Lean-Based Integrated Approach for Manual Work Design Optimization in Modular Construction
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.
Bibliographic record
Abstract
Well-designed manual work operations are critical to enhancing the productivity and safety of modular construction production lines. Thus, it is essential to analyze current work procedures, and then design the safest and most efficient work methods accordingly. However, what is lacking is an approach for identifying optimal work methods based on consideration, simultaneously, of several design criteria, such as workplace configurations, task time, and ergonomic risk. Furthermore, existing perception-based methods are not conducive to a careful examination of the trade-off between safety and efficiency for different work scenarios. To overcome these limitations, this paper proposes an integrated approach to manual work design optimization in modular construction. This is accomplished by coupling Lean manufacturing tools and statistical analysis of the design of experiments (DOE) with 3D-based ergonomic posture assessment and Predetermined Motion Time Systems (PMTS). As a case study, a drywall sanding task in a modular construction production line is designed. The results indicate the effectiveness of the proposed method to investigate multiple scenarios and thereby achieve optimum design.
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 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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it