Rockwell Automation Project Sherlock artificial intelligence module

Creating diagnostic analytics solutions in industrial operations has long required expert data scientists with a deep understanding of the specific application to be analysed. Those experts then require weeks, months or even years to understand and model the system.

Rockwell Automation has announced its Project Sherlock artificial intelligence (AI) module, in which a data-driven analytics algorithm is provided that fits directly into a controller chassis. Once installed, Project Sherlock AI leverages physics-based modelling to ‘learn’ the application that the controller manages. The solution scours controller tags to identify the application or allows users to choose what they would like modelled by selecting inputs and outputs via an add-on-instruction (AOI). Project Sherlock AI will then quickly learn from the stream of data passing through the controller to build a model.

Once the model is built, the Project Sherlock solution continuously watches the operation looking for anomalies against its derived, principled understanding. If it spots a problem, it can trigger an alarm on a HMI screen or dashboard. Future iterations will go beyond diagnostics to direct users on how to remedy the issue or to automatically adjust system parameters to fix the problem without human intervention.

Project Sherlock diagnostics are expected to offer reduced false-positive alarms due to the physics-based modelling and a foundation in industrial applications. For example, Project Sherlock AI can tell if a boiler temperature shift is related to a benign change in upstream operations or an abnormality that requires correction.