Predictive Maintenance and Route Optimization
A Leading Rail-Based Transportation Company Case Study
This leading rail-based transportation company is focused on rail transportation and real estate, supplying rail-based freight transportation. Their rail and intermodal businesses provide rail-based transportation services including traditional rail service and the transport of intermodal containers and trailers.
This customer needed to run predictive analytics on their equipment while ingesting and processing streaming data at scale, in order to monitor and diagnose potential failures to help its fleet operators reduce maintenance costs, improve the process of troubleshooting, and redirect trains in a timely manner.
- Process streaming data at scale and query from a live data mart
- Event-driven analytics and business logic
- Many small low-volume streams that require correlation and statefulness (the IoT streaming problem)
- Real-time analytics leveraging GPS, train sensor data
With GigaSpaces’ in-memory real-time analytics platform, this customer was able to ingest and process streaming data from millions of sensors and provide real-time insight and respond instantly to situations. By leveraging machine learning on real-time and historical data, the safety and reliability of the journey has improved as well as cost-saving measures that conserve fuel and increase safe operating speeds. Event-based triggers now direct the output to operational workflows and live dashboards for timely maintenance and redirecting of trains.
- Simplified big data pipeline
- High-performance stream processing with High Availability
- Real-time analytics on relevant data from train events, fence events, and GPS
- Event-based triggers to direct the output to operational workflows and live dashboards for timely maintenance and redirecting of trains