Abstract: Various embodiments described herein relate to an artificial intelligence system for integrity operating window optimization related to one or more assets. In this regard, a request to obtain one or more insights related to one or more assets is received. The request includes an asset descriptor describing the one or more assets. In response to the request, aspects of aggregated operational technology data within a knowledge graph data structure are correlated to provide the one or more insights. Additionally, one or more operational limits for the one or more assets are adjusted based on the one or more insights associated with the knowledge graph data structure.

Abstract: Various embodiments described herein relate to providing and/or employing a knowledge graph related to one or more assets. In this regard, a request to generate knowledge graph data related to one or more assets is received. The request includes an asset descriptor describing the one or more assets. In response to the request, aggregated operational technology data is obtained based on the asset descriptor and from one or more data sources associated with the one or more assets. Furthermore, the aggregated operational technology data is contextualized, based on configuration data for the one or assets and a set of contextualization rules for the one or more data sources, to generate the knowledge graph data. The knowledge graph data is also allocated within a knowledge graph data structure configured for the one or more assets.

Abstract: Various embodiments described herein relate to an enterprise data management dashboard. In this regard, a request to generate a dashboard visualization related to one or more assets is received. The request includes an asset descriptor describing the one or more assets. In response to the request, aspects of aggregated operational technology data within a knowledge graph data structure are correlated to provide one or more insights associated with the one or more assets. Additionally, the dashboard visualization is provided to an electronic interface of a computing device. The dashboard visualization includes visualization data for the one or more insights associated with the knowledge graph data structure.

Abstract: A system and method for performing management and diagnostic functions in a cloud computing system for advanced process control (APC). A cloud based APC management computer retrieves operating process data from an APC control computer and performs an iterative step test on the APC system. The iterative step test modifies at least one test parameter of the operating process data and identifies changes to a set of remaining parameters of the operating process data resulting from modification of the test parameter. The APC management computer determines at least one process variable from the iterative step test and generates at least one process model based on the process variable. The APC management computer transmits the process model to the APC control computer.

Abstract: A system and method for performing management and diagnostic functions in an advanced process control (APC) system. An APC management computer retrieves operating process data from an APC control computer and performs an iterative step test on the APC system. The iterative step test modifies at least one test parameter of the operating process data and identifies changes to a set of remaining parameters of the operating process data resulting from modification of the test parameter. The APC management computer determines at least one process variable from the iterative step test and generates at least one process model based on the process variable. The APC management computer transmits the process model to the APC control computer.

Abstract: A method includes performing an initial analysis using first data collected at a first collection frequency from a data source of a processing facility. The method also includes identifying at least one control loop in the processing facility having a potential problem based on the initial analysis and selecting a root cause analysis to execute in order to determine a root cause of the potential problem. The method further includes generating a schedule file and a loop identifier file associated with a request to collect, from the data source, second data for the at least one control loop at a higher second collection frequency for a specified duration. The request specifies the specified duration, the second collection frequency, and the at least one specified control loop. In addition, the method includes transmitting the schedule file to a data collector and the loop identifier file to a database.

Abstract: A system and method for performing management and diagnostic functions in a cloud computing system for advanced process control (APC). A cloud based APC management computer retrieves operating process data from an APC control computer and performs an iterative step test on the APC system. The iterative step test modifies at least one test parameter of the operating process data and identifies changes to a set of remaining parameters of the operating process data resulting from modification of the test parameter. The APC management computer determines at least one process variable from the iterative step test and generates at least one process model based on the process variable. The APC management computer transmits the process model to the APC control computer.

Abstract: A system and method for performing management and diagnostic functions in an advanced process control (APC) system. An APC management computer retrieves operating process data from an APC control computer and performs an iterative step test on the APC system. The iterative step test modifies at least one test parameter of the operating process data and identifies changes to a set of remaining parameters of the operating process data resulting from modification of the test parameter. The APC management computer determines at least one process variable from the iterative step test and generates at least one process model based on the process variable. The APC management computer transmits the process model to the APC control computer.

