As India accelerates its ambitions in semiconductor manufacturing and high-tech electronics, the role of advanced test and measurement technologies has become more critical than ever. From AI-driven validation systems to software-defined testing platforms, the industry is witnessing a major transformation in how products are designed, validated, and brought to market. In this exclusive interaction with Machine Edge Global, Shitendra Bhattacharya shares insights on how Emerson’s integration with NI is reshaping the automated test and measurement landscape, the opportunities emerging from India’s semiconductor push, and the growing convergence of AI, analytics, and automation in building the next generation of reliable, scalable semiconductor ecosystems. Speaking with Editor Sanjay Jadhav, he also highlights why connected, lifecycle-based testing strategies will be central to India’s ambitions of becoming a global technology and manufacturing hub.
Emerson’s Test & Measurement business has a legacy of more than five decades. How has the integration of National Instruments strengthened Emerson’s capabilities in the automated test and measurement space?
The biggest shift we’re seeing is that test is no longer about standalone instruments, it’s about connected, software-defined systems that span the entire product lifecycle. Traditional approaches still treat validation, production, and lifecycle testing as separate silos, and that’s where they fall short.
The integration of NI into Emerson brings together software-defined test with Emerson’s strength in industrial-scale deployment and operational reliability. By combining modular NI hardware and software platforms such as NI LabVIEW™, we enable a single, unified test architecture from early validation through to high-volume manufacturing. In practice, teams can move from PXI-based validation systems into production environments such as the NI Semiconductor Test System, reusing code, data, and workflows across stages.
Companies that lead in this environment are those that don’t rebuild their test strategy at every stage. A platform-based approach enables reuse of code, data, and workflows across the lifecycle, reducing rework, improving traceability, and accelerating time to market.
As India accelerates its ambitions in semiconductor manufacturing, how critical is advanced test and measurement infrastructure in building a robust semiconductor ecosystem?
India’s strength today is clearly in chip design, but the gap in validation and production test readiness remains significant and is often underestimated.
While there is strong momentum around building fabs, test infrastructure is what ultimately determines yield, reliability, and scalability. Without robust capabilities in device characterization, validation, and production testing, even well-designed chips struggle to transition into volume manufacturing.
This gap becomes most visible when test is not integrated early in the development process. In many cases, companies use different frameworks across R&D, validation, and production, which creates a disconnect across the lifecycle. When issues surface in production, it becomes extremely difficult to trace them back because the data, tools, and environments are not aligned.
The result is lower yield, longer debug cycles, and delays in time-to-market. In contrast, when a unified, software-defined test approach is adopted early, teams can correlate data across stages, identify issues faster, and scale more efficiently.
Artificial intelligence is rapidly transforming manufacturing and design workflows. How is Emerson leveraging AI and data analytics to accelerate semiconductor product development?
AI is already making a meaningful impact in test, but not in the way it is often positioned. The real value lies in improving engineering decision-making during development and validation rather than simply automating processes.
A good example is NI Nigel™AI, which is embedded in environments like LabVIEW and TestStand. Engineers use it to analyze test sequences and execution data generated during validation. In practice, it can identify inefficient test steps, highlight anomalous measurement patterns across runs, and suggest improvements in test logic.
This reduces the need for manual data comparison and accelerates the debugging process. Engineers can move more quickly from identifying an issue to understanding its root cause. This has proven especially valuable in areas such as automotive electronics and RF in India, where validation complexity is high, and timelines are tight. By catching issues earlier and improving test coverage, teams are better prepared before moving into production, which directly impacts yield and ramp efficiency.
With India focusing on semiconductor self-reliance, what opportunities do you see for advanced test and validation technologies in the country?
In India, we are seeing strong traction in areas such as automotive electronics, RF and wireless systems, and power electronics, where validation complexity is high, and reliability expectations are stringent.
The bigger challenge, however, lies in scaling from validation to production. This is where many companies face friction. Test strategies developed in the lab often fail to transition smoothly to production environments, leading to rework, delays, and increased risk.
