Story ID: 337
Aircraft MRO Industry Embraces Artificial Intelligence
By: Hanneke Weitering
Caption: New applications for AI are constantly emerging
Word Count: 807
Maintenance, repair, and overhaul (MRO) service providers are increasingly relying on artificial intelligence (AI) to make their work more efficient and reliable. In recent years, AI technologies such as computer vision, predictive analytics, and machine learning have percolated into just about every facet of MRO processes—from engine inspections to supply chain management to administrative tasks.
While business aircraft manufacturers and MRO service providers have been using forms of AI technology to automate some simple processes for years, recent advances in generative AI have opened the door to a world of new applications. For example, generative AI can automatically create maintenance log entries and reports, and it can analyze sensor data to predict when parts may require maintenance. It can also handle more mundane tasks such as customer service emails.
Over the summer, engine maker GE Aerospace began rolling out a generative AI platform for employees to use as a virtual assistant. Called AI Wingmate, the platform works similarly to ChatGPT: workers interact with a chatbot to search for information, spitball ideas, and generate written communications tailored to specific audiences. The company said AI Wingmate received more than 500,000 queries from employees between June and last month.
“Generative AI is changing the way we all work, enabling us to be more productive with our daily work tasks than ever before,” said GE Aerospace chief information officer David Burns. “Ultimately, this will strengthen our ability to help the aerospace industry meet our highest objectives of enhanced safety, sustainability, and reducing supply-chain constraints.”
Robotic Inspections
Automating inspection processes with robotic inspection tools and computer vision software not only saves time compared with manual inspections, but it also helps to ensure quality control, making inspection results more reliable.
At GE Aerospace’s Services Technology Acceleration Center facility, which opened last month near its Cincinnati headquarters, the company is introducing automated inspection processes that it said will make the inspection process more efficient and consistent. Equipped with white light optical scanners, robots automatically capture detailed images of a part. Rather than having humans look for defects such as scratches or corrosion, the system uses AI technology to analyze the imagery and identify potential issues.
Pratt & Whitney also recently launched an AI-based aircraft engine analysis tool for geared turbofan and V2500 powerplants. Called Percept, the inspection tool combines computer vision technology with a video intelligence operating system developed by Indian AI start-up Awiros.
The company's maintenance technicians use a cloud-based interface on a mobile device to capture images of an engine, and the app provides real-time parts availability status. According to Pratt & Whitney, Percept has reduced the time it takes to conduct an engine inspection by nearly 90%.
Automated inspections are now also being conducted by drones. For example, business aircraft service specialist Jet Aviation recently gained approval from the Swiss Federal Office of Civil Aviation to use AI-enabled drones to conduct general visual inspection work.
It uses drones to capture images of an aircraft’s entire surface and AI software then analyzes the images to identify defects and generate a digital report. Jet Aviation, a subsidiary of General Dynamics, first introduced its AI drone inspection technology last year for nonregulated services such as pre-purchase aircraft structure inspections, paint quality checks, and other inspections required for insurance and warranty purposes.
Tackling Supply and Demand
AI also enables more streamlined approaches to managing inventories and supply chains. Demand forecasting tools that use AI to predict the need for specific parts became incredibly valuable during the Covid-19 supply-chain crisis that plagued MROs with delivery delays and parts shortages.
Canadian business jet manufacturer Bombardier is one of the pioneers of AI-driven demand forecasting in the aerospace industry. To improve its aftermarket demand forecasting process, Bombardier’s inventory planning team partnered with Canadian AI start-up Ivado Labs to develop a predictive analytics pipeline that leverages machine-learning models. The partners detailed their methodology in a research paper published in May 2023.
Similarly, Honeywell Aerospace recently began using AI and machine learning to help manufacturers and MROs modernize their processes and save costs by leveraging data to inform critical decisions. Honeywell unveiled cloud-based software solution Forge Performance+ in April as an addition to its Forge suite of digital tools for aerospace manufacturers and MROs.
“During a time of increasing workplace complexity and operating costs, operators need to be able to leverage data to inform critical decision making and embrace automation,” said Karen Miller, general manager of Honeywell Connected Aerospace. “As the aviation industry grapples with issues such as aging fleets, higher maintenance costs, and ongoing supply chain challenges, Honeywell Forge Performance+ for Aerospace can help organizations achieve key outcomes such as quicker turnarounds, increased asset utilization, and decreased maintenance times.”