Abstract: 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.

Abstract: 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.).

Abstract: 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.

Abstract: 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.

Abstract: 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.).

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.).

Abstract: 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.).

Abstract: 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.).

Abstract: 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.

Abstract: 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.