A method includes a twin model management system presenting a video stream captured by a robot in an industrial facility, the video stream presented in a digital twin (DT) of the industrial facility to a user, receiving a user request to select an input device of an industrial machine, the user request provided by the user via the DT when the industrial machine is depicted in the video stream, providing, in the DT responsive to the user request, a list of input devices indicating input device(s) of the industrial machine that are depicted in a video image of the video stream, receiving a user selection provided via the DT that specifies a target input device in the list, generating, responsive to the user selection, control command(s) specifying operation(s) to be performed by the robot to physically interact with the target input device, and transmitting the control command(s) to the robot.
B25J 13/06 - Control stands, e.g. consoles, switchboards
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
2.
HIERARCHAL CASCADING SAFETY SIGNATURES FOR INDUSTRIAL AUTOMATION APPLICATIONS
Systems, methods, and media for hierarchal, cascading safety signatures for industrial automation applications. A method includes receiving a first user input including a safety configuration for a safety controller; generating an aggregate safety signature indicative of the safety configuration for the safety controller including a parent safety signature element and a first child safety signature element; receiving a second user input provided to the user interface including a modification to the safety configuration; generating a second child safety signature element based on the modification; updating the aggregate safety signature based on the second child safety signature element; and causing the safety controller to operate in accordance with the safety configuration and the aggregate safety signature.
G05B 19/406 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
3.
ANALYSIS WIZARD FOR OPTIMIZING CONTROL LOGIC USING OPERATIONAL DATA IN INDUSTRIAL AUTOMATION ENVIRONMENTS
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
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.
Embodiments of the present technology provide systems and methods for mounting a human interface module (HIM). According to various embodiments, the HIM may be configured to mount alternatively to a panel and a cradle. A panel mounting device is used to mount the HIM to a panel. The panel mounting device can be removably coupled to the HIM for panel mounting. The HIM may be installed in a cradle without the panel mounting device in accordance with some embodiments.
A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations that include receiving operational parameters for one or more automation devices, wherein the one or more automation devices are configured to implement control logic generated based on a decision tree. The operations also include receiving an output by the decision tree based on the operational parameters. Further, the operations include determining the output is an anomalous output based on a constraint associated with the decision tree. Further still, the operations include generating an updated decision tree based on the anomalous output. Even further, the operations include generating updated control logic for the one or more automation devices based on the updated decision tree. Even further, the operations include sending the updated control logic to the one or more automation devices.
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
A graphical user interface (GUI) for designing an industrial automation system via an electronic display includes a design window and a first accessory window. The GUI presents a library visualization representative of a plurality of objects within the first accessory window, each object represented by an icon and corresponding to a respective industrial automation device. The GUI receives a first input indicative of a first selection of a first object from the library, presents the first object in the design window, receives a second input indicative of a second selection of a second object from the library, presents the second object in the design window, determines a suggested next action based on historical data including a plurality of industrial automation system designs having the first and second objects, and updates the GUI to display a notification comprising the suggested next action.
G05B 19/042 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 9/451 - Execution arrangements for user interfaces
G06N 5/046 - Forward inferencingProduction systems
A (GUI) for designing an industrial automation system includes a design window and a first accessory window. The GUI presents a library visualization representative of a plurality of objects within the first accessory window, each object is represented by an icon and corresponds to a respective industrial automation device. The GUI receives inputs indicative of a selection of one or more objects of the plurality of objects from the library, presents the one or more objects in the design window, determines that the one or more inputs do not comply with a set of industrial automation system rules comprising one or more relationships between a plurality of industrial automation devices, and displays a warning message that the one or more inputs do not comply with the set of industrial automation system rules.
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
G06F 30/17 - Mechanical parametric or variational design
A cloud-based simulation generation service collects industrial data from multiple industrial customers for storage and analysis on a cloud platform. The service employs a simulation generator component that analyzes data to facilitate generating a simulation model that simulates an industrial automation system, including simulating or emulating industrial devices, industrial processes, other industrial assets, or network-related assets or devices, and their respective interrelationships with each other. The simulation generator component also analyzes modification data to facilitate generating a modified simulation model that simulates the industrial automation system based on the modification. The simulation generator component performs operation simulations using the simulation model or modified simulation model to facilitate determining whether making the modification is appropriate, determining or predicting performance of a modified industrial automation system, determining compatibility of a modification with an industrial automation system, or determining or predicting performance of the industrial automation system when processing a work order.
Techniques for converting an initial control program code version to a new control program code version are disclosed herein. In at least one implementation, input and output states of an industrial controller are monitored while the industrial controller executes the initial control program code version to operate a machine system and functional design specification for the industrial controller is generated. An instruction set of the industrial controller is converted into a new instruction set for a new industrial controller, and one or more equivalent instructions in the new instruction set that are equivalent to instructions in the instruction set of the industrial controller are identified. The new control program code version is generated based on at least the functional design specification and the one or more equivalent instructions in the new instruction set that are equivalent to the instructions in the instruction set of the industrial controller.
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 17/02 - Systems involving the use of models or simulators of said systems electric
G05B 19/05 - Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
Systems and methods of this disclosure may enable operations that include receiving, via a processor, an indication of a user identifier from an input device associated with a human machine interface terminal (HMI). The processor may identify a user type corresponding to the user identifier. The processor may generate HMI visualization data based on the user type, the user identifier, and a presentation priority data structure. The presentation priority data structure may include presentation priority data corresponding to the user type and the user identifier, which may enable the processor to adjust which subsets of multiple screens are presented to the operator via an HMI based on preferences indicated via the presentation priority data.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
12.
System and Method to Monitor and Balance Wear in an Independent Cart System
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.
A method may include receiving, via a processing system, a selection of a first dataset associated with one or more operations of one or more industrial automation components of an industrial system that may perform a batch operation. The method may involve generating an optimized dataset based on the dataset, receiving a second dataset associated with one or more additional operations of one or more additional industrial automation components of an additional industrial system that may perform an additional batch operation, and determining one or more deviations between the optimized dataset and the second dataset. The method may also involve determining a contribution of each of a set of parameters to the one or more deviations and generating a visualization representative of the contribution of each of a set of parameters to the deviation.
