An AI-powered logistics optimization platform designed to revolutionize supply chain management for the steel industry. This comprehensive solution leverages machine learning, blockchain technology, and real-time analytics to minimize costs, eliminate inefficiencies, and enhance operational reliability.
SAIL Logistics is an intelligent logistics optimization engine that addresses critical challenges in supply chain management for the steel sector. By integrating AI-driven optimization, blockchain transparency, and predictive analytics, the platform delivers:
- 4,000+ hours saved annually through automation
- 50-70% faster decision-making compared to manual processes
- Real-time supply chain visibility and control
- Enhanced operational efficiency and reliability
- Intelligent Optimization: ML algorithms optimize vessel, berth, rail, and rake allocations
- Sequential Discharge: Removes bottlenecks across ports/plants through smart sequencing
- Real-time Coordination: Synchronizes vessel arrivals with plant capacity and material flow
- Live Tracking: Real-time display of efficiency gains and performance metrics
- Comprehensive Analytics: Optimizes freight, port, rail, and storage operations
- Predictive Insights: Forecasts plant demand and syncs material flow to reduce holding time
- Tamper-proof Records: Immutable shipment, discharge, and rail records
- ESG Compliance: Ensures regulatory adherence and builds supplier/stakeholder trust
- Full Traceability: End-to-end visibility across the supply chain
- Disruption Modeling: Simulates strikes, weather events, demand spikes, and route changes
- Resilient Planning: Provides fallback strategies and contingency plans
- Risk Assessment: AI-based risk evaluation and mitigation strategies
- Real-time Monitoring: Tracks berth, rail, and weather conditions with ML forecasts
- Auto-rerouting: Prevents supply chain delays through intelligent rescheduling
- Traffic Optimization: Manages port queues and rail traffic efficiently
- Price Forecasting: Predicts supplier/country prices to aid negotiation
- Contract Optimization: Suggests best timing and deal strategies
- Inventory Management: Forecasts supply prices and freight rates
- Geographic Insights: Real-time visualization of vessels, ports, and plants
- Route Planning: Visual representation of optimal transportation routes
- Geospatial Analytics: Location-based decision support
- Seamless Import: Imports SAP & Excel records without disruption
- AI Conversion: Converts legacy data into actionable AI insights
- Zero Downtime: Maintains business continuity during integration
- Node.js - Runtime environment
- Express.js - Web application framework
- Python - AI/ML model development
- Flask - Microservices and ML API endpoints
- JavaScript - Interactive UI components
- Modern Web Technologies - Responsive design
- MongoDB - NoSQL database for flexible data storage
- Machine Learning Models - Predictive analytics engine
- Gemini AI - Advanced AI capabilities
- Custom ML Models - Delay prediction, congestion forecasting, optimization algorithms
- Blockchain - Distributed ledger for transparency
- Satellite APIs - Real-time geospatial data
- Weather APIs - Environmental condition monitoring
graph TB
A[SAIL Logistics Dashboard] --> B[Create Vessel]
A --> C[AI Optimization Engine]
B --> D[Manual Input]
B --> E[SAP and Excel Import]
D --> F[Input Form]
F --> G[Vessel Data]
F --> H[Parcel Data]
F --> I[Port Data]
F --> J[Rail Data]
E --> K[Import SAP/Excel Data]
K --> L[Database]
C --> L
C --> M[Delay Prediction]
M --> N[Berthing Delay]
M --> O[Arrival Delay]
M --> P[Weather Prediction]
M --> Q[Port Congestion]
C --> R[Port-to-Plant Optimization]
R --> S[Plant Allocation & Distribution]
R --> T[Port-to-Plant Cost Breakdown]
R --> U[Rail Data Visualization]
R --> V[Port-to-Plant Transportation Timeline]
R --> W[AI Risk Assessment & Mitigation]
C --> X[Optimization Analysis]
X --> Y[Traditional vs Optimized Comparison]
X --> Z[Environmental Impact Analysis]
X --> AA[Port Optimization]
X --> AB[Logistical Cost Analysis]
X --> AC[Satellite Map Simulation]
The dashboard provides a seamless interface for managing logistics data:
- Flexible Data Entry: Easily create vessels manually or import bulk data via Excel/SAP integration
- Dual Mode Input: Toggle between manual entry for specific adjustments and automated import for large datasets
- Centralized Database: Unified management of all logistics information including vessel, parcel, port, and rail data
- Berthing Delay Prediction: Forecasts port delays
- Arrival Delay Prediction: Estimates vessel arrival times
- Weather Prediction: Integrates meteorological data
- Port Congestion Prediction: Anticipates bottlenecks
- Plant Allocation: Intelligent distribution of materials
- Cost Breakdown: Detailed port-to-plant cost analysis
- Rail Optimization: Efficient rake scheduling
- Transportation Timeline: End-to-end journey planning
- Risk Mitigation: AI-based risk assessment
- Traditional vs. optimized comparison dashboards
- Environmental impact analysis
- Port optimization metrics (single & sequential)
- Logistical cost analysis
- Logistical cost analysis
- Interactive satellite map simulation
Landing Page
Main Dashboard
Centralized hub for managing vessels, tracking ROI, and accessing predictive insights.
