3D Printing of Surgical Instruments for Long-Duration Space Missions
Bibliographic record
Abstract
INTRODUCTION: The first off-Earth fused deposition modeling (FDM) 3D printer will explore thermoplastic manufacturing capabilities in microgravity. This study evaluated the feasibility of FDM 3D printing 10 acrylonitrile butadiene styrene (ABS) thermoplastic surgical instruments on Earth. METHODS: Three-point bending tests compared stiffness and yield strength between FDM 3D printed and conventionally manufactured ABS thermoplastic. To evaluate the relative speed of using four printed instruments compared to conventional instruments, 13 surgeons completed simulated prepping, draping, incising, and suturing tasks. Each surgeon ranked the performance of six printed instruments using a 5-point Likert scale. RESULTS: At a thickness of 5.75 mm or more, the FDM printing process had a less than 10% detrimental effect on the tested yield strength and stiffness of horizontally printed ABS thermoplastic relative to conventional ABS thermoplastic. Significant weakness was observed when a bending load was applied transversely to a 3D printed layer. All timed tasks were successfully performed using a printed sponge stick, towel clamp, scalpel handle, and toothed forceps. There was no substantial difference in time to completion of simulated surgical tasks with control vs. 3D printed instruments. Of the surgeons, 100%, 92%, 85%, 77%, 77%, and 69% agreed that the printed smooth and tissue forceps, curved and straight hemostats, tissue and right angle clamps, respectively, would perform adequately. DISCUSSION: It is feasible to 3D print ABS thermoplastic surgical instruments on Earth. Loadbearing structures were designed to be thicker, when possible. Printing orientations were selected so that the printing layering direction of critical structures would not be transverse to bending loads.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".