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.
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 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
3.
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 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
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 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 15/02 - Systems controlled by a computer electric
G05B 19/05 - Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
5.
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 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
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 - Scenes; Scene-specific elements in augmented reality scenes
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
9.
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 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
10.
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 - Routing or path finding in a switch fabric using establishment or release of connections between ports
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
12.
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.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
14.
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.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
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.
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 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
19.
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.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
22.
SMART SEARCH CAPABILITIES IN A PROCESS CONTROL SYSTEM
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 16/908 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/909 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
23.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 9/06 - Arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
25.
Operator Interactions with a Runtime Process Control System Via Enhanced Smart Search
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
28.
Methods and apparatus to generate and display trends associated with a process control system
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.
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 19/4065 - Monitoring tool breakage, life or condition
G05B 19/408 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
30.
I/O SERVER SERVICES CONFIGURED TO FACILITATE CONTROL IN A PROCESS CONTROL ENVIRONMENT BY CONTAINERIZED CONTROLLER SERVICES
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
32.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
33.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
36.
EASE OF NODE SWITCHOVERS IN PROCESS CONTROL SYSTEMS
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
A system for securely disseminating information relating to a process control plant includes a process control node and a controller that is coupled to a plurality of process control devices. The process control node includes a communicator module operable to transmit, via a first network, information of the process plant received from the controller. The system also includes a data services module operable to receive from the communicator module, via the first network, the information of the process plant and to transmit some or all of that information via a second network, and a mobile server, coupled to the second network and to a third network, and operable to receive data from the data services module. The mobile server is operable to communicate with a plurality of mobile computing devices via the third network.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04M 1/72472 - User interfaces specially adapted for cordless or mobile telephones for operating the device by selecting functions from two or more displayed items, e.g. menus or icons wherein the items are sorted according to specific criteria, e.g. frequency of use
H04W 12/088 - Access security using filters or firewalls
H04L 67/75 - Indicating network or usage conditions on the user display
G05B 15/02 - Systems controlled by a computer electric
H04L 41/0806 - Configuration setting for initial configuration or provisioning, e.g. plug-and-play
H04L 43/10 - Active monitoring, e.g. heartbeat, ping or trace-route
H04L 67/125 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
H04L 41/069 - Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
H04L 43/045 - Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
An industrial service device fleet management system implements an organized and easy to use methodology to manage the digital content stored on each of a plurality of portable or stationary devices used in a plant, such as portable maintenance devices, to assure that each of the portable devices receives or implements only the content that it is supposed to have and is upgraded at the appropriate time to include new content, features, etc. The fleet management system includes a memory for storing information related to the fleet of portable or stationary devices including device identifications, device descriptions, end user names and privileges, the current content of each of the portable devices, and templates defining configuration parameters for the portable or stationary devices. The system also includes a content downloader that obtains, stores, and downloads content (such as software and firmware upgrades, additional features, applications, drivers, knowledge articles, etc.) for execution or display in various ones of the portable or stationary devices, includes a content decider module that analyzes when and if various ones of the portable or stationary devices should be provided additional or new content, and includes a notification system that notifies users of the portable or stationary devices of the need to upgrade or provide new content to the portable or stationary devices.
H04L 67/06 - Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
39.
Methods and apparatus to implement safety applications associated with process control systems
Methods and apparatus to implement safety applications associated with process control systems are disclosed. An apparatus includes a configuration controller to: provide a plurality of available safety applications for implementation by a safety trip device to a user for selection, a first one of the safety applications associated with a first set of I/O signals, a second one of the safety applications associated with a second set of I/O signals, the first safety application implemented based on first pre-programmed instructions stored in memory of the safety trip device, the second safety application implemented based on second pre-programmed instructions stored in the memory; and, in response to a user selection of the first safety application, prompt the user to specify values for configuration settings associated with the first safety application. The apparatus also includes an I/O analyzer to implement the first safety application.
G05B 9/03 - Safety arrangements electric with multiple-channel loop, i.e. redundant control systems
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
40.
Automatic load balancing and performance leveling of virtual nodes running real-time control in process control systems
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 17/00 - Systems involving the use of models or simulators of said systems
41.
Cloud-Hosted Interface for Portable Device Communicators
A system for sharing plant device configuration data collected by handheld communicators during monitoring and servicing activities. Plant device configuration data is assigned relational identifiers such as equipment identifiers that provide additional information relevant to the configuration data for a plant device. Additional plant process identifiers may also be assigned to distinguish configuration profiles for various equipment sets. The relational data may be used to retrieve the configuration profiles for application in various efforts to replicate configurations across plants.
