Comparable Life Cycle cost Analysis of Heavy Rail with ... · The Strasbourg transport network is...

Comparable Life Cycle cost Analysis of Heavy Rail with

Euro Tram on the Strasbourg and Rotterdam Networks

Applied Sc © 1995 All Rights Reserved. Revised 2011

Class 165 Suburban Train Euro Tram Vehicle

Adtranz Bid for the Rotterdam/Strasbourg Tram

Applied Sc © 1995 All Rights Reserved

Adtranz Ltd, is part of the Daimler-Benz Group and purchased British Rail

Engineering Works in Litchurch Lane, Derby, England. Adtranz Ltd raised

a bid for the design, build and maintenance for the tram network in

Rotterdam and Strasbourg.

The key issues raised by the first bid of this type by Adtranz are as

follows:

Adtranz Ltd is the provider of maintenance services to Chiltern

Railways fleet of Class 165 commuter train.

Adtranz Ltd has an extensive database of cost and repair

charges for the heavy rail vehicle, but limited data on the light rail

vehicle obtained from trails on the Strasbourg

Adtranz Ltd has carried out a 7 year refit on the Class 165

vehicle, so provide further life and cost data.

The routes of the heavy rail and light rail vehicles have similar

stop and start cycle regimes .

Life Cycle Costs Analysis


The aim of life cycle cost analysis is to understand and predict the total cost of the product throughout the product life cycle. It will include or have an influence over the following: Construction Cost Professional Fees

Maintenance Refits

Upgrades

Parts

Training

Fares

The Strasbourg Transport Network


The Strasbourg transport network is an extensive integrated bus, heavy rail and

light rail network. The light rail network is a key aspect of the transportation system.

Length: 25km of tramlines Stations: 47 (of which one – the Central Station - is underground) have central pillar shelters with real time information displays, automatic ticketing and validation. Peek Speed: 60km/h Average Speed : 18 km/h for both bus and light rail. Frequency: Every 4-6 minutes off-peak and 3 minutes or less peak times Trams Vehicles: Electric powered 3 car articulated sets using 750 dc supply

The Marylebone – Aylesbury Route


The Marylebone Station (London) to Aylesbury route is a stand-alone suburban

railway linking London’s north-west commuter belt with Central London and

interchanging with London Underground rapid transit system to Central London,

Ruislip, Amersham and Chesham. Length: Via Amersham - 60.73Km Via High Wycombe - 70km Stations: Via Amersham- 10. Via High Wycombe- 18. Peek Speed: 120km/h. Average Speed : 80km/h. Frequency: Via Amersham - Approximately 5 train per hour. Via High Wycombe - 1 hour. Vehicles: Diesel Multiple Units.

Maintenance Costs of Heavy Rail to Light Rail


The maintenance costs are a function of the stop-start cycle programme of the rail vehicle. A predominately long distance and high speed operation will produce a different stress and loading cycles on vehicle components than a short frequent low speed operation: However, breaking down vehicle systems they share the following: The compartmentalise of individual components and engineering sub- systems can be assigned a probability of failure as discrete system and sub-systems e.g. - Traction system, Power Trains, Engine/Traction Motors, Car/Body Shells, Wheel Sets, Drivers Compartment, Interior Fittings and Fixtures

The each system can be assign a repair cost achieve by undertaking a Markov Analysis of the system. There after each system is considered a black box with the probability of failure based on the black box not the internal components.

System and Sub System Black Box Repair Cost


The System and Sub-System black boxes has a distinct advantages over a discrete component model these are : The black box enables fix a standard price for each black box system repair.

All systems component black boxes can be allocated an reliability, availability and maintainability factors as MTTF (Mean Time To Failure), MTBF (Mean Time Before Repair) and MTTR (Mean Time To Repair).

The systems and sub system black boxes reliability, availability and maintainability factors can be presented as failure per kilometre travel per period out of service. The period out of service is timed in minutes. The disadvantages of System and Sub-System black boxes are: System and sub system parts are considered not repairable which can lead to higher recycling costs.

