Abstract: A method includes using at least one processor to detect that a tool coupled to an end effector of a robot having multiple joints is contacting a surface. The robot includes multiple joint motors configured to control multiple motions of the multiple joints. One or more control systems are configured to control each of the joint motors in a joint position mode. The method also includes identifying, via the at least one processor, a first joint of the multiple joints in response to detecting that the tool is contacting the surface. The method also includes sending, via the at least one processor, a command to at least one of the one or more control systems associated with a first joint motor of the multiple joint motors that corresponds to the first joint. The command is configured to cause the at least one of the one or more control systems to operate in a torque mode. The method also includes sending, via the at least one processor, a joint torque value to the at least one of the one or more control systems.

Abstract: A system may include sensor device comprising a sensor configured to measure sensor data indicating an operational parameter of industrial automation equipment associated with an industrial automation process. The system may also include communication circuitry configured to transmit the sensor data. Additionally, the system includes a processor configured to receive the sensor data. Further, the system includes a non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause the processor to perform operations including identifying an operational state of the industrial automation equipment based on the sensor data. The operations may also include determining a discrepancy between the sensor data and the operational state. Further, the operations may include modifying an operation of the processor from a first operational mode to a second operational mode of a plurality of operational based on the comparison.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to visualize machine learning model status in an industrial automation environment. In some examples, a machine learning component receives process inputs associated with industrial devices in the industrial automated environment. The machine learning component processes the inputs to generate machine learning outputs and transfers the machine learning outputs to influence one or more functions of the industrial devices. The machine learning component reports operational data characterizing the machine learning outputs. A Human Machine Interface (HMI) component displays a visualization of the machine learning component and receives the operational data from the machine learning component.

Abstract: A computing device for collecting and preserving data acquired from various devices in a data model with the respective context of acquired data. The computing device may provide a user interface to receive the context or information model associated with a dataset. By providing data with its context, different software platforms may synthesize or analyze the retrieved data more efficiently. Moreover, the computing device may include transaction conditions to define a workflow for transferring the datasets using data model associated with one or more datasets for transmission of data to a destination. The transaction conditions may detail a custom workflow for data communication through an industrial automation system using the data model.

Abstract: A power supply system includes modular power supply modules interconnected via a wire harness. The power supply system can be installed in one or more electrical cabinets in a manufacturing facility, for example, among other possible applications. The wire harness includes a fault bus and a synchronization bus, and the individual power supply modules detect and report faults as well as synchronize operation, such as pre-charging, via communication using the wire harness.

Abstract: A system may include a control system for controlling one or more operations of one or more industrial devices in an industrial system. The control system may receive streaming data comprising one or more visualizations representative of one or more live operational parameters associated with one or more industrial devices. The streaming data may include multiple image frames. The control system may also identify multiple datasets associated with the streaming data and generate multiple machine-readable images based on the multiple datasets. In addition, the control system may embed the multiple machine-readable images within the multiple image frames of the streaming data to generate updated streaming data and send the updated streaming data to a computing system that may extract the multiple machine-readable images from the updated streaming data.

Abstract: The present technology relates to health metrics corresponding to industrial automation devices and a user experience for configuring calculation devices to produce the health metrics. Health metrics of a device can be produced by obtaining performance metrics of the device and contextualizing the performance metrics based on contextualization information. The health metrics can be categorized based on applying rule sets to the health metrics. Contextualization and application of rule sets can be selectively performed by one or more calculation devices, such as one or more servers, industrial devices, user devices, or the like based on configuration settings. The calculation devices can obtain the performance metrics, operations, and rule sets to produce the health metrics for instantiation on a user interface.

Abstract: The present technology relates to health metrics corresponding to industrial automation devices and a user experience for viewing and configuring health metrics. Health metrics of a device can be produced by obtaining performance metrics of the device and contextualizing the performance metrics based on contextualization information. The health metrics can be categorized based on applying rule sets to the health metrics. The rule sets can be selectively applied to the health metrics based on a type of a respective health metric. The health metrics and health metric categories can be instantiated in a user interface of a user device based on a request for device health information from the user device.

Abstract: The present technology relates to health metrics corresponding to industrial automation devices and a user experience for connecting to devices in an industrial automation environment to configure and view health metrics. Health metrics of a device can be obtained from a server, an industrial device, a controller coupled to the industrial device, or another source, and provided to a user interface device. The user interface device can display indications of the health metrics on a user interface. The user interface device can also establish a connection with a user device and provide the indications of the health metrics to the user device for display on a user interface of the user device.

Abstract: Various embodiments of the present technology generally relate to solutions for integrating machine learning models into industrial automation environments. More specifically, embodiments of the present technology include systems and methods for implementing machine learning models within industrial control code to improve performance, increase productivity, and add capability to existing control programs. In an embodiment, a system comprises: a storage component configured to maintain a set of model control schemes for controlling an industrial process, a control component configured to control the industrial process with a control program running a model control scheme, wherein the model control scheme is configured to optimize a first parameter of the industrial process, and a model management component configured to change the model control scheme to optimize a second parameter of the industrial process that is distinct from the first parameter.

