Data is clearly the underlying connection between the Internet of Things, edge computing, cloud computing, smart manufacturing, digitization, Industry 4.0 and other related technology developments and initiatives. But just as industry’s search for better data collection and analysis is showcasing technology’s adaptation to specific industry needs, it’s also highlighting how industry is evolving in reaction to data technology developments.
While speaking with Brett Burger of National Instruments (NI) at the IoT Solutions World Congress, he noted five trends in engineering that NI is watching closely—three of which revolve around industrial data collection, processing and analysis. Those three are the Industrial Internet of Things (IIoT), machine learning (ML) and the extension/breaking of Moore’s Law. (To learn more about all five trends, visit NI’s Trend Watch 2018.)
With regard to IIoT and ML, Burger said that the management of large numbers of systems using edge processing nodes and all the firmware required to deal with it has largely been addressed on the consumer side. As examples, he referred to Tesla’s cars and Apple’s mobile devices and computers that can be upgraded in the field—even while we sleep. Such advances are still being worked out for wide use in industrial applications, however. The reason for this is the widely varied and often antiquated technologies still in place throughout industry worldwide that need to be connected in some fashion to become part of IIoT and ML, not to mention the security concerns and other production-related issues.
NI is approaching the task of turning industrial data (both brownfield and greenfield) into information as a platform for use in advanced applications through the use of four tools that comprise NI’s Data Management Suite—Data Finder, Analysis Server, DIAdem and System Link. Burger said DataFinder specifically addresses industry’s “need to have the ability to index and/or parse data that comes from many sources. And because users need to standardize all this disparate data for automated processing, Analysis Server handles that by helping users process large amounts of data on a server and interactively set up logic to decide which analysis needs to be run on those data. The DIAdem Environment is then used for interactive viewing and reporting. It gives users the tools needed to test script algorithms, then takes those scripts and loads them into cloud analysis to see how they're working—with the ability to deliver reports daily. The firmware connecting them all is NI’s SystemLink, which verifies the status of all the interacting pieces of software.”
The breaking of Moore’s Law (i.e., the doubling of computing power roughly every two years) directly affects edge computing platforms for IIoT. Burger explained that Moore’s Law has been approaching its limits recently, but the application of heterogeneous processing is extending it. Heterogeneous processing refers to systems that use more than one kind of processor or core. “We’re now looking at the 3D scaling of processors—the stacking of chips and transistors in a module—to give these edge devices the computing power they need to deliver on these complex IIoT applications.”
Presenting at the IoT Solutions World Congress with Burger was Corey Catten, chief technology officer at Innovari, supplier of the Interactive Energy Platform, which uses artificial intelligence, Big Data analytics and optimization routines—all of which are at the core of IIoT and ML—to address capacity and demand variables for energy utilities.
“Utilities have always had problems optimally controlling large facilities, but it gets even more difficult with the incorporation of renewable energy because of lack of insight into customers’ usage and needs,” said Catten. “The systems Innovari is deploying are designed to bring utilities closer to their customers to get those insights.”
In other words, as much as OEMs are increasingly an example of how technology and industry are altering each other, so too are utilities. And the examples being set by utilities can offer a number of data and systems management lessons for industries of all types.
Catten explained that Innovari is working with NI to deploy edge computing hardware to monitor and control energy loads between the utility and its customers that will allow customers to essentially operate as part of a virtual power plant. Innovari explains the virtual power plant as delivering the ability to aggregate edge of grid resources in a utility’s control room via a two-way closed loop control system. The utility, in partnership with its customers, can access those resources—distributed generation and load management—to dramatically improve the efficiency and optimization of the entire energy value chain.
“We believe the utility is the only entity that can provide a safe, reliable and resilient grid. But with renewable sources changing the future of energy generation and delivery, we created a platform for utilities to connect more directly with the customer,” said Catten. “It [the combination of Innovari and NI technologies] looks across thousands of the utility’s circuits and uses algorithms to direct what functions to turn on and off to take a chunk out of peak load,” he said.
As an example of this energy data technology being put into practice, Catten referenced Kansas City Power and Light, which has begun using Innovari’s Energy Agent—a utility-owned asset which is positioned behind the meter in commercial and industrial buildings. Energy Agent uses NI’s CompactRIO, a Modbus/BACnet/meter protocol, digital I/O, a cellular gateway and Tempered Network’s HIPswitch for secure connectivity. Catten says Energy Agent gives the utility verifiable monitoring and control of a building or facility’s HVAC and lighting, as well as distributed generation of power.
“In this way, the utility establishes a relationship with the building directly and guarantees the building’s occupants an ‘envelope’ in which the temperature won’t change outside of set parameters and the lights won’t turn off at any time when they may be needed,” said Catten. “The collection of all these small changes across buildings connected in this way can drive 15-20 percent efficiency improvements across the grid.”
Catten added that Innovari is also working with American Electric Power in Indiana and Michigan with some of its big box retail and school campus customers. The company is also working with customers internationally, in India and South America.
In much the same way as OEMs are using gateways to connect to their equipment in the field at customer sites, the center of Innovari’s approach is the use of “IoT services for device troubleshooting,” Catten said. “The hardware and the software process all the data to provide the analytics you need to determine how things are performing.”
