Development and Characterization of Micro-Plasma Additive Manufacturing Process for Inconel 718 Superalloy
Bibliographic record
Abstract
Abstract A micro-plasma system was investigated for its capability in additive manufacturing (AM). Micro-plasma AM system has the advantage of lower cost and higher deposition rate over the laser-based AM systems, and generates leaner and cleaner weld deposit than other arc-based AM systems. However, the microplasma system is complex and involves a large number of process variables. In this study, the effects of two arc and wire feed modes on dimensional consistency and hardness were firstly examined. Subsequently, one set of the specimens was further subjected to oxidation tests and the results were compared to that from conventional wrought Inconel 718. It was found that all four processes could produce crack free samples without measurable distortion. Some surface discoloration was observed, ranging from light straw to a purple tint. After heat treatment, the hardness of the samples varies from 403 to 440 HV, with the transverse surface showing slightly lower hardness values. The oxidation tests at 900 °C yielded similar weight change for AM Inconel 718 and its counterpart wrought alloy; however, the rate constant for wrought alloy was slightly higher. Microstructural analysis with SEM and EDS revealed a dendritic structure in the AM Inconel 718 and the presence of Nb-rich compounds in the interdendritic region. The polycrystal grain structure was not delineated in AM material as that in wrought 718. With the increase of exposure time, the oxide layer continues to increase at a higher rate, along with a sublayer of Ni3Nb above the metal substrate. In addition, after 200 hours, the wrought alloy developed porous chromia, while AM material exhibited uneven oxide thickness. In consideration of all aspects of the evaluation carried out thus far, it is concluded that the AM material produced by micro-plasma process is equivalent to wrought material in mechanical properties and oxidation performance.
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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".