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Record W4408572353 · doi:10.3390/jmmp9030100

Integrated CAD/CAM Approach for Parametric Design and High-Precision Microfabrication of Planar Functional Structures Comprising Radially Oriented V-Grooves

2025· article· en· W4408572353 on OpenAlexaff
Jonas T. Churchill-Baird, O. Remus Tutunea‐Fatan, Evgueni V. Bordatchev

Bibliographic record

VenueJournal of Manufacturing and Materials Processing · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsNational Research Council CanadaWestern University
Fundersnot available
KeywordsCADMicrofabricationPlanarParametric statisticsParametric designComputer scienceMaterials scienceEngineering drawingEngineeringComputer graphics (images)Mathematics

Abstract

fetched live from OpenAlex

High-precision microfabrication is essential for enhancing or enabling new functionalities in parts and tooling surfaces. V-groove structures are commonly used in surface engineering for diverse applications. Selecting the optimal V-groove shape, array, and fabrication method is crucial for achieving the desired performance. This study integrates the parametric definition of V-groove structures in both design and fabrication modules using three main function blocks (MFBs). MFB1 defines a single V-groove’s parametric model using specific input parameters. MFB2 transforms these parameters into equations to generate a CAD model of the surface. MFB3 combines inputs from MFB1 with parameters related to cutting tool geometry, cutting strategy, and process planning, producing functional NC code for the machine tool. The approach focuses on micromachining radial V-grooves on planar surfaces, requiring precise alignment and multi-axis single-point diamond cutting (SPDC) with rotation tool center point (RTCP) support. Testing on acrylic samples achieved ±0.1° orientation accuracy and ±2 μm positional accuracy, demonstrating potential for applications in drag reduction, fouling resistance, light guiding, and open microfluidics.

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: none
Teacher disagreement score0.221
Threshold uncertainty score0.536

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 head0.015
GPT teacher head0.243
Teacher spread0.227 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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