Systems, apparatus, articles of manufacture, and methods are disclosed to generate device for an industrial network. An example apparatus includes machine-readable instructions; and programmable circuitry to at least one of instantiate or execute the machine-readable instructions to: import a device model for an industrial device; import source code for an industrial device; update the source code based on the device model; and generate an executable output of the source code.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
2.
METHODS AND APPARATUS TO IMPLEMENT A DEVICE ON AN INDUSTRIAL NETWORK
Systems, apparatus, articles of manufacture, and methods are disclosed to implement a device on an industrial network. An example application includes at least one of memory or storage to store a first model descriptive of a first industrial device and a second model descriptive of a second industrial device; instructions; at least one processor to execute the instructions to cause a machine to: construct a configuration object for the first industrial device based on the first model; update a data structure that contains data associated with the second model with data associated with the first model based on the configuration object; and operate the apparatus as the first industrial device based on the data structure.
Methods and apparatus to generate process diagrams in process control systems are disclosed. An example apparatus comprises interface circuitry, first machine-readable instructions, and at least one processor circuit to be programmed by the first machine-readable instructions to access input data that indicates a relationship between components in a diagram, the diagram graphically representing at least a portion of a process control system, determine coordinate locations associated with the input data within the diagram, and generate second machine-readable instructions including information corresponding to the coordinate locations, the second machine-readable instructions to cause a change to the diagram based on the input data, the changed diagram indicating the relationship between the components.
G05B 19/4097 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par l'utilisation de données de conception pour commander des machines à commande numérique [CN], p. ex. conception et fabrication assistées par ordinateur CFAO
4.
METHODS AND APPARATUS TO PROVIDE VERSION CONTROL IN A PROCESS CONTROL SYSTEM GRAPHICAL USER INTERFACE DEVELOPMENT ENVIRONMENT
Systems, apparatus, articles of manufacture, and methods to provide version control in a process control system development environment are disclosed. Example instructions cause at least one processor to at least cause presentation of a first graphical user interface to enable editing of a second graphical user interface of a process control system, the second graphical user interface based on information stored in a database, access a user instruction to modify the second graphical user interface from a first version to a second version, access user commit information associated with the second version, export the second version of the second graphical user interface from the database to a local file repository, and synchronize the second version from the local file repository to a remote repository, the synchronization to include the user commit information.
Systems, apparatus, articles of manufacture, and methods to provide version control in a process control system development environment are disclosed. Example instructions cause at least one processor to at least cause presentation of a first graphical user interface to enable editing of a second graphical user interface of a process control system, the second graphical user interface based on information stored in a database, access a user instruction to modify the second graphical user interface from a first version to a second version, access user commit information associated with the second version, export the second version of the second graphical user interface from the database to a local file repository, and synchronize the second version from the local file repository to a remote repository, the synchronization to include the user commit information.
Systems, apparatus, articles of manufacture, and methods to monitor asset health with cloud templates are disclosed. An example apparatus comprises interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access, via a cloud resource, sensor data associated with a process control device operating in a process control system, compare the sensor data to a threshold parameter associated with the process control device, obtain, from a cloud template deployed in the cloud resource, a health parameter of the process control device based on the comparison, and display the health parameter on a user interface of a computing device, the computing device accessing the cloud resource.
F16K 37/00 - Moyens particuliers portés par ou sur les soupapes ou autres dispositifs d'obturation pour repérer ou enregistrer leur fonctionnement ou pour permettre de donner l'alarme
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
Systems, apparatus, articles of manufacture, and methods to monitor asset health with cloud templates are disclosed. An example apparatus comprises interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access, via a cloud resource, sensor data associated with a process control device operating in a process control system, compare the sensor data to a threshold parameter associated with the process control device, obtain, from a cloud template deployed in the cloud resource, a health parameter of the process control device based on the comparison, and display the health parameter on a user interface of a computing device, the computing device accessing the cloud resource.
Methods and apparatus to display shift change notes generated via natural language processing models are disclosed. An example apparatus comprises interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access input data from a workstation in a process control system, the input data associated with a first user account, transmit the input data to a natural language processing (NLP) model, the NLP model to generate a representation of the input data based on stored data associated with the process control system, and display the representation of the input data on a user interface of the workstation after detecting an access of a second user account different from the first user account.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
G06F 40/40 - Traitement ou traduction du langage naturel
9.
HIGHLY-VERSATILE FIELD DEVICES AND COMMUNICATION NETWORKS FOR USE IN CONTROL AND AUTOMATION SYSTEMS
A highly versatile process control or factory automation field device is configured with an interface and communication connection structure that enables the field device to operate as a data server that communicates with and supports multiple different applications or clients, either directly or indirectly, while simultaneously performing standard process and factory automation control functions. Moreover, various different process control and factory automation network architectures and, in particular, communication architectures, support the versatile field device to enable the versatile field device to simultaneously communicate with multiple different client devices or applications (each associated with a different system) via a common communication network infrastructure, using the same or different communication protocols.
Methods and apparatus to display shift change notes generated via natural language processing models are disclosed. An example apparatus comprises interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access input data from a workstation in a process control system, the input data associated with a first user account, transmit the input data to a natural language processing (NLP) model, the NLP model to generate a representation of the input data based on stored data associated with the process control system, and display the representation of the input data on a user interface of the workstation after detecting an access of a second user account different from the first user account.
Disclosed examples include interface circuitry, first instructions, and programmable circuitry to at least one of instantiate or execute the first instructions to access a file in a request from a client device, the file including at least a second instruction to retrieve device parameter data associated with at least one field device in a process control system, convert at least the second instruction of the file from a first format to a field device request in a second format, cause access of a first device parameter value of the device parameter data in the at least one field device based on the field device request, query a database to retrieve a second device parameter value of the device parameter data, and provide the first device parameter value and the second device parameter value to the client device.
Disclosed examples include interface circuitry, first instructions, and programmable circuitry to at least one of instantiate or execute the first instructions to access a file in a request from a client device, the file including at least a second instruction to retrieve device parameter data associated with at least one field device in a process control system, convert at least the second instruction of the file from a first format to a field device request in a second format, cause access of a first device parameter value of the device parameter data in the at least one field device based on the field device request, query a database to retrieve a second device parameter value of the device parameter data, and provide the first device parameter value and the second device parameter value to the client device.
G05B 19/04 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/125 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance en impliquant la commande des applications des terminaux par un réseau
H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau
G05B 23/00 - Test ou contrôle des systèmes de commande ou de leurs éléments
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
13.
