The Relationship Between Geometrical Complexity and Process Capability
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a new method to estimate the process capability for a profile geometric tolerance as defined by the ASME Y14.5 standard. The novelty of the method is that it uses the known process capability of a given geometry to predict, using the order statistics theorem, new capabilities for different geometries of higher or lower complexity. By considering the geometrical complexity of mechanical parts, a manufacturing process may be capable (e.g., Cpk > 1.5) for parts with simple geometry and incapable (e.g., Cpk < 1) for parts with complex geometry. In the proposed model, the process capability becomes a mathematical function of both the statistical behavior of the process (e.g., expectation and variance) and the geometric complexity of manufactured surfaces. Three experimental case studies are presented to illustrate the usefulness and the validity of the developed model.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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