Rockwell Automation Technologies Incorporated

Stephen L Hickox

Jessica Lin Korpela

John Strohmenger

Jan Pingel

Matthew W Fordenwalt

Douglas B Weber

Abhishek Mehrotra

Bryan W Barnett

A method may include generating visualizations via a control system that controls one or more operations of one or more industrial devices. Each of the visualizations is representative of one or more live operational parameters associated with the one or more industrial devices. The method may also include continuously streaming one or more of the visualizations to a first computing system via the control system and receiving the one or more of the visualizations via a second computing system. Additionally, the method may include identifying one or more data fields in the one or more of the visualizations and retrieving values from each of the one or more data fields over a period of time via the second computing system. Each value may correspond to one or more frames of image data including the one or more of the visualizations. Furthermore, the method may include storing the values in a database.

Historical data extraction and trend identification from industrial streaming image data

A method may include generating visualizations each representative of operational parameters associated with industrial devices in an industrial system via a control system that controls operations of the industrial devices. The control system is communicatively connected to a first computing system and a second computing system. The method may also include receiving a request including credentials associated with a requester from the second computing system and determining rights to each of the visualizations. Additionally, the method may include identifying one or more of the visualizations based on the access rights and receiving a selection of the one or more of the visualizations from the second computing system. Moreover, the method may include transmitting the one or more of the visualizations to the first computing system that live streams the one or more of the visualizations to the second computing system.

Live streaming visualizations of industrial equipment operation

A system may include a control system for controlling one or more operations of one or more industrial devices in an industrial system. The control system may receive streaming data comprising one or more visualizations representative of one or more live operational parameters associated with one or more industrial devices. The streaming data may include multiple image frames. The control system may also identify multiple datasets associated with the streaming data and generate multiple machine-readable images based on the multiple datasets. In addition, the control system may embed the multiple machine-readable images within the multiple image frames of the streaming data to generate updated streaming data and send the updated streaming data to a computing system that may extract the multiple machine-readable images from the updated streaming data.

Interlacing data in streaming industrial image data

A cloud-based modeler component that generates interactive models of an industrial automation system(s) (IAS(s)) is presented. An interactive model facilitates remote viewing of, interaction with, troubleshooting of problems with, or optimization of industrial assets of an IAS. The modeler component polls industrial assets via cloud gateways to obtain information relating to the industrial assets to identify industrial assets of the IAS and relationships with other industrial assets or can receive information from a communication device that obtains information relating to legacy industrial assets to identify those legacy assets and their relationships. The modeler component generates an interactive model of the industrial assets of the IAS based on the information. The modeler component also can discover new industrial assets added to the IAS, can receive a pre-deployed model of an industrial asset from the industrial asset or another source, and can incorporate the pre-deployed model in the interactive model.

Modeling of an industrial automation environment in the cloud

A cloud-based analytics engine that analyzes data relating to an industrial automation system(s) to facilitate enhancing operation of the industrial automation system(s) is presented. The analytics engine can interface with the industrial automation system(s) via a cloud gateway(s) and can analyze industrial-related data obtained from the industrial automation system(s). The analytics engine can determine correlations between respective portions or aspects of the system(s), between a portion(s) or aspect(s) of the system(s) and extrinsic events or conditions, or between an employee(s) and the system(s). The analytics engine can determine and provide recommendations or instructions in connection with the industrial automation system(s) to enhance system performance based on the determined correlations. The analytics engine also can determine when there is a deviation or potential of deviation from desired system performance by an industrial asset or employee, and provide a notification, a recommendation, or an instruction to rectify or avoid the deviation.

Cloud-based analytics for industrial automation

A cloud-based industrial controller that controls devices, processes, and other assets of an industrial automation system via control algorithms that execute on a cloud platform is presented. A cloud-based collection component collects information from the industrial automation system via cloud gateways associated with the industrial automation system or extrinsic data sources. The cloud-based industrial controller can monitor and analyze the information, generate control instructions based on the analysis results, and communicate the control instructions to the devices, processes, and/or other assets of the industrial automation system to control operation of the industrial automation system. The cloud-based industrial controller also can interface with a industrial plant-based industrial controller, wherein the cloud-based industrial controller can determine supplemental control instructions to the industrial plant-based industrial controller, based on the information, including extrinsic information, to assist in controlling the industrial automation system and control decision-making.

Cloud-based industrial controller

Cloud-based backup provides a back up of an industrial plant comprising an industrial automation system(s) (IAS(s)). A cloud-based backup component comprising a modeler component can generate a model of industrial assets of the IAS(s) and relationships between industrial assets based on information obtained from the industrial assets via cloud gateways, a communication device associated with the IAS(s), or another source. The cloud-based backup component can store the model in a data store to be employed as a backup of the IAS(s) or to be used to configure a new IAS that is the same as or similar to the IAS(s). The model can be stored in the data store in a standardized or an agnostic format, wherein the backup component can translate the model to a format suitable to an IAS for which it is to be implemented based on characteristics associated with the IAS.

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Middlefield, OH, United States of America

Stephen L Hickox