Test bed To Be Ground Zero for IIoT Predictive Maintenance Applications

Predictive maintenance is one of the blockbuster use cases for the Industrial Internet of Things (IIoT), and a new partnership could make it easier to develop and test emerging applications.

National Instruments (NI), in partnership with IBM and SparkCognition, a provider of a cognitive data analytics cloud platform, announced the Condition Monitoring and Predictive Maintenance Test Bed, to help organizations pull together IIoT-driven solutions for managing and monitoring aging industrial equipment assets such as heavy machinery, power generation, and process manufacturing gear. Using the test bed technology, organizations would gain proactive intelligence into possible component failures before they happen, enabling them to identify and address suboptimal operating conditions and providing root-cause analysis on equipment degradation.

The Condition Monitoring and Predictive Maintenance Test bed integrates machine learning to identify machine failures and reduce maintenance costs. Image Courtesy of NI

NI’s open software-centric CompaqRIO data acquisition platform is at the heart of the Condition Monitoring Predictive Maintenance Test Bed while SparkCognition’s cognitive analytics employ machine learning capabilities on the data collected to proactively flag problems, officials say. As a result, organizations gain critical insights into the health of their legacy industrial assets, allowing them to remediate problems before they get out of hand, thus helping increase operational efficiencies, reduce maintenance costs, and improve overall safety in the environment.

NI’s CompactRIO data acquisition system is at the heart of the new test bed. Image Courtesy of NI

The test bed solution is aimed at companies in process industries like power generation, wind turbines, water/waste treatment, according to Brett Burger, NI’s principal marketing manager for monitoring solutions. “If you have a pump or motor or some other piece of equipment that you are relying on and that fails you, you are suddenly dead in the water,” he explains. “The goal for this solution is to have 24/7 monitoring, enabling companies to intelligently determine when they need to do maintenance on equipment so there is no work stoppage.”

The combination of the NI data acquisition technology and the SparkCognition capabilities, in particular, would give process engineers a heads up that a particular pump will need a bearing replacement in three weeks or that a motor was months away from failure, he says.

IIoT predictive maintenance applications become particularly important given that many industrial assets are decades old, thus more prone to breakdowns, Burger explains. In addition, he says many industrial equipment experts are nearing retirement and not necessarily being replaced with new engineers, which means there needs to be a more efficient way to keep abreast of the maintenance requirements of field assets.

The test bed, one of many sponsored through the Industrial Internet Consortium, is designed as a proof of concept where member companies and participants can come together to collaborate, advance and test the validity of new IIoT applications.

“Very few companies can offer an end-to-end IIoT solution, so there is support for interoperability,” Burger explains. “That’s the concept of the test bed. It’s a working partnership among a collection of companies that innumerate industry problems and address them.”

Here’s a video introduction to the SparkCognition platform.