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Record W2112960726 · doi:10.1504/ijmtm.2007.013323

The integration of manufacturing systems using visualised CAPP for agile manufacturing

2007· article· en· W2112960726 on OpenAlexafffund
Qingjin Peng, Chulho Chung

Bibliographic record

VenueInternational Journal of Manufacturing Technology and Management · 2007
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAgile manufacturingManufacturing engineeringComputer-integrated manufacturingIntegrated Computer-Aided ManufacturingManufacturing execution systemVRMLProcess development execution systemProcess (computing)Plan (archaeology)EngineeringComputer scienceComputer-aided process planningAgile software developmentSystems engineeringSoftware engineeringThe InternetMachiningMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

Agile manufacturing embedded in an integrated manufacturing system can drive the business for quick response to the market changes. Computer-Aided Process Planning (CAPP) has been an effective tool of integrated manufacturing systems. Existing CAPP systems were proposed generally based on traditional manufacturing systems, which cannot meet the requirement of customised production in dynamic manufacturing environments. This paper presents a visualised CAPP system to improve users' interactive ability in process planning to enhance the integration of manufacturing systems. The system is implemented using VRML, Java language and Database (DB). Structured Query Language (SQL) management module is developed to manage the customised DB. It is an enhanced CAPP system in an integrated manufacturing system for agile manufacturing. Based on the developed approach in this research, an efficient and dynamic process plan can be generated.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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 designNot applicable
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

Citations3
Published2007
Admission routes2
Has abstractyes

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