METHODS AND APPARATUS TO TRANSFORM PROCESS CONTROL DATA FOR USE IN A DISTRIBUTED CONTROL SYSTEM
Systems, apparatus, articles of manufacture, and methods are disclosed to transform process control data for use in a distributed control system. An example apparatus includes first instructions to access an output condition associated with a process control system, determine second instructions to control the system based on the output condition, the second instructions executable by a programmable logic controller (PLC), identify a pattern based on the second instructions and the output condition, compare the pattern to stored patterns in a first database, the stored patterns associated with at least one other process control system, determine a control narrative when the pattern matches at least one of the stored patterns, the control narrative corresponding to the at least one of the stored patterns, and transmit the control narrative to a second database associated with a distributed control system (DCS), the control narrative to modify a configuration of the DCS.
G05B 19/05 - Automates à logique programmables, p. ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes
14.
METHODS AND APPARATUS TO TRANSFORM PROCESS CONTROL DATA FOR USE IN A DISTRIBUTED CONTROL SYSTEM
Systems, apparatus, articles of manufacture, and methods are disclosed to transform process control data for use in a distributed control system. An example apparatus includes first instructions to access an output condition associated with a process control system, determine second instructions to control the system based on the output condition, the second instructions executable by a programmable logic controller (PLC), identify a pattern based on the second instructions and the output condition, compare the pattern to stored patterns in a first database, the stored patterns associated with at least one other process control system, determine a control narrative when the pattern matches at least one of the stored patterns, the control narrative corresponding to the at least one of the stored patterns, and transmit the control narrative to a second database associated with a distributed control system (DCS), the control narrative to modify a configuration of the DCS.
A distributed control system (DCS) of an industrial process plant includes a data center storing a plant information model that includes a description of physical components, the control framework, and the control network of the plant using a modeling language. A set of exposed APIs provides DCS applications access to the model, and to an optional generic framework of the data center which stores basic structures and functions from which the DCS may automatically generate other structures and functions to populate the model and to automatically create various applications and routines utilized during run-time operations of the DCS and plant. Upon initialization, the DCS may automatically sense the I/O types of its interface ports, detect communicatively connected physical components within the plant, and automatically populate the plant information model accordingly. The DCS may optionally automatically generate related control routines and/or I/O data delivery mechanisms, HMI routines, and the like.
G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme
G06F 13/38 - Transfert d'informations, p. ex. sur un bus
16.
I/O CARRIER AND BACKPLANE FOR INDUSTRIAL PROCESS CONTROL SYSTEMS
A backplane for use in an I/O device includes a first bus configured to communicatively couple each of a plurality of electronic marshalling component (EMC) slots to each of one or more I/O processor module slots. The I/O device also includes a second bus, redundant to the first bus, configured to communicatively couple each of the plurality of EMC slots to each of the one or more I/O processor module slots. For each pair of a one of the plurality of EMC slots and a one of the one or more I/O processor module slots, a first path length of the first bus between the pair is the same as a second path length of the second bus between the pair, such that data transmitted between the pair on the first bus has a same latency as data transmitted between the pair on the second bus.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
G05B 19/05 - Automates à logique programmables, p. ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
An I/O device is configured to couple a plurality of process control field devices to a process controller controlling a process in an industrial process plant. The I/O device includes a backplane and a plurality of electronic marshalling component (EMC) slots. The EMC slots are each configured to receive a respective EMC and to receive either of (i) a first-type EMC associated with a first communication protocol or (ii) second-type EMC associated with a second communication protocol. The I/O device also includes I/O processor module slots, each communicatively coupled, via the backplane, to each of the EMC slots and to each of a first one or more connectors and a second one or more connectors in each of the EMC slots. The I/O device further includes communication ports, each communicatively coupled to the I/O processor module slots via the backplane.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
G05B 19/05 - Automates à logique programmables, p. ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes
H05K 7/14 - Montage de la structure de support dans l'enveloppe, sur cadre ou sur bâti
18.
METHODS AND APPARATUS TO PERFORM PROCESS CONTROL ANALYTICS
Systems, apparatus, articles of manufacture, and methods to perform process control analytics are disclosed. An example method includes generating a prompt based on the request for analytics data, providing the prompt to a large language model for generation of analytics instructions, validating the analytics instructions to determine whether the analytics instructions are to be executed, and in response to the determination that the analytics instructions are to be executed, executing the analytics instructions to generate the analytics data.
Methods and apparatus to modify user interfaces using artificial intelligence are disclosed. An example apparatus comprises instructions access first image data corresponding to a first diagram representing a process control system, the first diagram to be displayed via a user interface of the process control system, the first diagram including a first feature having a first visual characteristic and a second feature having a second visual characteristic, determine a first visual perception score associated with the first feature and a second visual perception score associated with the second feature, determine a third visual characteristic for the first feature, the third visual characteristic to increase the first visual perception score, generate second image data corresponding to the second diagram including the first and second features, the first feature having the third visual characteristic and the second feature having the second visual characteristic, and display the second diagram via the user interface.
G06T 11/20 - Traçage à partir d'éléments de base, p. ex. de lignes ou de cercles
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
Techniques for automatically generating a process definition for an industrial process to create a product in an industrial plant are provided, including capturing sensor data associated with an individual performing a set of process operations to a set of process materials to make a product, analyzing the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product, and identifying, based on analyzing the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product, a process definition including the set of process materials, the equipment used to make the product, the set of process operations applied to the materials to make the product, a sequence of the process operations, a timing of the process operations, and/or a quantity of materials used in the process.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
Methods and apparatus for artificial intelligence control of process control systems are described. An example non-transitory machine readable storage medium comprising instructions to cause programmable circuitry to at least: collect a measurement of an operation of a process; utilize machine learning based on a state of the process and a goal function that references one or more measurement(s); and modify operation of a controller based on the machine learning.
Methods and apparatus for artificial intelligence control of process control systems are described. An example non-transitory machine readable storage medium comprising instructions to cause programmable circuitry to at least: collect a measurement of an operation of a process; utilize machine learning based on a state of the process and a goal function that references one or more measurement(s); and modify operation of a controller based on the machine learning.
G05B 13/04 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
23.
I/O CARRIER AND BACKPLANE FOR INDUSTRIAL PROCESS CONTROL SYSTEMS
A backplane for use in an I/O device includes a first bus configured to communicatively couple each of a plurality of electronic marshalling component (EMC) slots to each of one or more I/O processor module slots. The I/O device also includes a second bus, redundant to the first bus, configured to communicatively couple each of the plurality of EMC slots to each of the one or more I/O processor module slots. For each pair of a one of the plurality of EMC slots and a one of the one or more I/O processor module slots, a first path length of the first bus between the pair is the same as a second path length of the second bus between the pair, such that data transmitted between the pair on the first bus has a same latency as data transmitted between the pair on the second bus.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
24.
