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Record W2772066927 · doi:10.29173/mocs158

Design Breakdown in Industrialized Construction: Supporting Lean Manufacturing

2015· article· en· W2772066927 on OpenAlexvenueno aff
Helena Lidelöw, Gustav Jansson, Emma Viklund

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2015
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
FundersVINNOVA
KeywordsStandardizationLean manufacturingModular designContext (archaeology)Manufacturing engineeringLean constructionLean project managementProcess (computing)Supply chainProcess managementEngineeringComputer scienceBusinessConstruction engineeringConstruction industryMarketing

Abstract

fetched live from OpenAlex

A turn-key commitment towards the client compels the contractor to optimize the entire supply chain from design to delivery of the finished building. Industrialization of residential construction can be accomplished using either an open or a closed platform. In the case of an open platform, the client can greatly affect design solutions and the subsequent production phase. The aim of this research is to explain how design process breakdown into activities and deliveries supports Lean manufacturing in an open platform situation. The most successful industrialized contractor in Sweden was studied through mapping their design process of modular buildings using their visual planning display. Describing the improvement strategy, the visual content, and the standardization efforts in design revealed the support for Lean manufacturing. Analyzing each activity for repetitive elements identified the base for standardization. The conclusion is that design breakdown is a successful method that effectively supports Lean manufacturing and provides a base for standardization in an open platform context.

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)0.007
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0070.003
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.218
Teacher spread0.193 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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