Mechanical Fastener Designs for Use in the Microassembly of 3D Microstructures
Bibliographic record
Abstract
This paper describes micro-mechanical fastener designs used to create joints between surface micromachined micro-parts. This is part of ongoing research to develop a general microassembly system capable of assembling various types of microstructures. The microassembly system is based on sequential robotic operations and the use of a microgripper. Two new joint designs referred to as ‘key-lock’ joints and ‘inter-lock’ joints are introduced. Key-lock joints are created by the insertion of a ‘key’ on one micro-part, into a mating slot on another micro-part. By translating the first micro-part within the other, after the key is inserted, it becomes locked into position. Inter-lock joints are created by the perpendicular insertion of one micro-part with a slit, into another micro-part with a slit. The slits create an interference fit and are permanent once the micro-parts are joined. The design of these joints and the experimental results are detailed. In addition, ongoing work involving recent ‘snap-lock’ joint fastener designs is described. This includes an example of a 3D micro-transformer and a stacked microstructure. These various micro-mechanical fasteners demonstrate a number of ways in which micro-parts can be assembled into 3D microstructures.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".