Fibonacci Innovation Acceleration: A Scalable Ecosystem Model for India’s Manufacturing Ambitions

#Manufacturing #FibonacciInnovationAcceleration #AdvancedManufacturing #Atmanirbhar #India #InnovationEcosystem #RoboticsAndAutomation #StrategicTechnologies

Authored by
●    Dr. Anurag Srivastava – Program Head, CAMRAS, ARTPARK, IISc Bangalore
●    Shri Vijay Mittal - Joint Secretary, Ministry of Heavy Industries
●    Shri Vikas Dogra - Director, Ministry of Heavy Industries

October 2025 : India’s manufacturing sector is undergoing a profound transition. As the nation seeks to reduce technology imports, strengthen strategic autonomy, and build globally competitive production ecosystems, traditional linear innovation approaches are proving insufficient. The Fibonacci Innovation Acceleration (FIA) model offers a structured, recursive framework to accelerate innovation in robotics, autonomous systems, and AI while aligning startups, industry, academia, and government under one coordinated strategy

A Response to Strategic Gaps

Over the past five years, India has seen a surge in imports of industrial robots, actuators, controllers, and advanced automation components. In FY 2022–23 alone, imports of key robotics and automation items exceeded ₹42,000 crore. This dependency poses both economic and security challenges. To counter this, the Ministry of Heavy Industries (MHI) launched targeted interventions under its Capital Goods Scheme - Phase II, focusing on building domestic capacity in advanced manufacturing technologies

International benchmarks offer lessons: China leveraged MNC collaborations and university partnerships to scale; Germany’s Fraunhofer Institutes built deep, sustained R&D pipelines; the UK’s Catapult centers bridged startups and industry; and Japan fused digital and human capabilities through Society 5.0. India’s challenge is to achieve similar outcomes with greater agility, lower capital intensity, and indigenous leadership.

The Fibonacci Model: Layered Acceleration

Unlike exponential growth models that demand rapid scale from day one, FIA follows the Fibonacci sequence - building successive waves of innovation where each stage reinforces the previous one. This approach is well-suited to India’s starting point, where many strategic technologies are at Technology Readiness Level (TRL) 2–3, not Series A/B maturity.

The CAMRAS program (Center for Advanced Manufacturing for Robotics and Autonomous Systems), anchored at IISc Bangalore, became the proving ground for FIA. Launched in 2023, it set out to rapidly move technologies from TRL 3 to 7- 8 within three years, creating market-ready startups, IP portfolios, and indigenous supply chains in robotics, soft actuators, distributed IMUs, planar drives, and intelligent controllers

Tangible Results in Two Years

In just 27 months, CAMRAS supported the creation of 6 startups, 30+ new technologies, and 24 products, filing over 15 patents and achieving 70–85% cost competitiveness with global benchmarks. More than 465 Indian suppliers were engaged, and participating startups collectively raised over ₹417 crore in investments. Revenue projections show that the FIA curve catches up with exponential growth by year 10, while offering lower early-stage pressure and higher resilience

Blueprint for the Future

The authors argue that FIA should be scaled across multiple innovation accelerators nationwide, involving public research institutions, private industry, and venture investors from the outset. By blending policy flexibility, talent development, and financial innovation, India can create distributed manufacturing innovation hubs- propelling the country toward its Atmanirbhar Bharat goals and global competitiveness in strategic technologies

Why It Matters

For senior manufacturing leaders, FIA provides more than a funding scheme - it’s a framework for ecosystem orchestration. Whether you lead a plant, a division, or a startup, the FIA model demonstrates how India can build layered, scalable, technology-driven manufacturing capacity - not through isolated efforts, but through synchronized innovation cycles.

Download the full paper here: MHI_Paper_LateX_v7.pdf

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