Cyber-Physical Platform for Industry 4.0 Implementation
In the age of IoT and Big Data, Digital Twins have become the defining technology of intelligent industry — creating live virtual mirrors of physical assets that predict failures before they occur, optimise processes in real time, and transform raw sensor streams into actionable intelligence. From factory floors and railway networks to power grids, smart cities, and community health systems, Digital Twins are rewriting what is possible. IndusTANTRA builds these platforms — indigenously, with deep academic rigour, for India and the world.
Click any platform to explore its capabilities in detail.
Flagship · Integrated Platform
Unified orchestration layer integrating all digital twin modules into one operations intelligence platform.
Explore →Turbofan · Gas Turbine · Physics-Informed · NASA C-MAPSS
Four-stage physics pipeline — gas-path normalisation, signed deviation, component HI, RUL. Fan · LPC · HPC · Combustor · HPT resolved. 100% HI monotonicity. 709 engines. No run-to-failure labels.
Explore →Full-Aircraft IVHM · 9 Subsystems · Physics ODE · Safety-Critical
Nine coupled subsystem digital twins — 62 state variables, 32 governing ODEs, 13 cross-subsystem couplings. Safety-weighted system Health Index. EASA · FAA · MIL-SPEC traceable.
Explore →Helicopter · Drivetrain Health · STFT · ML Fault Classifier
Helicopter engine and drivetrain health — MGB, IGB, TGB. STFT spectral physics + ML fault classifier names the component before it fails. 3.5-year fleet case study recorded to failure. Offline → Online.
Explore →Wayside Intelligence · 21-Class Fault · CNN · EN Standards
Physics-informed wayside platform — 16 sensor channels, 21-class fault taxonomy, 96.4% weighted F1. Train HI + Track HI from one wayside array. Grad-CAM explainability. EN 50126 · EN 50128 · EN 15313. Invited lecture, Railways 2026, Budapest.
Explore →Wayside · Plug-In Intelligence · Sensor-Agnostic · 25+ Sites
Pre-trained Hyper-ML intelligence layer above any existing wayside system — WILD, DAS, fibre-optic, accelerometer. 12-class rolling stock fault taxonomy. Live Train Health Index per passage. No new hardware. 25+ sites. Day One deployment.
Explore →Onboard · OEM · White-Label · Fleet-Agnostic · European Market
Physics-informed onboard CBM engine for rolling stock OEMs. Fleet-agnostic, white-label ready. 28-channel hierarchical sensor fusion, dual-head CNN, Vehicle Health Index 0–100. New vehicle type in weeks. EN 50126 · ERA TAF TSI.
Explore →Rotating Machinery · VibLab IITK · CNN · STFT
STFT spectrogram → VibLab IITK CNN v2 → 5-class fault diagnosis. Healthy · Unbalance · Crack · BPFO · BPFI. 93–100% accuracy. t-SNE visualisation. Health Index trending. Automated DOCX/PDF report.
Explore →Power Generation · Condition Monitoring · FFT · Health Index
FFT condition monitoring for turbines and generators — 1× · 2× harmonic tracking, BPFO · BPFI · BSF bearing diagnostics, Health Index trending. LabVIEW → Python migration. DST-validated: NTPC · BHEL · CSIO.
Explore →Shopfloor DAQ · Live Dashboard · RFID · MCF Raebareli
Live shopfloor intelligence — CNC, robot, and manual machine DAQ homogenised into one dashboard. RFID WIP tracking, Android HMI geo-location, cloud VPS relay. Deployed at MCF Raebareli under TMIR.
Explore →Shopfloor Digital Twin · SimPy Discrete-Event · MCF Raebareli
Full shopfloor discrete-event simulation at 1-minute resolution — priority dispatching, Gantt charts, bottleneck identification. 10-day lead time reduction at MCF Raebareli. 86–88% constraint utilisation quantified.
Explore →Urban Digital Twin · Traffic · Event Management · IoT-Ready
City-scale digital twin for large-footfall event management — OSMnx road network, zone congestion multipliers, animated green-to-red visualisation. IoT/ANPR/GPS integration pathway. Streamlit dashboard.
