Tolerancing assistance methodology in a product life cycle perspective
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
The availability of three-dimensional tools for simulation and management of geometric uncertainties in CAD systems bear a strategic importance for the reduction in the number of physical prototypes and for the decrease in time to market. However, in spite of a growing interest for the various approaches which were proposed in this domain and in spite of the progress of CAD techniques, there are still no genuine computer aided tolerancing tools, in which the designer can have confidence. In reality, the current computer aided tolerancing tools are very limited and based on simplifying assumptions, which do not allow appreciating the validity of the results. To circumvent these problems, a novel tolerancing assistance methodology is proposed. This new approach takes into account all types of uncertainties and is intended to guide and assist the designer in making the most appropriate decision. In fact, it allows the designer to validate the manufacturing processes which can meet the applied tolerances, and even to choose the process leading to an optimal cost. Thus, as a result, the reality is reproduced at best, time and money are saved, specifications are respected, errors are reduced, assembly is guaranteed and operation is assured.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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