Fault detection tool for maintenance of wayside signalling and communication

The Kelana Jaya Line (KJL) is the leading urban metro train operator in Malaysia and the eldest unmanned train operation system service use the automatic train-controlled system owned by Rapid KL. The system provides the highest reliability on the signalling aspect system which equips with sensors,...

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Main Author:	Samion, Norhafiza
Format:	Thesis
Language:	English English English
Published:	2019
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/10938/1/24p%20NORHAFIZA%20SAMION.pdf http://eprints.uthm.edu.my/10938/2/NORHAFIZA%20SAMION%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/10938/3/NORHAFIZA%20SAMION%20WATERMARK.pdf
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id	my-uthm-ep.10938
record_format	uketd_dc
spelling	my-uthm-ep.109382024-05-13T07:13:49Z Fault detection tool for maintenance of wayside signalling and communication 2019-07 Samion, Norhafiza T Technology (General) The Kelana Jaya Line (KJL) is the leading urban metro train operator in Malaysia and the eldest unmanned train operation system service use the automatic train-controlled system owned by Rapid KL. The system provides the highest reliability on the signalling aspect system which equips with sensors, electronics, and communication tool along the wayside. The key issue for KJL Wayside Signalling Maintenance Department team is facing a huge historical data and retrieving data failure records from the KJL Wayside Signalling data logger by manual screening method for maintenance purposes. This issue leads to time constraint and data redundancy. Therefore, this study aims to propose a tool known as a dashboard which may provide to retrieve failure data records by using Microsoft Excel software. The dashboard facilitates the team with the visualization of four selections inputs and three graphical outputs. This interactive tool made instant visibility of signalling status and assist the maintenance team to capture the trends of signalling activities. The tools begin with raw data processing using AWK programming for filtering and data cleansing for six significant variables of wayside equipment (i.e. Inductive Loop, Switch, Train, ID, Station Controller, and Platform). The result from the SUS shows the usability survey score 70.7 which is 1.04% above the global average. The study is beneficial for the organization on maintenance work in reducing time-consuming as per screening data and decision making for planning and scheduling 2019-07 Thesis http://eprints.uthm.edu.my/10938/ http://eprints.uthm.edu.my/10938/1/24p%20NORHAFIZA%20SAMION.pdf text en public http://eprints.uthm.edu.my/10938/2/NORHAFIZA%20SAMION%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/10938/3/NORHAFIZA%20SAMION%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Teknologi Kejuruteraan
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	T Technology (General)
spellingShingle	T Technology (General) Samion, Norhafiza Fault detection tool for maintenance of wayside signalling and communication
description	The Kelana Jaya Line (KJL) is the leading urban metro train operator in Malaysia and the eldest unmanned train operation system service use the automatic train-controlled system owned by Rapid KL. The system provides the highest reliability on the signalling aspect system which equips with sensors, electronics, and communication tool along the wayside. The key issue for KJL Wayside Signalling Maintenance Department team is facing a huge historical data and retrieving data failure records from the KJL Wayside Signalling data logger by manual screening method for maintenance purposes. This issue leads to time constraint and data redundancy. Therefore, this study aims to propose a tool known as a dashboard which may provide to retrieve failure data records by using Microsoft Excel software. The dashboard facilitates the team with the visualization of four selections inputs and three graphical outputs. This interactive tool made instant visibility of signalling status and assist the maintenance team to capture the trends of signalling activities. The tools begin with raw data processing using AWK programming for filtering and data cleansing for six significant variables of wayside equipment (i.e. Inductive Loop, Switch, Train, ID, Station Controller, and Platform). The result from the SUS shows the usability survey score 70.7 which is 1.04% above the global average. The study is beneficial for the organization on maintenance work in reducing time-consuming as per screening data and decision making for planning and scheduling
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Samion, Norhafiza
author_facet	Samion, Norhafiza
author_sort	Samion, Norhafiza
title	Fault detection tool for maintenance of wayside signalling and communication
title_short	Fault detection tool for maintenance of wayside signalling and communication
title_full	Fault detection tool for maintenance of wayside signalling and communication
title_fullStr	Fault detection tool for maintenance of wayside signalling and communication
title_full_unstemmed	Fault detection tool for maintenance of wayside signalling and communication
title_sort	fault detection tool for maintenance of wayside signalling and communication
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Teknologi Kejuruteraan
publishDate	2019
url	http://eprints.uthm.edu.my/10938/1/24p%20NORHAFIZA%20SAMION.pdf http://eprints.uthm.edu.my/10938/2/NORHAFIZA%20SAMION%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/10938/3/NORHAFIZA%20SAMION%20WATERMARK.pdf
_version_	1804890123362369536

Fault detection tool for maintenance of wayside signalling and communication

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