India stands at a pivotal moment in its semiconductor journey. With policy momentum and a national push to build a world-class design-to-manufacturing stack, the country is moving from participant to contender. Yet demand is racing ahead, AI workloads are multiplying, and the power system is under strain—data centres already consume nearly 2% of global electricity.
The challenge is clear – scale without compromise. Expand production and digital infrastructure without overloading the grid, while improving efficiency, reliability, and sustainability.
What Digital Twins Bring
Digital twins are dynamic, AI-enabled models of physical assets and processes. They continuously analyse real-time data, model complex scenarios, and recommend actions to improve efficiency, from a wafer line to an entire campus that ingest real-time telemetry, simulate future states, and recommend optimizations before issues arise.
The technology has moved beyond static replicas to predictive systems that accelerate decisions and cut downtime. In fabs, twins anticipate yield drift, optimise equipment schedules, and tune energy profiles ahead of inefficiency. In data centres, they balance workloads, enhance cooling, and flag faults early—outcomes associated with up to 15% lower energy use and 20% faster fault resolution. Net result is – higher utilisation, steadier quality, and resilient capacity planning.Sustainability and Efficiency
Both fabs and facilities face an energy constraint. Semiconductor manufacturing is resource-intensive, and hyperscale growth compounds local grid pressure. Digital twins help reconcile ambition with physics. They embed measurement and verification in operations, improving transparency on energy, water, and carbon. For India, this is strategic; capacity can come online faster when it’s efficient, auditable, and grid compatible. Sustainability becomes a performance lever, not a trade-off.
Driving Innovation and Indigenous IPThe more profound impact is on innovation velocity. Digital twins compress the learn-build-validate cycle across the semiconductor stack. Designers iterate rapidly with realistic process assumptions; manufacturing teams validate flows virtually before committing capital; supply chains are stress-tested against disruption scenarios. That combination shortens time-to-market for Indian-designed chips, reduces reliance on imported IP, and concentrates value creation at home. It also compounds capability, each programme builds a richer model base data, physics, and know how that improves the next, creating a durable advantage.
Phased Adoption Approach:
- Start with pilot projects in specific operational areas, such as cooling optimisation or wafer yield improvement.
- Integrate IoT and sensor networks to feed real-time data
- Apply AI analytics for predictive and autonomous decision-making.
- Scale across facilities once results are validated.
Conclusion
The future of semiconductor and data-centre operations is adaptive, autonomous, and accountable. Digital twins provide the instrumentation, turning complexity into controllable systems that respond real time to demand, risk, and carbon constraints. First-movers in the sector will shape standards, talent, and investment and those who establish ownership, model validation, and KPIs will set the pace for the decade. For India, the mandate is clear: deploy twins as a core operating system for growth.
The question is no longer about adoption; it’s how quickly to scale before competitors and the grid set hard limits.
The author is Jayashankar Narayanankutty, Group Director, Cadence Design Systems.
Disclaimer: The views expressed are solely of the author and ETCIO does not necessarily subscribe to it. ETCIO shall not be responsible for any damage caused to any person/organization directly or indirectly.
