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Record W4392920021 · doi:10.1061/9780784485262.111

Simulation-Based Analysis of a Precast Factory Layout to Reduce Labor Travel Time and Production Time

2024· article· en· W4392920021 on OpenAlexaff
Sena Assaf, Fatima Alsakka, M.A. Darwish, Mohamed Al‐Hussein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPrecast concreteFactory (object-oriented programming)Production (economics)Computer scienceTravel timeManufacturing engineeringEngineeringTransport engineeringCivil engineering

Abstract

fetched live from OpenAlex

Inefficient facility layout in construction manufacturing leads to process waste, thereby increasing production time. In particular, it results in unnecessary movement of workers to transport materials/tools during production. The research presented in this paper examines the impact of a precast concrete factory’s layout on three parameters in the production of precast concrete panels: labor travel time, activity cycle time, and production time. Recommendations are proposed to reduce process waste regarding each of these parameters, that is, relocating the material preparation mills and introducing a cart-based material/tool handling system. The benefits are quantified using a discrete-event simulation model of the process. It shows a 10% reduction in the production time of a single panel and a 39% reduction in the labor hours incurred in transportation activities when compared to the current state. It also shows that 6.9% of the labor hours in the current state is allocated to unnecessary non-value-added transportation activities.

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 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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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