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Record W2955930255 · doi:10.29173/mocs117

Decision-making for Cross-Laminated Timber Modular Construction Logistics Using Discrete Event Simulation

2019· article· en· W2955930255 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2019
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsPrefabricationModular designSupply chainModular constructionDiscrete event simulationProcess (computing)Modularity (biology)Event (particle physics)Work (physics)EngineeringCross laminated timberConstruction engineeringComputer scienceCivil engineeringBusinessSimulationMechanical engineering

Abstract

fetched live from OpenAlex

Modular construction is being touted as one solution to address project delays and cost overruns in the construction industry. Modular construction is a delivery method wherein building components are prefabricated off-site and then transported to the job site for assembly. Thus, prefabrication is a significant element of modular construction that enables work to happen in parallel to accelerate project schedules, enhance safety, and reduce physical work on-site. Timber is becoming a primary material for prefabricating elements since wood is a renewable material, possesses high strength-weight ratio, and sequesters carbon. The use of wood in the form of cross-laminated timber (CLT) introduces new opportunities but also logistical issues in the supply chain from forest to the manufacturing facility to the construction site. Depending on the type of CLT and the level of modularity (i.e., 2D elements or volumetric), major constraints in this process have been identified including (1) fluctuation in the supply of raw wood to manufacturing facilities, (2) limitations in the capacity to create CLT panels, (3) shipping limitations based on allowable loads, and (4) crane availability for assembly of panels on the site. This paper explores the use of simulation models to study the effect of these logistical constraints in modular construction using prefabricated CLT on the total time and hence cost of projects. Specifically, discrete event simulation (DES) will be used to model CLT logistics to identify bottlenecks and provide sensitivity analyses of variables such as lumber supply, travel times, and manufacturing plant capacity on project cost and time. A case study of modular multi-story building construction is examined to showcase the utility of the developed simulation framework. It is expected that simulating modular CLT logistics will enable the identification of optimal strategies towards their successful implementation.

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)0.000
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: Empirical
Teacher disagreement score0.384
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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