A method may include receiving, via graphical user interface (GUI) of a processing system, a selection of a dataset associated with one or more operations of one or more industrial automation components of an industrial system. The method may also include receiving, via the GUI of the processing system, a set of input variables associated with the dataset, receiving a target variable associated with the dataset, and receiving a model type for analyzing the dataset. The method may also involve determining, via the processing system, a contribution of each of the set of input variables to the target variable based on the model type; and generating, via the processing system, a visualization representative of one or more statistical relationships between each of the set of input variables and the target variable based on the contribution of each of the set of input variables to the target variable.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
An integrated development environment (IDE) for uses a generative artificial intelligence (AI) model to generate industrial control code in accordance with functional requirements provided to the industrial IDE system as natural language prompts. The system's generative AI model leverages both a code repository storing sample control code and a document repository that stores device or software manuals, program instruction manuals, functional specification documents, or other technical documents. These repositories are synchronized by digitizing selected portions of document text from the document repository into control code for storage in the code repository, as well as contextualizing control code from the code repository into text-based documentation for storage in the document repository.
The disclosure describes an industrial automation environment including an industrial device in communication with a Near Field Communication (NFC) chip. The automation device identifies a fault condition and loads a fault code associated with the fault in the NFC chip. When the device is powered off, a mobile device retrieves the fault code from the NFC chip to facilitate device-troubleshooting. In some implementations, the mobile device loads configuration parameters into the NFC chip when the automation device is powered off. Upon startup, the automation device retrieves the configuration parameters and configures itself accordingly.
An integrated development environment (IDE) for uses a generative artificial intelligence (AI) model to generate industrial control code in accordance with functional requirements provided to the industrial IDE system as natural language prompts. The system's generative AI model leverages both a code repository storing sample control code and a document repository that stores device or software manuals, program instruction manuals, functional specification documents, or other technical documents. These repositories are synchronized by digitizing selected portions of document text from the document repository into control code for storage in the code repository, as well as contextualizing control code from the code repository into text-based documentation for storage in the document repository.
A method may include receiving, via a processing system, a request for information associated with an industrial automation system from a user, identifying a prompt associated with the request, and identifying one or more datasets associated with the request based on the prompt and the information. The method may also involve receiving the one or more datasets from one or more data sources, formatting the request and the one or more datasets into a package, and sending the package to a generative artificial intelligence (AI) system. The method may then involve receiving a response from the generative AI system, such that the response may be presented via a display of a human machine interface (HMI) system.
G05B 19/409 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using manual data input [MDI] or by using control panel, e.g. controlling functions with the panelNumerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control panel details or by setting parameters
An industrial technical support system acts as an interactive assistant that leverages generative artificial intelligence (AI) techniques to suggest solutions to industrial alarm conditions or other performance problems based on earlier documented solutions, thereby expediting the process of finding alarm resolutions. The system enhances a user's prompt with relevant contextual data retrieved from stored documentation as well as relevant past chat histories to assist the system's generative AI model in recommending accurate resolutions to alarm conditions or performance issues described by the user's prompt.
Systems and methods for establishing a secure session between an industrial device and an end-point device are provided herein. In an example, the method includes establishing, by a client device, a first channel, such as a short-range communication protocol, with an industrial device and extracting, by a software application executing on the client device, configuration information for the industrial device via the first channel. The method also includes establishing, by the client device using the software application, a second channel with an end-point device, generating, by the software application, modified configuration information based on the configuration information extracted from the industrial device, and transmitting, by the client device, the modified configuration information to the end-point device via the second channel.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
21.
FLEET DEPLOYMENT OF INDUSTRIAL DEVICE CONFIGURATIONS USING NEAR-FIELD COMMUNICATION
Systems and methods for modifying a configuration of an industrial device using near-field communication (NFC) are provided herein. For example, the method includes receiving, via a graphical user interface (GUI) of a software application, a configuration schema for a group of industrial devices. The configuration schema includes a parameter and a range of available values for the parameter for each industrial device of industrial devices. The method also includes determining, by the software application installed on a client device, a configuration for a respective industrial device within the group of industrial devices based on the configuration schema, where the configuration includes a value selected from the range of available values for the parameter and the value is selected based on an order of transmission of the configuration to the respective industrial device. The method also includes transmitting, via NFC from the client device to the respective industrial device, the configuration.
H04L 41/082 - Configuration setting characterised by the conditions triggering a change of settings the condition being updates or upgrades of network functionality
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
An industrial alarm monitoring system leverages generative artificial intelligence (AI) to perform dynamic monitoring and analysis of a customer's industrial processes, identify potential or active performance issues or alarm conditions, and assist users in resolving these issues. The system monitors and collects operational and status data from industrial devices and assets of industrial automation systems and stores information regarding active and historical alarm conditions indicated by this data in an alarm repository. Users can submit natural language requests for assistance with, or information about, active or historical alarms to the system, which leverages trained custom models and a generative AI model to process these requests. The system can formulate natural language alarm resolution guidance based on analysis of the user's request, content of the custom models, responses prompted from the generative AI model, and relevant information about the alarm condition obtained from the alarm repository.
An industrial integrated development environment (IDE) is extended to support creation of device profiles using an intuitive graphical development environment. The environment comprises a device profile development interface that allows a user to select device profile views to be included in a device profile for an industrial device, and to submit edits to the underlying code for the selected device profile views. The system can then generate a new device profile from the modified device profile code. The device profile can be registered with the industrial IDE and used to view and edit device parameters of a corresponding industrial device. The device profile development environment also supports dynamic validation of profile view edits, rendering of graphical previews of the modified device profile view, and submission of both code-based and graphical profile view edits.
An industrial integrated development environment (IDE) supports collaborative tools that allow multiple designers and programmers to remotely submit design input to the same automation system project in parallel while maintaining project consistency. These collaborative features can include, for example, brokering between different sets of design input directed to the same portion of the system project, generating notifications to remote designers when a portion of the system project is modified, sharing of development interfaces or environments, facilitating involvement of outside technical support experts to assist with design issues, and other collaborative features.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
G05B 19/4093 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by part programming, e.g. entry of geometrical information as taken from a technical drawing, combining this with machining and material information to obtain control information, named part programme, for the NC machine
G06T 19/00 - Manipulating 3D models or images for computer graphics
25.
