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Record W2069745579 · doi:10.1016/j.procir.2014.01.101

Architecture Framework for Manufacturing System Design

2014· article· en· W2069745579 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProcedia CIRP · 2014
Typearticle
Languageen
FieldEngineering
TopicFlexible and Reconfigurable Manufacturing Systems
Canadian institutionsUniversity of Windsor
FundersEuropean Regional Development FundAgence Nationale de la Recherche
KeywordsProcess development execution systemArchitectureComputer-integrated manufacturingIntegrated Computer-Aided ManufacturingSystems architectureComputer scienceManufacturing engineeringSystems engineeringProcess (computing)Representation (politics)EngineeringProduct (mathematics)

Abstract

fetched live from OpenAlex

An architecture framework which establishes a common practice for creating, analyzing and representing manufacturing systems during design and re-design processes is proposed. This paper includes a study of the main architecture frameworks and their use within a systematic design process for manufacturing systems. A class diagram is related to a physical architectural framework with manufacturing system components taxonomies that support it; it is applicable to manufacturing systems including RMS (Reconfigurable Manufacturing System). As product development life cycle becomes shorter and shorter, a systematic, structured and effective approach is needed to design or reconfigure the manufacturing system as needed. The proposed framework is comprehensive and specifies the system representation from various levels and dimensions. This paper considers not only abstract and general representation, but also illustration examples to represent manufacturing systems designs.

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.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.915

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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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