Improving the Efficiency and Quality of Sustainable Industrial CT by Optimizing Scanning Parameters.

Industrial Computed Tomography (CT) is a widely used Non-Destructive Testing (NDT) technique for evaluating internal and external geometries with high accuracy. However, its integration into industrial workflows is often hindered by long scan times and high energy consumption, raising sustainability concerns. This study introduces a novel approach to improving CT efficiency by integrating real-time energy consumption monitoring into the scanning process. A power measurement device was used to correlate scan parameters with energy usage and image quality, enabling a data-driven approach to parameter optimization. Results show that higher voltages improve image quality up to 32%, when evaluated using Contrast-to-Noise Ratio (CNR) amongst other image quality metrics, while reducing overall energy consumption by up to 61%. The results presented support the optimization of CT scan parameters by providing quantitative guidelines to balance efficiency, image quality, and sustainability. Additionally, deviations in dimensional measurements obtained through CT scans were compared against reference data from a Coordinate Measuring Machine (CMM), with differences up to ±45 μm. The findings contribute to enhancing CT performance while minimizing environmental impact.