A set of discrete input/output (I/O) channels for one or more field devices may be grouped, organized, and connected to a field module device, which may connect to an electronic marshalling apparatus in a marshalling cabinet via an I/O channel. The field module acts as an intermediary, decoding messages received via the I/O channel to identify commands for discrete output (DO) channels that are then forwarded appropriately. The field module may also receive variable values carried by signals on discrete input (DI) channels and encode the values to a message that may be transmitted to the marshalling apparatus and controller, thus making the variable values on the DI channels available to the controller. The field module may store a profile including information that facilitates various smart commissioning techniques, including autosensing of tags, automatic tag binding, and automatic configuration of a control element corresponding to the field module.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Graphical user interface (GUI) based systems and methods are disclosed for regionizing full-size process plant displays for rendering on mobile user interface devices. A regionizer application receives a full-size process plant display that graphically represents at least a portion of a process plant that includes graphic representations of a plurality of process plant entities. The regionizer app determines display region(s) of the full-size process plant display that define corresponding view portions of the full-size process plant display. The display regions are transmitted to a mobile user interface device for rendering by a mobile display navigation app. The GUI based systems and methods can also automatically detect graphical process control loop display portions within full-size process plant displays for rendering on mobile user interface devices. The GUI based systems and methods can further refactor full-size process plant displays at various zoom and detail levels for visualization on mobile user interface devices.
A manufacturing system for a biopharmaceutical product includes first and second sets of biopharmaceutical manufacturing equipment located at a first and second enterprise sites, and memory configured to store an enterprise configuration and a process specification. The enterprise configuration includes records of one or more equipment parameters of the multiple pieces of equipment of the first and second sets of biopharmaceutical manufacturing equipment. At least one processor is configured to execute instructions determine whether at least one of the first enterprise site and the second enterprise site is capable of manufacturing the biopharmaceutical product, transmit a generated set of instructions to the determined at least one of the first enterprise site and the second enterprise site, and operate the multiple pieces of equipment at the determined at least one of the first enterprise site and the second enterprise site to manufacture the biopharmaceutical product.
A software defined (SD) process control system (SDCS) implements controller and other process control-related business logic as logical abstractions (e.g., application layer services executing in containers, VMs, etc.) decoupled from hardware and software computing platform resources. An SD networking layer of the SDCS utilizes process control-specific operating system support services to manage the usage of the computing platform resources and the creation, deletion, modifications, and networking of application layer services with devices disposed in the field environment and with other services, responsive to the requirements and needs of the business logic and dynamically changing conditions of SDCS hardware and/or software assets during run-time of the process plant (such as performance, faults, addition/deletion of hardware and/or software assets, etc.). A visualization system of the SDCS provides a user with a view as to the state of the SDCS as currently configured/running on the computing platform to enable a user to view currently configured interrelationships between logical elements of the control system and other logical and/or physical elements of the control system. The visualization system also provides performance metrics of the system as currently configured to enable a user to understand the operational health of the control system as currently configured.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
47.
VISUALIZATION OF A SOFTWARE DEFINED PROCESS CONTROL SYSTEM FOR INDUSTRIAL PROCESS PLANTS
A software defined (SD) process control system (SDCS) implements controller and other process control-related business logic as logical abstractions (e.g., application layer services executing in containers, VMs, etc.) decoupled from hardware and software computing platform resources. An SD networking layer of the SDCS utilizes process control-specific operating system support services to manage the usage of the computing platform resources and the creation, deletion, modifications, and networking of application layer services with devices disposed in the field environment and with other services, responsive to the requirements and needs of the business logic and dynamically changing conditions of SDCS hardware and/or software assets during run-time of the process plant (such as performance, faults, addition/deletion of hardware and/or software assets, etc.). A visualization system of the SDCS provides a user with a view as to the state of the SDCS as currently configured/running on the computing platform to enable a user to view currently configured interrelationships between logical elements of the control system and other logical and/or physical elements of the control system. The visualization system also provides performance metrics of the system as currently configured to enable a user to understand the operational health of the control system as currently configured.
A gateway system securely delivers and exposes data generated by and/or related to a process plant for consumption by external systems, and includes an edge-facing component that receives process plant-related data from a process plant via a field-facing component of the system. The received data may comport with an exposable data type system utilizing a syntax known to the external systems. The edge-facing component stores the received data in a data lake, and mines the data lake to thereby discover relationships between stored data points. Indications of the received data and the discovered interrelationships are stored in a contextualized process plant knowledge repository, such as a graph database, that is accessible to the external systems and other systems and applications via one or more access mechanisms, which may include utilities, services, servers, and/or applications. Some of the access mechanisms allow external applications to be installed at the edge-facing component.