I/O CARRIER AND BACKPLANE FOR INDUSTRIAL PROCESS CONTROL SYSTEMS
An I/O device is configured to couple a plurality of process control field devices to a process controller controlling a process in an industrial process plant. The I/O device includes a backplane and a plurality of electronic marshalling component (EMC) slots. The EMC slots are each configured to receive a respective EMC and to receive either of (i) a first-type EMC associated with a first communication protocol or (ii) second-type EMC associated with a second communication protocol. The I/O device also includes I/O processor module slots, each communicatively coupled, via the backplane, to each of the EMC slots and to each of a first one or more connectors and a second one or more connectors in each of the EMC slots. The I/O device further includes communication ports, each communicatively coupled to the I/O processor module slots via the backplane.
Methods and apparatus to modify user interfaces using artificial intelligence are disclosed. An example apparatus comprises instructions access first image data corresponding to a first diagram representing a process control system, the first diagram to be displayed via a user interface of the process control system, the first diagram including a first feature having a first visual characteristic and a second feature having a second visual characteristic, determine a first visual perception score associated with the first feature and a second visual perception score associated with the second feature, determine a third visual characteristic for the first feature, the third visual characteristic to increase the first visual perception score, generate second image data corresponding to the second diagram including the first and second features, the first feature having the third visual characteristic and the second feature having the second visual characteristic, and display the second diagram via the user interface.
Systems, apparatus, articles of manufacture, and methods to perform process control analytics are disclosed. An example method includes generating a prompt based on the request for analytics data, providing the prompt to a large language model for generation of analytics instructions, validating the analytics instructions to determine whether the analytics instructions are to be executed, and in response to the determination that the analytics instructions are to be executed, executing the analytics instructions to generate the analytics data.
Techniques for automatically generating a process definition for an industrial process to create a product in an industrial plant are provided, including capturing sensor data associated with an individual performing a set of process operations to a set of process materials to make a product, analyzing the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product, and identifying, based on analyzing the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product, a process definition including the set of process materials, the equipment used to make the product, the set of process operations applied to the materials to make the product, a sequence of the process operations, a timing of the process operations, and/or a quantity of materials used in the process.
A cybersecurity system for use in a process plant provides whitelisting of device specific and common practice HART read commands in process controllers and safety controllers to perform communications in a process plant that are very secure, but that still enable the implementation of advanced functionality provided in HART devices. A whitelist implementation application applies one or more whitelists in a security gateway device to determine if messages, such as HART messages, should be allowed or processed. A whitelist learning application automatically creates and configures whitelists through the use of a lock/learn mode, and a whitelist configuration application discovers Device Specific and Common Practice HART commands by issuing device description requests to specific devices, parsing the response, and communicating the whitelist configuration information with the parsed command types to the relevant process controllers and safety controllers for use in the whitelists. A user interface enables users to interact with and guide the configuration process to provide for a highly secure system that still enables the diagnostic and other high level functionality of field devices in a process plant.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
Systems, methods, and media for monitoring and controlling an operation (e.g., an automotive manufacturing operation, a chemical processing operation, an oil and gas operation, etc.) using raw sensor data inputs. A system includes a sensor device and a control system in electrical communication with the sensor device. The sensor device includes a sensor configured to generate an electrical signal indicative of a measured process variable and a converter circuit configured to receive the electrical signal and generate a raw sensor data packet using the electrical signal. The control system is configured to receive the raw sensor data packet from the sensor device, calculate a value for the measured process variable based on the raw sensor data packet, and control the operation based on the value for the measured process variable.
Systems, methods, and media for monitoring and controlling an operation (e.g., an automotive manufacturing operation, a chemical processing operation, an oil and gas operation, etc.) using raw sensor data inputs. A system includes a sensor device and a control system in electrical communication with the sensor device. The sensor device includes a sensor configured to generate an electrical signal indicative of a measured process variable and a converter circuit configured to receive the electrical signal and generate a raw sensor data packet using the electrical signal. The control system is configured to receive the raw sensor data packet from the sensor device, calculate a value for the measured process variable based on the raw sensor data packet, and control the operation based on the value for the measured process variable.
Process control systems for operating process plants are disclosed herein. The process control systems include control modules that are decoupled from the I/O architecture of the process plants using signal objects or generic shadow blocks. This decoupling is effected by using the signal objects or generic shadow blocks to manage at least part of the communication between the control modules and the field devices. Signal objects may convert between protocols used by control modules and field devices, thus decoupling the control modules from the I/O architecture. Generic shadow blocks may be automatically configured to mimic the operation of field devices within a controller executing the control modules, thus partially decoupling the control modules from the I/O architecture by using the shadow blocks to manage communication between the control modules and the field devices.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
G05B 15/02 - Systèmes commandés par un calculateur électriques
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
G06F 13/36 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus ou au système à bus communs
A model predictive control (MPC) device includes an input interface configured to receive an industrial process input associated with at least one component of a process automation plant, an output interface configured to transmit a control instruction to control the component, memory configured to store first and second MPC process models corresponding to different states, and a processor configured to identify a current state parameter of an industrial process, and predict a future industrial process output using the first or second MPC process model, based on the current state parameter being associated with the first or second MPC process model. The processor is configured to calculate a target operating point according to the predicted future industrial process output, determine a control signal to drive the industrial process to the calculated target operating point, and output the determined control signal to control operation of the component of the industrial process plant.
G05B 13/04 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
G05B 17/02 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes électriques
33.
MODEL PREDICTIVE CONTROL SYSTEMS FOR PROCESS AUTOMATION PLANTS
A model predictive control (MPC) device includes an input interface configured to receive an industrial process input associated with at least one component of a process automation plant, an output interface configured to transmit a control instruction to control the component, memory configured to store first and second MPC process models corresponding to different states, and a processor configured to identify a current state parameter of an industrial process, and predict a future industrial process output using the first or second MPC process model, based on the current state parameter being associated with the first or second MPC process model. The processor is configured to calculate a target operating point according to the predicted future industrial process output, determine a control signal to drive the industrial process to the calculated target operating point, and output the determined control signal to control operation of the component of the industrial process plant.
G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme
34.
FIELD DEVICE LOOP WARNING PARAMETER CHANGE SMART NOTIFICATION
A system validates critical parameter changes in a DCS by intercepting commands, transmitting warnings, receiving responses, and releasing commands if allowed. A method involves intercepting parameter change commands, transmitting warnings, receiving responses, and releasing commands if responses allow. A non-transitory computer-readable medium causes a computer to intercept commands, transmit warnings, receive responses, and release commands if allowed.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
H04L 41/0686 - Présence d’informations supplémentaires dans la notification, p. ex. pour l’amélioration de métadonnées spécifiques
H04L 41/069 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant des journaux de notificationsPost-traitement des notifications
H04L 67/125 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance en impliquant la commande des applications des terminaux par un réseau
H04L 67/75 - Services réseau en affichant sur l'écran de l'utilisateur les conditions du réseau ou d'utilisation
A networking device and networking method for use in industrial automation applications. The networking device includes redundant circuitry that can allow the networking device to continue normal operation in the event of a failure that occurs with hardware of the networking device. The networking device includes both primary and secondary network switch circuits, and associated components. The networking device can be an advanced physical layer (APL) switch that interfaces with APL field devices.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
36.
