Interactive Cyber-Physical System for ExoBrake: a Novel Drilling Collaborative Platform for Aerospace Manufacturing
Bibliographic record
Abstract
A cyber-physical system with digital twins is developed for the designed ExoBrake — a novel drilling collaborative platform capable of withstanding large clamping forces. Traditional robotic manipulators for aerospace drilling operations are huge, expensive, and lack safety, while cobots, which are more affordable and safer, cannot produce the required clamping force for the drilling process. However, we designed ExoBrake as an add-on kit for a cobot —currently under patent application— which can produce and withstand the required clamping force for drilling stacked metallic sheets in aerospace manufacturing. Moreover, an interactive Cyber-Physical System (CPS) with a graphical user interface is developed for ExoBrake, including online digital twins of ExoBrake, the workpiece, and the test bed. This CPS replicates digitally the assembly of the cobot-ExoBrake and enables the operator to configure the workpiece, define and execute drilling tasks. The main novelty of this CPS is the interactive drilling task definition from the workpiece geometry itself, rendered in the visualization panel. It also controls the entire system and drilling sequence. Experiments are conducted to ensure the CPS functions to apply a specific clamping force and control it during the drilling process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".