A SCADA Web HMI system includes a drawing generation device (1) and an HMI terminal device (32). A drawing editor (11) generates SVG data (21) and part runtime attribute data (22). The HMI terminal device (32) includes a Web browser (321) that reads SVG data (21) and displays an HMI screen, and an HMI Web runtime (322) that reads the part runtime attribute data (22) as setting parameters and operates on the Web browser (321). When receiving signal data corresponding to unique signal names from a monitoring target device (7), the HMI Web runtime (322) changes display of parts corresponding to the unique signal names on the HMI screen.

A method includes determining a current situation to be present in a process controlled by an industrial process control and automation system (IPCS) that includes at least one process controller coupled to input output (I/O) modules coupled to field devices including sensors and actuators that are coupled to processing equipment. Responsive to the current situation, displaying a plurality of suggested actions each including at least one step in a selectable panel in a human machine interface (HMI) associated with an operator computing system for an operator that is coupled to the process controller. Responsive to the displaying, the operator selects in the selectable panel at least one of the plurality of suggested actions (selected action). The selecting of the selected action results in the IPCS automatically implementing at least in part the step(s) associated with the selected action.

Systems and methods for benchmarking operator performance for an industrial operation are disclosed herein. In one aspect of this disclosure, a method for benchmarking operator performance for an industrial operation includes receiving input data relating to the industrial operation from one or more data sources, and processing the input data to measure operator effectiveness and build a data repository for benchmarking/analytics. The data repository may include information relating to the measured operator effectiveness, for example. Biggest contributors of operator variability may be identified based on an analysis of the data repository, and one or more actions may be taken to reduce or eliminate the biggest contributors of operator variability.

A computing system has a processor that receives client data defining one or more electrical loads of an industrial automation project. The computing system generates one or more motor control lineups based on the client data and historical data associated with a plurality of previous industrial automation projects. The computing system receives a selection of a motor control lineup form a plurality of motor control lineups. A visual representation of the selected motor control lineup is generated and transmitted for display on a graphical user interface.

Systems and methods for controlling industrial an industrial plant comprise: inputting an engineering diagram for a unit of the industrial plant, the engineering diagram including symbols representing assets of the industrial plant; extracting one or more assets from the engineering diagram using machine learning to recognize the one or more assets, the one or more assets including equipment, instruments, connectors, and lines, the lines relating the equipment, instruments, and connectors to one another; determining one or more relationships between the equipment, instruments, connectors, and lines to one another using machine learning to recognize the one or more relationships; and creating a flow graph from the equipment, instruments, connectors, and lines and the relationships between the equipment, instruments, connectors, and lines.

A technique for controlling a human machine interface is provided. A first task includes outputting a predefined criterion applicable to each of a plurality of physical objects. Each object is associated with a category within a group of at least pairwise disjoint categories with the criterion fulfilled for each object in a first category and not fulfilled for each object in a second category. Controlling the HMI for the first task includes repeatedly performing the steps of rendering an object; monitoring the HMI for an input during a predefined first time period after the rendering of the object; and updating a first metric indicative of a performance measurement in the first task. The method further comprises rendering a plurality of receptacles each enclosing one of the objects for a second task.

A method for automatically configuring an electricity distribution microgrid includes: acquiring technical data describing properties of the microgrid, notably a topology of the microgrid, and properties of at least some of the electrical equipment connected to the microgrid, by way of a software configuration tool implemented by a remote computer server; automatically generating a set of executable software functions making it possible to automatically drive the equipment of the microgrid, by taking account of the properties of the microgrid acquired by the configuration tool; and automatically installing the software functions generated on an electronic controller belonging to a microgrid control system, the controller being connected to the equipment via a communication link.

The present disclosure is directed to systems, methods and devices for facilitating object-based cross-domain industrial automation control. An object library comprising a plurality of objects may be maintained. One or more of the objects may represent physical counterparts for use in an industrial automation process. Each object of the plurality of objects in the object library may have at least one property that an automated control device operation can be programmed to act on. Each object of the plurality of objects may also have at least one property that a human machine interface component can utilize in generating display elements corresponding to the objects for display on the human machine interface. When modifications to objects in the object library are received, those modifications may be automatically deployed and incorporated in controller logic and HMI graphics and control.

A system receives operations data and determines operations indicator(s) from the operations data. An operator on a manufacturing line reports a downtime event via a human machine interface device. The system receives downtime event and uptime information. The system calculates an operations indicator, such as an overall equipment effectiveness indicator, from the downtime event and uptime information. A user interface of the system includes the operations indicator(s) and visualizations. Some visualizations include a timeline indicating downtime events and other operations events. Additional downtime and uptime information is received by the system in substantially real-time. The system dynamically calculates updated operations indicator(s) from the additional downtime and uptime information.

Techniques to facilitate programming industrial control systems to operate machinery in an industrial automation environment are disclosed herein. In at least one implementation, a user interface is displayed for a control program comprising programming logic associated with at least one machine system. Operational data associated with operating the at least one machine system controlled by an industrial controller executing the programming logic is received. The programming logic and the operational data are processed to determine contextual associations between the programming logic and the operational data. In the user interface for the control program, the operational data is displayed in context with the programming logic associated therewith based on the contextual associations.