The Future of AI for Aerospace Manufacturing

Three-dimensional modeling with AI will be a pivot point that will allow engineers to create detailed and extremely accurate 3D models, which can be analyzed and optimized. (Image: Glebstock/Adobe Stock)

At $829 billion in revenues, 2023 was a banner year for the aerospace industry led by civil aviation companies. Despite its strength, operations were hampered by production constraints, the lingering effects of supply chain and workforce disruptions, and higher materials costs. Even as those issues abate, the commercial sector is chasing accelerated demand. A flood of new aircraft orders pushing backlogs at an accelerated pace is causing the industry to struggle as it seeks to ramp up production. If the dynamic persists, many airlines will be forced to revise or postpone existing plans for enlarging, refreshing, or greening their fleets.

The defense and space sectors are also experiencing surging demands. Defense spending is high amid increased global tensions and the wars in Ukraine and the Middle East. Many countries are grappling to meet increased production requirements in the pursuit of increased deterrence capabilities. And as the world continues to move to a space-based economy, small satellite networks are burgeoning. Analysts project that the space industry will triple in value over the next decade to $1.5 trillion in annual value.

In response, all aerospace industry sectors have embraced artificial intelligence (AI) and machine learning (ML) to improve practical and urgent concerns. AI has become fundamental in the management of safety, part design, inspection processes, maintenance, repair, and overhaul (MRO), and fuel efficiency. AI also enables engineers to give passenger, military, and emergency response craft new capabilities, including, in some instances, the ability to operate fully or semi-autonomously.

The root causes of production delays and quality issues can be mapped back to inefficient manual processes and poor manual planning. Aerospace companies that have implemented a robust AI platform for manufacturing are finding improved efficiencies through operational and process insights, predictive and prescriptive analytics, and scenario planning tools. They also benefit from a 360° visibility into performance levels across their operations. By leveraging explainable AI workflows, it is possible to minimize downtime incidents, improve yield and quality, reduce maintenance and operational costs, and improve visibility and productivity for their workforces.

AI has also emerged as the supply chain superhero. In manufacturing, an area that can create cost overruns, delays, or worse, AI plays a crucial role in enabling the ability to adapt to changing circumstances quickly. AI-powered analytics process vast amounts of data from suppliers, logistics providers, and maintenance teams, delivering real-time insights into the health of the supply chain. These insights allow decision-makers to identify bottlenecks or other risks and swiftly mitigate them before they escalate. By mitigating critical maintenance challenges that could compromise asset availability, some platforms integrate seamlessly with aerospace companies’ existing infrastructure. It allows them to track key performance indicators to accelerate capacity and capability to correct early-stage discrepancies detected on complex machinery. By analyzing historical demand patterns and real-time data, AI systems can provide highly accurate predictions of future supply needs, enabling more intelligent inventory management and efficient workflow automation and reducing downtime.

AI algorithms will grow more complex as the technology develops, allowing for even more automation and efficiency. As the number of aircraft in the skies increases, AI will play a significant role in real-time navigation and decision-making of autonomous aircraft. Behind the scenes, 3D AI will revolutionize the design and production of aerospace manufacturing. Three-dimensional modeling with AI will be a pivot point that will allow engineers to create detailed and extremely accurate 3D models, which can be analyzed and optimized.

AI already has predictive maintenance capabilities in aviation manufacturing, which allow for the collection and analysis of vast amounts of data from various sources. The AI algorithms detect patterns and anomalies in the data to predict potential equipment failures, allowing for proactive maintenance and reducing unplanned downtime. This can result in increased aircraft availability, reduced maintenance costs, and improved safety.

3D AI-driven generative design can create lightweight, optimized structures that maintain strength while reducing weight, which is crucial for aerospace components. AI models can then simulate physical conditions and stress tests on 3D models, identifying potential issues before physical prototypes are built. This accelerates the design process and reduces costs.

Virtual technology has been around for more than half a century, but augmented reality (AR), virtual reality (VR), and mixed reality (MR) is relatively new in manufacturing environments. All three are well on their way to widespread adoption as their power and efficiency mesh with the ingenuity and creativity of humans to further empower capabilities across all realms of the manufacturing process, including inventory management, design and build, maintenance and assembly training, safety, and the development of better products.

Smart glasses and AR will implement vision picking in warehousing operations. Designers will be able to test models in specific contexts that mimic real-world scenarios, an impossibility with legacy clay models. Team members will have no geographic boundaries as they thoroughly examine every step of the design and modeling process. Product designers and engineers will explore options previously considered cost- or time-prohibitive.

Immersive on-the-job training will significantly impact employee onboarding and improve worker productivity. AR smart glasses that project video, graphics, and text will visually guide workers, step by step, through assembly or maintenance tasks or repairs initiated by gazing at a machine component that requires attention.

Assembly lines will simulate the configurations and processes involved in production to identify and rectify potentially dangerous situations. Employees can be immersed in future workstations to capture task proficiency, movement, and feasibility, ultimately eliminating the risk of potential injuries or fatalities.

Technology will also be the catalyst for the manufacturing holy grail — a perfect assembly. Goggles with depth sensors, cameras, and motion sensors will provide a view of working environments, engineers, and assemblies to ensure faster work environments with near absolute accuracy. Engineers will evaluate designs and models’ efficacy, cost, and risk in a low-stakes environment.

Investing in VR, AR, and MR in the development stage will help determine whether a project will succeed and, at the assembly stage, will increase aerodynamics, performance, and longevity.

AI in aerospace manufacturing will accelerate rapidly over the next few years and permeate almost every part of the industry. Its true potential will not be in replacing humans with smart machines; rather, it will happen when activities become truly synchronized. As AI technologies mature and aerospace manufacturers consider the future, they’ll explore and discover innovative ways to use AI to make better decisions for increasing productivity and competitiveness and develop more effective, agile, sustainable, and rewarding business models. AI technologies will be the most important component for staying competitive in the marketplace.

This article was written by Art Sellers, President and GM, Avathon Government Systems (Pleasanton, CA). For more information, visit here .