Sasken Success Stories | Sasken Technologies Limited

Asset performance management for rolling stock

Written by Admin | Aug 26, 2019 4:00:00 AM

Scope: To enable predictive maintenance for heavy assets in order to prolong their lifespan as well as to reduce the operational/maintenance cost

Solution: 

  • Sasken’s approach focuses on Vibration Analysis to detect anomalies as vibration signature is most widely used methodology of anomaly detection in heavy machinery
  • Edge: Data acquisition using Accelerometer-based sensors, Protocol translation, Ingestion to the Cloud
  • Cloud and Analytics: Data assimilation on the Cloud enabling unified view of data
  • Supervised & Unsupervised Machine Learning models
  • Condition Monitoring: Current health of the asset and anomaly detection

Impact:

  • Enhanced visualization of machine critical parameters and analytics based key insights
  • Proactive repairs and maintenance planning