Indian Air Force has signed three contracts with IIT Bombay to develop an advanced predictive maintenance system for Su-30MKI fleet. The objective is to Create a ‘health index’ for every engine undergoing midlife maintenance.
Project Structure
- Three separate contracts with multiple milestone represents culmination of long-term collaboration between IAF and IIT Bombay
Outcome:
- Reduced service costs
- Increased availability and operational life of aircraft
AI Digital Twin Technology
- IIT Bombay is developing an AI-based digital twin model for gas turbine engines
- Led by Prof. Asim Tewari (Centre for Machine Intelligence and Data Science– C-MInDS & Mechanical Engineering)
What is an AI Digital Twin?
- A virtual replica of a physical system
- Uses AI to:
- Diagnose faults (diagnostics)
- Predict failures (prognostics)
- Optimise performance in real-time
- Applied to Su-30MKI engines for data-driven maintenance decisions
Predictive Maintenance Approach
- Moves towards:
- Prognostic maintenance (predict failures before they occur)
- Prescriptive maintenance (recommend corrective actions)
- Built using fully indigenous technology developed at IIT Bombay
- Aligns with IAF’s vision: “Minimal human intervention, maximum combat potential”
Operational Context
- IAF operates ~259–260 Su-30MKI aircraft
- Aircraft has been in service for 20+ years, generating large operational datasets
- Makes it ideal for AI-based predictive maintenance implementation
Expanded Applications
Similar AI digital twin models being developed for:
- Helicopters
- Radar systems
Expected Benefits
- Improved inventory management
- Better capacity utilisation of machines and weapons
- Enhanced 24×7 operational readiness