SECONDARY CONTROL FOR DE-ENERGIZING SAFETY FIELD DEVICES WITH DIGITAL PROTOCOLS
A two-wire routing device (102, 122, 124) includes an upstream communication interface for communication with a controller (112), a two-wire communication and power interface configured to convey communication and power to a field device (116) over a two-wire link, and a router electronic controller. The router electronic controller is coupled to the upstream communication interface and the two- wire communication and power interface. The router electronic controller receives, via the upstream communication interface, a safe state command from the controller, and transmits, via the two-wire communication and power interface, the safe state command to a field device over the two-wire link. The router electronic controller further executes a secondary de-energization scheme for the field device to control a power switch to cut power over the two-wire link to the field device.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
37.
Secondary control for de-energizing safety field devices with digital protocols
A two-wire routing device includes an upstream communication interface for communication with a controller, a two-wire communication and power interface configured to convey communication and power to a field device over a two-wire link, and a router electronic controller. The router electronic controller is coupled to the upstream communication interface and the two-wire communication and power interface. The router electronic controller receives, via the upstream communication interface, a safe state command from the controller, and transmits, via the two-wire communication and power interface, the safe state command to a field device over the two-wire link. The router electronic controller further executes a secondary de-energization scheme for the field device to control a power switch to cut power over the two-wire link to the field device.
G06F 15/173 - Communication entre processeurs utilisant un réseau d'interconnexion, p. ex. matriciel, de réarrangement, pyramidal, en étoile ou ramifié
A networking device and networking method for use in industrial automation applications. The networking device includes redundant circuitry that can allow the networking device to continue normal operation in the event of a failure that occurs with hardware of the networking device. The networking device includes both primary and secondary network switch circuits, and associated components. The networking device can be an advanced physical layer (APL) switch that interfaces with APL field devices.
To provide enhanced search capabilities in a process control system, a knowledge repository is generated that includes both contextual data and time series data. The contextual data organizes process plant-related data according to semantic relations between the process plant-related data and the process plant entities. When a user submits a process plant search query related to process plant entities within a process plant, search results are obtained by identifying a data set from the knowledge repository. The contextual data categorizes process parameters so that users can search for a particular process parameter category. Users can tag previous searches to execute them once again at a later time. Users can also execute queries for predicted or future states of process plant entities, batch queries regarding batch processes, soft sensor analytics and monitoring applications, parameter lifecycle applications, perturbation applications, step testing applications, or batch provisioning and scheduling applications using the knowledge repository.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric performs various control, monitoring, diagnostics, simulation, and configuration activities with respect to a plurality of devices at the one or more specific sites.
Gateway devices, systems, and methods for facilitating control system upgrades including hosting a web application via a gateway device that permits configuration of the gateway device via a web browser. A redundant gateway system can be implemented such that both a primary gateway device and a secondary gateway device are used in conjunction. The web application can provide significant advantages in terms of ease of configurability and integration of legacy input/output (I/O) systems to facilitate control system upgrades in a variety of applications.
H04L 12/66 - Dispositions pour la connexion entre des réseaux ayant différents types de systèmes de commutation, p. ex. passerelles
H04L 67/025 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP] pour la commande à distance ou la surveillance à distance des applications
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
42.
ENTERPRISE ENGINEERING AND CONFIGURATION FRAMEWORK FOR ADVANCED PROCESS CONTROL AND MONITORING SYSTEMS
An enterprise engineering and configuration system includes a common configuration database and support services stored in and executed in a compute fabric of an enterprise. The configuration database and support services use and implement a common configuration data schema to support the configuration of hardware and software in the compute fabric and at multiple different sites or physical locations of the enterprise even when different control and automation systems are used at these different sites or physical locations. The configuration system enables implementing hardware or software configuration changes to various different sites or locations of an enterprise either centrally from a configuration device connected directly to the compute fabric of the enterprise or locally from any physical location or site of the enterprise, while maintaining a single integrated enterprise configuration database that stores configuration data for each of the multiple sites of the enterprise. This configuration system is flexible as it enables engineering and configuration changes to be made by users anywhere in the enterprise for any of the sites of the enterprise and across different sites of the enterprise.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the software executing in the compute fabric by accessing and downloading new components for execution in the compute fabric from a centralized registry. The configuration system may provide feedback regarding the operation of the new component to a component developer to enable the developer to test and alter the component. The configuration system makes it possible for a user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric is implemented in a spoke and hub configuration in which the compute fabric includes computing infrastructure organized into one or more hubs, with each hub disposed in a particular geographical region or area. Each hub of the compute fabric may include communication connections in the form of spokes to each of a plurality of geographical locations or areas, such as plants, and may store and process the data from each of the associated spokes in the hub. The various different hubs may be used to organize or control what enterprise data is processed or handled in particular geographical regions and where enterprise actions, such as control actions, take place in the enterprise.
A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented. One or more applications, executing via the location-agnostic compute fabric, provide for access, management, and/or reconfiguration of various aspects of one or more process control systems across one or more physical sites operated by an enterprise. The one or more applications may, for example, provide for viewing of operational parameters and/or health statuses based upon information accessed from one, two, three four or more physical sites.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
G05B 19/18 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
47.
ENTERPRISE ENGINEERING AND CONFIGURATION FRAMEWORK FOR ADVANCED PROCESS CONTROL AND MONITORING SYSTEMS
An enterprise engineering and configuration system includes a common configuration database and support services stored in and executed in a compute fabric of an enterprise. The configuration database and support services use and implement a common configuration data schema to support the configuration of hardware and software in the compute fabric and at multiple different sites or physical locations of the enterprise even when different control and automation systems are used at these different sites or physical locations. The configuration system enables implementing hardware or software configuration changes to various different sites or locations of an enterprise either centrally from a configuration device connected directly to the compute fabric of the enterprise or locally from any physical location or site of the enterprise, while maintaining a single integrated enterprise configuration database that stores configuration data for each of the multiple sites of the enterprise. This configuration system is flexible as it enables engineering and configuration changes to be made by users anywhere in the enterprise for any of the sites of the enterprise and across different sites of the enterprise.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
48.
CONFIGURATION SUPPORT FOR A PROCESS CONTROL OR AUTOMATION SYSTEM
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the software executing in the compute fabric by accessing and downloading new components for execution in the compute fabric from a centralized registry. The configuration system may provide feedback regarding the operation of the new component to a component developer to enable the developer to test and alter the component. The configuration system makes it possible for a user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
G05B 19/18 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
49.