USER INTERFACE LOGICAL AND EXECUTION VIEW NAVIGATION AND SHIFTING
An industrial integrated development environment (IDE) comprises a development interface that affords a user a great deal of control over the editing tools, workspace canvases, and project information rendered at a given time. The industrial IDE system automatically filters the tools, panels, and information available for selection based on a current project development task, such that a focused subset of editing tools relevant to a current development task or context are made available for selection while other tools are hidden. The development interface also allows the user to selectively render or hide selected tools or information from among the relevant, filtered set of tools. This can reduce or eliminate unnecessary clutter and aid in quickly and easily locating and selecting a desired editing function. The IDE's development interface can also conform to a structured organization of workspace canvases and panels that facilitates intuitive workflow.
G06F 3/0483 - Interaction with page-structured environments, e.g. book metaphor
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
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.
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G06Q 10/0639 - Performance analysis of employeesPerformance analysis of enterprise or organisation operations
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.
An independent cart system, including a track having multiple track segments and multiple movers operative to travel along the track, has a support system with a thermal transfer member and a support member for each track segment. The thermal transfer member transfers heat generated by switching devices mounted on a first surface to a second surface remote from the first surface. The switching devices selectively deliver current to coils spaced along each of the track segments. The support member has a base operative to engage a fixed location and a support extending away from the base. The support includes an inner surface, an outer surface, opposite the inner surface, and an upper surface proximate the second surface of the thermal transfer member. The upper surface is configured to engage a complementary surface, and the continuous surface and the complementary surface each have a smooth finish to provide contact therebetween.
H02K 9/22 - Arrangements for cooling or ventilating by solid heat conducting material embedded in, or arranged in contact with, the stator or rotor, e.g. heat bridges
B65H 54/02 - Winding and traversing material on to reels, bobbins, tubes, or like package cores or formers
H02K 5/18 - Casings or enclosures characterised by the shape, form or construction thereof with ribs or fins for improving heat transfer
H02K 5/20 - Casings or enclosures characterised by the shape, form or construction thereof with channels or ducts for flow of cooling medium
H02K 9/18 - Arrangements for cooling or ventilating wherein gaseous cooling medium circulates between the machine casing and a surrounding mantle wherein the external part of the closed circuit comprises a heat exchanger structurally associated with the machine casing
H02K 9/19 - Arrangements for cooling or ventilating for machines with closed casing and closed-circuit cooling using a liquid cooling medium, e.g. oil
H02K 11/33 - Drive circuits, e.g. power electronics
H02K 41/03 - Synchronous motorsMotors moving step by stepReluctance motors
30.
Magnet Arrays for Vehicle Identification in an Independent Cart System
An independent cart system includes multiple track segments, multiple movers, multiple position sensors, and a controller. Each track segment includes multiple coils along a length of the track segment and a segment controller operative to selectively energize the coils to generate an electromagnetic field. Each mover includes a magnet array having multiple magnets, where the magnet array generates a magnetic field that interacts with the electromagnetic field generated by the coils to propel the mover along the track segments. The position sensors are spaced apart along the length of each track segment and generate a position feedback signal with a waveform as a function of the magnetic field generated by the magnet array on each mover. The controller is operative to receive the position feedback signal from each position sensor and to determine a unique identifier for each mover as a function of the waveform of the position feedback signal.
A system for identifying movers in an independent cart system includes movers having at least one magnet and sensors generating a feedback signal responsive to detecting a magnetic field from the magnet as each mover travels past the sensor. A memory stores an identifier and a corresponding digital fingerprint for each mover. The stored digital fingerprint is generated as a function of the magnetic field generated by the magnet on each mover. A controller receives the feedback signal from each sensor and determines a run-time digital fingerprint for each mover corresponding to the magnetic field generated by the magnet on each mover as a function of the feedback signal. The run-time digital fingerprint is matched to one of the stored digital fingerprints, and the identifier, corresponding to the stored digital fingerprint matching the run-time fingerprint, is read from memory.
There is provided a driver-support system for use with a human-operated material-transport vehicle, and methods for using the same. The system has at least one sensor, a human-vehicle interface, and a transceiver for communicating with a fleet-management system. The system also has a processor that is configured to provide a mapping application and a localization application based on information received from the sensor. The mapping application and localization application may be provided in a single localization-and-mapping (“SLAM”) application, which may obtain input from the sensor, for example, when the sensor is an optical sensor such as a LIDAR or video camera.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
G05D 1/223 - Command input arrangements on the remote controller, e.g. joysticks or touch screens
G05D 1/247 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons
A circuit includes a transistor configured to control pre-charging a charge storage device, and a diode coupled in parallel with the transistor. It also includes a shunt resistor coupled between the source of the transistor and a positive end of the charge storage device, an inductor coupled between the shunt resistor and the positive end of the charge storage device, and a current controller coupled to a gate of the transistor. The current controller is configured to receive a current measurement indicating an amount of current flowing through the transistor, process the current measurement to determine a switching duty cycle for the transistor, and to provide a signal to the gate of the transistor, the signal oscillating at the switching duty cycle. It also includes a power supply coupled with the source of the transistor and the drain of the transistor and configured to supply power to the current controller.
H02M 3/158 - Conversion of DC power input into DC power output without intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only with automatic control of output voltage or current, e.g. switching regulators including plural semiconductor devices as final control devices for a single load
H02M 7/06 - Conversion of AC power input into DC power output without possibility of reversal by static converters using discharge tubes without control electrode or semiconductor devices without control electrode
H02P 27/06 - Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using DC to AC converters or inverters
34.
Hybrid Cable for Reducing Common Mode Noise in a Distributed DC Bus System
A cable for reducing electrical noise within a distributed motor drive system includes an insulating jacket defining an outer periphery of the cable. The insulating jacket extends between a first end and a second end of the cable. At least one power conductor and a ground conductor extend between the first and second ends of the cable. A communication cable also extends between the first and second ends of the cable. The communication cable includes a second jacket having an outer surface and an inner surface, where the outer surface of the second jacket defines an outer periphery of the communication cable. At least one pair of communication conductors and a braided shield extend within the communication cable. The braided shield is positioned around the communication conductors and is electrically connected to the ground conductor at the first and second ends of the cable.
