GE Aerospace is leveraging artificial intelligence (AI) in aviation to enhance its engine inspection processes and predictive maintenance capabilities, aiming to boost efficiencies and continuously improve its products. The company’s extensive portfolio of AI-related patents and a dedicated team of specialists underscore its commitment to integrating AI into its operations.
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GE Aerospace VP David Tweedie confirmed they are leveraging @PalantirTech to improve engine maintenance for USAF jets:
“Proud to announce we’re doing a pilot program with Palantir to use AI to do better fleet management, predictive maintenance to really… pic.twitter.com/qhu7aObvNS
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AI in Engine Inspection
GE Aerospace has successfully integrated machine-learning models into its automated inspection processes. By using robotics and advanced machine learning, the company captures and analyzes standard images to drive better outcomes for customers. Nicole Jenkins, GE Aerospace’s chief MRO engineer, explained:
“Digital inspection and standard image collection allows us to apply advanced machine learning and AI models to really drive a better outcome for our customers.”
Predictive Maintenance with AI
AI-powered predictive maintenance is a key focus for GE Aerospace. The company uses data from its 44,000 in-service engines to predict maintenance issues before they become problematic. Jayesh Shanbhag, GE’s vice president of customer experience, noted,
“We are able to detect through analytics and through AI models an anomaly on an oil filter sensor if the signal that we are getting back is not in the normal parameters. We run those models automatically and are able to generate an alert for the maintenance team of an airline.”
This will help reduce the lifecycle cost of ownership and ensures high utilization of assets. GE provides this feature as a basic support service for all its airline customers at no additional cost.
Generative AI for Software Development
GE Aerospace is exploring the use of generative AI to support software development. Generative AI models like Chat GPT use existing data to create new and original content. Dinakar Deshmukh, vice president of data and analytics, explained:
“We are really looking to build out some of those capabilities. The technology has shown promising results in increasing productivity and accelerating software development life cycles.”
Advanced Inspection Technologies
The upcoming Services Technology Acceleration Center (STAC) in Cincinnati will feature cutting-edge inspection devices, including X-ray fluorescence spectroscopy (XRF) for detailed chemical composition analysis of metal parts. This technology will improve the detection of structural variations and alleviate supply chain constraints by clearly identifying airworthy repaired parts.
Russel Stokes, president and CEO of commercial engines and services, stated,
“We continuously strive to use AI, data analytics, and robotics to improve performance through our shops with white light inspection, allowing us to automatically see crack propagations in parts to be able to better disposition that hardware or to actually perform different levels of repair capability in shops.”
Core Principles of AI Integration
GE Aerospace’s approach to AI integration is based on three core principles: using trustworthy data, ensuring model transparency, and keeping humans involved in the process. David Burns, the company’s chief information officer, emphasized,
“We’ve got to ensure that everything we’re putting through artificial intelligence is built on a foundation of solid data. AI is great to bring decision recommendations and insights forward, but we’re really focused on making sure we’ve got humans in the loop on everything we’re doing with AI.”
Conclusion: How Will AI Transform Aviation?
GE Aerospace is at the forefront of leveraging AI in aviation to enhance engine inspection and predictive maintenance. By integrating advanced technologies and maintaining core principles, the company is setting new standards in the aviation industry. How do you envision AI transforming aviation in the next decade? Share your thoughts in the comments below.
