Influence of stirring conditions on hard anodising of aluminium A6061-T6 shapes
Bibliographic record
Abstract
Hard anodising is used to produce relatively thick and adherent coatings in order to improve the hardness, abrasion and corrosion resistance of aluminium components. In typical industrial conditions, the local variation of anodic oxide film thickness is often significant and it affects the dimensional tolerances and reliability of coating thickness. Electrolyte stirring is a simple and effective way to improve the uniformity of the oxide layer thickness. However, very little practical information is available in the literature to guide industry in this regard. In this work, extruded A6061-T6 specimens were anodised in industrial conditions. To reduce the thickness variability of the coating, three methods of electrolyte stirring were studied and compared. Air bubble stirring showed the best coating thickness uniformity and improved control over anodising parameters. However it did not reduce the variability due to metal forming texture.On utilise l’anodisation dure afin de produire un revêtement d’oxyde épais et adhérent à la surface de pièces en alliage d’aluminium. Ce revêtement accroît la dureté, la résistance à l’abrasion et la résistance à la corrosion des composantes. En milieu industriel, l’épaisseur de la couche d’oxyde a tendance à varier en fonction de la position dans la cellule et même d’un endroit à l’autre sur une pièce, ce qui réduit la précision dimensionnelle. L’agitation de l’électrolyte dans la cellule est un moyen simple et efficace d’améliorer l’uniformité de l’épaisseur du revêtement. Toutefois, très peu d’information est disponible dans la littérature pour guider les industriels et déterminer dans quelle mesure l’agitation permet de réduire cette variabilité. Dans ce travail, des composantes extrudées en alliage A6061-T6 ont été anodisées en milieu industriel. Afin de réduire la variabilité de l’épaisseur de la couche anodisée, trois types d’agitation d’électrolyte dans la cellule ont été étudiés et comparés. L’agitation par bulles d’air a permis d’obtenir la meilleure uniformité de l’épaisseur de la couche anodisée et le meilleur contrôle sur les paramètres d’anodisation. Toutefois, les résultats montrent aussi que l’agitation accentue la différence d’épaisseur de la couche anodisée occasionnée par la texture de laminage ou d’extrusion.
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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 | 0.000 | 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) | 0.001 | 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".