COMPUTE FABRIC FUNCTIONALITIES FOR A PROCESS CONTROL OR AUTOMATION SYSTEM
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric performs various control, monitoring, diagnostics, simulation, and configuration activities with respect to a plurality of devices at the one or more specific sites.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
50.
AUTHENTICATION/AUTHORIZATION FRAMEWORK FOR A PROCESS CONTROL OR AUTOMATION SYSTEM
An architecture supporting a process control or automation system may include an authentication service which determines whether an entity (e.g., a human, automated, virtual, or physical entity) is the party the entity claims to be, and an authorization service which determines whether a request of the entity to access a resource is allowed. The authentication service provides unique identities of entities and respective security credentials, e.g. tokens utilized during authorization. The authorization service authorizes an entity to access a requested resource based on role-based permissions of a role to which the entity is assigned and resource access permissions protecting the requested resource. The role-based permissions and/ or the resource access permissions may be respectively scoped to limit or restrict actions, activities, operations, and/or resource access based on specified criteria. Each entity may be authenticated, and each request of an authenticated entity may be authorized.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific plant sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices using a communications gateway device at each plant site that provides secured communications between the compute fabric and the one or more physical control or field devices at each plant site. The communications gateway at each plant site implements one or more secured point-to-point or peer-to-peer communication networks between the compute fabric and the plant site using one or more virtual private networks.
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
52.
SPOKE AND HUB CONFIGURATION FOR A PROCESS CONTROL OR AUTOMATION SYSTEM
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric is implemented in a spoke and hub configuration in which the compute fabric includes computing infrastructure organized into one or more hubs, with each hub disposed in a particular geographical region or area. Each hub of the compute fabric may include communication connections in the form of spokes to each of a plurality of geographical locations or areas, such as plants, and may store and process the data from each of the associated spokes in the hub. The various different hubs may be used to organize or control what enterprise data is processed or handled in particular geographical regions and where enterprise actions, such as control actions, take place in the enterprise.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
H04L 12/66 - Dispositions pour la connexion entre des réseaux ayant différents types de systèmes de commutation, p. ex. passerelles
53.
GENERAL REINFORCEMENT LEARNING FRAMEWORK FOR PROCESS MONITORING AND ANOMALY/ FAULT DETECTION
A method includes receiving a metric-reward mapping; and using reinforcement machine learning to train a state-action mapping. A method includes receiving a set of metrics corresponding to an ongoing industrial control process; determining anomaly/fault and normal action values by reference to a reinforcement learning-determined state-action mapping; and causing a remedial action to occur. A process control system includes an anomaly/fault detection device, that receives metrics, determines anomaly/fault and normal action values; and causes a remedial action to occur.
A method includes receiving a metric-reward mapping; and using reinforcement machine learning to train a state-action mapping. A method includes receiving a set of metrics corresponding to an ongoing industrial control process; determining anomaly/fault and normal action values by reference to a reinforcement learning-determined state-action mapping; and causing a remedial action to occur. A process control system includes an anomaly/fault detection device, that receives metrics, determines anomaly/fault and normal action values; and causes a remedial action to occur.
G06N 3/006 - Vie artificielle, c.-à-d. agencements informatiques simulant la vie fondés sur des formes de vie individuelles ou collectives simulées et virtuelles, p. ex. simulations sociales ou optimisation par essaims particulaires [PSO]
G05B 13/00 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé
Methods, apparatus, systems, and articles of manufacture are disclosed. An apparatus for executing a rule includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to access a property value from a data collector, the property value including an operational value of a workstation within a process control system, create a data model instance representing the workstation, apply the property value to the data model instance, identify a rule associated with the data model instance, cause execution of an executable package associated with the rule using the data model instance; and record a result of the execution of the executable package.
G07C 3/08 - Enregistrement ou indication de la production de la machine avec ou sans enregistrement du temps de fonctionnement ou d'arrêt
H04L 41/0663 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant la reprise sur incident de réseau en réalisant des actions prédéfinies par la planification du basculement, p. ex. en passant à des éléments de réseau de secours
H04L 41/0681 - Configuration des conditions de déclenchement
G06F 11/22 - Détection ou localisation du matériel d'ordinateur défectueux en effectuant des tests pendant les opérations d'attente ou pendant les temps morts, p. ex. essais de mise en route
Methods, apparatus, systems, and articles of manufacture are disclosed. An apparatus for executing a rule includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to access a property value from a data collector, the property value including an operational value of a workstation within a process control system, create a data model instance representing the workstation, apply the property value to the data model instance, identify a rule associated with the data model instance, cause execution of an executable package associated with the rule using the data model instance; and record a result of the execution of the executable package.
G05B 13/04 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
57.
Industrial process control system as a data center of an industrial process plant
A distributed control system (DCS) of an industrial process plant includes a data center storing a plant information model that includes a description of physical components, the control framework, and the control network of the plant using a modeling language. A set of exposed APIs provides DCS applications access to the model, and to an optional generic framework of the data center which stores basic structures and functions from which the DCS may automatically generate other structures and functions to populate the model and to automatically create various applications and routines utilized during run-time operations of the DCS and plant. Upon initialization, the DCS may automatically sense the I/O types of its interface ports, detect communicatively connected physical components within the plant, and automatically populate the plant information model accordingly. The DCS may optionally automatically generate related control routines and/or I/O data delivery mechanisms, HMI routines, and the like.
G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme
G06F 13/38 - Transfert d'informations, p. ex. sur un bus
G05B 19/05 - Automates à logique programmables, p. ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes
G05B 19/41 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par l'interpolation, p. ex. par le calcul de points intermédiaires entre les points extrêmes programmés pour définir le parcours à suivre et la vitesse du déplacement le long de ce parcours
58.
PUBLISH-SUBSCRIBE COMMUNICATION ARCHITECTURE FOR FIELD DEVICES IN CONTROL AND AUTOMATION SYSTEMS
A method includes receiving at a field device, from a first client device or application, a message indicating a selection of a first one of a plurality of publish categories corresponding to a type of information desired by the first client device or application. The method further includes transmitting, from the field device to the first client device or application, an identification of each of a plurality of publish lists corresponding to the first one of the selected publish category. The publish lists are stored on the field device and each includes a set of parameters associated with the field device. The method includes receiving at the field device, from the first client device or application, a selection of a publish list identified by the field device, and transmitting, from the field device to the first client device or application, the set of parameters associated with the selected publish list.
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
G05B 15/02 - Systèmes commandés par un calculateur électriques
G05B 19/05 - Automates à logique programmables, p. ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
59.