Various systems and methods are presented regarding utilizing a centralized knowledge base to analyze various data inputs pertaining to current/future operation of a process, identify prior data pertaining to the current data inputs, identify potential issues, and further provide solutions/recommendations to address the potential issues, as well as responding to the data inputs. Data inputs can be an operator query, current process operation data, HACCP/FMEA data, work instructions, and suchlike. Data can be processed, e.g., vectorized, to enable similarity comparison between the input data and the historical data present in the knowledge base.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
36.
INTELLIGENT MANUFACTURING SYSTEM FOR PROCESS AND COMPONENT SAFETY
Various systems and methods are presented regarding utilizing a centralized knowledge base to analyze various data inputs pertaining to current/future operation of a process, identify prior data pertaining to the current data inputs, identify potential issues, and further provide solutions/recommendations to address the potential issues, as well as responding to the data inputs. Data inputs can be an operator query, current process operation data, HACCP/FMEA data, work instructions, and suchlike. Data can be processed, e.g., vectorized, to enable similarity comparison between the input data and the historical data present in the knowledge base.
Various systems and methods are presented regarding utilizing a centralized knowledge base to analyze various data inputs pertaining to current/future operation of a process, identify prior data pertaining to the current data inputs, identify potential issues, and further provide solutions/recommendations to address the potential issues, as well as responding to the data inputs. Data inputs can be an operator query, current process operation data, HACCP/FMEA data, work instructions, and suchlike. Data can be processed, e.g., vectorized, to enable similarity comparison between the input data and the historical data present in the knowledge base.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
38.
SYSTEMS AND METHODS FOR SUSTAINABILITY RECOMMENDATIONS AS A SERVICE
A system includes processing circuitry and a memory. The memory stores instructions that, when executed by the processing circuitry, cause the processing circuitry to receiving operational data captured from an industrial automation system performing an industrial automation process, model the industrial automation process based on the operational data, model one or more adjustments to the industrial automation process, identify that the modeling of the one or more adjustments to the industrial automation process indicates that the one or more adjustments to the industrial automation process improve one or more sustainability metrics for the industrial automation process, generate one or more sustainability recommendations to implement the one or more adjustments to the industrial automation process, and implement the one or more adjustments to the industrial automation process.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
Disclosed are systems and methods for synchronizing emulation models (i.e., digital twins) of portions of industrial automation systems across distributed computing systems. The emulation models are configured with sending and receiving nodes, and a publish and subscriber networking protocol is used to transmit loads between the nodes. A communication broker (i.e., multi-model server) configures a load transmission graph using the nodes of the emulation models and brokers the transmissions of loads based on the load transmission graph to ensure that loads published from a sending node are sent to the receiving node. As such, the emulations on the distributed node depict loads moving from sending nodes of one model to the corresponding receiving nodes in another model in near-real time.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
40.
CONTROLLING AN INDUSTRIAL MOVER SYSTEM BASED ON SUSTAINABILITY FACTORS
A mover system includes a track, a plurality of movers configured to move along the track, and one or more processors configured to determine a first amount of energy consumption associated with a first portion of the plurality of movers and a second amount of energy consumption associated with a second portion of the plurality of movers and determine a first emissions per unit for each of the first portion of the plurality of movers based on the first amount of energy consumption and a second emissions per unit for each of the second portion of the plurality of movers based on the second amount of energy consumption. The one or more processors are also configured to determine one or more operating settings for the mover system based on the first emissions per unit, the first emissions per unit, or both and send one or more commands to the first number of the plurality of movers, the second number of the plurality of movers, or both based on the one or more operating settings.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
41.
SYSTEMS AND METHODS FOR CONTROLLING MANUFACTURING BASED ON SUSTAINABILITY FACTOR DATA
A system includes one or more automation devices and a computing system. The computing system is configured to receive motion data associated with a transit of a plurality of products, associate a first portion of the motion data to a first product of the plurality of products, and determine motion energy consumption data for the first product based on the first portion of the motion data. Further, the computing system is configured to receive machine data associated with one or more operations performed on the plurality of products at a location, associate a second portion of the machine data to the first product, and determine energy consumption data based on the motion energy consumption data and the machine energy consumption data. Moreover, the computing system is configured to send one or more control signals to the one or more automation devices based on the energy consumption data.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
42.
SYSTEMS AND METHODS OF IMPLEMENTING DISTRIBUTED CONTROLLER CONNECTIONS WITHIN INDUSTRIAL SYSTEMS
Systems and methods for providing distributed controller connections within industrial systems. One system may include an Ethernet physical media configured to facilitate a packetized cache-coherency protocol across a plurality of industrial controllers of an industrial system. The system may also include an industrial personal computer (“IPC”) included in the plurality of industrial controllers, where the IPC may be configured to control at least a first portion of an industrial process of the industrial system. The system may also include a programmable logic controller (“PLC”) included in the plurality of industrial controllers, where the PLC may be directly connected to the PLC with the Ethernet physical media and configured to control at least a second portion of the industrial process of the industrial system.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
43.
SYSTEMS AND METHODS FOR MANUFACTURING APPLICATIONS
A system includes a processor and a memory, accessible by the processor, and storing instructions that, when executed by the processor, cause the processor to run a scheduling application, a staffing application, an engineering application, a dashboards application, or a combination thereof. The scheduling application is configured to receive production data from an enterprise resource planning system, receive first constraint data from a manufacturing execution system and generate a staffing recommendation, and a prioritized schedule. The staffing application is configured to receive the staffing recommendation and the prioritized schedule from the scheduling application and generate a staffing plan. The engineering application is configured to receive constraint data and performance data and generate a notification that includes a visual alert indicating that the performance data does not satisfy a condition set by the second constraint data.
A system includes a controller having a memory configured to store instructions and one or more processors. The controller is configured to receive a constraint time from a first database and a plurality of production times from a second database. The controller identifies one or more outlier production times of the plurality of production times that fall below a lower constraint time limit or exceed an upper constraint time limit. The controller removes the one or more outlier production times from the plurality of production times, determines a mean production time based on the plurality of production times, and generates a notification in response to the mean production time exceeding an upper threshold time or falling below a lower threshold time.
