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Reliability Analysis of Switches and Crossings – A Case Study in Swedish Railway

Reliability Analysis of Switches and Crossings – A Case Study in Swedish Railway. Behzad Ghodrati, Alireza Ahmadi, Diego Galar Division of Operation and Maintenance Engineering Luleå University of Technology, Sweden. Introduction. Railway complexity: Mix of components with different age

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Reliability Analysis of Switches and Crossings – A Case Study in Swedish Railway

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  1. Reliability Analysis of Switches and Crossings – A Case Study in Swedish Railway Behzad Ghodrati, Alireza Ahmadi, Diego Galar Division of Operation and Maintenance Engineering Luleå University of Technology, Sweden

  2. Introduction • Railway complexity: • Mix of components with different age • Working together Minimize maintenance time • Maintenance be performed near capacity limits • Time between asset renewals be long enough Increase traffic volume Higher utilization of capacity Minimize unplanned interruption

  3. Introduction The key goal is to achieve availability target cost effectively. Availability Supportability Reliability Maintainability • To conduct reliability analysis: • Detail failure and maintenance recorded data • Detail maintenance action done • Mission profile: duty cycle and environmental characteristics

  4. RAMS Reliability: Ability of an item to perform a required function under given conditions for a given time interval. RAMS (reliability, availability, maintainability and safety) Availability: Ability of an item to be in a state to perform a required function under given conditions at a given instant of time or during a given time interval, assuming that the required external resources are provided.

  5. Switches A railroad switch, turnout or set of points is a mechanical installation enabling railway trains to be guided from one track to another at a railway junction. Name of switche in Swedish railway system: A-B-C-D (e.g. EV – SJ50 – 11 – 1:9), A: type of switch (single, double)Check rail B: type of railpanel C: radius or length of switch blade D: type of angle

  6. Switch and Crossing Elements • Ballast • Check rail • Cross over panel • Crossing • Fasteners • Heating system • Locking device • Rail • Rail joint (mostly protected rail joint) • Sleeper (bearer) • Snow protection • Switch blade • Switch blade position detector • Switch device (motor, gearbox, coupling, bars, etc.)

  7. Sweden railway network

  8. Data collection and evolution Number of registered failures Jan. 2005 – Dec. 2009 Switches with numbers inferior to 50 was eliminated Age and location of turnouts

  9. Final available data 10477 failures 29676 failures 3375 failures Take into account the 10 types of turnouts generating most failures and 60 tracks of interest 16627 failures

  10. Studied tracks and switches 9 (out of 60) focused tracks Tracks with more failures with at least 10 individuals asset names and at least 2 types of turnouts

  11. 10 types of turnouts generating more failures

  12. Data classification Dividing into 2 types of tracks Dividing into 2 seasons nhsp main track ahsp diverging track COLD from November to March (5 months) HOT from April to October (7 months)

  13. Subsystems affected by failures – Hot period

  14. Subsystems affected by failures – Cold period

  15. Comparison of subsystems with more failures during the two seasons

  16. Data analysis tool RDAT (Reliability Data Analysis Tool) software was developed by Alstom and the University of Bordeaux (France), and deal with highly censored field data which wasn’t taken into account properly with the already existing programs. RDAT was used to estimate the reliability functions and failure rates from field data Four failure models have been implemented in RDAT: exponential, Weibull, normal, and lognormal distributions. To select the best model, a goodness-of-fit test is applied. • The maintenance quality is considered by a parameter denoted Rho: • ρ = 1 means that the maintenance quality is AGAN (the maintenance operation is perfect). • ρ = 0 means that the maintenance quality is ABAO (the mission can continue but leaves the item with a reliability corresponding to the age accumulated so far).

  17. RDAT software methodology

  18. Data analysis – RDAT software output 70% of cases ρ =1 AGAN maintenance 30% of cases, ρ = 0,5-1 ABAO maintenance Trafikverket (Swedish Railway Administration) maintenance experts consulting: ABAO model was considered

  19. Data analysis – RDAT software output • Instantaneous failure rate λfailure rate βshape parameter • Instantaneous Mean Time Between Failures

  20. RDAT implementation and results Growth factor Beta as a function of types of turnout and season and type of track β < 1 → MTBF ↗ • Maybe the maintenance has improved in these 5 years (Case of infant mortality: many problems at the beginning) • The organisation learned how to deal with failures during 05/09 • Other possible explanation: • For SJ50-11 switch point detectors taken out (less failures) • Change of switch point detectors on the other types of turnouts (from mechanical to electrical) > reduces number of failures in Hot and Cold

  21. RDAT implementation and results Growth factor Beta as a function of types of turnout and season and type of track β > 1 → MTBF ↘ • ”Old equipment fails more” > Maintenance is not compensating the age of the turnout

  22. RDAT implementation and results • Comparisonbetween hot/cold • There are much more β< 1 during COLD season, better maintenance? More effective maintenance during winter time? • There are much more β > 1 during HOT season, worst maintenance? Is there any link with the number of failures avery year?

  23. Comparisonbetween hot/cold There is no relationship between the number of failures every year and the improved or not of the maintenance for these years.

  24. RDAT results Values of λ and β for different types of turnouts for the 9 tracks Example for tracks 124, 410 and 912 for main track and SJ50-11

  25. RDAT results Example for tracks 124, 410 and 912 for main track and SJ50-11 β β β ≤1 ≈1 ≥1

  26. RDAT results

  27. RDAT results

  28. Availability Turnouts are in serie in a track Turnout 2 Turnout 3 Turnout 4 Turnout 1

  29. Conclusion • The RAMS analysis confirms the more failure in Cold season than in Hot season • For tracks 124, 410 and 912 • Failure rate decreasing during Cold season • Failure rate almost constant during Hot season • Track 512, which has the lowest availability, needs to be focused for improvement • The RDAT software is not taking into account this parameter. However, it is possible to do a covariate analysis including this factor. • On the most important failure contributors, which are the switch blade position detectors, switch devices, heating system in the cold season, and switch blades

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