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Record W2111661238 · doi:10.1108/09576060310459384

Improving workplace material handling through consolidation of cribs and a dispatching system

2003· article· en· W2111661238 on OpenAlexaff
Biman Das, Alberto Garcia‐Diaz

Bibliographic record

VenueIntegrated Manufacturing Systems · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsDalhousie University
Fundersnot available
KeywordsWorkstationConsolidation (business)Gauge (firearms)EngineeringProduction (economics)Reliability engineeringComputer scienceManufacturing engineeringSimulationAutomotive engineeringMechanical engineeringBusiness

Abstract

fetched live from OpenAlex

The lost time arising from travelling and waiting of the production operators and manufacturing inspectors at the tool and gauge crib counters can be considerable in a large manufacturing plant. This travelling and waiting time can be eliminated or minimized by consolidating the tool and gauge cribs near the master crib, extending the totebox system and providing a dispatching system. In the proposed system the tools and gauges will be delivered at the workstation by the dispatchers. The new system would improve the utilization of the tool and gauge crib attendant’s time and reduce the tool and gauge inventory. The case problem revealed that a net annual labor cost saving of about $320,600 and a saving of $242,100 from the reduction of tool and gauge inventory could be achieved. The additional floor space requirement would be about 1,700sq. ft and the implementation cost would be about $144,500.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.003

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations3
Published2003
Admission routes1
Has abstractyes

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