Developmental review of metal additive manufacturing processes
Bibliographic record
Abstract
This work is devoted to the study of the progress in various areas of additive manufacturing technology usage - from the first theories of layer-by-layer manufacturing to modern additive manufacturing technologies. Additive manufacturing technologies are some of the most rapidly developing sectors of manufacturing, maintaining significant interest of the scientific community due to the their represent of both an alternative manufacturing method for existing structures, as well as opening up opportunities for the development of new structures with structural complexity unattainable for traditional technologies. During historical review of the development and implementation of various technological processes in additive manufacturing for metals, a gap in compiling a comprehensive picture of the general development of additive manufacturing technologies in metallurgy was discovered. For a better understanding and systematization of knowledge about additive manufacturing, on top of answering a number of common questions about these technologies, an analysis of publicly known knowledge about their historical applications in the leading countries of the world was conducted. A number of additive manufacturing technologies were considered, such as Wire-Arc Additive Manufacturing, Selective Laser Sintering, Selective Laser Melting, Electron Beam Melting, and Laser-Engineered Net Shaping. The study focused on the developments carried out by various countries of the world in the 20th and 21st centuries by scientists from such countries as the USA, the United Kingdom, France, Germany, Japan, Canada, the USSR and others. The main documents for the initial research efforts for each family of additive manufacturing processes and various applications of these technologies - from topography and stereolithography to modern medicine with the aerospace industry ‒ were reviewed; their main findings, breakthroughs and challenges were discussed. An analysis and classification of previous studies that focus on the development of various technological processes and their implementation was carried out. As a result of the analysis, a systematized approach to the creation of a comprehensive scheme for the development of additive technologies related to the development of technologies in various directions was proposed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".