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Record W2011669464 · doi:10.1080/09511920600877494

A networked virtual manufacturing system for SMEs

2006· article· en· W2011669464 on OpenAlexafffundabout
Qingjin Peng, C. Chung, Chunsheng Yu, T. Luan

Bibliographic record

VenueInternational Journal of Computer Integrated Manufacturing · 2006
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsManufacturing engineeringKey (lock)Virtual prototypingVirtual realityComputer-integrated manufacturingIntegrated Computer-Aided ManufacturingRapid prototypingProduct (mathematics)Computer scienceEngineeringSystems engineeringOperating systemSimulation

Abstract

fetched live from OpenAlex

Virtual manufacturing is an integrated system of CAD/CAM, virtual prototyping, virtual reality, production planning and control. It enables rapid and efficient product development by composing an accurate and integrated computer model in manufacturing systems. The virtual manufacturing technology can be shared using a networked system. This approach can be called networked virtual manufacturing (net-VM). The distributed, collaborated, and interactive operations are its major features of the net-VM. This paper proposes a net-VM to share usage of the latest integrated design and manufacturing facilities for SMEs. The paper discusses the key technology of the system development. Some sub-systems developed are used to demonstrate the proposed system and methods.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.006
GPT teacher head0.204
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations26
Published2006
Admission routes3
Has abstractyes

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