Improving accuracy reconstruction of parts through a capability study: A methodology for X-ray Computed Tomography Robotic Cell

Aeronautical performance is enhanced by increasingly complex and lightweight composite parts. The improve-ment of their manufacturing must ensure the quality measured by Non-Destructive Testing. To evaluate the health of aeronautical parts that are a few meters long, we built a high dimensional robotic cell including two industrial robots positioned on 5-meter-tracks equipped with X-ray Computed Tomography devices. Our main objective is to reconstruct the interior of the parts and detect any anomaly that may have occurred during life cycle or manufacturing (such as porosity or inclusions). In this way, the objective is to present a methodology, firstly, to evaluate the raw process capability and secondly, to assess the improved process capability. The raw process capability uses geometrical identification and we demonstrate that without proper identification, some defects can remain hidden. Three strategies are then developed. The first one involves improving the robot behavior model, which takes into account a thermo-geometrical model, including backlash compensation. Due to possible repositioning problems and to ensure the correct knowledge of the source with respect to the detector, the second strategy involves a real-time test phantom located on the detector named the comb prototype. Finally, a large-sized steel balls phantom is designed to allow a calibration in the full workspace of the robots. This phantom is also used to accurately determine the axis of the rotary horizontal-axis support on which the large parts to be controlled are fixed. We demonstrate that such an architecture, for reconstructing a perfect sphere, leads to an initial mean radius error of 0.05 mm which we improve to 0.016-0.017 mm with our methodology.

Automated summary

This study aims to evaluate the quality and health of aerospace parts using a high-dimensional robotic cell. By utilizing X-ray Computed Tomography devices, the interior of the parts can be reconstructed and anomalies can be detected. A methodology is proposed to assess both the raw process capability and the improved process capability, with three strategies developed to improve the robot behavior model and calibration.