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Record W3008561780 · doi:10.3390/jmmp4010012

Material Property-Manufacturing Process Optimization for Form 2 Vat-Photo Polymerization 3D Printers

2020· article· en· W3008561780 on OpenAlex
Elisa Aznarte Garcia, Cagri Ayranci, Ahmed Jawad Qureshi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Manufacturing and Materials Processing · 2020
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOrthotropic materialUltimate tensile strength3D printingMaterials scienceComposite materialTaguchi methodsPhotopolymerElastic modulusCuring (chemistry)Engineering drawingComputer scienceStructural engineeringPolymerizationPolymerFinite element methodEngineering

Abstract

fetched live from OpenAlex

This study aims to assess the effect of printing parameters on the final tensile properties of 3D printed specimens printed through a popular vat-photopolymerization printer—‘Form 2’. Elastic modulus, ultimate tensile strength and strain at break are analyzed as a function of process parameters in order to provide an optimized print parameter configuration. Design of Experiments (DoE) using Taguchi’s techniques was used to print the test samples. Tensile tests were performed on the 3D printed specimens following the ISO-527 standard. The post-experiment analysis provide more insight on the effect of each studied factor on the elastic properties of these specimens. To complete this study, an analysis of the total manufacturing process time is presented with respect to the aforementioned elastic properties. The study shows that the parts are orthotropic and sensitive to layer height and post-curing. The orthotropic behaviour can be substantially reduced by appropriate post-curing process, resulting in high improvement of the elastic modulus and ultimate tensile strength. This paper is of special interest to researchers and users of desktop 3D printers who wish to improve the performance of their equipment, compare printing capabilities or assess the effect of different hardware on a single resin.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.224
Teacher spread0.209 · 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