The platform offers a detailed step-by-step wizard for manual vessel configuration:
Captures comprehensive vessel details and supplier prerequisites.
Manages detailed parcel specifications and port discharge preferences.
Defines financial parameters for accurate cost optimization.
Integrates last-mile rail connectivity data.
| Metric | Value |
|---|---|
| Time Efficiency Gains | 4,000+ hours annually |
| Decision Speed Improvement | 50-70% faster than manual processes |
| Carbon Emission Reduction | 2.5 lakh tonnes yearly |
| Automation Level | Thousands of staff hours saved |
-
💡 Eliminate Inefficiency
- Unlock significant operational improvements through phased AI optimization
-
⚡ Instant AI-Driven Adjustments
- Go from planning delays to instant, AI-driven supply chain adjustments for faster shipments and fewer bottlenecks
-
⏱️ Automation of Manual Processes
- Save thousands of staff hours each year by automating manual scheduling and paperwork
-
🎯 Real-time Alignment
- Achieve real-time alignment from vessel arrival to finished steel dispatch, boosting plant output reliability
-
🌱 Carbon Emission Reduction
- Cut carbon emissions by 2.5 lakh tonnes yearly and secure ESG certifications through sustainable traceability
-
🛡️ Disruption Prediction
- Predict and overcome disruptions like strikes, weather, and volatility with smart scenario planning and fallback strategies
-
📋 Procurement Efficiency
- Enhance procurement efficiency by optimizing material selection and contract timing with AI analytics
| Feature | SAIL Logistics | SAP TM | Oracle SCP | Blue Yonder | FourKite |
|---|---|---|---|---|---|
| AI-Driven Vessel & Rail Scheduling | ✅ | ❌ | ❌ | ❌ | ❌ |
| Congestion Forecasting | ✅ | ❌ | ❌ | ✅ | ✅ |
| Interactive Satellite Map | ✅ | ❌ | ❌ | ❌ | ❌ |
| SAP/Excel Integration | ✅ | ✅ | ❌ | ❌ | ❌ |
| Live ROI Dashboard | ✅ | ❌ | ❌ | ✅ | ❌ |
| End-to-End Cost Optimization | ✅ | ❌ | ✅ | ❌ | ❌ |
- Data Reliability: AI cleansing, backups, and fallback ensure consistent accuracy
- Adoption Management: Phased rollout with user training minimizes resistance
- Security Protection: Encryption, blockchain trails, and monitoring safeguard data
- Performance Assurance: Cloud auto-scaling manages peak loads and crises
- Continuous Innovation: ML models evolve with changing logistics dynamics
- High Demand: Steel sector requires automation for competitiveness
- Scalability Potential: Easily replicable across other industries
- Regulatory Compliance: Keeps up with changing regulations
- Sustainable: Revenue through licensing and industry-wide expansion
- Partnerships: Foundation for collaboration with ports, railways, and shipping companies
- Node.js (v14 or higher)
- Python (v3.8 or higher)
- MongoDB (v4.4 or higher)
- npm or yarn package manager
# Navigate to backend directory
cd backend
# Install dependencies
npm install
# Set up environment variables
cp .env.example .env
# Edit .env with your configuration
# Start the backend server
npm start# Navigate to frontend directory
cd frontend
# Install dependencies
npm install
# Set up environment variables
cp .env.example .env
# Edit .env with your configuration
# Start the development server
npm run dev# Install Python dependencies
pip install -r requirements.txt
# Start ML services
python app.py- Open your browser and navigate to
http://localhost:3000 - Log in with your credentials
- Access the main SAIL Logistics Dashboard
- Navigate to Create Vessel section
- Choose between:
- Manual Input: Fill in vessel, parcel, port, and rail data
- SAP/Excel Import: Upload existing data files
- Submit the form to add vessel to the system
- Select vessels and routes for optimization
- Configure optimization parameters
- Run AI optimization engine
- Review results in the analytics dashboard
- Cost Dashboard: Real-time cost savings and ROI metrics
- Predictive Analytics: Delay predictions and congestion forecasts
- Satellite Map: Geographic visualization of logistics network
- Comparison View: Traditional vs. optimized approach analysis
Logistics-Optimizer/
├── backend/ # Node.js/Express backend
│ ├── controllers/ # Route controllers
│ ├── models/ # Database models
│ ├── routes/ # API routes
│ ├── services/ # Business logic
│ └── server.js # Entry point
│
├── frontend/ # Frontend application
│ ├── src/
│ │ ├── components/ # React components
│ │ ├── pages/ # Page components
│ │ ├── services/ # API services
│ │ └── utils/ # Utility functions
│ └── public/ # Static assets
│
├── ml-services/ # Python ML services
│ ├── models/ # ML models
│ ├── prediction/ # Prediction algorithms
│ └── optimization/ # Optimization algorithms
│
├── sail_data_new.csv # Sample logistics data
└── README.md # This file
We welcome contributions to the SAIL Logistics Optimizer project! Please follow these guidelines:
- Fork the repository
- Create a feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Website: SAIL Logistics
- Video Presentation: Watch Demo
- Prototype: Try Live Demo