G06F 16/2458 - Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
G06F 16/2457 - Query processing with adaptation to user needs
G06F 16/901 - Indexing; Data structures therefor; Storage structures
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
A software defined (SD) process control system (SDCS) includes a method executed by a discovery service for inferring information regarding a physical or logical asset of a process plant. The method includes obtaining an announcement indicative of a presence of a physical or logical asset of the process plant. The method also includes obtaining, from a context dictionary, one or more parameters retrievable from the physical or logical asset or one or more services associated with the physical or logical asset that were not indicated in the announcement. Furthermore, the method includes storing a record of the discovered physical or logical asset in a discovered item data store. The record includes an indication of the identity of the physical or logical asset and the one or more parameters or one or more services associated with the physical or logical asset that were not indicated in the announcement.
A software defined (SD) process control system (SDCS) includes a method executed by a discovery service for inferring information regarding a physical or logical asset of a process plant. The method includes obtaining an announcement indicative of a presence of a physical or logical asset of the process plant. The method also includes obtaining, from a context dictionary, one or more parameters retrievable from the physical or logical asset or one or more services associated with the physical or logical asset that were not indicated in the announcement. Furthermore, the method includes storing a record of the discovered physical or logical asset in a discovered item data store. The record includes an indication of the identity of the physical or logical asset and the one or more parameters or one or more services associated with the physical or logical asset that were not indicated in the announcement.
G05B 19/4155 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
H04L 9/30 - Public key, i.e. encryption algorithm being computationally infeasible to invert and users' encryption keys not requiring secrecy
H04W 12/069 - Authentication using certificates or pre-shared keys
H04L 9/14 - Arrangements for secret or secure communications; Network security protocols using a plurality of keys or algorithms
51.
Systems and Methods for Associating Modules in a Software Defined Control System for Industrial Process Plants
A process control system includes a plurality of field devices operating to control a process in a process plant. A communication infrastructure couples the plurality of field devices to a software-defined control system (SDCS) that receives data from the field devices and transmits instructions to the field devices. A data cluster, executing the SDCS, includes a plurality of compute nodes, each of which includes a processor executing an operating system, a memory, and a communication resource coupled to one or more other compute nodes in the data cluster. A plurality of instantiated containers, each of which is an isolated execution environment within the operating system of the compute node on which the container is instantiated, cooperate to facilitate execution of a control strategy in the SDCS. At least one of the containers in the SDCS is pinned to a component in the SDCS.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
52.
SYSTEMS AND METHODS FOR ASSOCIATING MODULES IN A SOFTWARE DEFINED CONTROL SYSTEM FOR INDUSTRIAL PROCESS PLANTS
A process control system includes a plurality of field devices operating to control a process in a process plant. A communication infrastructure couples the plurality of field devices to a software-defined control system (SDCS) that receives data from the field devices and transmits instructions to the field devices. A data cluster, executing the SDCS, includes a plurality of compute nodes, each of which includes a processor executing an operating system, a memory, and a communication resource coupled to one or more other compute nodes in the data cluster. A plurality of instantiated containers, each of which is an isolated execution environment within the operating system of the compute node on which the container is instantiated, cooperate to facilitate execution of a control strategy in the SDCS. At least one of the containers in the SDCS is pinned to a component in the SDCS.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
G06F 1/26 - Power supply means, e.g. regulation thereof
53.
Systems and Methods for Dynamically Maintained Redundancy and Load Balancing in Software Defined Control Systems for Industrial Process Plants
A software defined distributed control system (SDCS) in a process plant includes an application layer that includes a plurality of containers instantiated in a data cluster. Each of the containers is an isolated execution environment executing within the local operating system of a respective computing node. The containers cooperate to facilitate execution of a control strategy in the SDCS, and includes a hyper converged infrastructure (HCI) operating across the data cluster, which HCI is configured to communicate with the application layer via an adapter service. The HCI includes software-defined (SD) compute resources, SD storage resources, SD networking resources, and an orchestrator service. The orchestrator service is programmed to configure a first container to include a service executing within the first container. It also assigns the first container to execute on an available hardware resource to control a plurality of field devices operating in the process plant.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/455 - Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
54.
