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Record W1539570097 · doi:10.7315/jcde.2014.021

Survey on the virtual commissioning of manufacturing systems

2014· article· en· W1539570097 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

VenueJournal of Computational Design and Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicFlexible and Reconfigurable Manufacturing Systems
Canadian institutionsUniversity of Toronto
FundersAgency for Defense DevelopmentMinistry of Education, Science and Technology
KeywordsProject commissioningDebuggingEngineeringController (irrigation)Systems engineeringComputer scienceControl engineeringManufacturing engineeringOperating systemPublishing

Abstract

fetched live from OpenAlex

Abstract This paper reviews and identifies issues in the application of virtual commissioning technology for automated manufacturing systems. While the real commissioning of a manufacturing system involves a real plant system and a real controller, the virtual commissioning deals with a virtual plant model and a real controller. The expected benefits of virtual commissioning are the reduction of debugging and correction efforts during the subsequent real commissioning stage. However, it requires a virtual plant model and hence still requires significant amount time and efforts. Two main issues are identified, the physical model construction of a virtual device, and the logical model construction of a virtual device. This paper reviews the current literature related to the two issues and proposes future research directions to achieve the full utilization of virtual commissioning technology.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.534
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.198
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