Simulation Data for SAM 100 Adoption in Jordan’s Construction Sector
Description
This dataset includes Python scripts, simulation parameters, and cost models for evaluating the SAM 100 robotic bricklaying system in Jordan’s post-pandemic construction sector. Data supports findings on time efficiency, labor safety, and cost analysis. Keywords: Robotic bricklaying, construction automation, Jordan, SAM 100, pandemic resilience
Files
Steps to reproduce
Steps to Reproduce ------------------ Follow these steps to replicate the results from the study: 1. **Install Dependencies**: - Python 3.6+ (https://www.python.org/downloads/) - Required libraries: ```bash pip install pandas matplotlib ``` 2. **Run Python Scripts**: - Navigate to the `Python_Scripts` folder. - **Cost Analysis**: ```bash python cost_model.py ``` *Output*: Rental cost per unit, mortar savings, and payback period (matches Table 2 and Section 3.2). - **Time Efficiency Simulation**: ```bash python simulation_script.py ``` *Output*: Bricklaying days per unit under 30% absenteeism (matches Table 1 and Figure 2). 3. **Open Excel Models**: - Navigate to the `Excel_Models` folder. - **`labor_cost_analysis.xlsx`**: - Verify total costs (SAM 100: 15,168 JD vs. Traditional: 12,946 JD). - **`mortar_waste_calculations.xlsx`**: - Confirm 15% waste reduction (1,275 JD savings/unit). 4. **Import Simulation Data**: - Navigate to the `Simulation_Data` folder. - **`absenteeism_rates.txt`**: - Import into Excel/Python to plot productivity vs. absenteeism (Figure 6). - **`time_efficiency.txt`**: - Validate 84% time reduction (6.75 vs. 43.2 days/unit). 5. **Recreate AnyLogic Workflow** (Optional): - Use the logic in `AnyLogic_Models/SAM100_Simulation_Logic.txt` to rebuild the model in AnyLogic. - Input parameters from `Simulation_Parameters.txt`. - Compare outputs with `Output_Metrics.txt` (e.g., 540-day total project duration). 6. **Validate Results**: - Cross-check results against: - Figures 2–3 (time/mortar savings). - Tables 1–2 (costs and payback period). - Sensitivity analysis in Table 4 (productivity drop range). Notes: - All paths assume the folder structure is preserved. - For troubleshooting, refer to the `Readme.txt` in each subfolder. - Contact [rulaaa1993@hotmail.com] for dataset clarifications.
Institutions
- The University of Jordan