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Record W4405948438 · doi:10.3390/buildings15010103

Integrating Design for Manufacturing and Assembly Principles in Modular Home Construction: A Comprehensive Framework for Enhanced Efficiency and Sustainability

2024· article· en· W4405948438 on OpenAlexafffund
Sadaf Montazeri, Nicole Odo, Zhen Lei

Bibliographic record

VenueBuildings · 2024
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsModular designSustainabilityModular constructionManufacturing engineeringEngineeringSystems engineeringSustainable designArchitectural engineeringComputer scienceConstruction engineering

Abstract

fetched live from OpenAlex

The growing demand for sustainable and efficient construction practices has led to an increased interest in modular construction, with design for manufacture and assembly emerging as a pivotal approach. Despite its potential, the integration of design for manufacture and assembly in modular home construction lacks a structured methodology, posing challenges in aligning design, manufacturing, and assembly processes. This paper introduced a framework aimed at systematically incorporating design for manufacturing and assembly principles into modular home production, leveraging different software tools in the design stage for modular design standardization and streamlined manufacturing and assembly processes. Following a mixed-method research methodology, a comprehensive literature review was conducted to identify research gaps. To address these gaps, a framework was developed focusing on design, manufacturing, and assembly considerations, and retrospective validation of the framework was conducted to confirm its effectiveness. This study revealed the significant benefits of integrating design for manufacturing and assembly principles utilizing advanced digital tools, through a hybrid approach using 2D drafting software and 3D BIM software. The findings indicated that implementing design for manufacturing and assembly principles led to a 40% reduction in design phase duration and a 48% decrease in production errors. This paper offers a structured guide for practitioners while providing a basis for further research in sustainable modular construction.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.564
Threshold uncertainty score0.575

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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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 designTheoretical or conceptual
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

Citations8
Published2024
Admission routes2
Has abstractyes

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