Email: [email_address]