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Record W2955851017 · doi:10.29173/mocs88

Lean as an Integrator of Modular Construction

2019· article· en· W2955851017 on OpenAlexvenueno aff
Bruno Soares de Carvalho, Sérgio Scheer

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2019
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsModular designWorkflowLean constructionLean project managementFactory (object-oriented programming)Process (computing)Manufacturing engineeringLean manufacturingSystems engineeringEngineeringProcess managementIntegratorLean laboratoryComputer scienceConstruction engineeringConstruction industry

Abstract

fetched live from OpenAlex

The use of Lean concepts is growing in several industrial sectors. Corporations are seeking new ways to achieve improved operational performance and to identify process improvement measures to improve workflows. The research presented in this proposes to achieve a conceptual framework that can be used in the modular construction market. The research method selected is Design Science Research (DSR), since the research proposes to create a new artifact constituting the integration of Lean Manufacturing, Lean Thinking, Lean Construction and Lean Office in a consistent manner and one that can accommodate Integrated Project Delivery (IPD). In this paper, Permanent Modular Construction (PMC) will be investigated as an industrial construction process. PMC consists of the manufacture of components of the building with volumetric geometry, produced outside the construction site in a factory environment and then transported to the worksite to be assembled with a set of other modules, with comparably few construction activities carried out on site. In order to execute projects using this construction method it is necessary to integrated design, factory operations, transportation and construction site operations, accounting for different locations and different characteristics in a single workflow: this is one of the primary challenges of PMC.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
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 head0.004
GPT teacher head0.184
Teacher spread0.180 · 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.

Study designBench or experimental
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

Citations3
Published2019
Admission routes1
Has abstractyes

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