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Record W2896629983 · doi:10.2351/1.5061048

Automated laser fabrication of high performance saw blades

2007· article· en· W2896629983 on OpenAlexaff
C. P. Paul, M. Vaez Iravani, Amir Khajepour, Stephen F. Corbin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFabricationMaterials scienceLayer (electronics)LaserDeposition (geology)Substrate (aquarium)Indentation hardnessMetallurgyLaser beamsComposite materialMicrostructureOptics

Abstract

fetched live from OpenAlex

Automated Laser Fabrication (ALFa) is an emerging computer-aided manufacturing technology that uses a laser beam to melt and deposit the injected powder to fabricate near net shape 3-D components and add delicate features onto the existing components with short turn around time in a layer-by-layer fashion by metal deposition. Recently, we have extended our efforts to deposit WC on High speed steel substrate to fabricate high performance saw blades. This paper reports the fabrication and characteristics of High performance saw blades using ALFa by depositing WC-Co on High speed steel. The laser fabricated samples were subjected to various mechanical and metallurgical analyses. The results showed that fully dense and crack free deposition of WC-Co with an excellent metallurgical bonding and low dilution. No melting of WC particles in the Co matrix has been observed during the microscopy. The average microhardness at the tool surface was in the range of 1450 - 1850 HV, while that at blade was 700-850 HV.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.401

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 communication0.0000.000
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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2007
Admission routes1
Has abstractyes

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