Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 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
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 2 Introduction Railway complexity: Mix of components with different age Working together Increase traffic volume Higher utilization of capacity Minimize maintenance time Minimize unplanned interruption Maintenance be performed near capacity limits Time between asset renewals be long enough
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 3 Introduction The key goal is to achieve availability target cost effectively. Availability Reliability Maintainability Supportability To conduct reliability analysis: Detail failure and maintenance recorded data Detail maintenance action done Mission profile: duty cycle and environmental characteristics
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 4 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. RAMS
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 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
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 6 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.) Switch and Crossing Elements
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 7 Sweden railway network
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 8 Data collection and evolution Number of registered failures Jan – Dec Age and location of turnouts Switches with numbers inferior to 50 was eliminated
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering failures failures 3375 failures Final available data Take into account the 10 types of turnouts generating most failures and 60 tracks of interest failures
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 10 Tracks with more failures with at least 10 individuals asset names and at least 2 types of turnouts Studied tracks and switches Track number Type of track 124 Freight track 410 Commuter trians and some freight 414 Mixed passenger and freight 420 Mixed passenger and freight 512 Mixed passenger and freight 611 Mixed passenger and freight 811 Mixed passenger and freight 813 Mixed passenger and freight 912 Mixed passenger and freight 9 (out of 60) focused tracks
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering types of turnouts generating more failures EV-SJ :9 EV-SJ :15 EV-UIC :18,5 EV-UIC :18,5 BL33 EV-UIC :9 EV-UIC :14 EV-UIC :15 EV-SJ50-11 EV-SJ50-12 EV-UIC EV-UIC EV-UIC
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 12 Dividing into 2 types of tracks nhsp main track ahsp diverging track Dividing into 2 seasons COLD from November to March (5 months) HOT from April to October (7 months) Data classification
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 13 Subsystems affected by failures – Hot period
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 14 Subsystems affected by failures – Cold period
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 15 Comparison of subsystems with more failures during the two seasons
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 16 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. Data analysis tool 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).
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 17 RDAT software methodology
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 18 Data analysis – RDAT software output Trafikverket (Swedish Railway Administration) maintenance experts consulting: 70% of cases ρ =1 30% of cases, ρ = 0,5-1 AGAN maintenance ABAO maintenance ABAO model was considered
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 19 Instantaneous failure rate λ failure rate β shape parameter Instantaneous Mean Time Between Failures Data analysis – RDAT software output
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 20 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 RDAT implementation and results Growth factor Beta as a function of types of turnout and season and type of track
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 21 β > 1 → MTBF ↘ ”Old equipment fails more” > Maintenance is not compensating the age of the turnout RDAT implementation and results Growth factor Beta as a function of types of turnout and season and type of track
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 22 Comparison between 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? RDAT implementation and results
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 23 There is no relationship between the number of failures every year and the improved or not of the maintenance for these years. Comparison between hot/cold
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 24 Values of λ and β for different types of turnouts for the 9 tracks RDAT results Example for tracks 124, 410 and 912 for main track and SJ50-11
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 25 Example for tracks 124, 410 and 912 for main track and SJ50-11 β ≤1 ≈1 ≥1 ββ RDAT results
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 26 RDAT results
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 27 RDAT results
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 28 Turnout 1 Turnout 2 Turnout 3 Turnout 4 Turnouts are in serie in a track Availability
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 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
Division of Operation and Maintenance Engineering Division of Operation and Maintenance Engineering 30