Supply Chain Risk and Inventory Management Dashboard
Neeraj Jaiswal
Supply Chain Risk and Inventory Management Dashboard
Project Overview
This milestone integrates all previous milestones into a comprehensive supply chain risk management system with a modern web interface built using Streamlit. The system provides real-time monitoring, risk assessment, and intelligent decision support for managing lithium-ion battery supply chains.
Features
1. Real-Time Alerts & Analytics Dashboard
Live Monitoring: Real-time tracking of inventory levels, risk factors, and supply chain events
Email Notifications: Automated alerts for:
Low stock conditions (when inventory falls below minimum threshold)
High risk situations (when risk factor exceeds 7)
Visual Analytics:
Interactive bar charts comparing current stock vs. minimum thresholds
Risk factor gauge charts with color-coded risk levels
Historical damage distribution pie charts
Transport delay analysis graphs
2. Inventory Management
Track multiple battery products (LIB001, LIB002, LIB003)
Real-time stock updates
Minimum threshold monitoring
Maximum capacity management
Automated risk factor calculations
3. Risk Assessment System
Multi-factor Risk Analysis:
Stock level risk (70% weight)
News sentiment risk (30% weight)
Risk Calculation Factors:
Current stock levels relative to capacity
Minimum threshold violations
Market sentiment from news analysis
Risk Visualization: Color-coded gauge charts (Green: 0-3, Yellow: 3-7, Red: 7-10)
4. News Analysis and Sentiment Tracking
Real-time news fetching and analysis
Sentiment analysis of news articles
Risk analysis using LLaMA model
Downloadable JSON reports
Automatic risk factor updates based on news sentiment
5. Comprehensive Logging System
Damage Log: Track product damages with reasons
Transport Delays: Monitor shipping delays and reasons
Sales Log: Record and track sales transactions
Historical data visualization for all logs
6. AI-Powered Chat Interface
Interactive chat with LLaMA model
Context-aware responses incorporating:
Current inventory status
Recent news analysis
Historical data
Natural language queries about inventory and risks
Technical Architecture
Components
Frontend: Streamlit web interface
Backend Services:
InventorySystem: SQLite database management
NewsAnalyzer: News fetching and analysis
LLaMA Integration: AI-powered analysis and chat
Database Schema
Inventory Table: Product details and current stock
Damage Log: Damage incidents and quantities
Transport Delays: Shipping delay tracking
Sales Log: Sales transactions and status
External APIs and Models
Event Registry API: News fetching
Groq API: LLaMA model integration
SMTP: Email notifications
Plotly: Interactive visualizations
Installation and Setup
Prerequisites
Configuration
Email Setup:
API Keys:
Set up Groq API key
Configure Event Registry API key
Running the Application
Usage Guide
1. Initial Setup
Run the application
Navigate to "Run Scenarios" tab
Click "Run Scenarios" to initialize test data
2. Monitoring Inventory
Use "Inventory Management" tab
Add or remove stock
Monitor real-time updates
3. Risk Assessment
Go to "News Analysis" tab
Click "Fetch Latest News"
Review risk updates in "Alerts & Analytics"
4. Managing Alerts
Monitor "Alerts & Analytics" dashboard
Check email notifications
Review risk gauges and charts
5. Using AI Chat
Navigate to "LLaMA Chat" tab
Ask questions about inventory or risks
Review AI-generated insights
Best Practices and Recommendations
Inventory Management
Regularly monitor stock levels
Keep stock above minimum thresholds
Review risk factors daily
Risk Monitoring
Check news analysis regularly
Review alerts promptly
Monitor email notifications
System Maintenance
Regular database backups
API key rotation
Log review and cleanup
Troubleshooting
Common Issues
Email Notifications:
Verify App Password setup
Check SMTP configuration
Confirm email addresses
News Analysis:
API key validation
Internet connectivity
Rate limiting considerations
Database:
File permissions
Disk space
Connection handling
Future Enhancements
Machine Learning Integration:
Predictive analytics
Automated risk mitigation
Pattern recognition
Extended Features:
Supplier management
Cost analysis
Automated ordering
UI/UX Improvements:
Mobile responsiveness
Custom dashboards
Advanced visualizations
Contributing
Contributions are welcome! Please follow these steps:
Fork the repository
Create a feature branch
Submit a pull request
License
Neeraj Jaiswal
Acknowledgments
Streamlit for the web framework
LLaMA for AI capabilities
Event Registry for news data
Like this project
Posted Jul 6, 2025
Developed a supply chain risk management dashboard using Streamlit, AI Integrations, News Analysis and context based chat system.
Likes
0
Views
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Timeline
Dec 31, 2024 - Jan 15, 2025
Clients
Infosys
