Rockwell Automation Technologies Incorporated

Honeywell International Inc.

Jan Pingel

John Joseph Baier

Robert Joseph McGreevy

Bruce Gordon Fuller

Ian Edward Tooke

Kevin John Albert

Michael John Pantaleano

Jessica Lin Korpela

John Strohmenger

Matthew W Fordenwalt

Douglas B Weber

Stephen L Hickox

Micheal John Pantaleano

Rainer Hessmer

Matthew Burd

Chirayu S Shah

Matthew C Giordano

Todd M Smith

Damian Marshall

Kermit George Peters

Neville Patrick Van Der Merwe

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.

Backup of an industrial automation plant in the cloud

A method and apparatus for mapping measurement tags to assets. At least one memory is configured to store a plurality of tags. At least one processor is configured to parse a database of the plurality of tags to identify patterns of terms, wherein the plurality of tags include one or more terms and are related to measurements performed by an asset in an industrial process control and automation system. The processor is further configured to display the plurality of tags grouped by the identified patterns of terms. The processor is further configured to receive an input to map the tag related to the asset based on the identified patterns of terms. The processor is further configured to map the tag to the asset based on the input.

Method and system for contextualizing process data

A visualization system for creating, displaying and animating overview and detail heat map displays for industrial automation. The visualization system connects the heat map displays to an interface component providing manual or automatic input data from an industrial process or an archive of historical industrial process input data. The animated heat map displays providing quality, prognostic or diagnostic information.

Visualization employing heat maps to convey quality, prognostics, or diagnostics information

A visualization system utilizing pre-configured visualization profiles and templates to reduce the level of effort and time required to commission an industrial automation visualization system. The preconfigured visualization profiles and templates include graphic displays, informational reports and data sampling and collection strategies appropriate for the specific sector of manufacturing or industry.

Visualization profiles and templates for auto-configuration of industrial automation systems

A distributed and scalable data historian framework is provided that allows historian functionality to be efficiently incorporated at various levels of an industrial enterprise. The framework includes a historian data interface system that provides a single interface and common protocol for configuring, managing, and viewing historian data located throughout a network of historian distributed across the industrial enterprise. The historian data interface system leverages a data model that models the enterprise and sources of historian data to facilitate fast and efficient retrieval of desired historian data. By unifying the distributed historians under a common framework, the data model can facilitate enterprise-level management of historian data collection and storage.

Integrated and scalable architecture for accessing and delivering data

A visualization system integrated with an enterprise manufacturing intelligence (EMI) system utilizing preconfigured EMI data models, workflow reports and process event notifications to optimize a manufacturing process. The visualization system and the EMI system exchange data and information providing both systems with a broader process view than either system has independently. The visualization system can specifically target information and action requests to different classes of manufacturing personnel such as operators and engineers. Additionally, the visualization system maintains an audit log of all production identities, raw material usage, and requested corrective actions.

Industrial automation interfaces integrated with enterprise manufacturing intelligence (EMI) systems

A visualization system utilizing preconfigured overlay models and data models to create overlay displays representing different views of the same data or a single view of different data. The visualization system provides for collecting and sharing overlay displays and data sets with other communicatively connected visualization systems. The overlays can be automatically created by the visualization system and can be presented in different formats such as a three-dimensional or a translucent display.

Growing community of inventors

New Berlin, WI, United States of America

Jan Pingel