This project is a data-driven simulation tool designed to model the strategic localization of defense procurement within Saudi Arabia. By analyzing a 100-component Bill of Materials (BOM), the simulator identifies the optimal shift from international suppliers to local SMEs to meet national security and economic goals.
In supply chain management, localization is a strategic decision between Procurement Cost and Operational Readiness.
- International Sourcing: Offers lower unit costs due to global economies of scale but introduces "Lead Time Friction" (waiting for shipping/customs).
- Local Sourcing: Requires a "Localization Premium" (upfront investment in domestic capacity) but delivers "Operational Velocity" (faster part replacement and higher readiness).
This model uses a Heuristic Optimization approach to select components for localization based on their impact on overall supply chain speed vs. their cost-to-produce ratio.
Based on the current model calibration:
- Lead Time Improvement: -8.94 Days (Average reduction across the supply chain).
- Localization Premium: 49,000,000 SAR (Total spend variance).
- National Impact: Directly supports the Vision 2030 goal of localizing 50% of military spending.
- Language: Python 3.9+
- Framework: Streamlit (Dashboard UI)
- Data Handling: Pandas & NumPy
- Visualization: Plotly & Matplotlib
- Clone the repo:
git clone https://github.com/almon030-cloud/SAMI-Localization-Simulator.git - Install dependencies:
pip install -r requirements.txt - Run the app:
streamlit run app.py
Author: Saud Almonaiseer
- Student | University of Minnesota *