Reliability-centered Maintenance of the ElectricallyInsulated Railway Joint via Fault Tree Analysis:
A practical experience report
Enno Ruijters and Dennis GuckUniversity of Twente
Formal Methods and ToolsP.O. Box 217
7500 AE EnschedeThe Netherlands
Martijn van NoortProRail
P.O. Box 20383500 GA UtrechtThe Netherlands
Marielle StoelingaUniversity of Twente
Formal Methods and ToolsP.O. Box 217
7500 AE EnschedeThe Netherlands
AbstractMaintenance is an important way to increase systemdependability: timely inspections, repairs and renewals can sig-nificantly increase a systems reliability, availability and life time.At the same time, maintenance incurs costs and planned downtime. Thus, good maintenance planning has to balance betweenthese factors.
In this paper, we study the effect of different maintenancestrategies on the electrically insulated railway joint (EI-joint),a critical asset in railroad tracks for train detection, and arelative frequent cause for train disruptions. Together withexperts in maintenance engineering, we have modeled the EI-jointas a fault maintenance tree (FMT), i.e. a fault tree augmentedwith maintenance aspects. We show how complex maintenanceconcepts, such as condition-based maintenance with periodicinspections, are naturally modeled by FMTs, and how several keyperformance indicators, such as the system reliability, number offailures, and costs, can be analysed.
The faithfulness of quantitative analyses heavily depend onthe accuracy of the parameter values in the models. Here, wehave been in the unique situation that extensive data could becollected, both from incident registration databases, as well asfrom interviews with domain experts from several companies.This made that we could construct a model that faithfully predictsthe expected number of failures at system level.
Our analysis shows that that the current maintenance policy isclose to cost-optimal. It is possible to increase joint reliability, e.g.by performing more inspections, but the additional maintenancecosts outweigh the reduced cost of failures.
I. INTRODUCTIONReliability-centred maintenance (RCM)  is an important
trend in infrastructural asset management. Its goal is to obtainoptimal maintenance policies by maintaining crucial objectsmore intensively than less crucial ones. Thus, RCM tries tofind an optimal balance between maintenance cost and systemdependability, by placing maintenance effort where it mattersmost. To make such decisions, RCM requires a good insight inthe effect of a maintenance policy on the system dependability,with key performance indicators as the system reliability,availability, and mean time between failures, etc. In fact, sinceRCM intertwines dependability and maintenance, it asks for anintegral analysis of these two aspects. This paper demonstrateshow such integral analysis can work and leads to useful resultson RCM strategies, by studying a typical infrastructural assetvia fault-maintenance trees.
(insulating material) Bolt
Fig. 1. An electrically insulated joint with the visible components indicated.
Fault tree analysis (FTA)  is a popular methodologyfor dependability analysis. When the failure rates of thecomponents are known, then FTA can compute the odds of afailure of the entire system. In practice, however, these failurerates are strongly affected by maintenance, which is not takeninto account by fault trees. Thus, FTA is not suitable when themaintenance policy is subject to variation.
To overcome this limitation, and assess the impact of differ-ent maintenance strategies on system reliability and costs, faultmaintenance trees (FMTs) have been developed . Thesecombine fault trees with maintenance models, representing therequired ingredients for maintenance: component degradation,inspections, and repairs.
Moreover, FMTs necessitate the introduction of a newgate: the RDEP (rate dependency) gate makes that the failureof one component can accelerate the degeneration of othercomponents. In this paper, we show that RDEPs are essentialto faithfully model the EI-joint.
FMTs support the calculation of a number of importantdependability metrics, such as the system reliability, availabil-ity, MTTF, expected cost etc. Technically, these analyses arerealized via statistical model checking , a novel Monte Carlo
simulation technique .
EI-joints. Electrically insulated joints (EI-joints, see Figure1) are an important railroad element, facilitating train detec-tion and protection by electrically separating different tracksections. They are a relatively frequent cause for failures andservice disruption, so good maintenance is crucial for EI-joints.
