Supply Chain Management System

Overview

The Supply Chain Management System is a comprehensive solution to streamline logistics and supply chain operations for Company A, a production company located in Kandy. This system is designed to manage order scheduling, transportation logistics via railway and trucks, and generate analytical reports to optimize decision-making.

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Features

1. Logistics Management

• Railway Distribution:
  • Utilizes reserved train capacity for transporting products to major cities, including Colombo, Negombo, Galle, Matara, Jaffna, and Trinco.
  • Automatically reschedules orders exceeding train capacity for subsequent trips.
• Truck Distribution:
  • Coordinates delivery from city stores to customer locations using predefined routes.
  • Assigns drivers and assistants based on availability and roster constraints.

2. Order Processing

• Customers can place orders at least 7 days prior to delivery.
• Includes route selection for specific delivery addresses.
• Ensures capacity limits are respected for both train and truck deliveries.

3. Personnel and Resource Management

• Driver and Assistant Assignments:
  • Drivers: Maximum 40 hours/week; no consecutive schedules.
  • Assistants: Maximum 60 hours/week; up to 2 consecutive schedules.
• Tracks truck usage and personnel hours for optimized resource allocation.

4. Reporting System

• Quarterly Sales Reports:
  • Track sales data across different quarters.
• Item Trends:
  • Identify top-ordered items.
• Geographical Sales Insights:
  • Analyze sales by main cities and delivery routes.
• Personnel and Truck Utilization:
  • Monitor driver and assistant hours, along with truck usage.
• Customer Order History:
  • Detailed records of customer orders and delivery statuses.

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Installation and Setup

Prerequisites

• Python 3.7+
• MySQL Server

Steps to Set Up the Project

1. Clone the Repository:

   git clone https://github.com/Chinthanii/Supply_Chain_Management_System.git
   cd Supply_Chain_Management_System

2. Install Required Dependencies:

   • Install all the necessary libraries using the requirements.txt file:

     pip install -r requirements.txt

3. Set Up the Database:

   • Import the database/schema.sql file into your MySQL server.
   • Update the config.py file to set your database connection details:

     # config.py
     DB_CONFIG = {
         'host': 'localhost',       # Database host
         'user': 'USERNAME',            # Database username
         'password': 'PASSWORD',        # Database password
         'database': 'shopee_db',   # Database name
         'port': 3306               # MySQL port (default is 3306)
     }

4. Run the Application:

   • Start the Flask development server:

     python app.py

5. Access the System:

   • Open your web browser and navigate to:

     http://127.0.0.1:5000
     

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Entity-Relationship Diagram

Below is the ER Diagram for the Supply Chain Management System:

The ER diagram can be viewed by opening the ER_Diagram.pdf file available in the repository.

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Order Placement

• Customers can place orders through the system by logging into the platform.
• After logging in, customers can create a new order, specifying product details, quantities, and delivery addresses.
• The system will automatically schedule deliveries based on transport availability and capacity.

Monitoring and Analytics

• Administrators can log in to access the reports section.
• View detailed sales reports, top-selling items, and sales trends by city and route.
• Monitor driver and assistant work hours, along with truck utilization statistics.
• Generate custom reports based on specific criteria for data-driven decision-making.

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Project Details

Key Assumptions

• Orders and delivery schedules are manually populated for testing.
• Train and truck capacities, schedules, and routes are predefined.
• The current version supports manual data insertion without a user interface.

Data Features

• Includes 40 sample orders across 10 routes.
• Delivery details and train schedules are provided for testing purposes.

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Future Enhancements

• Add a graphical user interface (GUI) for order placement and reporting.
• Implement predictive analytics for demand forecasting and capacity planning.
• Expand delivery options to include additional transport modes (e.g., sea or air).