reliability analysis of switches and crossings 2013 v1.4

7/22/2019 Reliability Analysis of Switches and Crossings 2013 v1.4

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Reliability Analysis of Switches andCrossings A Case Study in

Swedish Railway

Behzad Ghodrati, Alireza Ahmadi, Diego Galar

Division of Operation and Maintenance EngineeringLule University of Technology, Sweden


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Introduction

Railway complexity:

Mix of components with different age

Working together

Increase

traffic

volume

Higher

utilization

of capacity

Minimize

maintenance

time

Minimizeunplanned

interruption

Maintenance be performed near capacity limits

Time between asset renewals be long enough


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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


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Reliability:Ability of an item to perform a required

function under given conditions for a given timeinterval.

RAMS(reliability, availability, maintainability and safety)

tetR )(

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 externalresources are provided.

timeTotal

repairofTimestimeTotalA

RAMS


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Switches

A railroad switch, turnout or set of points is a

mechanical installation enabling railway trains to beguided from one track to another at a railway junction.

Name of switche in Swedish railway system:A-B-C-D(e.g.

EVSJ50111:9),

A:type of switch (single, double)Check rail

B: type of railpanel

C:radius or length of switch blade

D:type of angle


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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


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BODEN

NGE

GVLE

NORRKPING

STOCKHOLM

MALM

GTEBORG

HALLSBERG

Sweden railway network


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Data collection and evolution

Number of registered failures

Jan. 2005Dec. 2009

Age and location

of turnouts

Switches with

numbers inferior to

50 was eliminated

Raw Data

43528 failures

Raw data without unnecessary types of turnouts

42221 failures

Installation

date known

Installation

date unknown

Turnouts

known

Turnouts

unkown

Turnouts

known

Turnouts

unkwown

- Changed between

05/09:

-in BESSY (1452

failures)

-not in BESSY

- Not changed

-installation date

0" (2004failures)

-the rest (25006

failures)

- In BESSY (30 failures)

- Not in BESSY

- Changed between

05/09:

-in BESSY (31

failures)

-not in BESSY

- Not changed

-installation date

0" (176failures)

-the rest (977

failures)- #N/A

- Unkwown (10477

failures)

29676

failures


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24%

8%68%

Turnouts unkown

Data not found in the

different files

Data available for study

29676

failures

10477

failures

3375

failures

Final available data

Take into account the 10types of turnoutsgenerating most failures and 60tracks of interest

16627 failures


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Tracks with more

failures with at least

10 individuals asset

names and at least 2

types of turnouts

Studied tracks and switches

Tracknumber Type of track124 Freight track410 Commuter trians and some freight414 Mixed passenger and freight420 Mixed passenger and freight512 Mixed passenger and freight611 Mixed passenger and freight811 Mixed passenger and freight813 Mixed passenger and freight912 Mixed passenger and freight

9 (out of 60) focused tracks


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641

715

867

1214

1745

28902997

3224

4291

5301

EV-SJ50-12-1:12

EV-SJ50-12-1:13

EV-UIC60-760-1:14

EV-UIC60-1200-

EV-UIC60-1200-1:18,5

EV-UIC60-300-1:9DKV-SJ50-

EV-SJ50-12-1:15

EV-UIC60-760-1:15

EV-SJ50-11-1:9

0 2000 4000 6000

Number of failures

10 types of turnouts

generating more failures

EV-SJ50-11-1:9

EV-SJ50-12-1:15

EV-UIC60-1200-1:18,5

EV-UIC60-1200-1:18,5 BL33

EV-UIC60-300-1:9

EV-UIC60-760-1:14

EV-UIC60-760-1:15

EV-SJ50-11

EV-SJ50-12

EV-UIC60-300

EV-UIC60-760

EV-UIC60-1200


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Dividing into 2 types of tracks

nhsp

main track

ahsp

diverging track

Dividing into 2 seasons

COLD

from November to March

(5 months)

HOTfrom April to October (7 months)

55%45%

Proportion of failures byseason

Cold

Hot

Data classification


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3

7

10

13

31

47

62

79

98109

120

710

1616

2057

2520

0 500 1000 1500 2000 2500 3000

Cross over panel

Check rail

Ballast

Sleeper (bearer)

Rail

Snow protection

Locking device

Crossing

FastenersRail joint (mostly insulated rail joint)

Heating system

Switch blade


(blank)


Hot

Subsystems affected by

failures Hot period


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4

7

8

10

36

57

66

79

80105

624

1194

1474

2521

2765

0 500 1000 1500 2000 2500 3000

Cross over panel

Sleeper (bearer)

Ballast

Check rail

Rail

Locking device

Fasteners

Crossing

Rail joint (mostly insulated rail joint)Snow protection

Switch blade

Heating system



(blank)

Cold

Subsystems affected by

failures Cold period


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1194

624

1474

2765

2521

120

710

1616

2057

2520

0 1000 2000 3000

Heating system

Switch blade

Switch device (motor,gearbox, coupling, bars, ...)

(blank)

Switch blade positiondetector

HOT

COLD

Comparison of subsystems with

more failures during the two

seasons


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RDAT (Reliability Data Analysis Tool) software was developed

by Alstom and the University of Bordeaux (France), and dealwith highly censored field data which wasnt 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:

= 1 means that the maintenance quality is AGAN (the

maintenance operation is perfect).

= 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).


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Intrinsic Reliability Analysis

Is Exponential best

Estimator?

Kijima

Rho = 0 Rho = 10 < Rho < 1

Work on

ABAO

Work on

First Failure

Work on

AGAN

Work onFirst Failure

YesNo

Work on

First Failure

Maintenance

effect analysis

POSSIBLE

Maintenance

effect analysis

NOT POSSIBLE

RDAT software methodology


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Data analysis RDAT software output

Trafikverket (Swedish Railway Administration) maintenance

experts consulting:

70% of

cases

=1

30% of

cases,

= 0,5-1

AGAN maintenance

ABAO maintenance

ABAO model was considered


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Instantaneous failurerate

failure rate

shape parameter

Instantaneous Mean Time BetweenFailures

T

n

n

i

iTTn

n

1

lnln

Data analysis RDAT software output


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< 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) > reducesnumber 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


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> 1 MTBF

Old equipment fails more > Maintenance is not compensating

the age of the turnout


Growth factor Beta as a function of types of turnout and season and type

of track


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Comparison between hot/cold

There are much more < 1 during COLD season, better

maintenance? More effective maintenance during winter time?

There are much more > 1 during HOT season, worstmaintenance?

Is there any link with the number of failures avery year?



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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


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Values of and for different types of turnouts for the 9 tracks

RDAT results

Example for tracks 124, 410 and 912 for main track and SJ50-11


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Example for tracks 124, 410 and 912 for main track and SJ50-11

11 1

RDAT results


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0

0.00005

0.0001

0.00015

0.0002

0.00025

0.0003

0.00035

0.0004

3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60

Fail

ure

rate

()

Months (from January 05 to December 09)

Instantaneous failure rate (SJ50-11 and nhsp-cold)

124

410

912

RDAT results


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Turnout

1

Turnout

2

Turnout

3

Turnout

4

Turnouts are in serie in a track

Availability


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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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reliability analysis of switches and crossings 2013 v1.4

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