Moreover, maintenance of the EI-joint is typical for otherassets as well, with both random and wear-induced failures,repairs and renewals, and different options for maintenancestrategies, and significant costs for failures and maintenance.
Modeling and analysis. In close collaboration with the Dutchnational railway network infrastructure manager ProRail, wehave conducted a reliability analysis of electrically insulatedjoints. We analyze the dependability of these joints, computingthe reliability, expected number of failures, and expected costsover time. In particular, we investigate a reference maintenancestrategy, as well as potentially better strategies. We study(1) variations in inspection intervals, (2) periodic preventivereplacements, (3) replacement of an entire joint instead of re-pairing individual components, and (4) repairs when observinghigher or lower degradation levels.
Our analysis finds that (1) the current inspection policyis nearly cost-optimal when combining cost of failure andcost of maintenance, (2) periodic preventive replacementsimprove reliability, but are more expensive than correctivereplacements, and (3) the optimal inspection policy does notvary much with the load level of the track.
An important contribution is the extensive validation of ourmodel: To provide confidence in the results of our analysis,we have compared the results predicted from our analysis withactual data from a failure database. Our predicted results agreewith actual results from the field strongly enough to makerecommendations based on our model.
Last but not least, we conclude that FMTs are a usefulframework to investigate maintenance optimization problemsfrom industrial practice: FMTs are a convenient model, havesufficient expressive power to capture complex maintenanceaspects; and are able to produce predictive analysis results.
Related work. Many analysis techniques and extensions forfault trees exist, for an overview we refer the reader to .Current FTA techniques support simple repair strategies byeither equipping leaves with repair times  or with repairboxes , but do not consider preventive maintenance.
More complex repair policies are supported by the Re-pairable Fault Tree  formalism by Codetta-Raiteri et al., butthis formalism still requires exponentially distributed failureand repair times.
Non-exponential failure time distributions can be used inthe tool by Bucci et al. , which can be used to analyzecomponent failures due to wear over time. This tool, however,does not consider maintenance to undo this wear.
Degraded states can be modeled in Extended Fault Treesby Buchacker et al.  which also supports components withfailure rates that depend on the states of other components.Failure times are still modeled as exponential distributions, andthis method does not include repairs or inspections dependenton full subtrees.
Looking outside FTA, Carnevali et al.  consider main-tenance in phased systems where resources are used in asequence of tasks, with detection and repair actions inbetween
Fig. 2. Depiction of the track circuit for train detection: the detection signal,depicted as the green line, is generated at the left of the images, and thedetector is at the right. The top image depicts the situation where the track isclear, the red lines on the bottom picture indicate the axles of a train. 1
these tasks.In systems consisting of identical components, Van
Noortwijk and Frangopol  consider in detail two modelsof the effects of various maintenance choices on the reliabilityand cost in civil infrastructure, but these do not generalize tosystems of multiple different components.
Organization of the paper. This paper begins with a de-scription of EI-joints in Section II and the methodology inSection III. The modeling of the EI-joint by FMTs is explainedin Section IV. Section V explains how this model is analyzed,and provides the results of this analysis. Finally, we provideour conclusions in Section VI.
II. CASE DESCRIPTION: MAINTENANCE OF EI-JOINTSElectrically insulated joints (see Figures 1 and 2) are a
railway component used in the detection of the occupancy of arailroad segment. They consist of a piece of insulating materialbetween the ends of two tracks, to keep different segmentsof track electrically separated, while mechanically holding thetracks together.
Due to the large number of these joints in the railroadnetwork, EI-joints are a relatively frequent cause of disrup-tions. Failures can occur for various reasons, both internalto the joint such as broken bolts, and external to the jointsuch as metal shavings bypassing the insulation. Inspectionscan be performed to determine whether some of these fail-ures are likely to occur soon, and corrective action, such assweeping away iron shavings, can prevent certain failures fromoccurring. Other failures can only be prevented or correctedby replacing the entire joint. Some