Smart train control and monitoring system with predictive maintenance and secure communications features - 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 (Transportation Research Interdisciplinary Perspectives)
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.