Rockwell Automation Technologies Incorporated

Noel Henderson

Stephen C Briant

Joachim Thomsen

Manuel Sukerman

Sujeet Chand

Juergen K Weinhofer

Scott A Miller

Bruce E Hammon

David Christopher Mazur

Scott N Sandler

Brian Fast

Daniel Baliey Seger

Steven C Briant

David Dale Brandt

Rob Alan Entzminger

Philip John Kaufman

Steven A Lombardi

Scott Duane Day

Linglai Li

Guolin Zhang

David Bradly Berman

Bruce K Venne

Richard Arthur Morgan

Phillip R Bush

Fred M Discenzo

Sean Charles Schmelzer

Robert H Prashad

Le Roy G Howe

Jeffrey Schmelebeck

Rob Allen Entzminger

An industrial data presentation system leverages structured data types defined on industrial devices to generate and deliver meaningful presentations of industrial data. Industrial devices are configured to support structured data types referred to as basic information data types (BIDTs) comprising a finite set of structured information data types, including a rate data type, a state data type, an odometer data type, and an event data type. The BIDTs can be referenced by both automation models of an industrial asset and non-automation models of the asset, allowing data points of both types of models to be easily linked using a common data source nomenclature.

Industrial automation information contextualization method and system

A cloud-based industrial data services (IDS) architecture leverage smart tags, asset models, and data service applications to facilitate secure transaction and exchange of contextualized factory data between different parties as part of a combined technology and commerce platform, or to perform provide asset owners with insights into operation of their industrial assets. The IDS platform supports a set of services that connect providers of smart industrial devices to plant floor and systems owned by the end users of these devices. The cloud-based platform allows asset providers to publish data service applications for purchase and use by end users of their assets, and allows equipment owners to control remote access to selected sets of their industrial data via the cloud platform.

Industrial data services platform

Provided herein are systems, methods, and software for facilitating message sessions. In one implementation, a method for building a type-based reporting model associated with an industrial automation environment includes interrogating a system control to acquire a data structure programmed therein, wherein the data structure includes properties of a component of the industrial automation environment. The method also includes correlating the data structure to a type package object, and generating a model object based on the correlation of the data structure to the type package object, the model object configured to visually display the properties of the component on a report.

Unique UDTs to exploit the power of the connected enterprise

An industrial data presentation system leverages structured data types defined on industrial devices to generate and deliver meaningful presentations of industrial data. Industrial devices are configured to support structured data types referred to as basic information data types (BIDTs) comprising a finite set of structured information data types, including a rate data type, a state data type, an odometer data type, and an event data type. The BIDTs are discoverable by a gateway device on which models of industrial assets can be defined, where the models reference the BIDTs defined on the industrial devices. The gateway device can retrieve industrial data from the data tags, formatted in accordance with the data types and associated user-defined metadata specific to the respective data types. The gateway device or a separate application server system can then generate graphical presentations of the industrial data in accordance with the model and the metadata.

Provided herein are systems, methods, and software for calculating energy effectiveness in an industrial automation system. In one implementation, a computing system is directed to at least acquire production energy information indicating the amount of energy used by a machine during a processing period to process one or more parts and acquire process energy information indicating the sum of energy used by the machine during the processing period to process the one or more parts and to not process any parts. The computing system also acquires a total number of parts expected to be processed during the processing period and a total number of good parts processed during the processing period. An overall equipment energy effectiveness is calculated based on a ratio of the production energy information to the process energy information and based on a ratio of the total number of good parts to the total number of parts.

Energy key performance indicators for the industrial marketplace

An energy monitoring system includes a memory storing instructions to execute an energy modeling technique and processing circuitry for executing the instructions to operate the energy modeling technique. The energy modeling technique includes receiving energy data from a plurality of segments representative of one or more logical subgroups. The energy modeling technique includes categorizing the energy data of the logical subgroups into a plurality of segments. The energy modeling technique includes organizing the plurality of segments into a plurality of state-based hierarchical levels. The energy modeling technique includes calculating energy usage and factors associated with the plurality of state-based hierarchical levels via an energy model. The energy modeling technique includes outputting a visualization representative of the energy data corresponding to each of the segments to a monitoring and control system, resulting in a graphical representation accessible by a user-viewable screen.

State-based hierarchy energy modeling

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Milton, FL, United States of America

Noel Henderson