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Record W7161968815 · doi:10.82308/49627

A digital platform for mass customization of housing

2014· dissertation· en· W7161968815 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsnot available
Fundersnot available
KeywordsMass customizationModularity (biology)DigitizationProduction (economics)NoveltyBuild to orderPersonalizationBuilding information modeling

Abstract

fetched live from OpenAlex

Introduced in the early twentieth century, mass production created the conditions for rapid expansions in modularity and repetition to the building industry. Since the 1960s, and with the integration of information technologies, digitization brought the possibility of customization. Diversity, difference, and individuality could now be implemented with the same ease as mass production. Accordingly, building components could be mass customized, allowing for optimal variances to respond to differing local conditions, and enabling the production of uniquely shaped and sized structural components. Ever a vital sector in the building industry, housing has witnessed a renewed surge of interest in the last two decades, especially following these new approaches to modes of design and production. While this interest has taken many forms and constituencies, digital design and manufacturing strategies have inspired the most diverse research and pragmatic solutions to contemporary industry challenges. However, there is marked gap between proposed research approaches and current production practices, specifically in the prefabricated housing industry, which otherwise represents an ideal model to adopt mass customization. Although unrecognized within standard housing production, current research acknowledges the need for advanced computer applications for enabling mass customization in the housing industry. This thesis thus proposes a novel framework and a systematic group of methodologies for constructing a computational design system that could support homebuyers' participation in the design of their dwellings. This framework derives its novelty by analyzing mass customization theories, technological enablers, various research endeavours in housing, and the standards currently adopted by the prefabricated housing industry. The aim of this framework is to redefine the traditional relationship between homebuyer, architect, and manufacturer. Consequently, this thesis proposes not only a computational tool, but also a comprehensive approach for customization. The framework is simulated by two case studies dedicated to customization in the early design stages. This leads to the development of both an advanced configuration system and a generative tool-based customization system. These simulations arise from an analysis of the profile and practice of a leading prefabricated housing company in Quebec, and thus create a platform that is intimately responsive to the contemporary needs of the industry. The proposed framework provides a rigorous method of customizing prefabricated housing, particularly through an advanced configuration system that builds on existing industry applications. However, the relevance and engagement of a generative tool-based system may still be questioned, especially depending on the available degree of automation and the system operator, among other factors. Implementation requires a fundamentally multi-disciplinary approach to technological dialogue; one that the prefabricated housing industry requires further time and effort to assimilate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.888

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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