Rockwell Automation Technologies Incorporated

Alexander B Cherpakov

Francisco Paul Maturana

Andrew R Stump

Ryan Cahalane

Bryan N Siafakas

Stephen C Briant

Jonathan D Walter

Nicholas J Marangoni

Marek Obitko

Deepa S Bekal

Sonal R Dubey

Robert Mavrov

Dale A Hawthorne

Todd M Smith

Derrick Awuah

Alexander K Bergsneider

Václav Jirkovský

Joshua W Buck

Anthony C Barrancotta

Sharath C R Baddam

A computing device for collecting and preserving data acquired from various devices in a data model with the respective context of acquired data. The computing device may provide a user interface to receive the context or information model associated with a dataset. By providing data with its context, different software platforms may synthesize or analyze the retrieved data more efficiently. Moreover, the computing device may include transaction conditions to define a workflow for transferring the datasets using data model associated with one or more datasets for transmission of data to a destination. The transaction conditions may detail a custom workflow for data communication through an industrial automation system using the data model.

Data models for defining data transmission workflow and facilitating data communication

A cloud-based operator training system includes a snapshot management architecture, which provides a hybrid system for generation of control system level scenarios and system-state snapshots, and which can improve the fidelity of a training simulation. By implementing the simulation system on a cloud platform, the system can generate a large and growing set of snapshot files representing various control states and corresponding process states. These files can then be leverage during operator training sessions to yield high fidelity simulated system operation.

Snapshot management architecture for process control operator training system lifecycle

A manifest generation system generates a system model for a cloud computing architecture. The system generates the system model in the form of system, data, and metrics manifests that act as an information concentrator for configuring various aspects of data ingestion and data management. The manifest generation system leverages both information extracted from industrial devices, applications, and programs that make up physical industrial automation systems, as well as user selections identifying which data tags are to be collected, specifying data collection preferences, etc. In this way, manifest data for configuring cloud-level data monitoring and collection is mapped to the automation and control system configurations via information extracted from the system-level topology. This approach can automate and simplify aspects of the cloud-based data collection configuration process.

Modular control manifest generator for cloud automation

A computer-implemented method for automatically exchanging data between a piping and instrumentation diagram (P&ID) and a control system comprises: parsing a P&ID and identifying instruments and/or groups of instruments within the P&ID, identifying one or more input tags and output tags associated with each identified instrument and/or with each identified group of instruments within the P&ID, and establishing at least one relationship among the one or more input tags and output tags, wherein the input tags and output tags for an instrument and/or a group of instruments and the at least one relationship between the corresponding input tags and output tags are derivable from a template library, and identifying a control loop for each established relationship among the input tags and the output tags, wherein said control loop is for controlling one or more instruments by the control system.

P and ID and control system synchronization

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Mayfield Heights, OH, United States of America

Alexander B Cherpakov