Rockwell Automation Technologies Incorporated

Abhishek Mehrotra

Timothy R Brennan

Richard S Turk

Tyler L Sheveland

Stephen L Hickox

Braun C Brennecke

Evan J Kausalik

Steven P Taylor

John D Mayer

Hugo Bernardino Da Silva

Tyler C Tamburlin

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 non-transitory computer-readable medium may include computer-executable instructions that, when executed, cause a processor to collect a portion of data associated with an asset from one or more sources based on a request received from a digital representation associated with the asset. The digital representation may perform a first set of simulations related to one or more operations of the asset over time. The processor may then generate a plurality of aligned datasets based the portion of the data, the one or more sources, and an identity of the asset. The processor may also aggregate the plurality of aligned datasets into a single dataset and transmit the single dataset to the digital representation to perform a second set of simulations based on the single dataset.

Systems and methods for industrial information solutions and connected microservices

A system may include a processor and a memory including computer-executable code that, when executed by the processor, causes the processor to receive a service request from a first device and to transmit a workflow dataset associated with an industrial automation device to the first device and the second device. The service request may cause a computing system to communicatively couple the first device to a second device. The workflow dataset may include one or more instructions associated with one or more operations for the industrial automation device and one or more virtual objects associated with the one or more instructions and the industrial automation device. The memory may include computer-executable code that, when executed by the processor, causes the processor to receive an input to the image data from the second device and to transmit the one or more additional visualizations to the first device for display.

Remote support via visualizations of instructional procedures

A non-transitory computer-readable medium includes instructions that, when executed, cause one or more processors of a first electronic device to receive data generated by a plurality of components of an industrial automation system and characterize one or more portions of the data by applying metadata to the one or more portions of the data. The metadata enables a second electronic device receiving the data to determine one or more contexts of the one or more portions of the data. Furthermore, the computer-executable instructions, when executed, cause the one or more processors to rearrange an order of the one or more portions of the data and cause the characterized and rearranged data to be sent to the second electronic device.

Common data pipeline for sharing data associated with industrial automation systems

A non-transitory computer-readable medium includes instructions that, when executed, cause one or more processors to perform operations. The operations include receiving a first request to access a digital representation that is assigned to an asset of an industrial automation system and includes code specific to operating, maintaining, or diagnosing the asset. The operations also include verifying a security access for the first request, providing the computing device access to the digital representation, receiving an input to modify the code from the computing device and, performing one or more simulations based on the modified code by utilizing the digital representation. Additionally, the operations include sending one or more simulation results to the computing device, receiving, from the computing device, a second request for pushing the modified code to the asset, and in response to receiving the second request, causing the modified code to be sent to the asset.

Systems and methods for data lifecycle management with code content optimization and servicing

A system may include a processor and a memory. The memory may include computer-executable code that, when executed by the processor, causes the processor to retrieve a workflow dataset from a database based on a query input associated with an industrial automation device. The workflow dataset may include an instruction associated with one or more operations for the industrial automation device and a virtual object associated with the one or more instructions and the industrial automation device. The memory may include computer-executable code that, when executed by the processor, causes the processor to transmit a first portion of the workflow dataset to a computing device corresponding to a first instruction. The memory may include computer-executable code that, when executed by the processor, causes the processor to transmit a second portion of the workflow dataset to the computing device in response to determining that the first instruction is completed.

Generating visualizations for instructional procedures

A method may include receiving a query input indicative of an identity of an industrial automation device and searching a database based on the query input to identify one or more workflow datasets corresponding to the identity of the industrial automation device. Each of the one or more workflow datasets may include one or more instructions associated with one or more operations of the industrial automation device and one or more virtual objects associated with the one or more instructions. The method may also include displaying one or more visualizations representative of the one or more workflow datasets via an electronic display of a computing device. Each of the one or more visualizations may receive an input that causes the computing device to receive at least a portion of a respective workflow dataset.

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Milwaukee, WI, United States of America

Abhishek Mehrotra