A Proposed Design System Model for the Delivery of Mass Custom Homes:
Bibliographic record
Abstract
Buying a new home is a significant investment usually undertaken only once or twice in a lifetime.Therefore, today's consumers are cautious and selective when buying a house, because it must satisfy their personal requirements in terms of customisation, product quality and affordability.Housing manufacturers in North America claim that they can customise a home to the same extent as conventional homebuilders.Their design process for the creation of customised homes, however, does not reflect the advantages of industrialisation of housing, in which mass-production of housing components helps reduce the design and production costs, while in-factory production ensures a steady supply of quality products.'Mass Customisation' is a seemingly contradictory term, for how can one combine mass production and customisation?In 1987, this revolutionary concept was first introduced in North America, recognised as a means to produce customised products on a mass basis.In many industries, the concept of mass customisation is applied to product design in order to satisfy the unique demands of each consumer.The housing industry is no exception.Today, Japanese housing manufacturers have already succeeded in mass customising housing, and their high-quality, reasonably priced homes have a good reputation.This paper examines how Japanese housing manufacturers apply the mass customising approach to improve their products, and the public's perception of industrialised housing.The authors surveyed five manufacturers on their mass customising techniques by visiting their manufacturing plants in order to analyse their production capability.The authors found that the manufacturers have developed a 'mass custom design system' in order to
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.011 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".