S Mohanakrishnan traces the six-decade journey of test and measurement instrumentation from analog to AI-driven systems.

The past sixty years have seen remarkable progress in the field of Test and Measurement (T&M) instrumentation. From the days of analog meters with moving coils and cathode-ray tubes to today’s smart, cloud-connected, AI-driven systems, T&M devices have become fundamental to precision, safety, and automation across nearly every industrial domain. This journey reflects not just technological growth, but also a shift in how industries perceive and practice quality control, diagnostics, and innovation.

The 1970s marked the era when analog instruments were paramount. Oscilloscopes, multimeters, signal generators, and frequency counters were based largely on analog electronics, designed with discrete components and cathode-ray displays. These instruments, although groundbreaking for their time, had significant limitations. They were bulky, manually calibrated, and constrained in terms of accuracy and data storage. Measurement and diagnostics were manual, slow, and operator-dependent. Despite these shortcomings, analog instruments were the backbone of industries such as telecommunications, aerospace, defense, and broadcasting, where signal integrity and system testing were critical.

It was also during this decade that Distributed Control Systems (DCS) emerged as a revolutionary concept in process industries. Introduced in the mid-1970s, DCS enabled decentralised processing and localised control. It drastically reduced the reliance on large centralised control rooms and enabled modular plant design and operation. Early adopters included sectors such as petrochemicals, oil and gas, power generation, pulp and paper, and pharmaceuticals. The deployment of DCS marked a pivotal and paradigm shift towards smarter, more scalable automation.

As industries stepped into the 1980s, the digital age began to dawn. The development of digital multimeters (DMMs), digital oscilloscopes, logic analysers, and waveform generators redefined accuracy and usability in T&M. Instruments became more compact, faster, and increasingly capable of internal processing. The integration of microprocessors allowed for digitised displays and more stable calibration. This decade also saw the beginning of software-driven control, although still rudimentary and primitive, using basic onboard firmware or PC interfaces.

One of the landmark developments in India during this period was the establishment of the National Accreditation Board for Testing and Calibration Laboratories (NABL) in 1988. NABL’s role in ensuring the traceability and accuracy of laboratory measurements established a new standard of credibility for test results across public and private sectors. It created the foundation for uniform measurement protocols in research, production, and quality assurance across industries.

The 1990s were characterised by rapid automation and the widespread integration of personal computers into test environments. Test instruments evolved into semi-intelligent systems that could be connected and controlled through communication standards such as IEEE-488 (GPIB) and RS-232. This allowed for the seamless exchange of data between multiple devices and computers, streamlining the testing process. Software platforms such as LabVIEW and MATLAB became critical tools for real-time data analysis, test automation, and simulation.

Instruments like spectrum analysers, network analysers, and signal conditioners became increasingly programmable and could now perform complex functions with minimal human intervention. This ushered in a new era of high-throughput, reproducible, and cost-effective testing in industries like automotive manufacturing, consumer electronics, and aerospace, where batch testing and certification needed to be fast and reliable.

With the arrival of the 2000s, the emphasis shifted toward portability, modularity, and network connectivity. Instrumentation manufacturers responded to market demands by designing compact, battery-operated, and field-deployable tools. Devices began to offer USB connectivity, LAN ports, and later, wireless (Wi-Fi) access. Test and measurement could now be conducted remotely, in real time, across multiple locations.

The emergence of platforms allowed engineers to build modular test setups tailored to specific applications. These systems often included embedded Linux operating systems, providing users with the ability to customise functions and interface software directly. This flexibility allowed for greater flexibility in industries where on-site diagnostics, mobile calibration, and fast deployment were vital—such as telecommunications, energy, and infrastructure.

At this stage, T&M maturity in industrial environments reached a point where traceability, modularity, and remote access became standard expectations. While large enterprises had fully integrated digital systems, smaller operations often struggled with interoperability and training gaps—highlighting the uneven maturity across the industry.

By the 2010s, smart technology had taken center stage in test and measurement. The integration of touchscreens, high-speed Field Programmable Gate Arrays (FPGAs), and Internet of Things (IoT) compatibility redefined the capabilities of modern instruments. Devices became capable of capturing, analysing, and transmitting high-bandwidth data in real time.

With cloud integration, engineers and decision-makers could monitor processes remotely and access test data from anywhere in the world. This decade also marked the increasing convergence of T&M systems with industrial automation tools. Instruments were now designed to seamlessly communicate with Programmable Logic Controllers (PLCs), Supervisory Control and Data Acquisition (SCADA) systems, and Ethernet/IP networks. Redundant hardware and microcontroller-based distributed control units enhanced operational safety and uptime in critical systems such as water treatment plants, power stations, and manufacturing hubs.

The role of test instruments had evolved from being passive validators to active participants in monitoring and control systems. The rise of IIoT and edge computing also allowed data to be processed at the point of measurement. This significantly reduced latency and bandwidth needs while enabling smarter, more decentralised architectures in manufacturing and process control.

Yet, challenges persisted—notably in the form of integration complexity, high initial investment costs, and a shortage of skilled technicians able to interpret increasingly complex datasets generated by AI-augmented systems. Ensuring interoperability between legacy systems and new technologies also remains a key roadblock in modern deployments.

Now, in the 2020s, we have entered a new era defined by artificial intelligence and software-defined instrumentation. Instruments are now cloud-native, embedded with AI engines, and capable of supporting digital twins—virtual replicas of physical systems used for real-time simulation and prediction. These twins allow engineers to simulate test scenarios, optimise configurations, and validate performance without disrupting actual operations. This evolution transforms T&M from reactive validation to proactive design and operational intelligence.

The future of test and measurement instruments in this era of artificial intelligence is not just about making devices more intelligent. It is about completely transforming the way testing is understood and conducted. These instruments will no longer simply assist engineers. They will actively contribute to engineering processes by enabling faster decision making, greater accuracy, and stronger, more resilient systems. This evolution from basic measurement tools to intelligent systems positions test and measurement as a foundation for the next wave of innovation and excellence in operations.

In this new era, test and measurement instruments are becoming intelligent, self-learning systems that go beyond traditional functions. They are capable of thinking, adapting, and predicting. We can expect instruments that automatically identify problems, optimise performance instantly, and improve themselves using real time data. The integration of artificial intelligence at the edge and in the cloud allows for smooth and distributed control, while virtual replicas known as digital twins are transforming how products are developed and tested in simulated environments.

Testing will no longer be a complicated process. Artificial intelligence is making it more intuitive and accessible, even for those without technical expertise. These smart systems offer the potential for almost zero downtime, faster innovation, and more sustainable operations. The future of test and measurement is more intelligent. It is faster, more environment friendly, and significantly more capable than anything we have seen before.

Artificial intelligence will redefine test and measurement instruments as intelligent partners in the innovation process. These systems will not only collect data. They will also anticipate needs, make informed decisions, and continually improve. This will lead to faster development timelines, greater accuracy, and reduced costs across nearly every industry.

S Mohanakrishnan, Managing Director, MAGS BIOMECHINST PRODUCTS AND SERVICES LLP, is a Bachelor of Physics, Master of Business Administration and post graduate Diploma holder in Computer Programming & System Analysis. Backed by over 35 years of marketing experience from a leading organisation (M/s Nagman Instruments & Electronics Pvt Ltd, Chennai), he is engaged in the field of manufacturing calibration instruments. As a true soldier/mercenary of the organisation, Mohanakrishnan has handled various international principals’ products. As the representative of the organisation, he has assisted in the areas of technology transfer, manufacturing, calibration, production, sales & marketing.  

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