A Study on Wear Resistance, Hardness and Impact Behaviour of Carburized Fe-Based Powder Metallurgy Parts for Automotive Applications
Bibliographic record
Abstract
In order to study the mechanical and triboloical properties of powder metallurgy (PM) parts under different process parameters, the specimens were used in pack carburizing processes. These specimens made from industrial test pieces were carburized in a powder pack for about two to five hours at a temperature of about 850?C - 950?C. The effects of austenitization and quenching are investigated on some specimens. Also the wear tests are performed by means of a pin-on-disc tribotester using roll bearing steel as the counterface material. The results indicate that by appropriate selection of process parameters, it is possible to obtain high wear resistance along with moderate toughness. It is concluded that surface treatments increases the wear resistance and performance of PM parts in service conditions. By increasing the role of PM in industry which resulted from their ability to produce the complex shapes, high production rate, and dimension accuracy of final products, they need to be heat treated. Carburizing method was selected as a surface hardening method for PM parts. Results of wear and hardness show considerable enhancement in mechanical properties of PM 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 | 0.000 | 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".