SYSTEMS AND METHODS FOR HIERARCHICAL ORGANIZATION OF SOFTWARE DEFINED PROCESS CONTROL SYSTEMS FOR INDUSTRIAL PROCESS PLANTS
A process control system includes a plurality of field devices operating to control a process. A communication infrastructure couples the field devices to a software-defined control system (SDCS) that receives data from the field devices and transmits instructions to the field devices. A data cluster, executing the SDCS, includes a plurality of computing nodes, each of which includes a processor executing an operating system, a memory, and a communication resource coupled to one or more other computing nodes in the data cluster. First and second containers, each of which is an isolated execution environment, are instantiated on a first computing node within the operating system of the first computing node. The second container is instantiated within the first container. The first and second containers correspond to levels of a hierarchical structure of the SDCS.
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 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
56.
I/O server services configured to facilitate control in a process control environment by containerized controller services
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.
An I/O server service interfaces 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 may utilize a quality-of-service metric to determine which controller outputs and/or I/O channel is “active.” 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.
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. The I/O server service may interact with other containerized services, such as containerized historian services or workstation services, to facilitate control in the plant.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
59.
Security services in a software defined control system
A software defined (SD) process control system (SDCS) includes a control container having contents which are executable during run-time of the process plant to control at least a portion of an industrial process. The SDCS also includes a security service associated with the control container and including contents which define one or more security conditions. The security service executes via a container on a compute node of the SDCS to control access to and/or data flow from the control container based on the contents of the security container.
G06F 21/33 - User authentication using certificates
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
60.
SOFTWARE DEFINED PROCESS CONTROL SYSTEM AND METHODS FOR INDUSTRIAL PROCESS PLANTS
A software defined (SD) process control system (SDCS) implements controller and other process control-related business logic as logical abstractions (e.g., application layer services executing in containers, VMs, etc.) decoupled from hardware and software computing platform resources. An SD networking layer of the SDCS utilizes process control-specific operating system support services to manage the usage of the computing platform resources and the creation, deletion, modifications, and networking of application layer services with devices disposed in the field environment and with other services, responsive to the requirements and needs of the business logic and dynamically changing conditions of SDCS hardware and/or software assets during run-time of the process plant (such as performance, faults, addition/deletion of hardware and/or software assets, etc.). Thus, dynamic (re-)allocation of hardware/software resources is primarily, if not entirely, and continually governed in real-time by present requirements and needs of application layer services as well as dynamically changing SDCS conditions.
G05B 19/4155 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
61.
SOFTWARE DEFINED PROCESS CONTROL SYSTEM AND METHODS FOR INDUSTRIAL PROCESS PLANTS
A software defined (SD) process control system (SDCS) implements controller and other process control-related business logic as logical abstractions (e.g., application layer services executing in containers, VMs, etc.) decoupled from hardware and software computing platform resources. An SD networking layer of the SDCS utilizes process control-specific operating system support services to manage the usage of the computing platform resources and the creation, deletion, modifications, and networking of application layer services with devices disposed in the field environment and with other services, responsive to the requirements and needs of the business logic and dynamically changing conditions of SDCS hardware and/or software assets during run-time of the process plant (such as performance, faults, addition/deletion of hardware and/or software assets, etc.). Thus, dynamic (re-)allocation of hardware/software resources is primarily, if not entirely, and continually governed in real-time by present requirements and needs of application layer services as well as dynamically changing SDCS conditions.
G05B 19/4155 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
62.
Security Services in a Software Defined Control System
A software defined (SD) process control system (SDCS) includes a control container having contents which are executable during run-time of the process plant to control at least a portion of an industrial process. The SDCS also includes a security service associated with the control container and including contents which define one or more security conditions. The security service executes via a container on a compute node of the SDCS to control access to and/or data flow from the control container based on the contents of the security container.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 29/06 - Communication control; Communication processing characterised by a protocol
G06F 9/455 - Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
63.
Discovery Service in a Software Defined Control System
A software defined (SD) process control system (SDCS) includes a method executed by a discovery service for inferring information regarding a physical or logical asset of a process plant. The method includes obtaining an announcement indicative of a presence of a physical or logical asset of the process plant. The method also includes obtaining, from a context dictionary, one or more parameters retrievable from the physical or logical asset or one or more services associated with the physical or logical asset that were not indicated in the announcement. Furthermore, the method includes storing a record of the discovered physical or logical asset in a discovered item data store. The record includes an indication of the identity of the physical or logical asset and the one or more parameters or one or more services associated with the physical or logical asset that were not indicated in the announcement.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/455 - Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
64.
