🏛 Department Breakdown
Tasks by department from TMS/SMMS/TDMS
📡 Data Source Integration
Maintenance tasks ingested per source
🛤️ Asset Availability
Monthly infrastructure uptime
—
% Available for Train Operations
Weekly Blocks
—
Monthly Blocks
—
Avg. Block Duration
—
📈 Corridor Utilization
Scheduled task coverage per corridor section
⚡
Generate a Block Plan
Click Generate Plan to run the AI scheduling engine. It will analyze maintenance priorities
and corridor availability to create an optimized block schedule.
🔧 Maintenance Tasks
—
Integrated from TMS (Track Management System),
SMMS (Signal & Telecom),
TDMS (Traction Distribution)
| Task ID | Description | Department | Criticality | Corridor | Overdue | Priority Score |
|---|
🛤️ Corridor Availability Windows (COA)
—
Corridor slot patterns categorized by Indian Railways operational block rules:
Integrated Traffic & Power Block (Joint Night Mega Corridor),
Power Block (25kV OHE isolation / TRD),
Traffic Block (Track Machine / Civil / S&T), and
Shadow Block.
| Corridor Section | Date | Window (COA Slot) | Block Pattern / Type | Available | Train Density |
|---|
🚆 About This System
The Automatic Block Planning System is an AI-powered scheduling solution developed for Indian Railways to address the challenge of decentralized and manually planned maintenance blocks across the Engineering, Traction Distribution, and Signal & Telecommunication (S&T) departments.
📡 Data Integration
- 🔵 TMS — Track Management System
- 🟢 SMMS — Signal Maintenance System
- 🟠 TDMS — Traction Distribution Mgmt
- 🟡 COA — Control Office Application
⚡ AI Engine
- 🎯 Priority-weighted scoring
- ⏰ Overdue urgency amplification
- 🔗 Multi-dept co-scheduling
- 📅 Weekly & Monthly horizons
Priority Score Formula
Score = base_criticality × (1 + overdue_days / 7)
Critical = 100 base · High = 60 base · Normal = 30 base
The system uses a greedy constraint-satisfaction algorithm that co-schedules tasks from multiple departments within the same corridor block window, maximizing utilization of each maintenance window and minimizing total asset downtime.