This news is classified in: Aerospace Aviation Engines / Power / Fuel MRO
Apr 10, 2024
As the number of LEAP engine operators grows worldwide and the fleet approaches the 50 million flight hour milestone, CFM International has expanded its engine health monitoring capabilities with machine learning to provide operators with more accurate insights than ever before.
The system now being used for CFM LEAP-1A and LEAP-1B engines models data from multiple engine sensors at takeoff, climb, and cruise via probabilistic diagnostic and prognostic machine learning tools. These tools then provide targeted alerts based on known engine operating signatures. The operational models being generated are the most accurate the company has seen to date and are resulting in earlier detection of potential issues.
The system has been used extensively for more than a decade on CFM56 and other engines and, thus, benefits from the experience of a wide portfolio of products, a quality dataset, and deep domain expertise. The CFM LEAP engine is helping advance the state-of-the art in predictive maintenance.
Forecasts by Aircraft Type (Narrow-Body Aircraft, Wide-Body Aircraft, Regional Aircraft), by Maintenance Type (Scheduled Maintenance, Unscheduled Maintenance, Preventive Maintenance, Predictive Maintenance), by Service Type (Engine Overhaul, Airframe Maintenance, Component Maintenance, Line Maintenance, Modification and Upgradation), by Component Type (Engine Components, Landing Gear Components, Avionics Components, Aircraft Interior Components, APU Components, Other) AND Regional and Leading National Market Analysis PLUS Analysis of Leading Companies AND COVID-19 Impact and Recovery Pattern Analysis
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“These state-of-the-art analytics are providing LEAP operators with the data they need to make informed, insightful decisions about fleet management,” said Agathe Venard, Head of Fleet Data Engineering for CFM parent company Safran Aircraft Engines. “As a result, they gain a level of fleet stability they can rely on in their day-to-day operations.”
