Investigation of laser cladding and heat treatment of H13 tool steel for colour matching repair of moulds/dies
Bibliographic record
Abstract
Tooling constitutes a significant fraction of production costs in many manufacturing processes, reaching as high as 50% in certain cases. Laser cladding offers the opportunity of substantially reducing such tooling costs through repair, reconfiguring, and/or surface enhancement. It can also potentially improve repaired tooling quality and productivity. In this work, the effects of laser cladding conditions and heat treatment of H13 tool steel for colour matching repair have been investigated, using hardness distributions over the processed regions as the major indicator. It has been shown that no softening zone exists between the laser clad and the base metal substrate. By optimal combination of laser cladding processing and heat treatment, the hardness difference between the clad and the base metal can be controlled to less than Hv 25 (HRc 1.5) while maintaining the original hardness of the pre-hardened base H13 tool steel (Hv 590/HRc 55).
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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 | 0.000 |
| 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".