Industrial process control system as a data center of an industrial process plant
A distributed control system (DCS) of an industrial process plant includes a data center storing a plant information model that includes a description of physical components, the control framework, and the control network of the plant using a modeling language. A set of exposed APIs provides DCS applications access to the model, and to an optional generic framework of the data center which stores basic structures and functions from which the DCS may automatically generate other structures and functions to populate the model and to automatically create various applications and routines utilized during run-time operations of the DCS and plant. Upon initialization, the DCS may automatically sense the I/O types of its interface ports, detect communicatively connected physical components within the plant, and automatically populate the plant information model accordingly. The DCS may optionally automatically generate related control routines and/or I/O data delivery mechanisms, HMI routines, and the like.
G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme
G06F 13/38 - Transfert d'informations, p. ex. sur un bus
G05B 19/05 - Automates à logique programmables, p. ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes
G05B 19/41 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par l'interpolation, p. ex. par le calcul de points intermédiaires entre les points extrêmes programmés pour définir le parcours à suivre et la vitesse du déplacement le long de ce parcours
60.
Quick Activation Techniques for Industrial Augmented Reality Applications
An augmented reality (AR) node location and activation technique for use in an AR system in a process plant or other field environment quickly and easily detects an AR node in a real-world environment and is then able to activate an AR scene within the AR system, which improves the usability and user experience of the AR system. The AR node location and activation system generally enables users to connect to and view an AR scene within an AR system or platform even when the user is not directly at an existing AR node, when the user is experiencing poor lighting conditions in the real-world environment and in situations in which the user is unfamiliar with the AR nodes that are in the AR system database. As a result, the user can quickly and easily activate the AR system and connect to an AR scene for an AR node close to the user in the field environment under varying weather and lighting conditions in the field and without requiring a large amount of image processing to locate the correct AR scene based on photographic images provided by the user.
G06V 20/20 - ScènesÉléments spécifiques à la scène dans les scènes de réalité augmentée
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
Methods, apparatus, systems, and articles of manufacture are disclosed for an application marketplace for process control systems. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to detect at least one of a configuration or a state of operation of a process control system based on telemetry data associated with the process control system, execute a machine learning model to generate an output based on the at least one of the configuration or the state of operation, the output to be representative of a recommendation to change a portion of the process control system, and cause a change of the portion of the process control system based on the recommendation.
Methods, apparatus, systems, and articles of manufacture are disclosed. An example system to modify an industrial control system includes: at least one memory; programmable circuitry; and instructions to cause the programmable circuitry to: configure a device driver based on a first command, the first command to configure the device driver to initiate a device-specific communication protocol to collect input data from a publisher device coupled to the device driver; access a second command from a subscriber device, the second command to include a device identifier of the publisher device and to specify at least one of a communication mode, a device calibration configuration, or a fault detection configuration, the second command based on a product quality prediction, the product quality prediction generated using a spectral data model; and provide the second command to the device driver.
Methods, apparatus, systems, and articles of manufacture are disclosed. An example system to modify an industrial control system includes: at least one memory; programmable circuitry; and instructions to cause the programmable circuitry to: configure a device driver based on a first command, the first command to configure the device driver to initiate a device-specific communication protocol to collect input data from a publisher device coupled to the device driver; access a second command from a subscriber device, the second command to include a device identifier of the publisher device and to specify at least one of a communication mode, a device calibration configuration, or a fault detection configuration, the second command based on a product quality prediction, the product quality prediction generated using a spectral data model; and provide the second command to the device driver.
Methods, apparatus, systems, and articles of manufacture are disclosed for an application marketplace for process control systems. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to detect at least one of a configuration or a state of operation of a process control system based on telemetry data associated with the process control system, execute a machine learning model to generate an output based on the at least one of the configuration or the state of operation, the output to be representative of a recommendation to change a portion of the process control system, and cause a change of the portion of the process control system based on the recommendation.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
65.
I/O Server Services for Selecting and Utilizing Active Controller Outputs from Containerized Controller Services in a Process Control Environment
An I/O server service interacts with multiple containerized controller services each implementing the same control routine to control the same portion of the same plant. The I/O server service may provide the same controller inputs to each of the containerized controller services (e.g., representing measurements obtained by field devices and transmitted by the field devices to the I/O server service). Each containerized controller service executes the same control routine to generate a set of controller outputs. The I/O server service receives each set of controller outputs and forwards an “active” set to the appropriate field devices. The I/O server service and other services, such as an orchestrator service, may continuously evaluate performance and resource utilization in the control system, and may dynamically activate and deactivate controller services as appropriate.
G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme
66.
LOCATION SPECIFIC COMMUNICATIONS GATEWAY FOR MULTI-SITE ENTERPRISE
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific plant sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices using a communications gateway device at each plant site that provides secured communications between the compute fabric and the one or more physical control or field devices at each plant site. The communications gateway at each plant site implements one or more secured point-to-point or peer-to-peer communication networks between the compute fabric and the plant site using one or more virtual private networks.
H04L 49/253 - Routage ou recherche de route dans une matrice de commutation en utilisant l'établissement ou la libération de connexions entre les ports
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
A process control system includes one or more field devices positioned in a process control plant and a control module configured to generate control signals for controlling the one or more field devices. The control module may be configured to operate on one or more internal parameters to execute a control strategy. A control module software interface may be configured to define a set of interface parameters based on a strategy type associated with the control strategy of the control module. Each interface parameter of the set of interface parameters may be linked to one of the one or more internal parameters of the control module. Additionally, each interface parameter may be accessible by other control modules and/or other external applications.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G06F 15/173 - Communication entre processeurs utilisant un réseau d'interconnexion, p. ex. matriciel, de réarrangement, pyramidal, en étoile ou ramifié
G05B 15/02 - Systèmes commandés par un calculateur électriques
G05B 19/414 - Structure du système de commande, p. ex. automate commun ou systèmes à multiprocesseur, interface vers le servo-contrôleur, contrôleur à interface programmable
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
Methods, apparatus, systems, and articles of manufacture are disclosed for sequence of event generation for a process control system. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of execute or instantiate the machine readable instructions to obtain a first digital signal from a first field device representative of a first sensor data value labeled with a first timestamp generated by the first field device, obtain a second digital signal from a second field device representative of a second sensor data value labeled with a second timestamp generated by the second field device, and store a data association of the first and second sensor data values in a datastore, the data association representative of a sequence of events including an ordering of the first sensor data value and the second sensor data value based on the first and second timestamps.
G05B 19/04 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique
H04L 67/125 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance en impliquant la commande des applications des terminaux par un réseau
G05B 19/414 - Structure du système de commande, p. ex. automate commun ou systèmes à multiprocesseur, interface vers le servo-contrôleur, contrôleur à interface programmable
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
G16Y 40/35 - Gestion des objets, c.-à-d. commande selon une stratégie ou dans le but d'atteindre des objectifs déterminés
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model. The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model. The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually- exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
73.