What is often missing is continuity. When test systems, code, and workflows are not aligned across the lifecycle, teams are forced to rebuild and revalidate at each stage. A platform-based approach addresses this by enabling continuity from the outset, and solutions like NI have been helping engineering teams bridge this gap. Engineers can develop test code in validation environments and deploy it directly into production systems, reusing the same logic, data models, and workflows.
This significantly reduces duplication and accelerates the path to production readiness. Emerson’s modular, software-defined test infrastructure, from the NI PXI platforms for validation to the NI Semiconductor Test System (STS) for high-volume production, allows companies to ramp yields faster and reduce production debug time, which is critical as India scales its semiconductor ecosystem.
Semiconductor reliability testing is becoming increasingly complex with advanced nodes and heterogeneous integration. How is the test ecosystem evolving to meet these challenges?
The core issue with reliability testing today is not just complexity; it’s that most teams are still trying to solve a system-level problem with component-level tools.
With chiplet-based architectures and heterogeneous integration, failure modes are increasingly tied to system-level interactions—thermal coupling between dies, mechanical stress at interconnects, and long-term degradation that only surfaces under real operating conditions. These cannot be caught through electrical parametric checks alone. You need correlated data across characterization, validation, and production to even see the risk, let alone act on it.
This is where a platform-based approach becomes critical. Emerson’s modular, software-defined NI test environment allows teams to build a persistent data layer that spans the full lifecycle so that what you observe during characterization can be directly correlated with what you see in production and, ultimately, in the field. That kind of longitudinal visibility is what the industry has been missing, and it is what makes reliability engineering proactive rather than reactive.
For India, where automotive and power electronics companies are now entering high-reliability application spaces for the first time, getting this foundation right early is not optional — it is the difference between qualifying for global supply chains and being locked out of them.
India’s automotive, aerospace, electronics, and wireless sectors are rapidly evolving. How do these industries benefit from advanced automated test and measurement solutions?
India’s automotive, aerospace, and wireless sectors are not just growing; they are moving into higher-complexity application spaces faster than the test infrastructure is being built to support them. That gap is where most of the friction occurs.
In automotive, India’s OEMs and Tier 1 suppliers are being asked to meet IATF and ISO 26262 requirements for EV powertrains and ADAS systems—requirements that demand rigorous functional safety validation well before a component reaches production. NI PXI-based test platforms are well-suited for this: they are modular, reconfigurable, and able to run the same test logic from bench validation through to production line, which significantly reduces the cost and time of re-qualification.
In RF and wireless, India is rapidly scaling 5G infrastructure deployment while simultaneously investing in 6G research. This creates demand for mmWave characterization and over-the-air testing at a level that few local ecosystems are currently equipped for. A software-defined test approach built on flexible RF hardware, where the same platform can address both R&D characterization and production verification, is a significant advantage for teams that need to move quickly without duplicating capital investment.
Across both sectors, the companies making the most progress are those that treat test as a unified flow rather than a stage-by-stage effort. That shift from siloed validation to lifecycle-connected test is where the NI platform-based approach delivers its clearest advantage in the Indian context.
Looking ahead, how do you see the convergence of AI, data analytics, and automation shaping the future of semiconductor testing?
The most important shift is not technological; it’s strategic. The companies that will define India’s semiconductor future are those that stop treating test as a cost centre and start treating it as a source of competitive advantage.
As AI, analytics, and automation converge, the opportunity is to build a closed-loop system in which test data from validation, production, and the field continuously inform one another. Tools like NI Nigel™ AI are an early signal of what this looks like in practice, surfacing patterns across large test datasets that engineers would not catch manually and feeding those insights back into test strategy. Over time, this moves organisations from reactive debugging to genuinely predictive quality management.
For India specifically, this matters more than anywhere else right now. The country is building its semiconductor manufacturing base at a time when AI-driven test infrastructure is already available, so it does not have to repeat the legacy-architecture mistakes others are now trying to undo. The window to build it right from the start is open. The question is whether organisations will treat that as an opportunity or let it pass.
Emerson’s test and measurement business is investing here precisely because we believe India will be one of the most consequential test markets over the next decade. Our commitment is to ensure that the infrastructure being built today is capable of sustaining that ambition long-term.