3D-Sensor Assisted Robotic Deburring of Aerospace Engine Bearing Rings

Aerospace manufacturing faces strict quality requirements and high part variety, often produced in low quantities. While conventional automation improves quality and efficiency, it is impractical in high-mix low-volume settings due to high planning overhead. Hence, deburring, requiring adaptive processing for workpiece tolerances, remains largely manual. This paper presents a novel method for adaptive robotic deburring of aerospace engine bearing rings manufactured in high-mix low-volume contexts. The proposed method uses two 3D sensors to reduce cycle times while meeting quality requirements. A 3D camera with a large measurement range locates the workpiece, while a second, high-resolution sensor scans the burr areas. Pairwise registration refines the scans for improved global consistency. An indirect RANSAC-based method detects adjacent edge surfaces and reconstructs the edge by computing surface intersections. Conventional offline planning strategies generate the adaptive robot path. The processing pipeline was implemented on a calibrated CNC robot with secondary encoders and yielded promising results in first experiments. The method succeeded where paths based on the nominal CAD model failed. It eliminated measurement and path planning effort. However, it can’t handle freeform surfaces and relies heavily on the robot’s accuracy as well as consistent matching.