Analysis of the Integration Between Digital Twins and Lean Construction for Construction Projects
Bibliographic record
Abstract
In recent years, academics and stakeholders in the Architecture, Engineering and Construction (AEC) industry have developed strategies to address the issue of low productivity, resulting in the emergence of two distinct approaches: the 'managerial' and the 'technological'.Recently, researchers have advocated the integration of these approaches, in particular by exploring the potential for an integrated implementation of the Digital Twin (DT) concept and Lean Construction (LC) theory.In order to contribute to the theoretical foundation of this integration, this study investigates the theoretical feasibility of an integration between DT and LC in the context of construction projects by adopting a mixed methods research approach, combining literature review with a hybrid analytical approach.The following general research question is addressed: "Is a synergy between the DT concept and the LC theory feasible and beneficial in the context of construction projects?If 'yes', in what contexts and how?"As a novelty, this study explores possible interactions between the principles, functionalities, potentials, barriers and challenges of both DT and LC in order to theorize the positive and negative aspects of this integration in the context of construction projects.Preliminary results show that some of the barriers that prevent the full use of LC in the execution of construction projects can be overcome if its implementation is supported by a technological application based on the concept of DT.In turn, a DT application can add value to the process and the final product, thus addressing some of the challenges to its wider adoption in the construction phase of AEC projects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".