Rockwell Automation has developed an artificial intelligence (AI) module that fits inside an industrial controller, “learns” the application that the controller is managing, and builds a model of it. It then monitors the operation continuously, looking for anomalies. If it spots a problem, it can trigger an alarm on an HMI screen or dashboard. Future versions will go beyond diagnostics to guide users on how to remedy the problem, or adjust system parameters automatically to fix the problem without human intervention.
Creating diagnostic analytics solutions in industrial operations has long required expert data scientists with a deep understanding of the specific application to be analyzed. Those experts then require weeks, months or even years to understand and model the system. That expertise has been boxed in the new Project Sherlock artificial intelligence (AI) module unveiled by Rockwell Automation.
A question often asked is whether companies have the data needed to enable machine learning, and whether the data is in a form suitable for such use. "People have more data than they think, but less than they hope," said Kavanaugh. "While there are a lot of data stores that don't lend themselves to machine learning, there are instances where great amounts of data simply aren't needed. At other times, companies can build on the power of accumulated data. Industrial manufacturers do have deep troves of simple data which can be converted to use cases, where they can go deep."