G05B 19/408 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
G08B 5/36 - Visible signalling systems, e.g. personal calling systems, remote indication of seats occupied using electric transmissionVisible signalling systems, e.g. personal calling systems, remote indication of seats occupied using electromagnetic transmission using visible light sources
A system includes a controller having a memory configured to store instructions and one or more processors. The controller receives one or more staffing inputs from a database, determine a staffing plan based on the one or more staffing inputs and an iterative algorithm. The staffing plan includes a table of a plurality of staffing assignments. Each staffing assignment of the plurality of staffing assignments includes a staff member identifier, a shift identifier indicative of an assigned shift, a product line identifier indicative of a product line to which a staff member is assigned, or a combination thereof. The controller controls a user interface to display the staffing plan. The controller receives real-time data indicative of day-of staffing adjustments and monitored attendance from an attendance system, updates the staffing plan based on the real-time data, and controls the user interface to display the updated staffing plan.
A system and method for monitoring and controlling assets to mitigate predicted future faults. The method includes receiving, by a processing circuit, data describing an asset from one or more data sources; generating, by the processing circuit, an asset data model based on the received data; receiving, by the processing circuit, an extensible data model describing an organizational structure of an enterprise associated with the asset; extending, by the processing circuit, the extensible data model to include the asset models executing, by the processing circuit, the extensible data model including the asset models to determine one or more key performance indicators for the asset; predicting, by the processing circuit, a future fault for the asset based on the key performance indicators; sending, by the processing circuit, an informed and prioritized notification to plant personnel regarding the predicted fault; and taking a corrective action to mitigate the predicted future fault.
A system and method for monitoring and controlling production of batches of products in an industrial process, the method comprising: receiving, by a processing circuit, data describing a batch of products generated in an industrial process from one or more data sources; contextualizing, by the processing circuit, the data describing the batch of products generated in the industrial process; generating, by the processing circuit, a batch data model based on the contextualized data; executing, by the processing circuit, the batch data model to determine key performance indicators for the batch of products; comparing, by the processing circuit, the key performance indicators to pre-determined key performance indicators; and performing an automated action based on a result of the comparison.
A tamper detection device (TDD) includes a current generation system positioned relative to a first portion and a second portion of an enclosure to generate an electric current when the first portion moves relative to the second portion, the enclosure contains a product object and the TDD powered by the product object; an electric storage device coupled to the current generation system to be charged by the electric current, the electric current is generatable when the product object is off and the TDD is unpowered; a controller that determines, within a time window since the product object is switched on and powers the TDD at a particular time, that the electric storage device is charged, generates, responsive to such determination, a tampering output indicating that a tampering event has occurred when the product object is off prior to the particular time, and transmits the tampering output to the product object.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
G01P 13/00 - Indicating or recording presence or absence of movementIndicating or recording of direction of movement
49.
AUTOMATED INDUSTRIAL AUTOMATION COMPONENT DISCOVERY AND EDGE INTEGRATION INTO A CONTAINER ORCHESTRATION SYSTEM
In a container orchestration environment implemented in an industrial automation environment, a new industrial automation component (e.g., device or software) attaches to an industrial automation network, and a pod of the container orchestration environment detects the attachment. In response, the pod creates a new pod representing the new industrial automation component by determining a type of the new industrial automation component, identifying functionality specific to the industrial automation component based on the type, provisioning software to implement the functionality, and generating a pod with containers for the software. The pod couples interfaces in the software to interfaces of the new industrial automation component and exposes the pod in the container orchestration environment, allowing the industrial automation component to participate in the container orchestration system.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
50.
SYSTEMS AND METHODS FOR MANUFACTURING APPLICATIONS
A system includes a controller having a memory configured to store instructions and one or more processors. The controller is configured to receive constraint data from a first database. The constraint data includes a constraint time, a shift time, a product line capability of a production line, or a combination thereof, as well as production data from a second database, and determine an objective function based on the constraint data and the production data. In response to a stop condition not being met, the controller determines a prioritized schedule of work orders and a staffing recommendation based on the objective function, the constraint data. The controller transmits the prioritized schedule and the staffing recommendation to a staffing application in response to the stop condition being met.
A system and method for monitoring and controlling energy use in an industrial process. The method includes: receiving, by a processing circuit, data describing energy use in an industrial process from one or more data sources; contextualizing, by the processing circuit, the data describing the energy use in an industrial process; generating, by the processing circuit, an energy data model based on the contextualized data; executing, by the processing circuit, the energy data model to determine key performance indicators for the energy use in an industrial process; displaying, by the processing circuit, the key performance indicators to a user; determining, by the processing circuit, if the key performance indicators are above one or more pre-determined thresholds; and taking a corrective action in response to the key performance indicators being above the one or more pre-determined thresholds.
A system and method for monitoring and controlling an industrial process using a data model extensible to different industry applications. The system is configured to: receive data describing the industrial process from one or more data sources in a first format; contextualize and transform the data by determining one or more tags for the data, the one or more tags comprising context information describing characteristics of the entities involved in the industrial process; generate a data model describing the industrial process based on the one or more tags; receive a first indication from a user indicating a first industry application to which the data model will be applied; and extend the data model to include a second plurality of nodes representing entities associated with the first industry application and a second plurality of edges connecting the second plurality of nodes and describing relationships between the second plurality of nodes.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
A method includes receiving, at a certificate authority, from a first organization in possession of an operational technology (OT) device, a first certificate signing request and a public key, verifying the first certificate signing request, generating, a certificate, transmitting the certificate to the first organization for storage in memory of the OT device along with the public key, receiving, from a second organization in possession of the OT device, a second certificate signing request and the public key, verifying one or more second pieces of information in the second certificate signing request, generating a new certificate, and transmitting the new certificate to the second organization for storage in memory of the OT device along with the public key.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
54.
USER-DEFINED EVENT-BASED VISUALIZATION CONTENT DELIVERY SYSTEM USING THIN CLIENTS
A system may include one or more devices, each of the one or more devices may include a respective electronic display. The system may also include a computing system that may receive a request to define an event-based trigger for deploying visualization content, present a graphical user interface for receiving inputs defining properties of the event-based trigger. The properties may include a type of the visualization content, match conditions for deploying the visualization content, and an indication of at least one device to receive the visualization content. The computing system may then monitor communication channels for the match conditions, generate the visualization content in response to detecting the match conditions via the communication channels based on the type of the visualization content, and transmit the visualization content to the at least one device. The at least one device may present the visualization content via an electronic display.
