On selective laser melting of Inconel 718: Densification, surface roughness, and residual stresses
Bibliographic record
Abstract
The current study investigates the effects of a wide range of process parameters on three part properties; density, surface roughness, and surface residual stresses simultaneously for selective laser melting of Inconel 718. In addition to the lack of investigations on surface roughness and residual stresses in selective laser melting of Inconel 718, process maps were developed for the selection of the best process parameters to achieve the desired values for the three parameters combined. Five laser powers, six scan speeds and three hatch spacings were chosen from the stable single tracks tests. Based on each property, a 99.5% density or a 2 μm surface roughness or the least surface tensile residual stress of 248 MPa were possible. However, no single process parameter combination was able to achieve good values for all three parameters. Prioritizing density and surface roughness, being crack initiators, over residual stresses for their effect on fatigue failure, it was found that 99.2% density and relatively low roughness of 3.5 μm are feasible at 320 W, 600 mm/s and 0.12 mm hatch spacing. Finally, opposite to the commonly observed columnar grain in Inconel 718, mixed grain structure was obtained at 600 mm/s and 1000 mm/s, indicating reduced anisotropy.
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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".