Article | May 7, 2019

AI In Aircraft Maintenance

Source: Apex Waves LLC

It's a well-known fact that some of the worst aircraft disasters have happened due to faulty or overlooked maintenance of aircraft. Even in the last year, aircraft maintenance was one of the primary causes of domestic aircraft delays. This prompted companies in the airline business to take a hard look at aircraft maintenance and how to overcome this issue. For this problem, artificial intelligence (AI) emerged as a boon for aircraft companies. Now with the implementation of AI, aircraft companies can predict potential maintenance failures on aircraft before any mishaps occur.

Augmented Reality

AI and augmented reality go hand in hand. With the latest advancements, augmented reality on smart glasses is changing the perspective of aircraft maintenance. With the technology in testing, now the AR glasses enable mechanics to see hands-free and with interactive 3D wiring diagrams, rather than viewing things on 2D, 20-ft.-long drawings. It also helps users retain the information more efficiently while doing repair work. According to the developers, this technology already shows a 90% improvement in first-time fixes and a 30% reduction in repair time.

Use of IoT

IoT already plays a significant role in aircraft maintenance. Some of the major UAE based aircraft maintenance companies use IoT smart sensors and data analytics for higher efficiency and less downtime for aircraft. The inside data from IoT sensors gives an insight into problems which can be easily detected. This data will also help predict issues which could otherwise be more prominent. It will also result in in fewer maintenance delays and overall improved flight safety.

AI in Military Aircraft

AI based technology is rapidly increasing the conditional awareness of military commanders, as well as pilots flying the military aircraft. This technology helps control large laser-based equipment and works as another set of eyes and ears for military pilots. AI technology driven and regulated by the US defense department is changing the course of action and use of AI in warfare.

Moreover, commercially developed AI-based applications help military engineers predict and act on accurate maintenance and any requirements for equipment. These applications additionally help reduce the costs of military aircraft.

Smart Maintenance

Predictive analytics by AI work through maintenance data. AI can interpret and organize data from sensors and send the data in a report which can easily be comprehended. This algorithm also identifies and reports on potential failures in real-time and arranges proper timelines for repairs. Companies like Airbus are already using and implementing smart AI based maintenance solutions for their aircraft, based on data from different types of sensors.

Innovative Product Designs

AI is providing new ways to design and develop lighter, more efficient parts for the aerospace industry. Efficient and lighter components are one of the most sought after things in aerospace. Design algorithms based on AI such as Generative enable engineers to encompass a set of tools and techniques for creating intricate product designs from the data. It allows engineers to view multiple design options and features in less time to find the best designs. This approach helps develop new products with more functionality, making aircraft more sustainable and lighter in weight.

Flight Health Checks and Maintenance

Recently Rolls Royce (premium manufacturer of aircraft engines) has partnered with Azure IoT Solutions to find and develop the power of AI and IoT to accumulate data and find the best predictive maintenance. IoT devices with sensors are being used in aircraft engines to check the health of the engines and monitor all the components in real-time.

Bonus: AI Leading to Develop Self-healing Airplanes

A new project, "Boeing lab," is using AI extensively and has already developed semi-self-driving airplanes. Additionally, they are working on something closer to self-healing airplanes. The project is using evidence-based predictions for components that are in bad shape and could stop working in the future. It will help in preventive inspection or replacement before the component failure can happen and will reduce the costs of maintenance as well as increasing safety while flying.

Sources: (1st para) (2), (6)