Green Machining Of P/M Parts Using Enhanced Green Strength Lubricating Systems
Bibliographic record
Abstract
P/M parts are often machined after sintering to meet tight dimensional tolerances or accommodate design features that cannot be molded during compaction. The development of new polymeric lubricants opens the possibility of machining P/M components prior to sintering, which could result in a considerable reduction of machining costs. This study compares the green and ejection characteristics of binder-treated FC-0205 mixes containing either a new high green strength lubricating system or conventional EBS wax. The comparison was carried out on TRS specimens and gears pressed from 6.8 to 7.2 g/cm3 on laboratory and production scale presses. The influence of these lubricating systems on green machining was also determined on gear shape specimens pressed to 6.8 and 7.0 g/cm3. Results showed that mixes containing the new lubricating system exhibit similar compressibility and a better lubrication behavior than mixes admixed with the conventional EBS wax. Moreover, the green strength of gears produced with the new lubricating system was sufficiently high to enable machining in the green state.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".