Smart train control and monitoring system with predictive maintenance and secure communications features

Predictive maintenance is a proactive and data-driven approach to service maintenance that aims to identify potential problems before they occur. Modern trains have a sophisticated train control and monitoring system (TCMS), a vehicle processing unit to deliver train status conditions. On top of the...

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Main Authors: Alfian Akbar Gozali, Muhammad Faris Ruriawan, Andry Alamsyah, Yudha Purwanto, Ade Romadhony, Febry Pandu Wijaya, Fifin Nugroho, Dewi Nala Husna, Agri Kridanto, Anang Fakhrudin, Mu’ammar Itqon, Sri Widiyanesti
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Transportation Research Interdisciplinary Perspectives
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590198225000880
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author Alfian Akbar Gozali
Muhammad Faris Ruriawan
Andry Alamsyah
Yudha Purwanto
Ade Romadhony
Febry Pandu Wijaya
Fifin Nugroho
Dewi Nala Husna
Agri Kridanto
Anang Fakhrudin
Mu’ammar Itqon
Sri Widiyanesti
author_facet Alfian Akbar Gozali
Muhammad Faris Ruriawan
Andry Alamsyah
Yudha Purwanto
Ade Romadhony
Febry Pandu Wijaya
Fifin Nugroho
Dewi Nala Husna
Agri Kridanto
Anang Fakhrudin
Mu’ammar Itqon
Sri Widiyanesti
author_sort Alfian Akbar Gozali
collection DOAJ
description Predictive maintenance is a proactive and data-driven approach to service maintenance that aims to identify potential problems before they occur. Modern trains have a sophisticated train control and monitoring system (TCMS), a vehicle processing unit to deliver train status conditions. On top of the proprietary TCMS system, the authors designed an intelligent TCMS fitted with two main functions. First, the data analytics features predict the product age and deliver real-time notifications. Second, a robust infrastructure for mobile conditions with data security protection exists. Thus, the authors named the solution as Smart TCMS. This research has designed a user-friendly dashboard to facilitate real-time condition monitoring and timely notification of any detected problems, focusing on different level component severity problems: air conditioning (low severity), battery (medium severity), and traction system components (high severity). This solution has been implemented on an electric diesel train, an Indonesian Rolling Stock Industry (INKA) product.
format Article
id doaj-art-e6f686b8a5284d4b94ba99b665183cab
institution OA Journals
issn 2590-1982
language English
publishDate 2025-05-01
publisher Elsevier
record_format Article
series Transportation Research Interdisciplinary Perspectives
spelling doaj-art-e6f686b8a5284d4b94ba99b665183cab2025-08-20T02:37:03ZengElsevierTransportation Research Interdisciplinary Perspectives2590-19822025-05-013110140910.1016/j.trip.2025.101409Smart train control and monitoring system with predictive maintenance and secure communications featuresAlfian Akbar Gozali0Muhammad Faris Ruriawan1Andry Alamsyah2Yudha Purwanto3Ade Romadhony4Febry Pandu Wijaya5Fifin Nugroho6Dewi Nala Husna7Agri Kridanto8Anang Fakhrudin9Mu’ammar Itqon10Sri Widiyanesti11Telkom University, Bandung 40257, IndonesiaTelkom University, Bandung 40257, IndonesiaTelkom University, Bandung 40257, Indonesia; Corresponding author.Telkom University, Bandung 40257, IndonesiaTelkom University, Bandung 40257, IndonesiaIndonesian Rolling Stock Industry, Madiun 63122, IndonesiaIndonesian Rolling Stock Industry, Madiun 63122, IndonesiaIndonesian Rolling Stock Industry, Madiun 63122, IndonesiaIndonesian Rolling Stock Industry, Madiun 63122, IndonesiaIndonesian Rolling Stock Industry, Madiun 63122, IndonesiaIndonesian Rolling Stock Industry, Madiun 63122, IndonesiaTelkom University, Bandung 40257, IndonesiaPredictive maintenance is a proactive and data-driven approach to service maintenance that aims to identify potential problems before they occur. Modern trains have a sophisticated train control and monitoring system (TCMS), a vehicle processing unit to deliver train status conditions. On top of the proprietary TCMS system, the authors designed an intelligent TCMS fitted with two main functions. First, the data analytics features predict the product age and deliver real-time notifications. Second, a robust infrastructure for mobile conditions with data security protection exists. Thus, the authors named the solution as Smart TCMS. This research has designed a user-friendly dashboard to facilitate real-time condition monitoring and timely notification of any detected problems, focusing on different level component severity problems: air conditioning (low severity), battery (medium severity), and traction system components (high severity). This solution has been implemented on an electric diesel train, an Indonesian Rolling Stock Industry (INKA) product.http://www.sciencedirect.com/science/article/pii/S2590198225000880Predictive maintenanceTrainMachine learningData analyticsSecurityMobile infrastructure
spellingShingle Alfian Akbar Gozali
Muhammad Faris Ruriawan
Andry Alamsyah
Yudha Purwanto
Ade Romadhony
Febry Pandu Wijaya
Fifin Nugroho
Dewi Nala Husna
Agri Kridanto
Anang Fakhrudin
Mu’ammar Itqon
Sri Widiyanesti
Smart train control and monitoring system with predictive maintenance and secure communications features
Transportation Research Interdisciplinary Perspectives
Predictive maintenance
Train
Machine learning
Data analytics
Security
Mobile infrastructure
title Smart train control and monitoring system with predictive maintenance and secure communications features
title_full Smart train control and monitoring system with predictive maintenance and secure communications features
title_fullStr Smart train control and monitoring system with predictive maintenance and secure communications features
title_full_unstemmed Smart train control and monitoring system with predictive maintenance and secure communications features
title_short Smart train control and monitoring system with predictive maintenance and secure communications features
title_sort smart train control and monitoring system with predictive maintenance and secure communications features
topic Predictive maintenance
Train
Machine learning
Data analytics
Security
Mobile infrastructure
url http://www.sciencedirect.com/science/article/pii/S2590198225000880
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