A system may include a computing system communicatively coupled to the one or more client devices. The computing system may receive an indication of an event-based trigger for deploying visualization content, receive tag data associated with the event-based trigger, and identify a client device executing an application associated with the tag data. The computing system may then present visualization content including code associated with the event-based trigger, such that the visualization content is received via the client device. The computing system may then send one or more instructions to the client device, such that the one or more instructions may modify the code.
G05B 19/408 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
G05B 19/409 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using manual data input [MDI] or by using control panel, e.g. controlling functions with the panelNumerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control panel details or by setting parameters
56.
MODULAR SOLID-STATE POWER MONITOR AND PROTECTION SYSTEM
A system includes one or more modular monitor systems. Each modular monitor system includes a modular control system that controls one or more switches that couple a power source to a load device. Each modular monitor system also includes one or more sensors that acquire sensor data including electrical characteristics associated with a respective modular monitor system. Additionally, the system includes a central monitor system that receives the sensor data, presents the sensor data via a display device integral to the central monitor system, generates one or more control signals based on the sensor data, and transmits the one or more control signals to the one or more modular monitor systems. The one or more control signals may cause a respective modular control system of the respective modular monitor system to operate one or more respective switches.
H02J 13/00 - Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the networkCircuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
H02J 3/00 - Circuit arrangements for ac mains or ac distribution networks
57.
System and Method for Electromagnetic Pinning and Hybrid Control of a Linear Drive System
A system and method for holding position of a mover in an independent cart system includes receiving a current feedback signal corresponding to a current present in at least one coil for a linear drive system in the independent cart system. A motion command for the mover is received, where the motion command defines a desired position along a track of the independent cart system to which the mover is to travel. An electromagnetic pinning control mode is disabled while controlling operation of the at least one mover to the desired position and enabled when the at least one mover is at the desired position.
A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations that include receiving image data after an operation is performed by an industrial automation device on a product; analyzing the image data based an object-based image analysis (OBIA) model to classify the product as one of a plurality of conditions related to manufacturing quality and the OBIA model includes property layers associated with features related to a manufacturing of the product; determining whether the one of the conditions indicates an anomaly being present in the product; sending a notification indicative of the one of the plurality of conditions is presently associated with the product; identifying a property layer associated with classifying the one of the plurality of conditions; and updating the OBIA model based on the property layer and the input indicative of the anomaly being incorrectly associated with the product.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
G06F 18/21 - Design or setup of recognition systems or techniquesExtraction of features in feature spaceBlind source separation
A system may include a computing system communicatively coupled to a plurality of client devices. The computing system may receive an indication of an event-based trigger for deploying visualization content, identify a deployment configuration file associated with the event-based trigger, and identify a first client device of the plurality of client devices for deploying a container specified in the deployment configuration file. The computing system may then schedule deployment of a pod associated with the container to the first client device. The first client device may then retrieve a container image associated with the pod, execute the container image to generate visualization content associated with the event-based trigger, and send the visualization content to a second client device of the plurality of client devices for display via an electronic display.
A system may include a computing system communicatively coupled to a plurality of client devices. The computing system may receive an indication of an event-based trigger for deploying visualization content and retrieve visualization content associated with the event-based trigger. The visualization content may be generated via a first client device of the plurality of client devices. The computing system may then identify a user associated with the-event based trigger, identify a second client device of the plurality of client devices associated with the user, and send the visualization content to the second client device.
An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.
A power supply for use in an industrial automation environment includes a housing, a safety input interface, a switched-mode power supply, safe-off circuitry, a first power output channel, a first protection circuit, a second power output channel, a second protection circuit, and a processor. The processor is configured to receive a safety input signal instructing the power supply to shut off power that is provided to industrial automation equipment via the first power output channel and further to cause the safe-off circuitry to shut off the power that is provided to the industrial automation equipment via the first power output channel.
Systems and methods for autonomous lineside delivery to an assembly-line using a self-driving vehicle are disclosed, comprising receiving a part-supply schedule having a part identifier identifying a part to be supplied, an assembly-line location to be supplied with the part, and a delivery time for supplying the part to the assembly-line location. A mission is generated based on the schedule, and sent to a self-driving vehicle. The self-driving vehicle executes the mission such that the part is supplied to the assembly-line location in accordance with the part-supply schedule.
An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.
G05B 19/408 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
G05B 19/409 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using manual data input [MDI] or by using control panel, e.g. controlling functions with the panelNumerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control panel details or by setting parameters
66.
System and Method for Reducing Energy Loss from Multiple Inverters Utilizing a Shared DC Bus
A system and method for reducing energy loss in a multiple inverter system provides a DC voltage to multiple inverters via a shared DC bus. Each inverter is configured to control operation of a motor operatively connected to a corresponding inverter. An amplitude of the DC voltage present on the DC bus is monitored, and each inverter selectively draws current from or delivers current to the DC bus. An amplitude of the current drawn from or delivered to the DC bus is monitored by each inverter. A level of energy delivered by at least one of the inverters to the DC bus is determined when the amplitude of the DC voltage exceeds a predefined threshold during a first operation of the multiple inverter system. At least one subsequent operation of the multiple inverter system is adapted responsive to the level of energy delivered to the DC bus.
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02J 3/46 - Controlling the sharing of output between the generators, converters, or transformers
H02M 7/5387 - Conversion of DC power input into AC power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters in a bridge configuration
67.
GENERATIVE AI FOR INDUSTRIAL AUTOMATION CONTROL DESIGN ENVIRONMENT
An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.
G05B 19/409 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using manual data input [MDI] or by using control panel, e.g. controlling functions with the panelNumerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control panel details or by setting parameters
68.
GENERATIVE AI FOR INDUSTRIAL AUTOMATION DESIGN ENVIRONMENT TEST
An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.
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.
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.
G05B 19/406 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
71.