Abstract: A latch system for an electrical equipment enclosure includes a chassis and a latch arm, engaged with a circuit breaker, that moves between first, second, and intermediate arm positions. A handle operatively connected to the circuit breaker is movable between ON, TRIP, OFF, and RESET handle positions. The handle is operatively connected to the latch arm such that the latch arm is positioned in the second arm position when the handle is located in said RESET handle position. The latch arm spring biases the latch arm into the first or intermediate positions when the handle is in the ON, TRIP, or OFF handle position. A lockout plunger is connected to the handle to rotate with the handle and is movable between disengaged and engaged positions. The lockout plunger prevents movement of the handle from the OFF to the ON handle position when the lockout plunger is in its engaged position.

Abstract: A tangible, non-transitory, computer-readable medium includes instructions that, when executed by processing circuitry, are configured to cause the processing circuitry to receive user input indicative of a selection of a user experience of a plurality of user experiences. The plurality of user experiences include a first user experience associated with a first event that occurred in an industrial automation system at a first time prior to receiving the user input and a second user experience associated with a second event expected to occur in the industrial automation system at a second time after receiving the user input. When executed, the instructions also cause the processing circuitry to determine, based on the user input, output representative data associated with the industrial automation system and instruct an extended reality device to present the output representative data.

Abstract: Various embodiments of the present technology generally relate to solutions for improving industrial automation programming and data science capabilities with machine learning. More specifically, embodiments include systems and methods for implementing machine learning engines within industrial programming and data science environments to improve performance, increase productivity, and add functionality. In an embodiment, a system comprises a machine learning-based analysis engine configured to perform an analysis of operational data from an industrial automation environment. The analysis engine is further configured to perform an analysis of control logic and identify, based on the analysis of the operational data and the analysis of the control logic, a variable that is in the control logic but is not used in the operational data. The system further comprises a notification component configured to surface a notification that the variable is in the control logic but is not used in the operational data.

Abstract: An industrial system includes a load control assembly, an integrated absence of voltage tester (AVT), and an absence of voltage indicator. The load control assembly has a supply input, a load output, a disconnecting device, and a load controller coupled to the load output, with the disconnecting device coupled between the supply input and the load controller. The AVT is integrated into one of the disconnecting device and the load controller, and the AVT configured to detect an absence of an operating voltage of the load control assembly. The absence of voltage indicator is coupled to the AVT and configured to indicate the absence of an operating voltage of the load control assembly detected by the AVT.

Abstract: A connector for receiving a ribbon cable, to be assembled via a clamping tool, is provided. The connector includes a housing, a cover, and a protection cap. The housing includes an open top and a bottom. The cover is configured to selectively cover the open top of the housing to enclose the ribbon cable within an interior of the housing. The protection cap is configured to cover the bottom of the housing. The protection cap includes a nonplanar surface with a bump, where the clamping tool contacts the cover and the bump to force the cover toward the housing when the connector is assembled.

Abstract: A non-transitory, computer-readable medium includes computer-executable instructions that, when executed, by one or more processors associated with a first input/output (I/O) component in an industrial automation system, cause the processors to perform operations. The first I/O component may operate in a single duplex (“suplex”) mode of operation. The operations include detecting a second I/O component in the industrial automation system, determining that a first hardware configuration, a first software configuration, or both, associated with the first I/O component is compatible with a second hardware configuration, a second software configuration, or both, associated with the second I/O component, and reconfiguring the first I/O component to operate in a duplex mode of operation.

Abstract: Systems and methods for providing fault detection for input/output modules of industrial systems. One system includes a plurality of channel circuits for interfacing with industrial control equipment of an industrial system. The system also includes an electronic processor communicatively coupled to each channel circuit via a dedicated hardware communication channel. The electronic processor is configured to control a current load supply for at least one channel circuit included in the plurality of channel circuits.

Abstract: An industrial automation device includes first processing circuitry configured to perform a first set of operations associated with controlling the industrial automation device or one or more industrial automation devices communicatively coupled to the industrial automation device. The industrial automation device includes input/output circuitry communicatively couplable to an electronic device having second processing circuitry that is configured to execute computer-readable instructions to execute a software container and receive, in the software container, data from the industrial automation device, the one or more industrial automation devices, or both. The second processing circuitry executes the computer-readable instructions to perform, using the software container, a second set of operations associated with controlling the industrial automation device or the one or more industrial automation devices.

Abstract: An adapter of a common gateway platform associated with an industrial automation system is described for communicating data acquired from various devices using a data model of the common gateway platform with external components using various data models. The computing device may determine a relationship between datasets of the native data model and datasets of an external component based on obtaining an application programming interface (API) and/or software development kit (SDK) of the external component. Accordingly, the adapter may enable the common gateway platform to interact with the external component by providing functionalities of the external component as native functions of the computing device. That is, the adapter may provide functions to connect, create, read, write, update, delete, run commands and queries, and disconnect from the external component using native commands and actions of the common gateway platform.

Abstract: A method may include receiving, via at least one processor, a first set of data indicative of a fault being present and send a first signal to a breaker based on the first set of data. The first signal may cause the breaker to open a plurality of poles of the breaker. The method may then involve receiving a second set of data indicative of the fault being cleared and sending a second signal to the breaker based on the second set of data. The second signal may cause the breaker to close a first pole of the plurality of poles at a first time and close a second pole of the plurality of poles at a second time different from the first time.