September Chennai-GE Aerospace announced today that its GEnx commercial aviation engine family achieved a milestone of two million flight hours with South Asian airlines. The first GEnx was delivered in the region in 2012 with 90 GEnx engines now powering Air India, Vistara and Biman Bangladesh flights.
“The GEnx engine has been instrumental in supporting South Asia’s aviation growth. This milestone is a testament to its engineering excellence and technology maturity,” said Mahendra Nair, Group Vice President for Commercial Program at GE Aerospace,during a visit to New Delhi.“We continue to support our customers’ business goals, with our best technology and services offerings.”
“We are proud of our long relationships with the South Asian airlines, including most recently Air India as it plans expansion of operations with 20 new wide-body aircraft that will be powered by 40 GEnx engines,” said Vikram Rai, South Asia Chief Executive Officer, GE Aerospace.
“GE Aerospace has been a trusted partner in our journey towards expanding our wide-body operations, and the GEnx engine has consistently delivered in terms of reliability, efficiency, and sustainability,” said Nipun Aggarwal, Chief Commercial Officer, Air India. “As we continue to grow our fleet, we are confident that the GEnx engine will play a critical role in helping us achieve our operational goals.”
Reliable & sustainable technology
As a preferred choice for airlines worldwide, powering Boeing’s 787 Dreamliner and the 747-8, the GEnx engine showcases a leap forward in propulsion technology. The engine’s superior performance contributes to reduced operating costs and a lower carbon footprint, aligning with the global aviation industry’s sustainability goals by making it 15% more fuel-efficient and emitting up to 15% less CO2 than its predecessor, the CF6 engine. The GEnx engine is a product of decades of operational knowledge and experience, derived from the GE90 engine. With its innovative twin-annular pre-swirl (TAPS) combustor, the engine significantly reduces nitrogen oxide (NOx) emissions by up to 60% below current regulatory limits. Researchers and engineers at GE Aerospace’s technology centre in Bengaluru worked closely with regional customers and implemented various performance improvement solutions and deployed various innovative on-wing technologies like foam wash, advance blade inspection and operational data-based insights to improve engine’s time-on-wing and reduce maintenance burden.
In March 2023, the GEnx engines powered the first wide-body aircraft on a long-haul route to India using Sustainable Aviation Fuel (SAF). Vistara’s Boeing 787-9 Dreamliner flew from Charleston, South Carolina, to New Delhi on a blend of 30% SAF with conventional jet fuel.
To further enhance the engine’s efficiency and sustainability, GE Aerospace introduced 360 Foam Wash, a cutting-edge alternative to traditional water washing methods. This advanced cleaning process helps maintain optimal engine performance by removing dirt and debris, improving fuel efficiency, and extending the time between maintenance cycles. The 360 Foam Wash has already been implemented by seven airlines, including Air India, Emirates, Etihad Airways, Japan Airlines, Qatar Airways, Royal Jordanian, Saudi Arabian Airlines, and SkyWest. There have been thousands of foam washes conducted in the field with customers, further driving down operational costs and environmental impact.
Improving service quality with AI
GE Aerospace continually monitors its GEnx commercial engines in service and uses digital insights to help identify predictive maintenance measures to enhance the quality of service. To support this effort, the company uses advanced artificial intelligence (AI) and machine learning (ML) driven models to increase the number of conditions that can be monitored with even greater accuracy. GE Aerospace’s AI-enabled Blade Inspection Tool (BIT) guides the selection of Stage 1 and 2 High Pressure Turbine engine blade images in GEnx commercial engine for technicians to inspect for faster, more accurate inspections. This helps in obtaining consistent images, a key input to building predictive models.