Rockwell Automation Technologies Incorporated

Joachim Thomsen

Andrew R Stump

Norman Andrew Weatherhead

Haithem Mansouri

Axel Rodriguez

Noel Henderson

Sujeet Chand

Stephen C Briant

Manuel Sukerman

Robert Guenther

Brian Fast

Michael D Kalan

Christopher E Stanek

Juergen K Weinhofer

Scott A Miller

Robert J Miklosovic

Lorenzo P Majewski

Scott N Sandler

Daniel S DeYoung

Daniel Baliey Seger

Bruce E Hammon

Stephen P Proctor

Phillip F Pemberton

Danie Beckett

Bijan Sayyarrodsari

Robert H Schmidt

Mark A Chaffee

Douglas W Reid

Jonathan D Hoffman

Gerry M Nagel

Aderiano M Da Silva

Jon P Vanderpas

Steven C Briant

Vincent Bourrelly

Douglas M Reid

A smart gateway platform leverages pre-defined industrial expertise to identify limited subsets of available industrial data deemed relevant to a desired business objective, and to collect and model this relevant data to apply useful constraints on subsequent artificial intelligence or machine learning analytics applied to the data. This approach can reduce the data space to which AI analytics are applied, and assist data analytic systems to more quickly derive valuable insights and business outcomes. In some embodiments, the smart gateway platform can operate within the context of a multi-level industrial analytic system, feeding pre-modeled data to one or more AI or machine learning systems executing on one or more different levels of an industrial enterprise.

Smart gateway platform for industrial internet of things

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

Industrial smart data tags conforming to structured data types serve as the basis for creating a digital twin of an industrial asset. The digital twin can comprise an automation model and a mechanical model or other type of non-automation model, both of which reference the smart tags in connection with digitally modeling the industrial asset. The structured data topology offered by the smart tags allows the digital twin to be readily interfaced with artificial intelligence (AI) systems. AI analysis can leverage the smart tags to discover new relationships between key performance indicators and other variables of the asset and encode these relationships in the smart tags themselves. These enhanced smart tags can also be leveraged to perform AI-based validation the digital twin. Additional contextualization provided by the enhanced smart tags can simplify AI analysis and assist in quickly converging on desired analytic results.

AI extensions and intelligent model validation for an industrial digital twin

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.

Industrial automation information contextualization method and system

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.

A system and method for online simulation of a controlled machine or process utilizes a simplified model of the system dynamics and may be used with hardware in the loop to evaluate performance of the controlled system or with software in the loop to perform commissioning of the control program prior to completion of the mechanical installation. The simplified model includes dominant order dynamics of the controlled system such as the inertia of the system and a damping factor. Further, the online simulation is scheduled to execute at an update rate slower than the update rate of the control loops within the motor drive. The simplified model and reduced update rate reduce the computational burden on the processor such that the simulation may be performed either on the industrial controller or on the motor drive.

Method and apparatus for online simulation of complex motion systems

A system and method for real-time detection of anomalies in a motor drive includes a controller receiving one or more signals corresponding to real-time operation of a controlled system. The controller samples the real-time signal during operation of the controlled system and maintains a moving window of the sampled data. A signature of the sampled data within the moving window is then generated. Each signature corresponds to operation of the controlled system within the period of time defined by the moving window. An identifier and a number of occurrences of each signature may be stored with the signature. An initial table of expected signatures may be generated, for example, by executing a training, or learning, period within the control system. The controller compares each real-time signature against the table of expected signatures to detect the occurrence of an anomaly.

Method and system for real-time anomaly detection in a motor drive

The disclosed subject matter comprises a design management component that facilitates managing and storing information, including respective customized information of respective entities and/or relating to objects, projects, controllers, or industrial automation systems within a project file or controller. The design management component facilitates enabling custom data, including custom metadata, to be injected by object into a project file or in a controller associated with the project file. The design management component operates with a data management component that can allow respective entities to view, edit, or delete their respective data on objects associated with a project file or controller in accordance with their respective rules. The design management component facilitates desired library management, version management, virtualization of a system for emulation and testing, data exchange between application, and application development and management in relation to controllers, devices, or components, in connection with control of industrial automation systems.

Custom properties in an application environment

Certain embodiments of the present invention provide techniques for representing components of an industrial system with a visualization tool, in accordance with a physical layout of the industrial system. Other embodiments of the present invention provide techniques for simulating the representations of the components of the industrial system with a simulation engine. In particular, in such embodiments, the utilization of these representations is optimized through an operator interface, and graphical indicia of the utilization are displayed. In addition, the graphical indicia may further comprise a representation of the normalized utilization for each representation. In yet other embodiments, the present invention provides techniques for auto-calibrating the representations of the components of the industrial system based on information received during operation of the industrial system.

Conveyor visualization system and method

Content management includes populating a library with modular objects and metadata associated with the modular objects. In response to a query, the library can be searched based in part on the metadata. The query can relate to implementation of an industrial process. One or more modular objects in the library can be identified as satisfying the query. A result of the query can be output and the output can include the identified modular objects and the respective metadata associated with the identified modular objects. The metadata can be anything known about the object that might not be accessible at runtime control.

Content management

Integration of workflow and library modules

Growing community of inventors

Singapore, Singapore

Joachim Thomsen