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AI Is Taking Automation in Aerospace Manufacturing to New Heights

AI is transforming automation in aerospace manufacturing, improving efficiency, and powering innovation. Advances are also bringing other new technologies to the forefront of the industry— including 3D printing and collaborative robotics.

Adopting AI and combining it with other technologies enables aerospace manufacturers to streamline production processes and craft high-quality, next-generation aircraft. Which applications of AI in aerospace manufacturing automation should industry professionals know about? Read on to increase your understanding of AI in automation. 

AI-Powered 3D Printing

3D printing is a significant advancement in automation aerospace manufacturing. It allows the streamlining of what would otherwise be numerous disparate steps into one simple one. AI is helping innovators implement 3D printing on an effective scale for the industry.

For example, aerospace company Relativity Space manufactures rockets almost exclusively with 3D printing. Its groundbreaking “Stargate” metal printer is the largest in the world as of 2023. It uses AI and machine learning to control and optimize the printing process so it can manufacture the complex geometry of rocket components.

Real-time quality control is integral to AI in Relativity Space’s printers. It can autonomously correct course during the process to reduce and prevent manufacturing defects.

This is one of the first large-scale applications of a recent advancement in AI 3D printing. In 2022, researchers at MIT developed an AI model that can correct 3D printer performance in real time. The model was trained in a simulated environment for efficiency —a strategy any developer can use today. The result was a machine learning algorithm that can adjust course based on numerous factors— like the complexity of a print or the material being printed.

Models like this greatly expand the possibilities of 3D printing in the aerospace industry. Combined with AI defect prevention and guidance, they can streamline several steps of a lengthy process into one simple one.

Automation in aerospace manufacturing could soon be as simple as sending a print file to an AI-guided industrial 3D printer. The printer would manufacture finished products complete with quality control, reducing complexity and waste. There are also a growing number of technologies for 3D printing metals today, making them more accessible and flexible for the aerospace industry.

Generative Materials Science

AI is changing how materials for the aerospace industry are designed and manufactured. Developing new items for aircraft can be a long and complex process, requiring months of research. AI can automate parts of the R&D process so new planes receive optimal materials with less time and money spent.

Aerospace materials scientists can utilize AI to make the discovery process more efficient. Algorithms can rapidly analyze many possible composites, fibers, and polymers to identify those with the most potential for a specific application.

For example, the evacuation slide is one of the most materially complex aircraft components to design. It must be strong enough to resist damage in emergencies yet light and flexible to be compressed for storage. Most evacuation slides are made of a combination of carbon fibers and nylon with certain protective coatings.

AI can help manufacturers discover innovative materials for evacuation slides and similarly complex aircraft components. Developers give the algorithm a list of ideal parameters for the new material, then the AI rapidly simulates options and pinpoints those that best meet the required criteria.

Automated Quality Control

Quality control is one of the top applications for AI in automation in aerospace manufacturing. This time-consuming process requires close attention to detail for an extended period, which is a lot to ask of any manufacturing employee. AI can fully automate the most tedious part of aerospace QC.

Computer vision— a specific type of AI technology— makes this possible. Machine learning algorithms are trained to recognize certain types of manufactured parts or product units in pictures. They’re then taught to distinguish between correct and defective manufacturing.

The algorithm is integrated into a manufacturing setting after training. This integration includes a few main components: one (or more) camera(s), lights, a processor, and communication equipment. The quality control AI utilizes these products to analyze aircraft components in real time as they pass through the inspection checkpoint. It takes mere moments to process the images of each part and identify any defects.

AI-Powered Manufacturing Robotics

Robots have been common in automation in aerospace manufacturing for several years now, and AI is expanding their capabilities and functionality to make them both smarter and safer. Increasing manufacturing robots’ intelligence with AI allows them to perform their jobs with greater accuracy, precision, and efficiency.

Aerospace manufacturing uses robots in various tasks— including sanding, drilling, painting, coating, and assembling. Conventionally, robots would be carefully programmed to perform these jobs while requiring extensive physical safety measures to protect employees.

AI allows aerospace manufacturing robots to adapt to their environment. For example, IoT sensors can tell the robot’s AI when an employee gets too close, triggering a stop. This can significantly improve safety in aerospace manufacturing.

Similarly, AI allows robotics to perform a greater variety of tasks. Robots are no longer limited to a single preprogrammed purpose. Advances in engineering alongside the intelligence upgrade of AI open up new possibilities in aerospace manufacturing.

For example, one aerospace manufacturer reduced required work hours by 20% for an engine shroud using smart adaptive robots. The collaborative robots —or cobots— were mobile, safe, and capable of controlling various types of machinery. Cobots leverage AI to maximize safety and adaptability, making them ideal for working alongside humans in a flexible manufacturing environment.

AI Automation in Aerospace Manufacturing

AI is revolutionizing automation in aerospace manufacturing. AI can help companies create more durable, high-quality aircraft with less time, money, and waste throughout every step of the process— from materials to quality control.

AI quality control fully automates tedious visual inspections. 3D printing could streamline the entire manufacturing process with the help of machine learning, and generative AI can help manufacturers develop innovative materials for next-gen aircraft components. It’s even upgrading a whole new generation of aerospace manufacturing robots that are safer, smarter, and more efficient. These advances will undoubtably lead to smoother, more efficient processes that will increase company productivity and result in high-quality products.

Emily Newton
Emily Newton
Emily Newton is the Editor-in-Chief of Revolutionized, an online magazine celebrating advances in science and technology.

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