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.

An industrial automation system that allows for communication between an operator and a processing unit, which includes contextual information, such as data, and retrieval of historical messages, for a processing unit when abnormal operational conditions are encountered, resulting in faster responses and more complete information to address the abnormal condition.

Techniques for predictive water condition monitoring are described herein. An aspect includes a method that includes monitoring, by one or more processors, at least one water sensor to establish a baseline of a water condition model and monitoring one or more water conditions. A predicted water condition is determined based on the water condition model and the one or more water conditions. An alert is transmitted to one or more devices based on determining that the predicted water condition indicates a predicted contaminant level above a threshold.

A smart digital computer platform is disclosed that collects, analyzes, and/or renders appropriate information about fugitive emissions identified by a sensor network-based emissions monitoring system in a facility. More specifically to the methods used by the smart digital computer platform to analyze, filter, and transform the collected monitoring data into a visual output that is capable of being rendered on a graphical user interface (GUI) on a screen display with, in some embodiments, a restricted form factor. For example, smart analytics may be used to cull, filter, and transform the data displayed in a pop-up dialog box on a GUI. In another example, the transformed data may be translated into a visual, graphical element that conveys an abundance of appropriate, tailored information to a particular type of user viewing the GUI.

Pellet grills and associated methods of operation are disclosed. An example pellet grill includes a main body defining a cooking chamber. The example pellet grill further includes a grease deflection bar assembly located within the main body. the grease deflection bar assembly includes a first rack removably positioned on first tabs of the main body, a second rack removably positioned on second tabs of the main body, and a grease deflection bar extending between and removably positioned on the first and second racks.

An industrial asset may have monitoring nodes that generate current monitoring node values representing a current operation of the industrial asset. An abnormality detection computer may detect when a monitoring node is currently being attacked or experiencing a fault based on a current feature vector, calculated in accordance with current monitoring node values, and a detection model that includes a decision boundary. A model updater (e.g., a continuous learning model updater) may determine an update time-frame (e.g., short-term, mid-term, long-term, etc.) associated with the system based on trigger occurrence detection (e.g., associated with a time-based trigger, a performance-based trigger, an event-based trigger, etc.). The model updater may then update the detection model in accordance with the determined update time-frame (and, in some embodiments, continuous learning).

A display system according to one or more embodiments includes: a control unit; a display unit; and a storage unit. The storage unit is configured to store a causal relationship model representing a relationship between two or more components of the plurality of components and an abnormality that may occur in the production facility, and the control unit is configured to: display, on the display unit, a model diagram that has nodes and one or more edges connecting the nodes to each other, based on the causal relationship model; and in response to a mode selection, such as a request from a user, display the model diagram in either a first mode in which all the nodes are displayed, or a second mode in which the nodes are allocated among a predetermined number of groups based on a predetermined criterion and the groups are displayed as nodes.

A software-implemented, alert-enabled passive element and method that allows a user to receive updates from unrelated sources and to provide alerts and status information within a centralized information source without customization or modification of the unrelated sources. Data and information from multiple, independent systems is integrated into a single element that provides a centralized information source. A user is provided with the ability to specify the type of data to be gathered from the independent systems, the specific location where the data is to be retrieved, and a reference value for each instance of data to be retrieved. A comparison between the retrieved data and the reference value is thus enabled. Information regarding a mismatch or retrieved value beyond or outside an acceptable value or range of values may then be provided to the user within the passive element.

An information processing apparatus includes a processing portion. The processing portion is configured to obtain information on a location of a worker associated with time information, and information on a state of a production apparatus associated with the time information. And the processing portion is configured to display an accumulated time on a display portion by using the obtained information, the accumulated time being obtained in a predetermined combination of the location of the worker and the state of the production apparatus.

A method, electronic device and system are provided for collecting information associated with operational changes made by plant operators. Episodes of operational changes are identified that include a triggering event and the operational changes performed are reviewed and compared to standard operating data or historical data. The operational changes that differ from such standard operating data or historical data are classified as inadvertent operations based upon a set of pre-determined characteristics. Training may follow to avoid recurrence of such inadvertent operations in the future.