There's a Goldmine in Big Test and Measurement Data

Big data's getting really really huge in test and measurement. According a recent study from Frost & Sullivan (F&S), the revenue allocated to big data projects will grow from $421 million in 2014 to $2.4 billion by 2021, a compound annual growth rate of 28%. F&S researchers note that R&D, risk management, and asset management are the key applications in test and measurement where big data analytics is gaining traction. Real-time monitoring and preventive maintenance are also racing to the top of investment priorities across multiple industries.

Each industry deploying big data has its own priorities. Automotive manufacturers are looking to utilize big data analytics to optimize products in the production line and keep track of maintenance and repair requirements. The aerospace industry is using big data analytics for component manufacturing, preventive maintenance services, and real-time structural health monitoring.

The report shows that high initial costs involved with big data will slow down the large-scale adoption to some degree. Many companies prefer to stick to in-house systems managed by their IT departments rather than investing in advanced big data solutions for test and measurement. Plus, several OEMs remain skeptical on the reliability of data analytics.

Researchers point to a number of prompts that are pushing big data adoption, from usable systems to widespread connectivity. "Test and measurement vendors such as National Instruments are coming out with versatile, scalable, and functional test systems to address the demands from the OEMs," Apoorva Ravikrishnan, research analyst for measurement and instrumentation at F&S, told Design News. "Increasing connectivity is changing not only the product that is being manufactured but also the test systems which are used to ensure its functioning." Ravikrishnan says that this has created an exponential increase in the data that gets generated.

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Big production benefits from big data

Ravikrishnan acknowledged that test and measurement may be a tad late to the party on big data, but the applications are wide enough for it to eventually gain wide adoption. "One of the reasons for big data analytics' slow uptake in test and measurement is because OEMs were focused on implementing big data analytics in other domains like marketing, where its application was more straightforward," Ravikrishnan told us. "In many industries, especially in industries where time-to-market is critical, testing is considered a necessary liability. It took some time for OEMs to understand its value."

According to Ravikrishnan, that value translates to a 25% reduction in product development costs, a 20% reduction in operating costs, and a 50% reduction in maintenance costs.

Not just for big companies

The report shows that much of the big data analytics has been used by large companies. Ravikrishnan believes that's about to change. Much of the aggressive growth in big data will come as small firms take up analytics. "Toward the end of 2016 there will be many smaller companies in different industries looking to implement big data analytics for testing," said Ravikrishnan. "This will be further aided by numerous big data analytics' providers -- now start-ups -- that small OEMs can utilize for a cost-effective implementation of big data analytics."

Rob Spiegel has covered automation and control for 15 years, 12 of them for Design News. Other topics he has covered include supply chain technology, alternative energy, and cyber security. For 10 years he was owner and publisher of the food magazine Chile Pepper.

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