MONITORING AND OPERATIONAL FUNCTIONALITIES FOR AN ENTERPRISE USING PROCESS CONTROL OR AUTOMATION SYSTEM
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model. The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented. One or more applications, executing via the location-agnostic compute fabric, provide for access, management, and/or reconfiguration of various aspects of one or more process control systems across one or more physical sites operated by an enterprise. The one or more applications may, for example, provide for viewing of operational parameters and/or health statuses based upon information accessed from one, two, three four or more physical sites.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
An industrial process control system includes a compute fabric having a first portion operating on-premises at an industrial process plant controlled by the industrial process control system and a second portion operating remotely from the industrial process plant controlled by the industrial process control system. The system also includes one or more transmitters in the process plant measuring or sensing physical parameters and includes one or more physical control elements in the process plant, each physical control element responsive to a respective setpoint parameter. The system further includes a plurality of micro-encapsulated execution environments instantiated in the compute fabric, each executing at least a portion of a control module that receives data from the one or more transmitters and transmits at least one setpoint parameter to each of the one or more physical control elements to cause the physical control elements to control a process in the industrial process plant.
An architecture supporting a process control or automation system may include an authentication service which determines whether an entity (e.g., a human, automated, virtual, or physical entity) is the party that/who the entity claims to be, and an authorization service which determines whether a request of the entity to access a resource is allowed or denied. The authentication service provides unique identities of entities and respective security credentials, which may include tokens utilized during authorization. The authorization service authorizes an entity to access a requested resource based on role-based permissions of a role to which the entity is assigned and resource access permissions protecting the requested resource. The role-based permissions and/or the resource access permissions may be respectively scoped to limit or restrict actions, activities, operations, and/or resource access based on specified criteria. Each entity may be authenticated, and each request of an authenticated entity may be respectively authorized.
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
79.
EMBEDDED DEVICE IDENTIFICATION IN PROCESS CONTROL DEVICES
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model. The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually- exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
80.
SECURING ACCESS OF A PROCESS CONTROL OR AUTOMATION SYSTEM
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model. The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
81.
SECURING CONNECTIONS OF A PROCESS CONTROL OR AUTOMATION SYSTEM
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model. The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
82.
MANAGEMENT FUNCTIONALITIES AND OPERATIONS FOR PROVIDER OF PROCESS CONTROL OR AUTOMATION SYSTEM
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model. The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually- exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs. A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
83.
Embedded Device Identification in Process Control Devices
A process control device for use in an industrial process control or automation system of an industrial process plant includes a sensor configured to measure a parameter of a process in the industrial process plant and to output to a controller in the industrial process plant the parameter measured. The process control device also or alternatively includes a control element configured to perform an action in the industrial process plant according to an input received from the controller in the industrial process plant. The process control device also includes an embedded device identifier, unique to the process control field device and associated with one or more of an owner of the process control field device, a plant location of the process control field device, a country or geographical or geopolitical region, and a device tag.
G05B 19/414 - Structure du système de commande, p. ex. automate commun ou systèmes à multiprocesseur, interface vers le servo-contrôleur, contrôleur à interface programmable
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices. The compute fabric includes an application layer that includes configured containers or containerized software modules that perform various control, monitoring and configuration activities with respect to one or more devices, control strategies and control loops, sites, plants, or facilities at which control is performed, and includes a physical layer including computer processing and data storage equipment that can be located at any desired location, including at or near a site, plant, or facility at which control is being performed, at a dedicated location away from the location at which control is being performed, in re-assignable computer equipment provided in the cloud, or any combination thereof. This control architecture enables significant amounts of both computer processing and IT infrastructure that is used to support a process plant, an industrial control facility or other automation facility to be implemented in a shared, in an offsite and/or in a virtualized manner that alleviates many of the communications and security issues present in current process and industrial control systems that attempt to implement control with shared or virtualized computing resources set up according to the well-known Purdue model.
The industrial control system architecture is protected via more secure and customizable techniques as compared to those used in Purdue model-based control systems. For example, communications between any (and in some cases, all) endpoints of the system may be protected via one or more virtual private networks to which authenticated endpoints must be authorized to access. Endpoints may include, for example, containerized components, physical components, devices, sites or locations, the compute fabric, and the like, and the VPNs may include mutually-exclusive and/or nested VPNs. External applications and services, whether automated or executing under the purview of a person, may access information and services provided by the system via only APIs, and different sets of APIs may be exposed to different users that have been authenticated and authorized to access respective sets of APIs.
A configuration system operates within the compute fabric to enable a user to easily make configuration changes to the compute fabric as the user does not generally need to specify the computer hardware within the compute fabric to use to make the configuration changes, making it possible for the user to deploy new configuration elements with simple programming steps, and in some cases with the push of a button.
A process control or automation system comprising a plurality of instantiated micro-encapsulated execution environments (MEEEs) includes a first one or more instantiated MEEEs communicatively connecting a provider of the plurality of instantiated MEEEs to a first enterprise operating a first one or more industrial or automation processes at a first one or more physical locations or sites. The system also includes a second one or more instantiated MEEEs communicatively connecting the provider to a second enterprise operating a second one or more industrial or automation processes at a second one or more physical locations or sites.
To provide search capabilities in a process control system, a contextual knowledge repository is generated that organizes process plant-related data according to semantic relations between the process plant-related data and the process plant entities. When a user submits a process plant search query related to process plant entities within a process plant, search results are obtained by identifying a data set from the contextual knowledge repository which is responsive to the process plant search query. The search results are then presented on a user interface device based on the identified data set. To allow for searches to be performed by user interface devices external to the process plant, a data diode is disposed between a field-facing component and an edge-facing component of the process plant so that data flows from the field-facing component to the edge-facing component without flowing from the edge-facing component to the field-facing component.
G06F 16/9035 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
G06F 16/9038 - Présentation des résultats des requêtes
G06F 16/908 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
G06F 16/909 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
87.
Framework for privacy-preserving big-data sharing using distributed ledger
To provide a trusted, secure, and immutable record of storage operations executed by a storage center for storing measurement data provided by a process plant, techniques are described for utilizing a distributed ledger. When a data contributor such as a process plant generates measurement data, an encrypted version of a set of measurement data is transmitted to a storage center for secure storage of the measurement data. In some instances, the data contributor divides the set of measurement data into several subsets and transmits each subset of encrypted measurement data to a different storage center. Furthermore, the storage center generates a transaction for the storage operation which is recorded in a distributed ledger. When a data subscriber retrieves the encrypted measurement data from a storage center, the data subscriber can verify the authenticity of the data based on the information recorded in the distributed ledger.
