Supply Chain Risk and Inventory Management Dashboard

Neeraj Jaiswal

Completed work

ML Engineer

Dash Plotly

SQLite

Streamlit

Computer Software

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

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

pip install streamlit pandas plotly groq eventregistry transformers textblob

Configuration

Email Setup:

EMAIL_CONFIG = {
    "smtp_server": "smtp.gmail.com",
    "smtp_port": 587,
    "sender_email": "your-email@gmail.com",
    "sender_password": "your-app-password",
    "recipient_email": "recipient@email.com"
}

API Keys:

Set up Groq API key

Configure Event Registry API key

Running the Application

streamlit run Milestone_4/python_scripts/streamlit_app.py

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

Completed work

Posted Jul 6, 2025

Developed a supply chain risk management dashboard using Streamlit, AI Integrations, News Analysis and context based chat system.

Likes

Views

Timeline

Dec 31, 2024 - Jan 15, 2025

Clients

Infosys