PREDICTION AND INVESTIGATION OF SURFACE ROUGHNESS WHILE TURNING SG IRON WITH CUBIC BORON NITRIDE (CBN) AND TUNGSTEN CARBIDE INSERTS
Bibliographic record
Abstract
This work compares the effect of cubic boron nitride (CBN) and multilayer (TiCN+Al 2 O 3 +TiN) coated tungsten carbide (WC) tools during the turning of spheroidal graphite (SG) nodular iron. Nodular irons have more ductility which is required in mechanical components that demand high fatigue resistance like crankshafts, cam shafts, bearing caps and clutch housings. The impact of various process parameters like the depth of cut, cutting speed and feed on the surface roughness (R a ) of SG iron is studied and optimized using the response surface model. The chip morphology is also discussed for evaluation of the quality of the turned surface. The experimental outcomes reveal that the WC tool offers a high surface finish at the optimal combination of the cutting speed at 102 meter/minute, feed at 0.051 millimeter/revolution and depth of cut at 0.5 millimeter and that, for the CBN insert, at 245 meter/minute of cutting speed, 0.051 millimeter/revolution of feed and 0.75 millimeter of depth of cut.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".