Systems and Methods for Dynamically Maintained Redundancy and Load Balancing in Software Defined Control Systems for Industrial Process Plants
A software defined distributed control system (SDCS) in a process plant includes an application layer that includes a plurality of containers instantiated in a data cluster. Each of the containers is an isolated execution environment executing within the local operating system of a respective computing node. The containers cooperate to facilitate execution of a control strategy in the SDCS, and includes a hyper converged infrastructure (HCI) operating across the data cluster, which HCI is configured to communicate with the application layer via an adapter service. The HCI includes software-defined (SD) compute resources, SD storage resources, SD networking resources, and an orchestrator service. The orchestrator service is programmed to configure a first container to include a service executing within the first container. It also assigns the first container to execute on an available hardware resource to control a plurality of field devices operating in the process plant.
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
65.
Systems and Methods for Dynamically Maintained Redundancy and Load Balancing in Software Defined Control Systems for Industrial Process Plants
A software defined distributed control system (SDCS) in a process plant includes an application layer that includes a plurality of containers instantiated in a data cluster. Each of the containers is an isolated execution environment executing within the local operating system of a respective computing node. The containers cooperate to facilitate execution of a control strategy in the SDCS, and includes a hyper converged infrastructure (HCI) operating across the data cluster, which HCI is configured to communicate with the application layer via an adapter service. The HCI includes software-defined (SD) compute resources, SD storage resources, SD networking resources, and an orchestrator service. The orchestrator service is programmed to configure a first container to include a service executing within the first container. It also assigns the first container to execute on an available hardware resource to control a plurality of field devices operating in the process plant.
A software defined (SD) process control system (SDCS) implements controller and other process control-related business logic as logical abstractions (e.g., application layer services executing in containers, VMs, etc.) decoupled from hardware and software computing platform resources. An SD networking layer of the SDCS utilizes process control-specific operating system support services to manage the usage of the computing platform resources and the creation, deletion, modifications, and networking of application layer services with devices disposed in the field environment and with other services, responsive to the requirements and needs of the business logic and dynamically changing conditions of SDCS hardware and/or software assets during run-time of the process plant (such as performance, faults, addition/deletion of hardware and/or software assets, etc.). A visualization system of the SDCS provides a user with a view as to the state of the SDCS as currently configured/running on the computing platform to enable a user to view currently configured interrelationships between logical elements of the control system and other logical and/or physical elements of the control system. The visualization system also provides performance metrics of the system as currently configured to enable a user to understand the operational health of the control system as currently configured.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 17/00 - Systems involving the use of models or simulators of said systems
68.
FIELD DEVICE LOOP WARNING PARAMETER CHANGE SMART NOTIFICATION
A system for preventing inadvertent or untimely parameter changes to an active online field device from a secondary system different from a distributed control system application providing control instructions to the field device, where the parameter changes may cause detrimental effects to a plant process or activity. A request for a parameter change from the secondary system may be intercepted before the request is received by a field device or a controller for evaluation by an operator of the distributed control system. The validation process may provide a plant operator with override authority to approve or deny a set of critical parameter changes to an active field device or other active plant device.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 41/0686 - Additional information in the notification, e.g. enhancement of specific meta-data
H04L 41/069 - Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
H04L 67/125 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
H04L 67/75 - Indicating network or usage conditions on the user display
69.
Centralized Knowledge Repository and Data Mining System
A system for securely and efficiently obtaining data from a process plant and processing that data for consumption by one or more external applications or systems includes receiving event data from various data sources in or associated with a plant via various different data formats and data communication structures at a centralized server or gateway, striping off the communication format structure from the data, placing the data, including metadata associated with the data, into an event stream, and making the data in the event stream available to a processing infrastructure that processes that data in a comprehensive and robust manner for easy consumption by external data mining, data visualization and data analytic systems or applications.
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 16/908 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/909 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
71.
