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Record W2113472923 · doi:10.1109/isic.1998.713639

Agent-based control system for next generation manufacturing

2002· article· en· W2113472923 on OpenAlexaff
Lihui Wang, S. Balasubramanian, Douglas H. Norrie, Robert W. Brennan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFlexible and Reconfigurable Manufacturing Systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAgile manufacturingAgile software developmentComputer scienceControl systemArchitectureCode generationAgent architectureControl (management)Block (permutation group theory)Systems engineeringInterface (matter)Multi-agent systemEmbedded systemDistributed computingControl engineeringEngineeringSoftware engineeringArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

Future manufacturing systems will be required to be agile, flexible and fault-tolerant. The next-generation intelligent manufacturing systems will be multi-agent systems containing distributed control and application entities that dynamically collaborate to satisfy both local and global objectives. This paper focuses on the development of a generic control system design based on IEC-1499 function block standards, for real-time distributed manufacturing environments. The paper first describes the related research into the control system architecture using multi-agent cooperation, then reports on the intelligent controller design interface and automatic control code generation.

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 score0.004
Threshold uncertainty score0.012

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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.043
GPT teacher head0.199
Teacher spread0.156 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

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