Post-Simulation Visualization Application for Production Improvement of Modular Construction Manufacturing
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Bibliographic record
Abstract
Post-Simulation Visualization Application for Production Improvement of Modular Construction Manufacturing M. Moghadam, B. Barkokebas, M. Al-Hussein Pages 270-277 (2014 Proceedings of the 31st ISARC, Sydney, Australia, ISBN 978-0-646-59711-9, ISSN 2413-5844) Abstract: The modular construction manufacturing (MCM) process is a complex operation that combines line flow product movement with a complex activity precedence network. There are physical constraints related to the given facility, as well as logical constraints caused by demand variation. In order to change production line layout and make improvements within the context of Lean, a tool is needed to assist MCM to quantify, at the planning and evaluation stages, the benefits they can expect from proposed changes to their system. Simulation is a technique by which to facilitate identifying changes and benefits of future transformation and to determine where valuable resources should be applied prior to actual implementation. Despite the benefits of simulation, project management teams typically are unwilling to make decisions based on current simulation outputs, since they are very difficult to understand and require specialized skills in interpretation of the information. Visualization is a more popular technique since it fosters better understanding of the construction process. However, to be effective for decision making purposes, such a model must be linked to project information. The visual interpretation of the simulation results constitutes a more effective approach. In this paper, a simulation model is thus generated to provide results for different production scenarios, and then the near-optimum scenarios are run to visualize the production constraints, which facilitates precise scenario comparison. The developed model capitalizes on the advantages of both simulation and visualization, whereby critical information such as the 3D model, time constraints, and resource demand are incorporated into the system. The proposed methodology is validated by a case study, a residential modular factory in Edmonton, Canada, which illustrates the effectiveness of the proposed methodology. Keywords: Modular Construction Manufacturing, Lean, Production, Simulation, Visualization, Resource Utilization DOI: https://doi.org/10.22260/ISARC2014/0036 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
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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 it