Most efficient tool feed direction in three‐axis CNC machining
Bibliographic record
Abstract
The objective of CNC machining is to produce mechanical parts with designed quality most efficiently. To generate CNC tool paths for machining a sculptured part using a three‐axis CNC machine, surface geometry, cutter shape and size, as well as tool path interval and direction need to be considered. In this work, the relation between the direction of a tool motion and cutting efficiency is studied. A new measure of cutting efficiency in three‐axis CNC milling – the length of effective cutting edge (ECE) is introduced. The ECE length is mathematically proven to reach its maximum when the tool cuts a sculptured surface along its steepest tangent direction at the cutter contact point. The steepest tangent direction is thus proven to be the most efficient tool feed direction in three‐axis sculptured part machining. The study identifies tool feed direction as a new control parameter in CNC tool path planning, and forms the foundation for further research on three‐axis tool path generation of sculptured parts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".