Rockwell Automation Technologies Incorporated

Rockwell Automation, Inc.

Mark Joseph Balewski

Kenwood H Hall

Robert J Kretschmann

Charles Martin Rischar

Kendal R Harris

Jonathan D Bradford

Timothy Siorek

Martin George Gach

Systems and methods that correlate among disparate pieces of synchronized data, collected from an 'internal' data stream (e.g., history data collected from an industrial unit) and an 'external' data stream (e.g., traffic data on network services). A process trend component that determines/predicts an outcome of an industrial process and facilitates diagnostics/prognostics of an industrial system. Accordingly, relations among various parameters can be discovered (e.g., dynamically) and proper corrective adjustments supplied to the industrial process. Such enables a tight control and short reaction time to process parameters, and for a modification thereof.

Correlation of non-times series events in industrial systems

Systems and methods that vary multiple data sampling rates, to collect sets of data with different levels of granularity for an industrial system. The data for such industrial system includes sets of data from the 'internal' data stream(s) (e.g., history data collected from an industrial unit) and sets of data from an 'external' (e.g., traffic data on network services) data stream(s), based in part on the criticality/importance criteria assigned to each collection stage. Each set of data can be assigned its own unique data collection rate. For example, a higher sample rate can be employed when collecting data from the network during an operation stage that is deemed more critical (e.g., dynamic attribution of predetermined importance factors) than the rest of the operation.

Adjustment of data collection rate based on anomaly detection

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Independence, OH, United States of America

Mark Joseph Balewski