The Supply Chain Management System is a web-based application built using the MERN stack and machine learning to streamline supplier-employee interactions, inventory management, and demand forecasting.
- Suppliers list products with name, description, price, and stock quantity.
- Products are available for employees to browse and order.
- Employees can browse the marketplace, place orders, and track statuses.
- Purchased products are added to inventory with quantity and sold details.
- Low stock alerts appear when inventory falls below reorder thresholds.
- ML models predict future sales using historical data.
- Product Listing: Suppliers add products with stock levels.
- Order Placement: Employees order items from the marketplace.
- Order Confirmation: Suppliers confirm orders, triggering inventory updates.
- Inventory Management: Products are added to and managed in inventory.
- Sales Prediction: Historical data is analyzed to forecast sales.
- MongoDB: NoSQL database
- Express.js: Backend framework
- React: Frontend UI
- Node.js: Server environment
- Flask: ML model deployment
- NumPy, Pandas: Data analysis
- Scikit-learn: ML algorithms
- Jupyter Notebook: Model development
- Postman: API testing
- MongoDB Compass: DB inspection
git clone https://github.com/TracyHT/ISM--Supplychain-Management-System.git
cd ISM--Supplychain-Management-Systemcd server
npm installStart server:
npm startcd client
npm install
npm run devPlease follow the README.md inside "Sales Prediction Model" folder.
- Employee:
a@gmail.com, Password:123456 - Supplier:
b@gmail.com, Password:123456
- Login: Use test accounts.
- Supplier: Add products, confirm orders.
- Employee: Order products, view dashboard stats, update inventory.
Based on the original project by Akhil Binoy: Intelligent-Supplychain-Management-System