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Record W3094168242 · doi:10.37775/eis.2020.2.5

Product configuration system development for CAD/CAM software

2020· article· en· W3094168242 on OpenAlexaff
László Karker, Mátyás Andó

Bibliographic record

VenueMérnöki és Informatikai Megoldások · 2020
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsSavaria (Canada)
Fundersnot available
KeywordsUSableCADComponent (thermodynamics)Palette (painting)Computer scienceEngineering drawingProcess (computing)Product (mathematics)MachiningSoftwareReliability (semiconductor)Manufacturing engineeringComputer-aided manufacturingNew product developmentSoftware engineeringEngineeringMechanical engineeringProgramming languageOperating systemPower (physics)

Abstract

fetched live from OpenAlex

The application designed in this research establishes a connection between Autodesk Inventor and Edgecam. In case of the component-group the automatic toolpath generation is efficiently usable even in changing product palette. The perfect CAD model with the suitable toolpath is generated in just 92 seconds with only 20 clicks. The application takes into account the used technological considerations through the manufacturing. The program is reliably usable from the first machining because the automatically filled parameters minimizes the possibility of errors. The solution increases the reliability of the quotation (even for ERP systems) because it ensures valid process time and toolset.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.877

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 head0.014
GPT teacher head0.194
Teacher spread0.180 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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