IIoT CROSS-DOMAIN AUTHENTICATION USING IDENTITY FEDERATED SMART CONTRACTS
Identity-federated smart contracts can be combined with an identity provider to provide uniform, customizable, secure, and immutable authentication across many different domains. Such can address the challenges of cross-domain authentication in the context of a decentralized environment such as a decentralized IIoT environment in which a host application resident in a host domain can functionally integrate with, and potentially be bundled or packaged as a single product, many remote applications that reside in many different (e.g., customer) domains that use different forms of authentication, and where some domains may have no authentication mechanisms at all.
Systems and methods of controlling graphic displays within a multi-display human machine interface (“HMI”) environment for industrial systems. One system includes an electronic processor configured to execute the HMI-client application for the industrial system. The electronic processor may be configured to determine a set of display parameters for the HMI-client application. The electronic processor may be configured to determine, based on the set of display parameters, a configuration for a first display frame included in a plurality of display frames for the HMI-client application. The electronic processor may be configured to generate, based on the configuration, a first graphic display within the first display frame. The electronic processor may be configured to display, via a first display device of the plurality of display devices, the first graphic display within the first display frame such that the first graphic display is maintained within the first graphic display.
Systems and methods of controlling graphic displays within a multi-display human machine interface (“HMI”) environment for industrial systems. One system includes an electronic processor configured to determine a display parameter for a header portion of a graphic display of the plurality of graphic displays. The electronic processor may be configured to determine, based on the display parameter, an arrangement for the graphic display, where the arrangement maintains the header portion of the graphic display within a display frame for the graphic display. The electronic processor may be configured to generate the graphic display based on the arrangement. The electronic processor may be configured to display the HMI-client application across the plurality of display devices and display the graphic display within the display frame for the graphic display on a first display device of the plurality of display devices.
Industrial devices and edge compute platforms are configured to synchronize their internal clocks to provide a common sense of time across application and data acquisition tasks, thereby allowing for an inherent common understanding of time across the devices and data sets. The industrial devices can synchronize their internal clocks using Precision Time Protocol (PTP) or IEEE 802.1AS synchronization. The accurate time stamping achieved by this synchronization can yield more accurate analysis of data sets acquired from multiple devices, and greater fidelity and synchronization between a digital twin of an automation system and the physical system represented by the digital twin.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
75.
GENERATIVE AI FOR INDUSTRIAL AUTOMATION DESIGN ENVIRONMENT TROUBLESHOOTING
An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
77.
SYSTEMS, DEVICES, AND METHODS FOR INTERFACING WITH INDUSTRIAL AUTOMATION EQUIPMENT
An industrial motor drive and associated human interface module (HIM) for interfacing with the industrial motor drive to control operation of a motor in an industrial operation. The human interface module receives inputs from a human related to control parameters associated with the industrial motor drive and presents progressively narrowing lists and suggestions to assist the user in accessing and modifying control parameters associated with the industrial motor drive. Based on a modification to a control parameter, the industrial motor drive controls the operation of the motor in the industrial operation accordingly.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
78.
ORIGINAL EQUIPMENT MANUFACTURER (OEM) DATA APPLICATION PROGRAMMING INTERFACE (API) TO MODEL REPOSITORY
Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to train machine learning systems to perform autonomous control in an industrial automation environment. In some examples, a data aggregation component receives operational data from Original Equipment Manufacturer (OEM) devices, identifies a device type for the operational data, and transfers the operational data for the device type to a machine learning interface component. The operational data characterizes the operations of the OEM devices. The interface component receives the operational data for the device type and generates feature vectors based on the operational data configured for ingestion by a machine learning model. The interface component transfers the feature vectors to a machine learning model. The interface component receives a training indication from the machine learning model that indicates an autonomous control output for the device type of the OEM devices.
Blockchain-enabled industrial devices and associated systems are configured to support the use of industrial blockchains in connection with product and machine tracking, subscription-based industrial services, device lifecycle management, and other functions. Collections of industrial devices can collectively serve as an industrial blockchain system, with multiple such systems within a supply chain yielding an industrial blockchain ecosystem. This architecture can create distributed, decentralized, tamper-proof records of manufacturing statistics for a product, a product's history within the larger supply chain, industrial asset usage histories that can be leveraged in connection with lifecycle management, machine usage history for use in connection with subscription-based machine operation, and other such information. The blockchain-enabled industrial devices can be configured to generate multiple versions of a product or machine's blockchain having respective different access permissions, allowing public and private industrial data to be segregated between public and private industrial blockchains.
G05B 19/4093 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by part programming, e.g. entry of geometrical information as taken from a technical drawing, combining this with machining and material information to obtain control information, named part programme, for the NC machine
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
The present disclosure is directed to systems, methods and devices for facilitating object-based industrial automation control. An automation control library comprised of a plurality of objects may be maintained in association with one or more industrial automation applications. Code defining the execution of an industrial automation process may be received. A plurality of objects in the object library for implementing the industrial automation control process may be identified. The plurality of identified objects may be matched to one or more hardware components based on one or more operational requirements included in the code, and available hardware resources for performing the automation control process.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
G05B 19/04 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers
G05B 19/05 - Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
An illustrative method includes a voice agent system establishing a plurality of user-agent conversations, wherein each user-agent conversation between a user and the voice agent system is established in response to the user speaking a trigger word and the plurality of user-agent conversations continue simultaneously in a same physical area, detecting an utterance in an audio stream associated with the physical area, determining, based on the utterance, that the utterance potentially belongs to a particular user-agent conversation among the plurality of user-agent conversations and determining a confidence score that the utterance belongs to the particular user-agent conversation, identifying a candidate action to be performed by the voice agent system based on the utterance, determining an overall confidence score of the candidate action based on the confidence score that the utterance belongs to the particular user-agent conversation, and performing an operation based on the overall confidence score of the candidate action.
A motor controller executes an axis module for each of multiple motors coupled to a shared load. A first control module passes at least one state variable to a second control module without experiencing communication delays between the axis modules. In order to decouple interaction between axes, the first control module determines the desired state variable at a periodic update rate and stores the desired state variable in memory. The first control module provides an indication to the second control module that the desired state variable is available. Within the same period at which the desired state variable is determined, the second control module receives the indication that the desired state variable is available and reads the state variable from the memory of the controller. The second control module executes using the desired state variable to reduce coupling between the two control modules.
