Early Warning for Fleetwide Assets

Through our partnership with SAS, we showcased our beta Predix application, Early Warning Alerts for Fleetwide Assets, at Minds + Machines. The application has the ability to predict early alerts, in this case, for a fleet of aerospace turbofan engines. Fleet sensor data flowed through a SAS Event Stream Processing (ESP) machine learning algorithm in near real-time into a customized Predix frontend we designed and developed. Advanced analytics in the cloud provided actionable insights for maintenance engineers to:

• Maximize Uptime (lost production avoidance and reduced unplanned costs)
• Optimize Fleet Asset Performance
• Increase Operational Efficiency (efficient use of IT infrastructure)

The intuitive user interface provided these benefits:

• Alarm management best practices prioritize early warning alerts
• Easily understood alert descriptions
• Data visualizations translate complex analytics for the non-expert
• Improved decision making
• Team messaging to promote collaboration
• Integrated tools for each persona