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Outlook 2016: When exposed to IoT, ‘Big Iron ATE’ will rust

Darcy Dement, marketing manager, EMEIA, automated test & RF

Though creating smart devices is left to inventors and designers, test engineers must ensure that they function safely and reliably, while meeting the requirements of a disruptive business model.

When the first ‘smart’ refrigerators were released in the early 2000s, consumers weren’t sure what to do with them. But when Nest released its smart thermostat a decade later, a revolution began. Humans were taken out of the loop because the thermostat learned on its own about desired temperature and how quickly it could cool or heat a house – and it could synchronise all of this better than a human could schedule it. Consumers started to understand what a smart device could do.

As the Internet of Things (IoT) gathers pace, Gartner estimates there will soon be more connected devices on the planet than humans and, by 2022, each household could contain more than 500 connected devices. As society continues to reap the benefits of connecting devices and freeing up humans to do more productive things, automated test will continue to be challenged to keep pace economically.

Traditional automated test equipment (ATE) was optimised to test technology that harnessed the power of Moore’s law – mostly digital, increasing transistor count, decreasing footprint – and it does this very well. But over the past few decades, a subtle shift to integrate more analogue technology into ICs has resulted in a test challenge that is much more than Moore. Innovation for the IoT has tasked test engineers to verify mixed-signal systems that not only include digital signals, but also analogue signals from sensors, RF antennas and more – all at consumer volumes and for the lowest price possible. For the testing challenges of tomorrow, traditional ‘Big Iron ATE’ falls short. Test engineers need smart ATE for the smart devices of the IoT.

Same instrumentation from characterisation to production

Every week counts in the customary 12 month design cycle of an IC, which makes data correlation a costly exercise. Test engineers must conduct data correlation because of the often isolated nature of the characterisation and production tests implemented at different locations by different teams in different setups. Characterisation is typically conducted in a laboratory using an array of fixed-functionality instruments, whereas the production tester is a large ‘test head’ filled with proprietary instrumentation that is suspended by a manipulator. Each setup has different instrumentation from different vendors, different connectors and different cables at varying lengths. The result is an endless permutation of variables that could cause misalignment in measurements between characterisation and production test.

IoT innovators have three options to reduce the variables in the equation. First, they can move the production tester into the characterisation lab; this requires additional capital investment in the most expensive equipment. Second, they can take the pile of box instruments into the production line for testing, but this cripples measurement throughput, which results in a testing bottleneck. The last option is to invest in a smarter ATE platform that gives test engineers the flexibility to have the same instrumentation in different form factors for characterisation and production testing. Though data correlation concerns are never completely eliminated, test engineers can use the ATE platform’s modularity to simplify this process as the IoT squeezes time-to-market and cost-of-test.

Test equipment that scales with product innovation

When the end goal is to sense, compute, communicate and connect everything, smart devices built for the IoT must evolve at a gruelling pace. According to teardown.com, when Samsung released the Galaxy S5 smartphone, the company decreased the cost of test by .09 compared with the S4 and added five new sensors (humidity, infrared, proximity/gesture, heart rate and fingerprint). How is this possible? One approach is to build a test strategy on open standards with maximum interoperability.

In a platform based, modular approach to smarter test equipment, test engineers can construct a system that meets their initial requirements from commercial off-the-shelf instrumentation. While this gives them the flexibility to select instrumentation from a variety of specialised vendors, it requires interoperability between platform elements and places a high value on software – the ultimate source of ‘smartness’ in test system design. Nevertheless, with this approach, engineers can scale up the capability of a tester by adding modules when necessary, which eliminates the high cost of retooling the hardware or rewriting the lowest levels of software.

Regardless of the approach, cost and time to market are the driving factors when choosing the platform for test equipment in the IoT. Certain companies, such as those that test memories and microcontrollers, are satisfied with fixed-functionality ‘big iron’ testers. But as companies innovate and rapidly evolve the functionality of their devices, they need a smarter ATE platform that can productively scale with that innovation.

Future proofing test equipment with software

When Tesla Motors discovered that its car was riding a little too close to the ground at higher speeds, it did not force a recall; instead, Tesla sent out an over-the-air firmware update to stiffen the suspension of the car at higher speeds. Users were once forced to purchase a new device to gain new functionality. Now, smartphones, televisions, computers and even cars take advantage of reprogrammable firmware technology to extend or improve the functionality of hardware devices after initial release.

As the market continues to evolve and grow in complexity, we will be forced to embrace change and expect the unexpected. And just as these smart devices increase situational intelligence through upgradable software, so should the test equipment.

With software-defined test equipment, organisations can invest in a platform that meets the test challenges of today but also adapts to new requirements while mitigating capital expenses. Modular hardware definitely plays a role in this approach, but software is what ties everything together in a platform-based, smart ATE approach.

Each year, a company similar to Nest or Tesla will revolutionise a market and change the way that we interact (or do not interact) with a device. Each year, additional sensor technology will be created to give us insight into the world around us. Each year, a new communication protocol will be defined that allows us to embed more data in fewer bytes. And each year, test engineers will be required to validate that all of these new devices deployed into the IoT are working safely, reliably and cost-effectively.

More and more companies have adopted a smarter, platform-based approach for their test equipment to address these challenges. As cost and time-to-market are continually reduced, innovative companies cannot afford to have their devices-under-test outsmart their ATE.

National Instruments

For nearly 40 years, NI has worked with engineers and scientists to provide answers to the most challenging questions by providing powerful, flexible technology solutions that accelerate productivity and drive rapid innovation. From daily tasks to grand challenges, NI helps engineers and scientists overcome complexity, and customers in nearly every industry—from healthcare and automotive to consumer electronics and particle physics—use NI’s integrated hardware and software platform for measurement and control to improve the world around us. Through these pursuits, NI customers have brought hundreds of thousands of products to market, overcome innumerable technological roadblocks, and engineered a better life for us all. If you can turn it on, connect it, drive it, or launch it, chances are NI technology helped make it happen.


Author
Darcy Dement

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