Lean as an Integrator of Modular Construction
Bibliographic record
Abstract
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.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".