Rockwell Automation Technologies Incorporated

Accenture Global Solutions Limited

Heureka, Inc.

Bradford Henry Hegrat

Jessica Lin Korpela

Rainer Hessmer

Juan Asenjo

Joseph A Harkulich

Edward Alan Hill

John Strohmenger

John Dyck

Jenifer Rydberg Wright

Stephen Nawalaniec

Sal Conti

Salvatore T Conti

Vikram Desai

Martin Mangan, Iii

Benjamin James Lipczynski

Sadhana Joliet

Douglas Ray Wylie

Daniel Carl

Ronald K Copfer

Nathaniel H Latessa

Sadhana Joilet

A cloud-based simulation generation service collects industrial data from multiple industrial customers for storage and analysis on a cloud platform. The service employs a simulation generator component that analyzes data to facilitate generating a simulation model that simulates an industrial automation system, including simulating or emulating industrial devices, industrial processes, other industrial assets, or network-related assets or devices, and their respective interrelationships with each other. The simulation generator component also analyzes modification data to facilitate generating a modified simulation model that simulates the industrial automation system based on the modification. The simulation generator component performs operation simulations using the simulation model or modified simulation model to facilitate determining whether making the modification is appropriate, determining or predicting performance of a modified industrial automation system, determining compatibility of a modification with an industrial automation system, or determining or predicting performance of the industrial automation system when processing a work order.

Using cloud-based data for industrial simulation

A device may receive historical operational technology data and historical information technology data associated with historical systems and may train a machine learning model with the historical operational technology data and the historical information technology data to generate a trained machine learning model. The device may receive real-time operational technology data and real-time information technology data associated with a system and may process the real-time operational technology data and the real-time information technology data, with the trained machine learning model, to determine a trust score and a risk score for an event or set of events associated with the real-time operational technology data and the real-time information technology data. The device may perform one or more actions based on the trust score and the risk score.

Utilizing a machine learning model to determine real-time security intelligence based on operational technology data and information technology data

A cloud-based performance enhancement service captures and collects data relating to interactions of users with industrial automation systems of multiple industrial customers for storage and analysis on a cloud platform. The service employs a performance enhancement component that analyzes the data to facilitate determining correlations between certain user interactions and favorable performance of an industrial automation system, determining user interactions that are less favorable or unsafe, determining alternative actions that a user can take to achieve a same or similar preferred operational result, generating recommendations relating to the alternative actions, determining or designing components or techniques that can automate a preferred user action, determining improved user assignments in connection with the industrial automation system, and/or generating training modules or presentations based on preferred user actions that can be used to train users to more efficiently interact with an industrial automation system to achieve improved system performance.

Using cloud-based data for industrial automation system training

System and methods are provided for identifying, searching, collecting, locking, executing deleting, comparing and/or analyzing data from a plurality of computer devices and environments from a centralized interface. The endpoint computer devices utilize an agent to index data contained on each device and that allows for a distributed action model using simple or advanced analytics by authenticated users. The agent can be embedded in an integrated circuit of the endpoint computing device or otherwise stored in permanent read only memory (i.e., firmware). The system allows for one or more users to conduct actions via device indexes utilizing a centralized computing device for comparison and analyzation purposes.

Remote processing of memory and files residing on endpoint computing devices from a centralized device

A cloud-based virtualization generation service collects industrial-automation-system-related data from multiple industrial automation systems of multiple industrial customers for storage and analysis on a cloud platform. A virtualization management component analyzes the data and generates a virtualized industrial automation system of the industrial automation system based on the analysis results. The virtualization management component updates the virtualized industrial automation system based on operation of, and user interactions with, the industrial automation system. The virtualization management component receives user interactions with the virtualized industrial automation system to facilitate remotely interacting with and/or controlling the industrial automation system and/or generates corresponding control signals that it sends to the industrial automation system to facilitate controlling operation of the industrial automation system. The virtualization management component also customizes a user's view of the virtualized industrial automation system based on user's role, authorization, or location.

Using cloud-based data for virtualization of an industrial machine environment

Cloud-aware industrial devices feed robust sets of data to a cloud-based data analyzer that executes as a service in a cloud platform. In addition to industrial data generated or collected by the industrial devices, the devices can provide device profile information to the cloud-based analyzer that identifies the device and relevant configuration information. The industrial devices can also provide customer data identifying an owner of the industrial devices, contact information for the owner, active service contracts, etc. The cloud-based data analyzer leverages this information to perform a variety of custom analytics on the data and generate reports or notifications catered to the particular industrial assets' optimal performance and business goals of the owner's industrial enterprise, as well as perform real-time decision making and control.

Industrial data analytics in a cloud platform

A cloud-based virtualization generation service collects industrial data from multiple industrial automation systems of multiple industrial customers for storage and analysis on a cloud platform. A virtualization management component (VMC) generates a virtualized industrial automation system of an industrial automation system based on data analysis results. The VMC facilitates remotely controlling the industrial automation system based on user interactions with the virtualized industrial automation system, and updates the virtualized industrial automation system based on collected data relating to the industrial automation system. The VMC customizes a user's view of the virtualized industrial automation system based on a user's role, authorization, location, or preferences, wherein different views of the virtualized industrial automation system with different data overlays are presented on different communication devices of different users. The VMC enables a user to filter data of a virtualized view and share information, including virtual notes, with other users.

Using cloud-based data for virtualization of an industrial automation environment with information overlays

An infrastructure deployment platform may receive configuration data relating to a plurality of devices included as components of a system, or a system of systems. The infrastructure deployment platform may process the configuration data, and may determine contextual information concerning the plurality of devices based on processing the configuration data. The contextual information may identify communicative relationships or associations between the plurality of devices. The infrastructure deployment platform may define an organizational structure of a network for the plurality of devices. The organizational structure may constrain communications between the plurality of devices based on the communicative relationships or associations. The infrastructure deployment platform may transmit the contextual information or data regarding the organizational structure to a network infrastructure controller device. The infrastructure deployment platform may perform an action to cause the network to be deployed based on the functional responsibility of the system and/or system of systems.

Dynamic, endpoint configuration-based deployment of network infrastructure

A cloud-based risk assessment service collects industrial data from multiple relevant and connected sources for storage and analysis on a cloud platform. The service analyzes gathered data from internal and external sources and customers across different industries to identify operational trends as a function of industry type, application type, equipment in use, device configurations, and other such variables. Based on the analysis, the risk assessment service identifies risk factors inherent in a customer's particular industrial enterprise. The cloud-based system generates a risk profile for the customer that identifies the determined risks and recommends risk aversion strategies based on the customer's specific profile, compared to industry standards, product information, internal business expectations, external regulatory bodies, and/or past performance. Risk profiles are tailored for both plant-level users and business-level users to provide intelligent strategies to improve performance and prevent avoidable losses.

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Montville, OH, United States of America

Bradford Henry Hegrat