Cost-effective micro-CT system for non-destructive testing of titanium 3D printed medical components
Why this work is in the frame
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Bibliographic record
Abstract
Micro-CT imaging can be used as an effective method for non-destructive testing (NDT) of metal 3D printed parts-including titanium biomedical components fabricated using laser powder-bed-fusion (LPBF). Unfortunately, the cost of commercially available micro-CT scanners renders routine NDT for biomedical applications prohibitively expensive. This study describes the design, manufacturing, and implementation of a cost-effective scanner tailored for NDT of medium-size titanium 3D printed biomedical components. The main elements of the scanner; which include a low-energy (80 kVp) portable x-ray unit, and a low-cost lens-coupled detector; can be acquired with a budget less than $ 11000 USD. The low-cost detector system uses a rare-earth phosphor screen, lens-coupled to a dSLR camera (Nikon D800) in a front-lit tilted configuration. This strategy takes advantage of the improved light-sensitivity of modern full-frame CMOS camera sensors and minimizes source-to-detector distance to maximize x-ray flux. The imaging performance of the system is characterized using a comprehensive CT quality-assurance phantom, and two titanium 3D-printed test specimens. Results show that the cost-effective scanner can survey the porosity and cracks in titanium parts with thicknesses of up to 13 mm of solid metal. Quantitatively, the scanner produced geometrically stable reconstructions, with a voxel size of 118 μm, and noise levels under 55 HU. The cost-effective scanner was able to estimate the porosity of a 17 mm diameter titanium 3D-printed cylindrical lattice structure, with a 0.3% relative error. The proposed scanner will facilitate the implementation of titanium LPBF-printed components for biomedical applications by incorporating routine cost-effective NDT as part of the process control and validation steps of medical-device quality-management systems. By reducing the cost of the x-ray detector and shielding, the scan cost will be commensurate with the overall cost of the validated component.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it