IIT Kanpur · FEP Incubated

Cyber-Physical Platform for Industry 4.0 Implementation

Digital Twins · Real-Time Monitoring · AI / ML Analytics · Process Intelligence · Smart Cities · Community Health

MODULAR. SCALABLE.

38+Years Research
10Platform Modules
15+Major Projects
100+Publications

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.

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Platform Modules

Click any platform to explore its capabilities in detail.

Flagship · Integrated Platform

MaintelliGenX

Unified orchestration layer integrating all digital twin modules into one operations intelligence platform.

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Turbofan Engine Prognostics

AeroEngineTwinX

Physics-informed Health Index for gas turbine engines. NASA C-MAPSS validated. No run-to-failure labels needed.

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Railway · WILD · Digital Twin

RailTwin

Digital twin platform for rolling stock condition assessment — WILD-based CNN classification, on-board force estimation, and cross-functional railway network analytics.

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Rotating Machinery · VibLab IITK

RotorTwinX

Vibration-based fault classification for rotor-bearing systems using STFT, CNN, and t-SNE. 93–100% accuracy.

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Power Generation Assets

PowerPlantTwin

FFT-based condition monitoring for turbines and generators. Migrates legacy LabVIEW PoP Monitor to Python analytics.

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DAQ · Dashboard · HMI

Real-Time Monitoring

Shopfloor data acquisition from CNC, robots, and manual work centres — live dashboard with RFID tracking.

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Shopfloor Digital Twin

Process Scheduling

Discrete-event simulation with priority dispatching and Gantt chart generation. Reduced MCF lead time by 10 days.

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Smart City · Urban Twin

Smart City Digital Twin

City-scale digital twin for traffic, mobility, and urban infrastructure — live congestion mapping with event scenario modelling.

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SCADA · Power Infrastructure

Hyper-ML for SCADA

Non-intrusive ML overlay on existing SCADA systems — anomaly detection, RUL prediction, digital twin bridging.

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Social Impact · Public Health

Comprehensive Community Health

AI analytics platform for health camp data — 18+ biomarker risk scores, individual + population PDF reports.

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Social Impact · Clinical AI

Dr_AIde

AI-powered clinical decision support — symptom analysis, differential diagnosis, and triage intelligence for healthcare providers.

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OT · IT Integration

OT–IT Bridge

Indigenous platform bridging shopfloor controllers with enterprise analytics — Modbus, OPC-UA, MQTT, RFID.

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Component & System Dynamics Manufacturing Process Optimisation Sensors & Instrumentation Imaging & Quality Assurance Machine Learning · Deep Learning Health Diagnosis & Prognosis Rail–Wheel Contact Dynamics Nonlinear Parameter Estimation Smart City Systems Community Health Analytics

Major Projects

Flagship implementations and sponsored research across Indian industry and government.

Railways · Instrumentation

Wheel Impact Load Detection System (WILD)

Design and development of instrumentation system for wheel-flat detection — RDSO, 2001. Pioneering on-track load measurement system for Indian Railways.

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Automotive · Electronics

Electronic Stability Program for Automobiles

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.

Space · MEMS

IITK NanoSatellite — JUGNU

Design, development and launch of a MEMS-based micro-satellite. Project Coordinator under ISRO support. Successfully launched 2011.

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Power · DST

Condition Monitoring of Power Generation Machinery

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.

Aerospace · ARDB

Turbine Blade Life Estimation Software

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.

Smart Systems

B-SMART / NPMASS

Board for Smart Materials Research and Technology; National Programme on Micro and Smart Systems. National coordinator and project leader.

Founder & Director

Prof. Nalinaksh S. Vyas

vyas@iitk.ac.in

+91 9956292801

NL-103, MED, IIT Kanpur — 208016

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Prof. Nalinaksh S. Vyas

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.

Incubated at IIT Kanpur under the Faculty Entrepreneurship Program (FEP)

Get In Touch

Integration, Monitoring and Analytics of Large Systems & Processes

Phone +91 9956292801 +91 512 2597040 (Office)
Address NL-103, Department of Mechanical Engineering IIT Kanpur, Uttar Pradesh — 208016, India

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