Redesign and Validation of an Accessible and 3D-Printable 24-Channel Peristaltic Pump
Bibliographic record
Abstract
Peristaltic pumps are essential for research applications in many labs, but they are not accessible to all of them. Labs in the Global South are affected by the time and cost barriers that commercial peristaltic pumps pose. These commercial pumps have high purchasing costs and become more expensive when shipping and importation are considered. When these commercial pumps incur damage, the costs of repairing them are also expensive. As her Master’s Degree project, Erin Huitema, M.S., designed and produced a 3D printable 24-channel peristaltic pump using ABS-M30 material and off-the-shelf components. The project aimed to make the pump accessible, easy to use and able to function properly in an incubator while keeping flow rates between its channels consistent. User safety was also considered in the design. Although it operates continuously, the pump needs further development on some of its features. The pump’s motor-driver pair is unable to generate enough torque to power all 24 channels, and there is a fatigue component to the loading of the shaft introduced by a middle ball bearing, which was inserted to sustain a constant flow rate across all channels. A stronger, compatible motor driver providing ample current replaced the old one and has been proven to meet the 24-channel requirement. To eliminate the fatigue component on the shaft and still retain a consistent flow rate across all channels, the old 4mm rollers were replaced by 10mm rollers. These changes entailed redesigning some 3D printed parts to fit the new design. The modified pump design has been fabricated, and overall functionality has been tested. Validation and reliability testing are in progress. There is potential for an enhanced electronic system that allows the pump’s flow rate to be adjusted via control buttons and monitored in real time through an integrated LCD. An accessible, affordable and reliable 24-channel peristaltic pump has been designed, fabricated, and tested. Drawings are available upon request to the Queen’s Bone and Joint and Biomechanics Lab.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".