
Sameer Gandhi
Managing Director, Omron India
“Control lives at the edge. Coordination scales in the cloud.”
— Sameer Gandhi
India’s manufacturing target: 25% of GDP by 2047, requiring a sustained 15% CAGR.
Machine tool operator deficit: 5.9 lakh workers — bridged by vision AI and automation.
AI-assisted optical inspection collapses programming times from 90 minutes to 15.
India’s manufacturing target—anchoring 25% of GDP by 2047—rests on a sustained 15% CAGR. As Sameer Gandhi, Managing Director, Omron India, observes, this math cannot be solved by capacity expansion alone.
“Growth must come from increasing the value-add on every unit produced.”
Achieving this trajectory requires a shift from volume-led assembly toward higher value-add. The objective is proprietary capability: the ability to capture value by owning the logic of the process. Without it, assembly lines merely capture thin margins while the intellectual value leaks elsewhere. In this framework, precision is the baseline for industrial survival.
Design-to-Build Transition
The frontier has moved from “print-to-build”—executing external blueprints—to proprietary design ownership.
While sectors like automotive and pharmaceuticals have established design capabilities, the transition remains uneven across India’s industrial base.
“It is not a one-size-fits-all progression; maturity varies significantly by sector,” Gandhi notes.
The bottleneck is moving from importing blueprints to owning the practical assembly logic of the floor.
“We need the machines and the engineering capability to design the processes they execute,” he says.
Dual Architecture: Edge and Cloud
Industrial intelligence is migrating toward the edge, driven by production speeds—often exceeding 500 PPM—where physics won’t wait for a data round-trip. At these speeds, even a millisecond of latency can compromise output quality or increase defect risk.
“Control lives at the edge,” Gandhi observes. “Coordination scales in the cloud.”
This is a dual architecture. The edge handles real-time defect detection and machine-level execution. The cloud provides the enterprise-level view, turning floor physics into strategic data. Collapsing this OT-IT divide allows for extracting only high-impact metrics, replacing the traditional “data lake” approach with actionable operational intelligence.
Rapid Upskilling
Automation serves as industrial life support in a market facing a 5.9 lakh machine tool operator deficit. By utilising AI tools in optical inspection, programming times are collapsing from 90 minutes to 15, allowing junior operators to achieve expert-level benchmarks almost immediately.
This upskilling does not replace the worker; it levels the floor. By automating manual sorting and high-risk tasks, the workforce is reassigned to tactical problem-solving. This human-machine harmony is the only recourse to maintain speed and safety as processes increase in complexity. On this floor, the machine absorbs the physical risk, and the human provides the command logic.
Frugal Digitalisation and the MSME Curve
India’s maturity curve is often defined by “frugal digitalisation”—the ability to retrofit legacy hardware with modern controllers. A Bengaluru-based supplier recently achieved 2026 precision standards on 1990s-era lathes by bridging them into a single data view.
“A robot without an integrator is sunk capital,” Gandhi insists.
Integrators are the practitioners who marry the machine logic to the floor. Their role is to ensure that a Tier-3 supplier can meet the precision and traceability requirements of a global giant without a total facility rebuild.
Sovereign Depth and the Buffer
Diversification strategies like “China Plus One” are entry points, not terminal objectives. While assembly generates immediate scale, it does not solve the structural dependency on high-precision sensors or specialised components.
Domestic depth is the ultimate requirement. Strategic investments, such as Japan’s ¥10 trillion commitment, provide the capital to build this depth. A textile machinery integrator in Coimbatore recently neutralised a significant import delay by localising sensor production—demonstrating how capital creates the depth that prevents a line from halting. In a multipolar economy, the only sustainable advantage is the ownership of the engineering logic inside the machine.
Solutions Spotlight
Legacy Integration
Utilising modern controllers to bridge 20-year-old hardware silos into a single data view, bypassing total capex replacement.
Vision AI at the Edge
Deploying real-time inspection to catch defects at 500 PPM, neutralising the latency inherent in cloud-based systems.
OT-IT Interoperability
Using integrated bridges to extract high-impact metrics, ensuring floor-level precision informs executive-level strategy.
The Capability Doctrine
Value Over Volume
Growth is a function of value-add per unit, not just factory headcount.
Integrators as the Lead Domino
Robotics without a practitioner ecosystem is an unutilised asset.
The Latency Rule
Control must happen at the edge; coordination must happen in the cloud.
Frugal Digitalisation
Retrofitting is the primary bridge to the 2047 precision mandate.
Excerpts from Interview with Sameer Gandhi
You’ve noted that the 15% CAGR math requires value density. What does that look like on the shop floor?
It looks like moving from simple assembly to high-precision engineering. If you are just putting parts together, your margin is limited. If you own the design and the process logic, you are creating more value per square foot. That is the only way the macro-math works.
How should an MSME approach the “Edge vs Cloud” decision?
It’s not an either-or. You need the edge for the real-time stuff—the defect detection and machine control where every millisecond counts. You need the cloud to look at your overall production patterns. Start with the edge to fix your quality, then use the cloud to scale your strategy.
Is “frugal digitalisation” a permanent solution or just a stopgap?
It’s a bridge. We have thousands of legacy machines that are mechanically sound but digitally blind. Retrofitting them with modern sensors and controllers is the fastest way to bring them up to global precision standards. It allows us to scale now while we plan for the next generation of capex.
How does automation solve the “Skill Gap Paradox”?
It levels the playing field. If you have a shortage of expert operators, you use automation to handle the technical inspection and sorting tasks. This allows a junior operator to be productive immediately, giving the human the tools to perform at an expert level.