Abstract: A method of dynamic model selection for hybrid linear/non-linear process control includes developing a plurality of process models including at least one linear process model and at least one non-linear process model from inputs including dynamic process data from a processing system that runs a physical process. At least two of the plurality of process models are selected based on a performance comparison based on at least one metric, wherein the selected process models number less than a number of the plurality of process models received. A multi-model controller is generated that includes the selected process models. The physical process is simulated using the multi-model controller by applying the selected process models to obtain closed loop performance test data for each of the selected models. The performance test data is compared. A selected process model is then selected.

Abstract: Various graphical displays used for visualization of control techniques in a process control system can be provided to an operator. For example, the graphical display could include an image associated with a portion of a process and icons that are associated with corresponding process variables. At least some of the icons include a symbol that represents a change of one value of the associated process variable relative to another value of the process variable. Another graphical display could include a pigeonhole display that includes visual elements associated with corresponding process variables. Selection of a visual element could present the operator with a peephole display that includes information associated with process variables associated with the selected visual element. Each visual element displays layers of information that are associated with its process variable.

Abstract: A method of dynamic model selection for hybrid linear/non-linear process control includes developing a plurality of process models including at least one linear process model and at least one non-linear process model from inputs including dynamic process data from a processing system that runs a physical process. At least two of the plurality of process models are selected based on a performance comparison based on at least one metric, wherein the selected process models number less than a number of the plurality of process models received. A multi-model controller is generated that includes the selected process models. The physical process is simulated using the multi-model controller by applying the selected process models to obtain closed loop performance test data for each of the selected models. The performance test data is compared. A selected process model is then selected.

Abstract: Various graphical displays used for visualization of control techniques in a process control system can be provided to an operator. For example, a graphical display could include (i) an image associated with at least a portion of a process and (ii) one or more icons identifying one or more process variables associated with at least the portion of the process. Selection of an icon could present the operator with a faceplate containing information associated with at least one of the process variables. Another graphical display could include (i) a focal variable symbol identifying a focal process variable and (ii) one or more additional variable symbols identifying one or more additional process variables associated with the focal process variable. Gains associated with the additional process variables could be identified in the display. Yet another graphical display could be used to remotely invoke and control applications executing in a process control system.

Abstract: Various graphical displays used for visualization of control techniques in a process control system can be provided to an operator. For example, the graphical display could include an image associated with a portion of a process and icons that are associated with corresponding process variables. At least some of the icons include a symbol that represents a change of one value of the associated process variable relative to another value of the process variable. Another graphical display could include a pigeonhole display that includes visual elements associated with corresponding process variables. Selection of a visual element could present the operator with a peephole display that includes information associated with process variables associated with the selected visual element. Each visual element displays layers of information that are associated with its process variable.

Abstract: A method and system for process control. The control system can be operably coupled to a processing system. The control system can include control devices operably coupled to the processing system; a modeling module to provide a linear model based at least in part on the processing system; a computational module to provide controller algorithms associated with the control devices; a user interface module to present at a user interface controller information based at least in part on the linear model and the controller algorithms; and a separate coordination module for establishing communication between the modeling module, the computational module and the user interface module. One or more control signals can be provided to at least one of the control devices for controlling the processing system. In one embodiment, the modeling module can generate the linear model from a non-linear process.

Abstract: A method and system for process control. The control system can be operably coupled to a processing system. The control system can include control devices operably coupled to the processing system; a modeling module to provide a linear model based at least in part on the processing system; a computational module to provide controller algorithms associated with the control devices; a user interface module to present at a user interface controller information based at least in part on the linear model and the controller algorithms; and a separate coordination module for establishing communication between the modeling module, the computational module and the user interface module. One or more control signals can be provided to at least one of the control devices for controlling the processing system. In one embodiment, the modeling module can generate the linear model from a non-linear process.

Abstract: Various graphical displays used for visualization of control techniques in a process control system can be provided to an operator. For example, a graphical display could include (i) an image associated with at least a portion of a process and (ii) one or more icons identifying one or more process variables associated with at least the portion of the process. Selection of an icon could present the operator with a faceplate containing information associated with at least one of the process variables. Another graphical display could include (i) a focal variable symbol identifying a focal process variable and (ii) one or more additional variable symbols identifying one or more additional process variables associated with the focal process variable. Gains associated with the additional process variables could be identified in the display. Yet another graphical display could be used to remotely invoke and control applications executing in a process control system.