Authors :
Tapash Paul; Jay Saha
Volume/Issue :
Volume 8 - 2023, Issue 4 - April
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/41aGO5M
DOI :
https://doi.org/10.5281/zenodo.7811159
Abstract :
Indian Railways is one of the largest railway
networks in the world, and the efficient functioning of its
infrastructure is essential for safe and timely
transportation. The point machine is one of the most
critical components of the railway system, which
controls the movement of trains at junctions. Regular
maintenance of the point machine is necessary to ensure
its proper functioning and prevent failures that can lead
to accidents and delays. Predictive maintenance is a
proactive approach that can significantly improve the
reliability and availability of the point machine. This
research paper aims to explore the application of
predictive maintenance techniques to Indian Railway
Point Machine and analyze its benefits.
Keywords :
IoT, Predictive, Point Machine, Machine Learning, Artificial Intelligence, K-means, Clustering, Indian Railways.
Indian Railways is one of the largest railway
networks in the world, and the efficient functioning of its
infrastructure is essential for safe and timely
transportation. The point machine is one of the most
critical components of the railway system, which
controls the movement of trains at junctions. Regular
maintenance of the point machine is necessary to ensure
its proper functioning and prevent failures that can lead
to accidents and delays. Predictive maintenance is a
proactive approach that can significantly improve the
reliability and availability of the point machine. This
research paper aims to explore the application of
predictive maintenance techniques to Indian Railway
Point Machine and analyze its benefits.
Keywords :
IoT, Predictive, Point Machine, Machine Learning, Artificial Intelligence, K-means, Clustering, Indian Railways.