SYSTEMS AND METHODS FOR EMBEDDING A WEB FRAME WITH PRECONFIGURED RESTRICTIONS IN A GRAPHICAL DISPLAY VIEW OF A PROCESS PLANT
Techniques for embedding a web browser in a graphical display view of a process plant include presenting a graphical display view including (i) indications of one or more process control elements, such as a control module, a function block, a process plant entity, or a process section of the process plant, and (ii) a web browser having web content from a source address. The web browser is presented according to one or several presentation parameters, such as such as a size and position of the web browser within the display view. Furthermore, the presentation parameters include restrictions on functions performed within the web browser, such as a sandbox or sandbox attributes. The presentation parameters also include a source whitelist that specifies web addresses which are allowed to be set as the source address for presenting web content.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
A network design tool enables users to easily and quickly graphically design a model of a wireless communication network in a process control environment. Specifically, the network design tool may provide an interactive user interface including a canvas that enables users to design network models by way of the users placing and arranging within the canvas symbols representing model devices and links. The tool may dynamically indicate the strengths of communication links at potential locations as the user moves a pointer or cursor around the canvas, and may automatically suggest devices to be added to desired locations. After a desired device has been selected, the tool may automatically connect the selected device to other devices in the model based on an analysis of the plant environment, real-world positions of the existing devices and the new device, and signaling attributes of the existing devices and the new device.
A first component of a process control loop (e.g., a controller or I/O gateway) monitors for and detects performance degradation of a second component of the loop by sending heartbeat messages to the second component via a diagnostic channel different from a control communications channel via which the first and second components communicate control messages for controlling an industrial process. The second component utilizes its control message interpreter to return received heartbeat messages to the first component via the diagnostic channel. The first component detects degradation of the second component when the round trip time (RTT) of a heartbeat message falls outside of an acceptable range of RTTs for the second component, and may suggest or automatically initiate mitigating actions. The first component may determine the average RTT or expected response time of the second component and acceptable range of variations based on a sample number of measured RTTs.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 43/10 - Active monitoring, e.g. heartbeat, ping or trace-route
A process control system software security architecture, that is more effective at preventing zero-day or other types of malware attacks, implements the use of “least privileges” when executing the applications and services run within a computer device. The least privileges based architecture separates “service” processes from desktop applications that run on behalf of a logged-on user by partitioning the global namespace of the software system into service namespaces and logged-on user namespaces, and by strictly controlling communications between the applications and services in these different namespaces using interprocess communications. Moreover, the security architecture uses custom accounts to assure that each service process has the least set of privileges that are needed for implementing its function regardless of the privileges associated with the calling application or user.
The described methods and systems enable process control devices to transmit and receive device variable values in a manner that enables the receiving device to verify the integrity of the received values on a variable-by-variable basis. To facilitate verification of integrity, any desired number of variables in a message may have a data integrity check in the message. For each received value that has a data integrity check, the receiving device can calculate its own data integrity check based on the received value and a seed (known to both the transmitting and receiving devices), which it can then compare to the received data integrity check to verify if the received value has been altered during communication.
H04L 1/18 - Automatic repetition systems, e.g. Van Duuren systems
H04L 1/16 - Arrangements for detecting or preventing errors in the information received by using return channel in which the return channel carries supervisory signals, e.g. repetition request signals
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 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
G05B 19/05 - Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
G05B 19/41 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by interpolation, e.g. the computation of intermediate points between programmed end points to define the path to be followed and the rate of travel along that path
78.
Network resource management in a communication network for control and automation systems
A method and associated system, includes implementing a controller, configured to communicate, over a communication network, with a plurality of highly-versatile field devices coupled to the controller. The method and system also include configuring the network to facilitate communication of traffic over an advanced physical layer (APL) medium. One or more APL power switches are configured to provide connectivity to other devices and each includes a power supply to provide power via the medium. One or more APL field switches, each receiving power from a power switch, are configured to distribute both communication signals and power signals to field devices communicatively coupled to a respective field switch. The method further includes configuring a network resource management component to manage network resources to facilitate communication over the network of traffic that includes both managed traffic, of which the management component is aware, and unmanaged traffic, of which the management component is not aware.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 67/125 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
79.
Systems and methods for facilitating creation of a map of a real-world, process control environment
In a method for facilitating creation of a map of a real-world, process control environment, locations of a mobile device are tracked as a user moves through a mapped environment. A camera of the mobile device captures images of the mapped environment as the user moves through the mapped environment, and the user indicates an intention to add a node to the map. One or more images of the captured images are provided to a machine learning (ML) model, and the ML model is trained to process images to recognize object types. The ML model may predict an object type corresponding to a specific object within a field of view of the camera. A display of the mobile device may then superimpose, on a real-world view presented to the user, an indication of the predicted object type to facilitate user designation of a descriptor for the new node.
G06V 20/20 - Scenes; Scene-specific elements in augmented reality scenes
G01C 21/16 - Navigation; Navigational instruments not provided for in groups by using measurement of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
80.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 17/00 - Systems involving the use of models or simulators of said systems
81.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 17/00 - Systems involving the use of models or simulators of said systems
82.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 17/00 - Systems involving the use of models or simulators of said systems
83.
