In the aerospace industry, it typically takes years to move from planning to production. But AI-driven technologies are helping to drive change: by optimizing production processes, enabling predictive maintenance and facilitating quality control.
At ALL IN, a panel of industry leaders shared examples of how AI projects are being deployed in the aerospace industry, from enhancing predictive maintenance controls to revolutionizing training for pilots.
For example, Air Canada is using AI to improve on-time arrivals and departures, said Bruce Stamm, managing director of enterprise data and artificial intelligence with Air Canada, which started its AI program in 2018.
“This is the first thing that your customer will remember, even if the flight is super smooth,” he said. “They’re going to remember their flight was late.”
Air Canada builds schedules for about 270 flights a day, and that’s been largely managed by Excel spreadsheets and PowerPoint tools, based on ideal conditions. Not only is this a manually intensive process, but it doesn’t take into account the myriad factors that could impact on-time performance.
With advanced AI tools, Air Canada is able to create ‘what if’ scenarios and conduct real-time analysis of flight scheduling data to understand stress points and make adjustments—a solution that will be going live within the next couple of months.
AI is also being used for training purposes. For example, CAE develops flight simulators, but identifies as a training company with more than 1,000 simulators—across multiple types of aircraft—in service around the world.
The use of AI and digital twins creates a realistic, immersive training environment for pilots, providing competency-based assessments that go beyond traditional testing methods.
“This is where the industry is going and this is something that we are at the forefront of,” said Philippe Couillard, vice-president of global product engineering with CAE, during the panel discussion. “And AI is instrumental in doing that work.”
One of the biggest challenges that aerospace companies deal with—or any company, really—is the ability to handle vast amounts of data in real time. An aircraft can produce terabytes of data in mere minutes through its vast network of sensors and devices. But, it can only communicate that data wirelessly.
To deal with its data challenge, Bombardier developed a health management dashboard that analyzes data in real time and provides valuable insights.
Elza Brunelle-Yeung, senior director of aftermarket products and services with Bombardier, said AI-enabled analysis also provides a competitive advantage for their customers—since those customers have access to the entire fleet’s data—helping to enhance both operational and predictive maintenance controls.
But panelists pointed out that implementing AI requires transforming people and processes, which is difficult for any company, but particularly for more mature companies. Change management will be a key consideration as AI-driven technologies create a pathway to more efficient, reliable and sustainable production in the aerospace industry.
