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Record W1587734337 · doi:10.1109/robot.2003.1241591

Deadlock-free scheduling of flexible manufacturing workcells using automata theory

2004· article· en· W1587734337 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPetri Nets in System Modeling
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScheduling (production processes)Computer scienceAutomatonJob shop schedulingAutomationDistributed computingDirected acyclic graphWorkcellSupervisory control theoryBatch processingRoboticsScheduleSupervisory controlRobotMathematical optimizationArtificial intelligenceControl (management)EngineeringAlgorithmProgramming languageMathematicsOperating system

Abstract

fetched live from OpenAlex

This paper presents a novel method for the scheduling and control of flexible manufacturing cells (FMCs). The approach employs automata. Augmented by time labels proposed in the paper, for the modeling of machines, transportation devices, buffers, part types, precedence constraints, and part routes. The Ramadge-Wonham's supervisory-control theory is then used to synthesize a controller for the workcell representing its deadlock-free behaviour and capable of keeping track of time. For any given batch of parts to be processed by the FMC, a best-first (BF) graph-search strategy is subsequently employed to determine an optimal, or near-optimal, deadlock-free schedule using a novel heuristic function. The proposed approach is illustrated through a typical FMC example, adopted from [HH Xiong, M Zhou, and RJ Caudil IEE Conf. On Robotics and Automation, Albuquerque, USA, Vol. 3, pp. 2793-2797, 1996] to demonstrate the significant reduction in node 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.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.526
Threshold uncertainty score0.725

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 communication0.0000.001
Open science0.0020.001
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 head0.035
GPT teacher head0.268
Teacher spread0.233 · 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

Quick stats

Citations9
Published2004
Admission routes1
Has abstractyes

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