INDUSTRIAL CONTROLLER HAVING AI-ENABLED MULTICORE ARCHITECTURE

    公开(公告)号:US20240402679A1

    公开(公告)日:2024-12-05

    申请号:US18327355

    申请日:2023-06-01

    Abstract: An industrial controller supports deterministic execution of control programs (e.g., ladder logic, function block diagrams, structured text, or other such control code) and is also capable of executing non-deterministic execution cycles, including mathematical optimization algorithms—in which a systematic search in a solution space is performed to identify a desired solution—or machine learning algorithms, either of which can be used by the controller to dynamically update the deterministic control program or code based on current or predicted states of the automation system being controlled by the controller.

    SYSTEMS AND METHODS FOR MONITORING AND ADJUSTING OPERATION OF A MOVER SYSTEM

    公开(公告)号:US20240094718A1

    公开(公告)日:2024-03-21

    申请号:US17947779

    申请日:2022-09-19

    CPC classification number: G05B19/4189 G05B2219/35499 G05B2219/45054

    Abstract: A non-transitory computer-readable medium includes instructions that, when executed by processing circuitry, are configured to cause the processing circuitry to receive a first dataset associated with a mover system having a track and a plurality of mover assemblies independently movable along the track, identify a subset of the first dataset associated with a normal operating state of the mover system based on state data associated with the mover system, receive a second dataset associated with the mover system after receiving the first dataset and having a first set of differences from the subset of the first dataset, determine whether the second dataset is indicative of an anomaly state of the mover system based on a relationship between an anomaly signature dataset and the second dataset, and adjusting operation of the mover system in response to determining that the second dataset corresponds to the anomaly signature dataset.

    DEVICE CONTROL USING PROCESSED SENSOR DATA CORRESPONDING TO UNEXPECTED OPERATIONS

    公开(公告)号:US20240019847A1

    公开(公告)日:2024-01-18

    申请号:US18366426

    申请日:2023-08-07

    CPC classification number: G05B19/4155 G05B2219/31368

    Abstract: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, cause a processor to perform operations including receiving a first dataset from a first automation component, the first dataset corresponds to raw data acquired by a first sensor; receiving a second dataset from a second automation component, the second dataset corresponds to raw data acquired by a second sensor; receiving data indicating an expected operation related to operations of an industrial automation system including the first and second automation components; determining a signature based on the first and second datasets and the data indicating the expected operation, wherein the signature indicates an unexpected operation as compared to the expected operation; performing a root cause analysis using the signature to determine a relationship indicating a first set of changes of the first dataset corresponding to a second set of changes in the data indicating the expected operation.

    EDGE DEVICE FEATURE ENGINEERING APPLICATION
    14.
    发明公开

    公开(公告)号:US20230280723A1

    公开(公告)日:2023-09-07

    申请号:US18299142

    申请日:2023-04-12

    CPC classification number: G05B19/4155 G05B2219/31449

    Abstract: 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.

    SYSTEMS AND METHODS FOR CONTROLLING INDUSTRIAL DEVICES BASED ON MODELED TARGET VARIABLES

    公开(公告)号:US20200103878A1

    公开(公告)日:2020-04-02

    申请号:US16146664

    申请日:2018-09-28

    Abstract: An industrial automation system may include an automation device and a control system communicatively coupled to the automation device. The control system may include a first module of a number of modules, such that the first module may receive an indication of a target variable associated with the industrial automation device. The first module may then receive parameters associated with the target variable, identify a portion of data points associated with controlling the target variable with respect to the parameters, generate a model of each data point of the portion over time with respect to the parameters based on the data points, determine functions associated with the model. The functions represent one or more relationships between the each data point of the portion with respect to controlling the target variable. The first module may then adjust one or more operations of the automation device based on the functions.

    System and Method to Monitor and Balance Wear in an Independent Cart System

    公开(公告)号:US20250145374A1

    公开(公告)日:2025-05-08

    申请号:US18502050

    申请日:2023-11-05

    Abstract: A system for distributing wear on multiple movers in an independent cart system includes a machine learning model executing on a processor. The machine learning model may include models of operation for each of the movers, and the machine learning model is operative to receive multiple inputs for each of the movers. Each of the inputs corresponds to an operating condition for one of the movers as the mover travels along a track for the independent cart system. Each of the inputs are received for each of the movers over multiple runs along the track, and the inputs received generate a training set of data for the movers. A weighting value is determined for each of the movers as a function of the training set of data, where the weighting value corresponds to a level of wear present on each of the movers.

    INDUSTRIAL ARTIFICIAL INTELLIGENCE DATA NAVIGATORS

    公开(公告)号:US20250044765A1

    公开(公告)日:2025-02-06

    申请号:US18363154

    申请日:2023-08-01

    Abstract: Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth/processing, and expedited system optimization.

    Device control using processed sensor data corresponding to unexpected operations

    公开(公告)号:US12204312B2

    公开(公告)日:2025-01-21

    申请号:US18366426

    申请日:2023-08-07

    Abstract: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, cause a processor to perform operations including receiving a first dataset from a first automation component, the first dataset corresponds to raw data acquired by a first sensor; receiving a second dataset from a second automation component, the second dataset corresponds to raw data acquired by a second sensor; receiving data indicating an expected operation related to operations of an industrial automation system including the first and second automation components; determining a signature based on the first and second datasets and the data indicating the expected operation, wherein the signature indicates an unexpected operation as compared to the expected operation; performing a root cause analysis using the signature to determine a relationship indicating a first set of changes of the first dataset corresponding to a second set of changes in the data indicating the expected operation.

    Product lifecycle management
    19.
    发明授权

    公开(公告)号:US12147944B2

    公开(公告)日:2024-11-19

    申请号:US17469397

    申请日:2021-09-08

    Abstract: A method for correlating data from different sensors for product lifecycle management includes receiving sensor information from an additional sensor of a plurality of sensors of an industrial operation. The additional sensor is different from component sensors used for functionality of a component of the industrial operation. Sensor information from the additional sensor monitors conditions of a portion of the industrial operation different from sensor information of the component sensors used for the functionality of the component. The method includes deriving, using the sensor information, a correlation between an operational parameter of the component and sensor information of the additional sensor. The operational parameter is related to a predicted operational lifetime of the component. The method includes identifying an abnormal operating condition of the component based on a comparison between additional sensor information from the additional sensor and the operational parameter, and sending an alert with the abnormal operating condition.

    Aggregate and correlate data from different types of sensors

    公开(公告)号:US11830341B2

    公开(公告)日:2023-11-28

    申请号:US17406309

    申请日:2021-08-19

    CPC classification number: G08B21/182 G01M99/005 G05B19/4155 G05B2219/31449

    Abstract: A method for correlating data from sensors includes receiving sensor information from a plurality of sensors of an industrial operation. Sensor information from component sensors is used for functionality of a component of the industrial operation and sensor information from additional sensors monitor conditions of a portion of the industrial operation different from the component. The method includes deriving, using the sensor information, correlations between component sensors and additional sensors and deriving a baseline signature from the sensor information and the correlations. The baseline signature encompasses a range of normal operating conditions. The method includes identifying an abnormal operating condition based on a comparison between additional sensor information and the baseline signature. The sensor information is used differently for functionality of the component than for deriving the correlations and baseline signature and identifying the abnormal operating condition. The method includes sending an alert with the abnormal operating condition.

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