Rockwell Automation Technologies Incorporated

Michael John Pantaleano

Douglas J Reichard

Ryan Cahalane

Jonathan D Walter

Scott N Sandler

Ronald Eric Bliss

Jessica Lin Korpela

Sujeet Chand

Bruce T McCleave, Jr

Christopher Wayne Como

Kyle K Reissner

Edward Anthony Gray

Jan Pingel

John Joseph Baier

Robert Joseph McGreevy

Bruce Gordon Fuller

Ian Edward Tooke

Kevin John Albert

Rainer Hessmer

David W Farchmin

Joseph A Harkulich

Douglas C Lawson

David Alan Vasko

Subbian Govindaraj

Sharon M Billi-Duran

Bijan Sayyarrodsari

Juergen K Weinhofer

Eugene Liberman

Kyle A Crum

David Wayne Comeau

Kenneth Scott Plache

Edward Alan Hill

John Dyck

Michael Robert Keller

Anthony Carrara

Andrew Wilber

Axel Rodriguez

Mohit Singhai

Jonathan M Wise

Petr Ptacek

Andrew J Ellis

Sharon M Billi

Nancy Lynn Burnham

Ka H Lin

Matthew C Giordano

Chirayu S Shah

Ka-Hing Lin

David Robert Curry

Todd M Smith

George K Peters

Kermit George Peters

Neville Patrick Van Der Merwe

Nancy Lynne Burnham

Joshua Searles

David P Rapini

Matthew G White

Daniel A Vanbrocklin

Brian Alan Porter

Jason W Malzahn

Alex G Castle

Guangwen Sun

Jerry L Foster

Andrew James Ellis

Jürgen Weinhofer

Mohit Shinghai

Bruce T Mccleave

Brian A Porter

Daniel B Seger

Jürgen K Weinhofer

A multi-tenant, cloud-based Software-as-a-Service (SaaS) manufacturing platform offers a variety of industrial applications to end customers—including but not limited to MES, ERP, quality management, supply chain management, and customer relationship management (CRM)—and implements associated architectural features that address a number of issues relating to data sharing, security, scalability, and other concerns.

Multi-tenant database replication and sharding

An industrial data broker system receives contextualized industrial data from one or more industrial devices that support data modeling at the device level. The received industrial data is augmented with contextualization metadata that defines correlations between the data relevant to an analytical objective, and labels specifying analytic topics to which each data item is relevant. The broker system allows external systems, such as analytic systems, to subscribe to topics of interest, and streams a subset of contextualized device data relevant to the topic of interest to the external system for analysis.

Artificial intelligence channel for industrial automation

An industrial control programming development platform simplifies generation of an industrial control program and associated tag definitions by generating at least a portion of the control program and tag definitions based on analysis of digital engineering drawings of an automation system to be monitored and controlled. This drawing-based program generation includes creation and configuration of smart data tags that model and contextualize controller data at the device level for processing by higher level analytic systems. This device-level contextualization can be based in part on inferences drawn from the digital engineering drawings.

Industrial automation control program generation from computer-aided design

An industrial device supports device-level data modeling that pre-models data stored in the device with known relationships, correlations, key variable identifiers, and other such metadata to assist higher-level analytic systems to more quickly and accurately converge to actionable insights relative to a defined business or analytic objective. Data at the device level can be modeled according to modeling templates stored on the device that define relationships between items of device data for respective analytic goals (e.g., improvement of product quality, maximizing product throughput, optimizing energy consumption, etc.). This device-level modeling data can be provided to higher level systems together with their corresponding data tag values to high level analytic systems, which discovers insights into an industrial process or machine based on analysis of the data and its modeling data.

Contextualization of industrial data at the device level

A cloud gateway for coupling an industrial system to a cloud platform is provided. The cloud gateway collects data from one or more industrial controllers, meters, sensors, or other devices comprising an industrial automation system. The cloud gateway optionally performs additional transformations on the data to add context, summarize, filter, reformat, and/or encrypt the data. The cloud gateway then sends data to a cloud platform for use by one or more cloud-based applications or services. The cloud gateway can facilitate cloud-based data collection from both fixed-location and mobile industrial systems. The cloud gateway can also support store-and-forward logic, allowing industrial data to be temporarily stored in local storage in the event that communication between the cloud gateway and the cloud platform is disrupted.

