Machine learning and artificial intelligence (AI) are increasingly becoming part of the aviation industry, making underlying algorithms and technologies ever smarter and more robust. Still, AI would not be developing at the same pace if it weren’t for the people behind it.
The recently released AI roadmap by the European Union Aviation Safety Agency (EASA) has found just that: the approach to AI in the aviation industry needs to be human-centric. In other words, the experts behind AI need to remain involved with the technologies they create to ensure they become better and advance at the pace the industry demands.
The roadmap looks into many potential applications of machine learning and AI, including aircraft design and operation, aircraft production and maintenance, air traffic management and drones, and urban air mobility.
At Mainblades, we are at the forefront of bringing robotization and machine learning to the aviation industry. We aim to develop drone-based solutions that digitize and automate aircraft inspections.
Digitalization and predictive maintenance
“With digitalisation, the amount of data handled by production and maintenance organisations is steadily growing and so the need to rely upon AI to handle this data is also increasing”, reads the roadmap.
Being able to process large amounts of data is also crucial for the technology we are developing. Transitioning aircraft inspections from manual to ever more automated is bound to increase the amounts of data being generated. Machine learning algorithms are, therefore, necessary to make sense of all the information coming in.
But that isn’t all. With the data that drones collect after a complete inspection, it is possible to create an entire digital copy of an aircraft, also known as a digital twin. A digital twin generated by the Mainblades technology consists of visual information from the complete fuselage, wing and tail section of an aircraft. This applies for any type of aircraft, both narrow and wide-body.
Creating digital twins is among the trends mentioned by the AI roadmap as well as “the introduction of internet of things (IoT) in the production chains and the development of predictive maintenance where the vast amount of data […] will most certainly require the use of AI.”
By collecting large amounts of data through automated inspections, airlines can identify maintenance patterns and be able to predict when works need to be done, increasing their overall efficiency. In fact, “certain university researchers estimate that predictive maintenance can increase aircraft availability by up to 35%.”
Want to learn more about other trends in the aviation industry? Check out the last blog post.
A paradigm shift
“Nowadays, engine manufacturers do not sell engines and spare parts anymore, but rather flight hours”, the roadmap reads. “This paradigm shift implies that, to avoid penalties for delays, engine dispatch reliability and safety are part of the same concept.”
Similarly, we have also identified a paradigm shift in our field of work. At Mainblades, we are not only providing a solution for specific inspections but are also offering a product that reduces the time an aircraft spends on the ground, thus increasing aircraft fleet availability.
Our team realizes this by keeping the human in the loop and focusing on AI, not as a tool that would replace personnel, but that will instead enhance human skills and efficiency. We are looking forward to the collaboration with EASA and our industry partners in the coming years. We believe that regulation and certification of AI in safety-critical applications is essential for the industry and could set a precedent for other industries.
Are you considering integrating AI in your business? How is it going to change the landscape of your workplace?
Stay tuned for more updates from Mainblades and do get in touch if you want to know more.
Written by: Mina Nacheva