NI and IBM bring IoT analytics to heavy industry

The collection of raw data can be used for analysis and to improve operations, equipment and processes. The companies propose to use artificial intelligence-driven prognostics warn of component failures before they occur, identify suboptimal operating conditions and assist with root-cause analysis.

The aim is to apply Austin, Texas-based SparkCognition’s cognitive analytics to NI’s open, software platform in a testbed for machine learning.

Stuart Gillen

The analytics can be used to identify equipment fatigue and failure of critical assets; thus, enhancing system capabilities by gaining advanced insights into equipment health and remediation solutions.

“With Industrial IoT technologies driving vast sensorisation of industrial equipment, and massive amounts of data being collected on those assets, the collaboration between NI and SparkCognition powers the complex and intelligent processing of information to produce valuable insights,” said Stuart Gillen, director of business development at SparkCognition.

The companies claim this software-defined approach improves upon traditional, fixed-functionality methods of the past, which often take too much time, rely on hard-to-find talent and require custom model building for each type of asset.