Explore →SCADA · Power Infrastructure · Non-Intrusive ML
Non-intrusive ML overlay on existing SCADA and DCS systems — OPC UA · IEC 61850 · Modbus. Anomaly detection, RUL prediction, digital twin bridging. No control-plane modification.
Explore →Social Impact · Health Camp Analytics · Doctors Consortium
Digital twin of population health — 18+ biomarker risk scores, individual patient PDF reports, locality-level risk stratification. Doctors consortium collaboration. Same twinning philosophy as industrial platforms.
Explore →Social Impact · Clinical AI · Decision Support
AI-powered clinical decision support — symptom analysis, differential diagnosis, and triage intelligence for physicians and community health workers in resource-limited settings.
Explore →OT · IT Integration
Indigenous platform bridging shopfloor controllers with enterprise analytics — Modbus, OPC-UA, MQTT, RFID.
Explore →Flagship implementations and sponsored research across Indian industry and government.
Pilot-scale implementation of an integrated Industry 4.0 platform at Modern Coach Factory (MCF), Raebareli — India's most modern coach manufacturing facility. Three interconnected pillars: shopfloor monitoring, production scheduling, and RFID-based material tracking. Priority-based scheduling reduced completion time for highest-priority coach variants by up to 10 days vs random dispatching. Bottleneck analysis identified key stations at ~86–88% utilisation.
Design and implementation of a five-layer open-source digital twinning framework for Indian Railways, developed in collaboration with CRIS (Centre for Railway Information Systems). The Waltair (WAT) Division — serving Visakhapatnam Port, RINL steel, and petroleum freight — was selected as pilot. Framework spans data acquisition, model layer, analytics, and a cloud dashboard for remote monitoring. Presented at RAIL 26, Budapest.
Design and development of instrumentation system for wheel-flat detection — RDSO, 2001. Pioneering on-track load measurement system for Indian Railways.
Details →Consortium project with IIT Bombay, TATA Motors, M&M, Ashok Leyland, TCS, Pricol — development of ABS, TCS and ESC for automobiles. Supported by CAR–TIFAC, DST.
Design, development and launch of a MEMS-based micro-satellite. Project Coordinator under ISRO support. Successfully launched 2011.
Details →Instrumentation systems for health monitoring of critical rotating machines for electric power generation. Joint project with CSIO Chandigarh, BHEL and NTPC. DST funded, 1996–2001.
Software development for life estimation of turbine blades, and development of new techniques for determination of damping in rotors. Aeronautical Research & Development Board, MoD, 1992–2000.
Board for Smart Materials Research and Technology; National Programme on Micro and Smart Systems. National coordinator and project leader.
Professor Emeritus, Department of Mechanical Engineering, IIT Kanpur
Former Chairman, Technology Mission for Indian Railways (TMIR), Govt. of India
Prof. Vyas holds a Ph.D. (1986), M.Tech. (1983) and B.Tech. (1980) — all in Mechanical Engineering — from IIT Delhi and IIT Bombay, and has been a faculty member at IIT Kanpur since 1987. His research spans Machine Dynamics, Nonlinear Parameter Estimation, Instrumentation, and AI/ML applications for Smart Infrastructure and Industry 4.0.
As Chairman of TMIR (till April 2022), he spearheaded the digital modernisation of one of the world's largest railway networks, including Industry 4.0 protocols at MCF Raebareli, on-board diagnostics for rolling stock, and deep learning for rail asset management.
He has held leadership roles including Head of Mechanical Engineering, Nuclear Engineering, and Centre for Mechatronics at IIT Kanpur; Vice Chancellor of Rajasthan Technical University (2013–15); and Visiting Professor at Virginia Tech, INSA Lyon, Lulea University, and National Chung Cheng University. He is a Founding Director of the International Society on Asset Management, Australia.
Integration, Monitoring and Analytics of Large Systems & Processes