A Systematic Approach to Determine the Cutting Parameters of AM Green Zirconia in Finish Milling
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Bibliographic record
Abstract
Additive manufacturing (AM) opens new possibilities of obtaining ceramic green parts with a tailored complex design at low cost. Meeting the requirements of highly demanding industries (aeronautical and biomedical, for example) is still challenging, even for machining. Hybrid machines can solve this problem by combining the advantages of both additive and subtractive processes. However, little information is currently available to determine the milling parameters of additively fabricated ceramic green parts. This article proposes a systematic approach to experimentally determine the cutting parameters of green AM zirconia parts. Three tools, one dedicated to thermoplastics, one to composites, and a universal tool, were tested. The tool–material couple standard (NF E 66-520-5) was followed. The lower cost and repeatable generation of smooth surfaces (Ra < 1.6 µm) without material pull-out were the main goals of the study. The universal tool showed few repeatable working points without material pull-out, while the two other tools gave satisfying results. The thermoplastic tool ensured repeatable results of Ra < 0.8 µm at a four times lower cost than the composite tool. Moreover, it exhibited a larger chip thickness range (from 0.003 mm to 0.036 mm). Nevertheless, it generated an uncut zone that must be considered when planning the milling operations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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