Publishing data across a data diode for secured process control communications
To secure communications from a process plant across a unidirectional data diode to a remote system, a sending device at the plant end publishes data across the diode to a receiving device at the remote end. The publication of various data is respectively in accordance with context information (e.g., identification of data sources, respective expected rate of data generation/arrival, etc.) that is descriptive of data sources of the plant and that is recurrently provided by the sending device across the diode. A recurrence interval may be based on a tolerance for lost data or another characteristic of an application, service, or consumer of data at the remote system. The publishing may leverage an industrial communication protocol (e.g., HART-IP) and/or a suitable general-purpose communication protocol (e.g., JSON).
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.
A highly versatile process control or factory automation field device is configured with an interface and communication connection structure and security features that enable 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 in a highly secure manner. The security features include a root of trust component, a secure boot component, secure memory components, secure communication components, security audit components, secure provisioning components and endpoint identity components, making the field device communications and operations secure and trustworthy. 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 in a very secure manner, using the same or different communication protocols.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 19/05 - Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
G05B 15/02 - Systems controlled by a computer electric
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
86.
Node management of nodal communication networks for highly versatile field devices in control and automation systems
A nodal communication network of a process control or factory automation system includes nodes that are highly versatile (HV) field devices storing respective tag identifications. A DHCP server assigns respective endpoint identifications to nodes that connect to the network. A network node manager manages a mapping database that stores associations of tag identifications of network nodes with the assigned endpoint identifications, and a state database that stores updated states of the network nodes. A DNS server responds, in conjunction with the network node manager, to requests for endpoint identifications to allow nodes to be discovered within the network. An HV device node is a data source that establishes and maintains (sometimes simultaneously) respective communication sessions over the network with one or more other nodes that are consumers of the data generated by the HV devices, and data delivered via the communication sessions may be used to control an industrial process.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
87.
Publish-subscribe communication architecture for highly-versatile field devices in control and automation systems
A method and system for publish-subscribe communication architecture for highly-versatile (HV) field devices in control and automation system implements reception at an HV field device, from a client device or application, of a message indicating a selection of one of a plurality of publish categories. The publish category corresponds to a type of information desired by the client device or application. The field device transmits to the client device or application an identification of each of a plurality of publish lists corresponding to the selected publish category, which publish lists are each stored on the field device and each include a set of parameters associated with the field device. The field device receives, from the client device or application, a selection of one of the publish lists identified by the field device, and transmits to the client device or application the set of parameters associated with the selected publish list.
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
88.
Edge gateway system with data typing for secured process plant data delivery
An edge gateway system securely delivers and exposes data generated by and/or related to a process plant for consumption by external systems, and includes a field-facing component that sends, to an edge-facing component of the system, a collection of data types defined based on configurations of the process plant and represented using a syntax that is native to the one or more external systems. The field-facing component streams process plant-related content data indicated by one or more interest lists to the edge-facing component, where the streamed data is expressed using the collection of data types. Each interest list may include multiple types of data (e.g., control, I/O, diagnostic, device, historical, etc.) that collectively represent a particular named entity of the plant. Accordingly, the streamed data is securely delivered and exposed, via the edge-facing component, to the external systems.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
H04L 29/06 - Communication control; Communication processing characterised by a protocol
H04L 65/61 - Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
A method and associated system, includes implementing a controller, configured to communicate, over a communication network, with a plurality of highly-versatile field devices coupled to the controller. The method and system also include configuring the network to facilitate communication of traffic over an advanced physical layer (APL) medium. One or more APL power switches are configured to provide connectivity to other devices and each includes a power supply to provide power via the medium. One or more APL field switches, each receiving power from a power switch, are configured to distribute both communication signals and power signals to field devices communicatively coupled to a respective field switch. The method further includes configuring a network resource management component to manage network resources to facilitate communication over the network of traffic that includes both managed traffic, of which the management component is aware, and unmanaged traffic, of which the management component is not aware.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
90.
Multi-Protocol Field Device in Process Control Systems
A field device includes components to communicate with a control and/or asset management system of a process control system or with other field devices using any of several different communication protocols such as several different internet protocol (IP) protocols. This architecture allows for a single version of a field device to be provided in automation or plant control systems that use any of these communication protocols, thus saving on inventory and product development costs. Moreover, the multi-protocol field device or a system using the multi-protocol field device can manage the asset (read and write parameterized data from and to the asset) using one protocol while at the same time communicating real-time process/factory automation information using a second and different protocol. Moreover, the field device may be able to communicate to other devices including other field devices and host devices using both of these protocols or other protocols for different purposes.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
H04M 1/253 - Telephone sets using digital voice transmission
91.