The Markov model for repairable systems


The Markov method for calculating the Mean Time To Failure (MTTF) of a system with repair considers the states which each system and sub-system can exist. Its assumed that a system and sub- system will have a constant failure rate and a constant repair rate. If constant failure rate or constant repair rate cannot be assumed then the Markov method cannot be used. With two identical systems or sub-systems have a failure rate of λ and an repair rate of μ (which is the reciprocal of the mean down time) then there are three possible state.

State (0) Both units operate . State (1) A single unit operates. State (2) Both units fail.

Partial Active Redundancy With n Repair Crews


The Mean Down Time (MDT) and therefore the system unavailability can be determined from the MTTF. A summary of functions for partial active redundancy with n repair crews that represent the MTTF (Mean Tine To Failure) for up to four connected units are illustrated in the following table.

System MTTF Table

Total number of Units

1

2

3

4

1 2 3 4

Number of units required to operate

1

22

3

3

22

6

2711

124

323 1850

2

1

26

5

3

22

12

513

3

1

212

7

4

1

Bayes Rule


Bayes Rule (or Bayes Theorem) can be used to determine the comparative life cycle cost , since Bayes Rule essentially an expression of conditional probabilities to an inverse condition. The conditional probability represents the probability of an event in a system or sub-system occurring based on prior evidence of the probability of the event’s happening again. The probability of failure P(A) of a systems A in light railway vehicle based on the known probability of failure P(B) of a the identical system in a heavy rail vehicle system B (prior knowledge). The joint probabilities of each system is (i.e. P(A,B)) as follows:

)(

)()|()|(

)()|()()|(

),(),(

BP

APABPBAP

APABPBPBAP

ABPBAP

Comparative Life Cycle Cost Using Bayes Theorem


)(

)()|()|(

)()|()()|(

),(),(

BP

APABPBAP

APABPBPBAP

ABPBAP

The life cycle cost model adopts the general form of Bayes Theorem and compares the probability of a failure P(A) of a system and lever’s the probability of a failure on a similar system P(B).

Where P(A|B) is the posterior event, P(B|A) is the likelihood , P(A) is the evidence and P(B) is the prior probability.

evidence

priorlikelihoodposterior

Computational model


The computational model operates on the database of probability of unit failures from the Class 165 Diesel Train as the prior probability, except where the Eurotram has already evidence of failure such as bogie and wheel sets. The probability of individual unit system failures on EuroTram where no evidence is available from Eurotrams in service (i.e. not under test or time in service is too short to evaluate failure rates), is derives as follows:- 1. Select a system unit from EuroTram that not the bogie or wheel sets.

2. Calculate the lilelihood using the identical system from the diesel train and

Eurotram as P(B|A). Body shell to body shell, power train to power train etc.

3. Determine the posterior probability of the Eurotram unit system or sub-

system using Bayes rule.

4. Calculate the MTTF from the Markov analysis matrix and hence determine the system failure rates, together with the system unavailability.

5. Convert the failure data into the Eurotram database and/or print report.

Conclusions and Observations


The computational model was successful implemented and assisted in ABB securing the maintenance contract for the Strasbourg and Rotterdam tram network The Bayesian Life Cycle Cost model ensures the vehicles high can sustain high usage, with over 30 million journeys per annum on the Strasbourg network Key points to note:- The processing power require to solve the computational model was low, requiring only a low speed i386 pc. Planned Maintenance and redesign of contentions low reliability systems and sub-system was eliminated. Update of the Eurotram database is advisable in the light of real service failure data. A clear picture of the total of Eurotram operation over one, seven and fifteen cycles (cycles are period of years between major overhauls. The computational model has the ability to predict maintenance cost which intern has informed accurate fares and pricing policy. Low fares and subsidy levels is obtained in part, from prior knowledge of maintenance changes and designing high reliability, maintainability and availability into systems.

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