3D Simulation of Manufacturing Defects for Tolerance Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract When a new product is designed in an industrial context, it must be possible to produce this product with the desired level of quality and at an acceptable cost for the market. One of the important quality criteria is compliance with functional tolerances. To evaluate the impact of manufacturing defects on the quality of parts produced, designers simulate the influence of the error stack-up in different machining operations to check compliance with functional tolerances. This paper builds on the model of manufactured part and the Jacobian–Torsor model and presents a combined approach for analyzing machined part tolerance taking into account the geometrical defects occurring in a multistage machining process (positioning defects and machining defects). This combined approach aims to help designers when evaluating the different process plans by predicting the worst quality of finished parts. This study uses interval arithmetic because it offers the advantage of expressing uncertainties and deviations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 0.002 |
| 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