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Record W4416879830 · doi:10.37665/weixhkx17651

3D Printing: What Is it and an Example of Its Use

2022· article· W4416879830 on OpenAlexaffabout
Tim Repetski

Bibliographic record

VenueOn-Demand Webinars · 2022
Typearticle
Language
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsCentennial College
Fundersnot available
KeywordsAerospaceAutomationTechnician3D printingCentennialCertificateRapid prototypingAdvanced manufacturingCertification

Abstract

fetched live from OpenAlex

ABSTRACT Technical Presentation: Over the last 20 years, 3D printing has evolved from a technology that was once used primarily by hobbyists into a mainstream prototyping and production tool. Spurred on by the “maker movement” of the 2010's, 3D printing technology enjoyed high levels of adoption in the education sector. As graduates have entered the workforce, 3D printing technology has now made its way into advanced manufacturing facilities for prototype iteration, jigs and fixtures, as well as low piece count production. While many different types of 3D printing technologies exist, currently none is more prevalent than Fused Deposition Modeling (FDM). This presentation will cover FDM technology use cases, materials, limitations, and equipment considerations, and highlight prototype iteration as one of the technology's main advantages in today's advanced manufacturing sector. Biography: Tim Repetski has been working with Centennial College within the Mechanical Engineering, Automation & Robotics, and Aerospace Manufacturing Engineering Technology programs since 2012. Tim currently works as Professor and Program Coordinator for the Aerospace Manufacturing Engineering Technician and Technology Programs that operate out of the Bombardier Centre for Aerospace and Aviation at Downsview Campus in Toronto, Canada. Prior to joining the post-secondary sector, Tim's career has been focused on advanced manufacturing in Ontario, specializing in design and build of production tooling, automation lines, robotic welding, as well as CNC programming and machining. Tim is currently completing a Master of Education at University of Toronto, holds a red seal trade certificate as a licensed Tool and Die Maker, and is a member of Ontario College of Teachers. Files Available to Download: • Slides (PDF) On Demand Webinar

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.259
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2022
Admission routes2
Has abstractyes

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