Cloud gateway for industrial automation information and control systems

A conversation interface system provides remote access to manufacturing operation information using plain language message exchange. A cloud-based conversation interface service is exposed to an instant messaging application, and receives plain language queries from via the instant messaging application's interface requesting information relating to one or more industrial systems. The cloud-based system synchronizes the queries to one or more on-premise conversation interface agent devices residing at one or more plant facilities. The on-premise agent devices translate the queries and apply the translated queries to local sources of manufacturing operation data. The on-premise agent devices then generate and return response messages based on the retrieved information, and the cloud-based system directs the response messages the originators of the queries via the instant messaging interface.

Conversation interface agent for manufacturing operation information

Systems, methods, and software to facilitate visualization of an application associated with an industrial automation environment are disclosed herein. In at least one implementation, a graphical user interface to the application having a plurality of key performance indicators (KPIs) is rendered. A selection of at least one KPI of the plurality of KPIs is received along with instructions to link the at least one KPI to a home screen of an operating system. Dynamic KPI data associated with the at least one KPI is fed to the operating system for visualization of the at least one KPI on the home screen.

Mobile computing application for industrial automation manufacturing data

A cloud-based operator interface system is provided that runs as a cloud service on a cloud platform. The cloud-based operator interface system collects industrial data from one or more industrial systems via respective cloud gateway devices. A set of predefined operator interface screens are stored on cloud storage associated with the operator interface system, and delivered to authorized Internet-capable client devices upon request. The industrial data received from the cloud gateways can be delivered to the client devices from the cloud platform via the operator interface screens. Additional cloud-side services can correlate and analyzes the industrial data on the cloud platform to facilitate additional reporting, alarming, and notification features.

Cloud-based operator interface for industrial automation

The subject matter disclosed herein relates generally to industrial automation systems, and, more particularly, to collecting video streams from a variety of video devices in an industrial environment, identifying and analyzing potential problems in the industrial environment using the video streams, and presenting the video streams and data associated with the potential problem to appropriate recipients.

Analyzing video streams in an industrial environment to identify potential problems and select recipients for a display of video streams related to the potential problems

A multi-platform industrial search system facilitates indexing and searching of plant-wide data residing on multiple different data platforms. The industrial search system automatically inventories industrial devices and other data sources located throughout a plant, and identifies available data items on each data source. The search system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The federated data model records references to data items found on different types of data sources, including but not limited to industrial controller programs, human-machine interface applications, data historians, device documentation stores, inventory tracking systems, and other such data sources. The search system can also initiate automated searches of the federated data model in response to detected performance issues and deliver notifications and contextual information to plant personnel.

Dynamic search engine for an industrial environment

A layered industrial analytics architecture enables the flow of information from intelligent assets into tools and engines that perform analytics and enable decision-making in substantially real-time. The analytics architecture comprises analytic nodes that are distributed across multiple layers of an industrial enterprise, and includes system features that optimize movement of data across this layered architecture. Each analytic node includes base architectural constructs that host various analytic, data acquisition, and storage elements. These base constructs can operate autonomously, or in conjunction with other instances of base constructs or other elements of the control system. The system design uses a multi-platform compatible implementation that allows the base elements to be deployed on various different computing platforms.

Scalable analytics architecture for automation control systems

An industrial data indexing system facilitates discovery and indexing of plant-wide data residing on multiple different data platforms. The indexing system automatically inventories industrial devices and other data sources located throughout a plant, and identifies available data items on each data source. The indexing system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The federated data model records references to data items found on different types of data sources, including but not limited to industrial controller programs, human-machine interface applications, data historians, device documentation stores, inventory tracking systems, and other such data sources. The search system also caches selected portions of the data model to a user's personal device to allow these portion of the model to be accessed locally on the user's device without being online with the higher level indexing system.

Selective online and offline access to searchable industrial automation data

A multi-platform industrial search and notification system performs automated and manually initiate information searches across multiple disparate industrial data platforms. The search system is built on a search platform that unifies plant-wide control system information from multiple diverse sources under a common namespace, or federated data model. The system can monitor this federated data model for conditions that may warrant attention by plant personnel, and deliver proactive notifications and operational data to selected users via their personal devices. The system can customize presentation of this data based on the user's role, location, and/or other contextual information. To this end, the system can automatically generate user-specific and context-specific dashboards, widgets, or other visualizations, and render these custom visualizations to the user at appropriate times.

Automated creation of industrial dashboards and widgets

Growing community of inventors

Willoughby, OH, United States of America

Michael John Pantaleano