Information systems in the railway industry is on a new journey—towards an increasingly digital and virtual infrastructure. The focus is on improving asset availability and operational performance. Having a robust condition monitoring system for rolling stock is critical to ensure seamless functioning of the rail network, planning corrective maintenance actions, and proactively scheduling component replacements. Smart railway companies are effectively using big data analytics to monitor asset condition in near real time giving them greater control over their operations and significantly enhancing decision making.
Download this paper to know how the Cyient data analytics team developed and implemented a comprehensive condition monitoring system for rolling stock by analyzing big data. Learn how terabytes of raw data generated across railway networks can be leveraged to ensure optimal functioning of rail assets, increase efficiency, improve safety, and streamline processes across the network.