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Techniques for physically removing and replacing a simplex I/O component include plant personnel placing the component into a “REPLACEABLE” state via a user interface of the component. In response, the simplex I/O component informs the I/O subsystem thereof. The I/O subsystem stores a record of the component's REPLACEABLE state and begins to hold data values (e.g., field device values) most recently received from the component. When the I/O subsystem detects that the simplex I/O component is uncommunicative (e.g., due to being removed and replaced), based on the stored record of the “REPLACEABLE” state, the I/O subsystem retrieves the most recently received held data value and transmits it to a controller, thereby maintaining controlled (e.g., non-disruptive) execution of a control loop. When the replacement simplex I/O component initializes to an “IN-SERVICE” state, the I/O subsystem updates its state record accordingly, and resumes forwarding live field data values to the controller.
To provide enhanced search capabilities in a process control system, a knowledge repository is generated that includes both contextual data and time series data. The contextual data organizes process plant-related data according to semantic relations between the process plant-related data and the process plant entities. When a user submits a process plant search query related to process plant entities within a process plant, search results are obtained by identifying a data set from the knowledge repository. The contextual data categorizes process parameters so that users can search for a particular process parameter category. Users can tag previous searches to execute them once again at a later time. Users can also execute queries for predicted or future states of process plant entities, batch queries regarding batch processes, soft sensor analytics and monitoring applications, parameter lifecycle applications, perturbation applications, step testing applications, or batch provisioning and scheduling applications using the knowledge repository.
To provide enhanced search capabilities in a process control system, a knowledge repository is generated that includes both contextual data and time series data. The contextual data organizes process plant-related data according to semantic relations between the process plant-related data and the process plant entities. When a user submits a process plant search query related to process plant entities within a process plant, search results are obtained by identifying a data set from the knowledge repository. The contextual data categorizes process parameters so that users can search for a particular process parameter category. Users can tag previous searches to execute them once again at a later time. Users can also execute queries for predicted or future states of process plant entities, batch queries regarding batch processes, soft sensor analytics and monitoring applications, parameter lifecycle applications, perturbation applications, step testing applications, or batch provisioning and scheduling applications using the knowledge repository.
To provide enhanced search capabilities in a process control system, a knowledge repository is generated that includes both contextual data and time series data. The contextual data organizes process plant-related data according to semantic relations between the process plant-related data and the process plant entities. When a user submits a process plant search query related to process plant entities within a process plant, search results are obtained by identifying a data set from the knowledge repository. The contextual data categorizes process parameters so that users can search for a particular process parameter category. Users can tag previous searches to execute them once again at a later time. Users can also execute queries for predicted or future states of process plant entities, batch queries regarding batch processes, soft sensor analytics and monitoring applications, parameter lifecycle applications, perturbation applications, step testing applications, or batch provisioning and scheduling applications using the knowledge repository.
Methods and apparatus to generate and display trends associated with a process control system are disclosed. An example apparatus includes memory, machine readable instructions, and processor circuitry to execute the instructions to generate a first graphical user interface. The first graphical user interface to include a graphical representation of a component in a process control system. The processor circuitry to generate a second graphical user interface. The second graphical user interface to include a chart region with a trend represented therein. The trend indicative of values of a process parameter of the process control system over a period of time. The processor circuitry to automatically generate the trend in the chart region in response to a graphical element being dragged and dropped from the first graphical user interface to the second graphical user interface.
Methods and apparatus to generate and display trends associated with a process control system are disclosed. An example apparatus includes memory, machine readable instructions, and processor circuitry to execute the instructions to generate a first graphical user interface. The first graphical user interface to include a graphical representation of a component in a process control system. The processor circuitry to generate a second graphical user interface. The second graphical user interface to include a chart region with a trend represented therein. The trend indicative of values of a process parameter of the process control system over a period of time. The processor circuitry to automatically generate the trend in the chart region in response to a graphical element being dragged and dropped from the first graphical user interface to the second graphical user interface.
G06T 11/20 - Traçage à partir d'éléments de base, p. ex. de lignes ou de cercles
G05B 15/00 - Systèmes commandés par un calculateur
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
G06Q 10/0639 - Analyse des performances des employésAnalyse des performances des opérations d’une entreprise ou d’une organisation
Techniques for detecting suspicious performance of a throttling control valve (also referred to herein as a “valve”) in a process plant are described herein. For each of N time periods, a computing device determines and analyzes process parameter values for process parameters related to a valve to determine a status of the valve for the time period. The computing device compares the valve statuses over the N time periods to determine whether the valve is operating well for at least a threshold portion of at least a subset of the N time periods. In response to determining that the valve is not operating well for at least the threshold portion of at least the subset of the N time periods, the computing device determines that the valve is suspected of performing poorly, and provides an indication of the suspect valve to a user interface for display to a user.
G05B 19/408 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le maniement de données ou le format de données, p. ex. lecture, mise en mémoire tampon ou conversion de données
G05B 19/4063 - Contrôle du système de commande général
G05B 19/4065 - Contrôle du bris, de la vie ou de l'état d'un outil
An I/O server service interacts with multiple containerized controller services each implementing the same control routine to control the same portion of the same plant. The I/O server service may provide the same controller inputs to each of the containerized controller services (e.g., representing measurements obtained by field devices and transmitted by the field devices to the I/O server service). Each containerized controller service executes the same control routine to generate a set of controller outputs. The I/O server service receives each set of controller outputs and forwards an “active” set to the appropriate field devices. The I/O server service and other services, such as an orchestrator service, may continuously evaluate performance and resource utilization in the control system, and may dynamically activate and deactivate controller services as appropriate.
A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
G05B 17/00 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes
97.
Publish/subscribe protocol for real-time process control
A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
G05B 17/00 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes
98.
Industrial control system architecture for real-time simulation and process control
A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
G05B 17/00 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes
In one aspect, a micro-service control architecture provides a modular, flexible platform for designing, diagnosing, updating and/or expanding process control systems. Each service is containerized to provide portability and isolation from other components of the process control system. In another aspect, a function block diagram includes a “shadow” block that acts as an interface to an external, custom calculation engine, thereby enabling the custom calculation engine to operate synchronously with respect to other function blocks of the function block diagram.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
Process knowledge creation, development, and management techniques allow for and enable the creation of a universal process definition (UPD) of an industrial process, the automatic conversion or transformation of the UPD into different site-specific process definitions, and the implementation of the site-specific process definitions at different manufacturing, production, and/or automation sites. Typically, the UPD is site- and equipment- agnostic, and the transformation may generate and provide a set of site-specific process definition implementation files or routines to configure and/or govern the behavior of various site-specific execution systems, e.g., as site-specific operational instances of the UPD. The techniques may utilize feedback and information generated by site-specific operational instances to generate learned knowledge and update the UPD accordingly so that subsequent instantiations of the UPD may incorporate (and reap the benefits of) the learned knowledge. The techniques may automatically select a most suitable site for a particular instantiation of the UPD.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
