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A Review of Metal Additive Manufacturing Technologies

2018· review· en· W2884812296 on OpenAlexaff
Mostafa Yakout, M.A. Elbestawi, Stephen C. Veldhuis

Bibliographic record

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2018
Typereview
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceInconelMetallurgyMicrostructureAerospaceAluminiumNickelAlloyEngineering

Abstract

fetched live from OpenAlex

Additive manufacturing is a layer based manufacturing process aimed at producing parts directly from a 3D model. This paper provides a review of key technologies for metal additive manufacturing. It focuses on the effect of important process parameters on the microstructure and mechanical properties of the resulting part. Several materials are considered including aerospace alloys such as titanium (TiAl6V4 “UNS R56400”), aluminum (AlSi10Mg “UNS A03600”), iron-and nickel-based alloys (stainless steel 316L “UNS S31603”, Inconel 718 “UNS N07718”, and Invar 36 FeNi36 “UNS K93600”).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.008

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.

Opus teacher head0.058
GPT teacher head0.321
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations188
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomenaSame topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207