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Record W2106445620 · doi:10.1109/3477.875444

Supervisory control of multiworkcell manufacturing systems with shared resources

2000· article· en· W2106445620 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

VenueIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · 2000
Typearticle
Languageen
FieldComputer Science
TopicPetri Nets in System Modeling
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWorkcellFlexibility (engineering)AutomatonComputer scienceDeadlockDistributed computingVariety (cybernetics)Set (abstract data type)Supervisory controlControl (management)RobotTheoretical computer scienceProgramming languageArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Flexible-manufacturing systems (FMSs) may comprise a number of workcells where production resources are shared among the workcells for a variety of practical reasons. Although the utilization of independent workcells with sharing resources improves the flexibility of FMSs, avoiding deadlocks is essential for their successful implementation. This paper introduces a novel methodology for the synthesis of a set of conflict- and deadlock-free supervisors to individually control every workcell within a FMS inter-related by common (shared) resources. The proposed methodology is based on Extended Moore Automata (EMA) and Controlled-Automata theories. A new algorithmic procedure to analyze the concurrent operation of supervisors is also introduced in order to check for the existence or absence of deadlock states.

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 categoriesMeta-epidemiology (narrow)
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 score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.021
GPT teacher head0.208
Teacher spread0.187 · 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