As manufacturers generate huge volumes of high-speed industrial data at the edge, the challenge of quickly discovering insights—using low-footprint hardware—and applying them to the control systems at low latency response times has gained importance. At the same time, relying on a centralized data science or IT analysis function can take days or months before a turnaround can happen at the plant floor.
To break this deadlock, OT professionals need the ability to easily navigate data challenges and deploy machine learning applications for applying streaming data directly from the control application—the source of high-speed and voluminous industrial data. They should be able to apply the model outputs to both the Rockwell Automation control system layer and other off-the-shelf hardware. With these powerful capabilities, OT professionals can improve manufacturing yield, improve overall equipment effectiveness, and other KPIs that matter to their key business outcomes.
