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One of the largest US-based airlines operating domestic and international routes.
The airline operator sought a robust data analytics framework to capture and analyze operational as well as asset data for predictive maintenance of its aircraft fleet.
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An Infosys predictive maintenance analytics system maximizes aircraft uptime for a leading airline operator
The Infosys team developed a predictive maintenance analytics system to identify maintenance interventions through datamining of maintenance logs and statistical modeling of engine health monitoring sensor data.
We integrated multiple streams of structured and unstructured data from onboard devices and enterprise systems. It enabled text analytics and correlation analysis of maintenance logs, messages from the aircraft / ground stations, and component / part information.
We created a dashboard for log analytics visualization. Patterns correlating typical machinery/ aircraft faults optimize the asset maintenance program. Further, it helps enterprise maintenance teams apply analytical findings to minimize turnaround time and boost aircraft availability.
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Predictive maintenance improves airline fleet utilization