Modelling of MTRC train maintenance system

Pao Yue-kong Library Electronic Theses Database

Modelling of MTRC train maintenance system

 

Author: Chan, Hing-lun
Title: Modelling of MTRC train maintenance system
Degree: M.Sc.
Year: 1997
Subject: Subways -- China -- Hong Kong
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Pages: vi, 87 leaves : ill. ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1398650
URI: http://theses.lib.polyu.edu.hk/handle/200/2355
Abstract: The objective of this project is to study the availability of trains in the MTRC under two different maintenance schemes, namely unit based maintenance (UBM) and train based maintenance (TBM). A mathematical model of the current train maintenance system of the MTRC is developed based on the discrete Markov chain approach. In similar studies, the presence of peak and non-peak periods is often neglected. In this project this feature is specially built into the model. The stochastic transitional probability matrix for the model was set up in the form of a spreadsheet in a personal computer. The steady state solution for the system was obtained by the inverse matrix method. Distributions for failure rate and repair probability during different times of a day were established from historical data. Parameters of these distributions were then fed into the computer model, the outputs of which were verified and validated against past data. Sensitivity modelling runs were carried out to study the behaviour of the system under a number of possible scenarios. Differences between UBM and TBM were compared in terms of train availability, the number of train reformations and the frequency of train shortages. The results of the study indicate that the presence of spare trains is the most important factor to achieve high availability. Under the current failure and repair rates and with the provision of 3 spare trains, no significant impact on train availability is expected when TBM is implemented. The model could be applied to other urban transport operations which have similar peak / non-peak service and repair patterns.

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