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Record W1980730102 · doi:10.5555/1030818.1030974

Simulation test bed for manufacturing analysis: a simulation test bed for producton and supply chain modeling

2003· article· en· W1980730102 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

VenueWinter Simulation Conference · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceKanbanSupply chainSimulationVisual Basic for ApplicationsMacroInterface (matter)Material requirements planningTransient (computer programming)Production (economics)Operating system

Abstract

fetched live from OpenAlex

Production systems and supply chains are difficult to model at the level of detail required to understand factors affecting the behavior of material flow. This is particularly true when use of centralized planning systems, such as MRP or DRP, is of interest. Therefore a test bed, comprised of a planning module and a simulator module, has been developed. This test bed is designed to be simple, transparent and flexible. It supports research as well as training. The planning module uses a spreadsheet-based interface and logic embedded in extensive VBA macros. The simulator module is made up of a generic ARENA program that requires no direct modeling inputs when scenarios are changed. Dynamic communication between the modules is facilitated using VBA. Transient and steady-state behavior can be observed under diverse conditions. Production systems or supply chains using MRP/DRP, reorder points, or Kanban systems can be compared.

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)0.002
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-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 score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.145
GPT teacher head0.408
Teacher spread0.264 · 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