Smarter Assembly:

AI’s Role in Precision, Inspection, and Production

In the space industry, the cost of failure is astronomical… literally. Every weld, every circuit, every component must meet the highest standards of precision and reliability. That’s where artificial intelligence (AI) is stepping in as an indispensable partner on the production floor.

From visual inspections to predictive maintenance, AI is revolutionizing quality control across aerospace manufacturing. Traditional inspection methods, human-based visual checks or manual measurements, are slow, inconsistent, and often unable to detect microscopic or systemic issues. AI-powered systems, by contrast, can identify defects invisible to the human eye and learn from every inspection to get smarter over time.

One of the most powerful applications is computer vision, where cameras and machine learning algorithms scan surfaces, joints, and electronic assemblies for flaws. These systems can detect issues like cracks, delamination, or wiring errors in real time, and alert technicians instantly. Companies like Raytheon Technologies, Northrop Grumman, and SpaceX are deploying AI inspection tools to minimize rework, reduce human error, and accelerate throughput.

For example, at Lockheed Martin’s “Factory of the Future” in Fort Worth, AI-driven quality assurance tools are integrated into both automated and human-led processes. These systems not only catch anomalies, but also gather data to improve performance on future builds. Over time, the factory itself becomes smarter, adjusting workflows and maintenance schedules based on real-world conditions.

AI is also proving critical in non-destructive testing (NDT). Ultrasonic, infrared, and X-ray systems enhanced with machine learning can analyze massive volumes of sensor data and identify inconsistencies within composite materials or propulsion systems without damaging the part. In space manufacturing, where many parts are one-of-a-kind or prohibitively expensive to reproduce. This ability is a game-changer.

Another growing use of AI is in predictive maintenance. By analyzing operational and environmental data from machines, AI systems can forecast failures before they happen. This minimizes downtime, protects tooling, and ensures that precision manufacturing equipment stays in peak condition. For facilities producing satellite payloads or rocket engines, even a few hours of prevention can save millions in costs and delays.

What sets AI apart from traditional automation is its adaptability. These systems improve with each use and learn from false positives, adjusting to material differences, and recognizing new defect patterns. And as digital threads become standard across space manufacturing, AI will increasingly be embedded not just in inspection tools, but across the entire production lifecycle.

Of course, implementation isn’t without challenges. Effective AI requires large, high-quality datasets, robust computing infrastructure, and close collaboration between human technicians and machine intelligence. But the industry is making strides. The U.S. Air Force and NASA, among others, have invested heavily in AI research for aerospace quality assurance, recognizing its value in boosting both efficiency and safety.

In an industry where missions rely on flawless execution, AI is helping manufacturers make smarter decisions, faster and ensuring that every component leaving Earth is built to withstand the harshest environments beyond it.