Strategic Automation in Aerospace: Understanding Robot Autonomy for Surface Processing

Since the 1960s, industrial robots have enhanced manufacturing by increasing productivity and reducing errors. However, surface processing in aerospace remains under-automated due to its variability and the precision required. Automation is even less widespread in aerospace maintenance and sustainment operations, which often involve tasks that are dull, dirty, and dangerous.

Intelligent robots with sensory capabilities are beginning to change these assumptions, allowing the automation of tasks once considered too complex. However, skepticism from industry leaders is understandable, given that emerging technologies often come with inflated promises and underestimated costs. A major concern is the risk that advanced robotic systems might not perform reliably in real-world conditions, showing high failure rates when exposed to operational variability.

To facilitate better communication and set realistic expectations, we will use the Industrial Robot Autonomy Levels, (similar to the levels for autonomous vehicles) to classify the capabilities of robotic systems and align them with the specific needs of surface processing tasks. By clarifying key differentiators and mapping them to task features, this framework aims to support aerospace stakeholders in understanding their processes, engaging effectively with technology providers, and making strategic automation investments.