H02P 21/16 - Estimation of constants, e.g. the rotor time constant
H02P 27/06 - Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using DC to AC converters or inverters
83.
INDUSTRIAL ARTIFICIAL INTELLIGENCE SYSTEM NODE NETWORK OPTIMIZATION
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.
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.
G05B 19/408 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
G05B 19/406 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
86.
DYNAMIC INDUSTRIAL ARTIFICIAL INTELLIGENCE CONFIGURATION AND TUNING
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.
G05B 19/4097 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using design data to control NC machines, e.g. CAD/CAM
87.
SYSTEM LEVEL INDUSTRIAL ARTIFICIAL INTELLIGENCE AGGREGATION OF BASELINE DATA DEVIATION
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.
Systems and methods described herein may involve monitoring an asset based on multiple device models representing the asset as operated in different process states. The systems and methods may involve receiving acquired data corresponding to a current operation of the asset and identifying a device model of the multiple device models based on the acquired data. The device model may correspond to a process state of the different process states, an operational parameter that the asset is operated in, and a training status indication.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
89.
INDUSTRIAL ARTIFICIAL INTELLIGENCE MODEL INTERDEPENDENCY LEARNING AND DEPLOYMENT
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.
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
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.
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
An industrial software management system uses subscription tokens to license industrial software to customers. According to an example licensing structure, a software customer can purchase subscription tokens that are shared among users within the customer's organization and that allow those users to check out and use industrial software products. The subscription tokens regulate the number of software product instances that may be used concurrently by the users. When a user checks out a software product for use, the customer's total number of available subscription tokens commensurate with a cost of the selected software product. When the user relinquishes use of the product, the subscription tokens are returned to the pool of available tokens. Users may only check out a software product for use is if a sufficient number of unused subscription tokens are available.
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.
The present disclosure is directed to systems, methods, and devices for facilitating object-based cross-domain industrial automation control. An object library comprising a plurality of objects may be maintained. One or more of the objects may represent physical counterparts for use in an industrial automation process. Each object of the plurality of objects in the object library may have at least one property that an automated control device operation can be programmed to act on. Each object of the plurality of objects may also have at least one property that a human machine interface component can utilize in generating display elements corresponding to the objects for display on the human machine interface. When modifications to objects in the object library are received, those modifications may be automatically deployed and incorporated in controller logic and HMI graphics and control.
A non-transitory computer readable medium stores instructions that, when executed by a processor, cause the processor to receive data associated with a plurality of simulated cyberattacks on a virtual operational technology (OT) network, wherein the virtual OT network comprises a virtualized representation of an OT network based on configuration data of the OT network, identify, based on the received data, one or more cybersecurity vulnerabilities of the OT network, identify one or more modifications to a set of cybersecurity rules implemented in the OT network to address the one or more cybersecurity vulnerabilities of the OT network, provide an indication of the one or more modifications to a computing device associated with the OT network for approval; and update, via a third-party network security service utilized by an operator of the OT network, the set of cybersecurity rules to implement the one or more identified modifications.
Systems and methods described herein may involve an industrial control system that performs one or more operations in association with an industrial automation system based on data received via one or more of its input terminals. Processing circuitry may provide a virtualized industrial automation device communicatively coupled to the industrial control system via one or more output terminals. The processing circuitry may receive an event notification from a first container provided by one or more computing devices external to the industrial automation system, where the first container may perform a monitoring operation and generate the event notification based on the monitoring operation. The processing circuitry may operate the virtualized industrial automation device to expose the event notification to the one or more input terminals and may transmit the data via the one or more input terminals to the industrial control system.
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
96.
DEPLOYING APPLICATIONS WITH ACCESS TO CONTROL PLANE USING EDGE COMPUTE MODULES AND INDUSTRIAL DESIGN ENVIRONMENTS
A method may include receiving, via a computing system, a request to install an application for execution via an industrial computing device within an industrial system. The method may also include retrieving an image file associated with the application from a storage component, retrieving a profile file associated with the application form the storage component, and presenting one or more visualizations based on the profile file. The one or more visualizations may include one or more input fields that may receive user input for defining one or more parameters associated with the application. The method may also include receiving the one or more parameters via the one or more input fields and sending the image file and the one or more parameters to the industrial computing device. The industrial computing device may install the application and adjust one or more settings of the application based on the parameters.
A method may include receiving, via a computing system, a request to generate one or more visualizations based on one or more datasets provided by an industrial device within an industrial system. The computing system may be communicatively coupled to the industrial device via a data backplane. The method may also involve accessing a visualization platform system in response to receiving the request, sending design data associated with the one or more visualizations to the visualization platform system, and receiving a visualization project file for execution by the computing system from the visualization platform system. The visualization project file may be generated based on the design data. The method may also include generating the one or more visualizations based on the visualization project file and presenting the one or more visualizations via an electronic display device.
A non-transitory computer readable medium stores instructions that, when executed by a processor, cause the processor to receive configuration data representative of one or more operational parameters of the network security system, execute a virtual network including a virtual network security system configured based on the configuration data, deploy simulated cyberattacks on the virtual network, identify one or more of the simulated cyberattacks that were not detected by the virtual network security system, and generate a notification identifying the one or more of the simulated cyberattacks that were not detected by the virtual network security system.
A non-transitory computer readable medium stores instructions that, when executed by a processor, cause the processor to retrieve, from a catalog, a set of characteristics associated with a cyberattack, generate a plurality of packets having the set of cyberattack characteristics, wherein the plurality of packets collectively simulate the cyberattack, transmit the plurality of packets over a virtual operational technology (OT) network comprising a virtual network security system, and receive an alert indicating whether one or more of the plurality of packets was detected by the virtual network security system.
Systems and methods described herein may involve an industrial network device that performs an operation based on symbolic data received via an input terminal. The systems and methods may involve processing circuitry coupled via an output terminal to the input terminal. The processing circuitry may provide a virtualized control system communicatively coupled to the industrial network device via the output terminal, receive an event notification from a first container provided by one or more computing devices external to the industrial automation system, operate the virtualized control system to expose the event notification via a symbolic common industrial protocol (CIP) namespace to provide the symbolic data to the input terminal based on the event notification, and transmit the symbolic data corresponding to the virtualized control system via the one or more input terminals to the industrial network device.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
patents
