To many people, the phrase "Internet of Things" conjures images of consumer gadgets like wearable fitness monitors, Google Glass or maybe even self-driving cars. But some of the most exciting and practical applications are happening in the Industrial Internet of Things (IIoT): smart agriculture, smart cities, smart factories and the smart grid.
That said, the IIoT brings with it tremendous amounts of complexity. To tackle that complexity, organizations must overcome five key challenges, according to a new report by National Instruments (NI), the $1.25 billion company that makes the automated test equipment and virtual instrumentation software at the heart of much of the IIoT equipment out there.
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"We essentially make the brain that goes inside all of this industrial equipment that everyone is trying to add industrial intelligence to," says Eric Starkloff, executive vice president of Global Sales and Marketing for NI. "We make the hardware technology and software infrastructure that enables someone building a machine, robot, healthcare device or factory to build the intelligence for their particular application on top of that platform."
At its root, the IIoT is a vast number of connected industrial systems that communicate and coordinate their data analytics and actions to improve performance and efficiency and reduce or eliminate downtime. A classic example is industrial equipment on a factory floor that can detect minute changes in its operations, determine the probability of a component failure and then schedule maintenance of that component before its failure can cause unplanned downtime that could cost millions of dollars.
Starkloff points to another example, NI customer Airbus Group, which is prototyping the "factory of the future" with NI's help.
"They're reimagining how to build airplanes," Starkloff says. "They're adding intelligence to their tools, intelligence to their drills and fastening machines. They're adding robotic machines that can work and interact side-by-side with humans."
For instance, he says, an operator might be looking at a bolt she needs to fasten. That operator could be wearing smart glasses that can identify what the required bolt is and where it's located on the factory floor. That intelligence can also be communicated to the drill the operator is using to ensure it's the correct tool for the job and then adjust itself to provide just the correct amount of torque to fasten the bolt. On the back end, the system could automatically update inventory systems as parts are used.
"The future is here, it's just unevenly distributed," Starkloff says. "Airbus is still in the prototyping phase, but there are working prototypes of all these things today."
The possibilities in the industrial space are nearly limitless: smarter and more efficient factories, greener energy generation, self-regulating buildings that optimize energy consumption, cities that adjust that can adjust traffic patterns to respond to congestion and more. But, of course, implementation will be a challenge.
Precision Is (More) Essential
Building the consumer Internet was and is a complex challenge, but the IIoT is more daunting still.
"Both involve connecting devices and systems all across the globe, but the IIoT adds stricter requirements to its local networks for latency, determinism and bandwidth," the NI report notes. "When dealing with precision machines that can fail if timing is off by a millisecond, adhering to strict requirements becomes pivotal to the health and safety of the machine operators, the machines and the business."
Industry consortiums are working to address this challenge using standards originally developed for Audio/Video Bridging — the deceptively complex task of synchronizing video and audio in a stream.
"One of the places we'd like to use that technology is vehicle-to-vehicle communication for automotive," Starkloff says. "It doesn't do much good to have an adaptive cruise control system that applies the brakes just a few seconds too late."
Adaptability and Scalability Is Paramount
Adopting the Industrial Internet of Things will require a change in the way organizations design and augment their industrial systems. IIoT systems must be adaptive and scalable through software or added functionality that integrates with the overall solution, Starkloff notes.