Rockwell Automation Technologies Incorporated

Chirayu S Shah

Bijan Sayyarrodsari

Stephen C Briant

Ryan P Dunn

Manuel Sukerman

Cyril Perducat

Achim Thomsen

Anoop Mohan

Arvind Vijayanagar Rao

Christopher Wayne Como

Rainer Hessmer

Bruce T McCleave, Jr

Michael John Pantaleano

Nathaniel S Sandler

Jan Pingel

James M Teal

Matthew C Giordano

Taylor Mathewson

Nabin Acharya

Todd M Smith

Bruce T Mccleave, Jr

Meraj Imani

Stuart Fergusson

Kermit George Peters

Sneha R Jadhav

Jennifer M Kite

Neville Patrick Van Der Merwe

Heiko Ott

Adrian Dams

Bruce T Mccleave

James Michael Teal

Kermit George Peter

Bruce Mccleave Jr

Industrial automation data staging and transformation (e.g., using a computerized tool) is enabled. For example, a system can comprise: a memory that stores executable components, and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a model condition component that determines whether a defined data connection condition, applicable to an industrial asset model, has been satisfied, and a device interface component that in response to the defined data connection condition being determined to be satisfied, determines an industrial data source that comprises industrial data associated with the defined data connection condition, sends a request to the industrial data source determined to comprise the industrial data to provide the industrial data in a second data format determined to be compatible with the industrial asset model, and retrieves the industrial data from the industrial data source, wherein the industrial data has been converted by the industrial data source from a first data format to the second data format.

Industrial automation data staging and transformation

A cloud-based edge-as-as-service (EaaS) system allows edge gateways to be easily configured and deployed on the cloud for collection, contextualization, and egress of industrial data to downstream applications, including analytic applications, work order management systems, or visualization systems. The EaaS system uses predefined device profiles to automatically discover relevant data items on plant floor devices and present these data items to a user. Model configuration interfaces served by the EaaS system allow the user to map selected data items to predefined models for organizing or contextualizing the selected data, and for egressing the contextualized data to the target applications. These model configurations can be deployed on the cloud platform as edge gateways that use the resulting information models to collect and contextualize relevant items of device data during runtime and to export the modeled data to the target application.

Industrial automation data management as a service

An industrial gateway device supports interactive feature engineering tools that guide a user through an intuitive process for configuring data analytics for key performance indicators (KPIs) of interest. A feature engineering interface renders an interactive model view that displays available data points such that the data points are organized hierarchically according to plant, machine, machine property, or other elements. The user can select, from this model view, data points having an impact on the KPI of interest. The interface also allows the user to define an executable script that defines a mathematical relationship between the selected data points and the KPI. This configuration yields an output model that defines a reduced set of data points to be collected and analyzed, as well as an executable script for assessing a state of the KPI as a function of the reduced data point values.

Edge device feature engineering application

An industrial information hub (IIH) and an industrial development hub (IDH) serve as an industrial ecosystem platform where multiple participants can deliver repeatable and standardized services relevant to their core competencies. The IIH system is centered around the development of an ecosystem that creates and delivers value to users—including industrial enterprises, OEMs, system integrators, vendors, etc.—through the aggregation of digital content and domain expertise. The IIH system serves as a trusted information broker between the ecosystem and the OT environments of plant facilities, and provides a platform for connecting assets, contextualizing asset data and providing secure access to the ecosystem. As part of this ecosystem, the IIH system uses a secure remote access architecture to allow users to remotely access data on their plant floor assets via a virtual private network connection.

Digital engineering secure remote access

An industrial information hub (IIH) serves as a single industrial ecosystem platform where multiple participants can deliver repeatable and standardized services relevant to their core competencies. The IIH system can interface with a work order management system to facilitate automated creation and submission of work orders for maintenance tasks. To this end, the IIH system can monitor real-time data from industrial devices and identify conditions indicative of a performance issue requiring a maintenance action. When such a condition is identified, the IIH system can initiate creation of a work order in the work order management system for tracking and recording of the maintenance task.

Industrial machine monitoring path for computerized maintenance management system

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

Growing community of inventors

Milwaukee, WI, United States of America

Chirayu S Shah