Research on Space Cam Automation Design and Manufacturing Scheme Based on CAD and CAM Systems
Bibliographic record
Abstract
The aim of this study is to realize the fast and accurate design and manufacture of spatial CAM by introducing CAD/CAM system. By using Pro/ENGINEER software widely used in CAD/CAM system, the follower displacement curve is quickly and accurately drawn according to the curve equation of the motion specification of the spatial CAM follower, and the 3D model of the spatial CAM is created according to the curve by Pro/Feature module. Then, the contour surface quality of the spatial CAM is checked by surface analysis, and the detection results are fed back to the modeling design of the spatial CAM. After analyzing the machining theory of the spatial CAM, according to the theory and the modeling completed in the Pro/Manufacture module, the NC machining code of the spatial CAM is automatically programmed. Based on the feedback data of the surface inspection information, the design and manufacturing process of the spatial CAM are continuously optimized. Therefore, the created contour surface has high precision, excellent kinematic and dynamic characteristics. This research provides an effective method and scheme for the automatic design and manufacture of space CAM.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".