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 - Scenes; Scene-specific elements in augmented reality scenes
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
G06T 19/00 - Manipulating 3D models or images for computer graphics
An asset management system used in a process control plant or other control system includes a database that stores asset data for each of a plurality of devices within the plant and a viewing system that accesses the asset data to provide statistical information to a user pertaining to the plant assets. The asset management system enables a user to define and store one or more projects within the plant and a set of plant assets associated with each of the projects. Thereafter, the asset management system performs statistical analyses on the assets within one or more of the defined projects and presents, to a user via a user interface, raw and statistical information pertaining to the assets within the project. The analysis engine may determine the device states or health statuses of the assets associated with the project and may present statistical and/or historical information regarding the number or percentage of assets within the project that are in a particular state or status. The system enables a user to use this information to determine the progress of or completion percentage of the entire project.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
93.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 17/00 - Systems involving the use of models or simulators of said systems
94.
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.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G05B 17/00 - Systems involving the use of models or simulators of said systems
95.
SYSTEMS AND METHODS FOR IMPLEMENTING STANDARD OPERATING PROCEDURES IN A GRAPHICAL DISPLAY CONFIGURATION
Systems and methods for generating an SOP object and executing the SOP object is described herein. The SOP object may include (a) a first element corresponding to a description for performing one or more steps of an SOP when monitoring or controlling a process plant, (b) a second element corresponding to a link to process control data associated with a first process control element included in an operating environment of the process plant to receive real-time data corresponding to a process being controlled in the process plant; and (c) a layout defining a visual representation of the first element and the second element.
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
An Ethernet I/O card (EIOC) scanner device facilitates configuration of a process control system to enable improved integration of EIOC-enabled field devices (and associated field device variables) into the process control system. Specifically, the EIOC scanner may: (i) analyze decoder files for EIOC-enabled field devices to automatically identify field device variables that the EIOC-enabled field devices are configured to transmit or receive; and (ii) quickly and easily facilitate a configuration of the process control system to integrate into the process control system the EIOC-enabled field devices and any associated field device variables identified by the EIOC scanner.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 13/20 - Handling requests for interconnection or transfer for access to input/output bus
97.
Remote deployment and commissioning of workstations within a distributed control system
A method and a system facilitate remote commissioning of workstations for controlling, maintaining, and/or configuring process control field devices in a process control plant. Using a configuration workstation coupled to the workstation by a communication network, a user may specify a configuration for the workstation in software and, upon selecting the workstation for commissioning, can effect configuration of the workstation, according to the specified configuration, remotely from the configuration workstation. Effecting configuration of the workstation may include installing/updating an operating system, installing/updating an operator, maintenance, or configuration interface application, and/or installing/updating a process plant configuration. Upon completion of the configuration, the workstation is operable to communicate with a process controller to implement control, maintenance, and/or configuration of the process control plant.
A system and method of configuring monitor blocks and effect blocks associated with a process control system for a process plant includes causing a display device to display a graphical user interface, the graphical user interface indicating a first monitor block, a second monitor block, and an effect block. The system and method further includes enabling a user to input configuration data via the input device, including: (i) configuring one of the outputs of the first monitor block to serve as one of the inputs of the second monitor block, (ii) configuring an additional one of the outputs of the first monitor block and one of the outputs of the second monitor block to serve as inputs to the effect block, and (iii) designating at least one of the plurality of cells of each of the first monitor block, the second monitor block, and the effect block as a trigger associated with the respective input/output pair for the respective cell and corresponding to a condition in the process plant.
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 - Communication control; Communication processing characterised by a protocol
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
H04L 9/06 - Arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
A smart process control switch can implement a lockdown routine to lockdown its communication ports exclusively for use by devices having known physical addresses, enabling the smart process control switch to prevent new, potentially hostile, devices from communicating with other devices to which the smart process control switch is connected. Further, the smart process control switch can implement an address mapping routine to identify “known pairs” of physical and network addresses for each device communicating via a port of the smart process control switch. Thus, even if a new hostile device is able to spoof a known physical address in an attempt to bypass locked ports, the smart process control switch can detect the hostile device by checking the network address of the hostile device against the expected network address for the “known pair.”
H04L 45/028 - Dynamic adaptation of the update intervals, e.g. event-triggered updates
H04L 47/12 - Avoiding congestion; Recovering from congestion
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
patents
