PREDICTIVE MAINTENANCE PLATFORM DESIGN USING IOT ON RAILWAY TURNOUT SYSTEM
The significant public interest in utilizing rail transportation necessitates careful consideration of the condition of railway facilities and infrastructure to uphold service quality for passengers. The government's initiative to enhance train speeds and services will inevitably impact the...
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| Main Author: | |
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/80808 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The significant public interest in utilizing rail transportation necessitates careful
consideration of the condition of railway facilities and infrastructure to uphold
service quality for passengers. The government's initiative to enhance train speeds
and services will inevitably impact the state of railroad facilities and infrastructure.
This study focuses on the turnout system, crucial for guiding trains along their
intended paths. Regular inspection of the turnout system is imperative to prevent
derailments, collisions, schedule disruptions, and other issues that hinder railway
performance. This research aims to develop a platform integrating planned
maintenance procedures with real-time analysis using lidar and accelerometer
sensors at the point machine, identifying anomalies, particularly in roller and
motor components. Platform testing, conducted in a laboratory/workshop setting
using point machine simulation equipment, yielded promising results: a throughput
of 270,000 per second with a test sample of 3000 threads and a response time of
1742 responses per millisecond. These findings are deemed satisfactory and can
serve as a benchmark for predictive maintenance efforts. |
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