Provided are embodiments including a system for performing health monitoring. The system includes a measurement device configured to measure pressure of an environment, a heating element of the heater section coupled to the measurement device, a first sensing element operably coupled to a first region of the measurement device, and a second sensing element operably coupled to a second region of the measurement device. The system also includes a programmable logic that is configured to generate a status signal or flag based at least in part on conditions of the first region or the second region of the measurement device, a processing system configured to control the heating element responsive to reaching a threshold temperature, and a display configured to display a status of the first region or second region of the measurement device based at least in part on the status signal or flag.

A data classification apparatus and method for providing expanded information are proposed. The method may include collecting time-series sensor data from an Internet-of-Things (IoT) sensor provided in or installable in a machine, and generating first processed data in which the time-series sensor data is highlighted. The method may also include generating, based on the first processed data, second processed data for determining a state of the machine, and classifying the state of the machine, based on the second processed data. The state of the machine may include one or more of a first state in which the machine is active and the first processed data is included in a non-pattern section in which no pattern is visualized, and a second state in which the machine is active and the first processed data is included in a pattern section in which an arbitrary pattern is visualized.

Systems and methods for improved visualization of events logged by an asset management system are provided herein. In one aspect, a priority index can be determined for respective assets based upon the events they experience. In another aspect, one or more graphical user interfaces (GUIs) can be generated by a computing device for navigation between different assets. The GUIs can allow a user to choose from multiple navigation options for display of assets and respective asset information. As an example, asset views can include views based upon one or more of an asset hierarchy within a fleet, a priority index, or a shortlist of assets based upon personal interests of a user or shared interests of a group, also referred to as a watchlist herein. The GUIs can further allow a user to view summaries of events and/or details regarding events for selected assets, such as alarms and case assignments.

In one aspect, a method includes receiving data characterizing an alarm event report associated with a first industrial machine generated by a first user via a first web-based graphical user interface (GUI). The first web-based GUI associated with an enterprise monitoring system of an industrial enterprise that includes the first industrial machine. The alarm event report includes at least a portion of an event dataset including information of an alarm event associated with the first industrial machine, and an identity of a second user assigned to work on the alarm event report by the first user. The method further includes providing the alarm event report to a second web-based graphical user interface (GUI) associated with the enterprise monitoring system. The method also includes receiving, via a first GUI of a first monitoring system, data characterizing additional information associated with the alarm event and/or edits to the event dataset.

In some aspect, a method includes receiving data characterizing user selection of a industrial machine via a web-based graphical user interface (GUI) associated with an industrial enterprise including a plurality of industrial machines. The web-based GUI includes a first portion and a second portion. The first portion includes a first interactive graphical object indicative of a industrial machine of the plurality of industrial machines. The method also includes retrieving the data associated with the industrial machine from a first monitoring system configured to monitor the industrial machine. The method further includes generating a first visual representation of the data associated with the industrial machine. Generating the first visual representation is based on a first visual framework associated with a first identifier characteristic of the industrial machine. The method also includes displaying, in the second portion of the web-based GUI, the first visual representation.

A system for predicting machine failure may include a controller for controlling a machine, a plurality of sensors, a plugin device, a first computing device, a second computing device, and/or a third computing device. The sensors and/or the plugin device may be communicatively coupled to the controller. The first computing device may be communicatively coupled to the plugin device. The plugin device may transmit data associated with the machine to the first computing device. The first computing device may execute at least one low fidelity model to determine an interesting event associated with the machine. The second computing device may be communicatively coupled to the first computing device. The first computing device may transmit data associated with the interesting event to the second computing device. The second computing device may execute at least one high fidelity model to determine a machine failure prediction.

The present invention provides a machine abnormality marking and abnormality prediction system connected with a factory host and including a parameter streaming unit connected with the machines, an abnormality reporting unit, a prediction analysis unit, and a neural network classifier. The parameter streaming unit and the abnormal reporting unit collect data of each machine in the factory, and the collected data are compared and analyzed with historical records by the prediction analysis unit. The generated parameter values can be continuously compared with the collected data to predict the state of each machine in the factory, and provide an early warning of possible abnormality or need of maintenance, so that the personnel in the factory can arrange production line maintenance or capacity adjustment in advance or adjust the machine of the factory production line, to avoid occasional shutdown and reduce factory losses.

A method for visualizing process data in which a process control system controls and monitors an industrial technology plant, wherein the process control system automatically triggers a process alarm if the process data fulfills a trigger condition such a corresponding alarm message is transferred to an alarm system for output to an operator, triggered process data alarms are archived as a history, such that by selecting a process data item and specify a display period by the operator the alarm system simultaneously requests the history of the selected process data item process alarms assigned to a process object for the display period, where the alarm system outputs a time sequence of the process data item as a graphic and presents process data points in the graphic in an encoding that specifies for each process data point the highest priority with which process alarms have occurred during the acquisition period.

In the technical field of industrial automation, a fault diagnosis method and apparatus for a numerical control machine tool are disclosed which can improve the efficiency of diagnosing faults of numerical control machine tools by utilizing feedback information provided by users. In a fault diagnosis method of an embodiment, the fault diagnosis apparatus receives a fault symptom to be diagnosed from a user terminal, diagnoses the fault for the fault symptom to be diagnosed, returns a fault diagnosis result to the user terminal, receives feedback on the fault diagnosis result from the user terminal, and adjusts the diagnosis policy for the fault symptom to be diagnosed according to the fault diagnosis result if the feedback of the user on the fault diagnosis result indicates that the fault has been cleared.

A system and method for controlling automation includes a machine performing at least one operation and including a sensor for generating data in response to a performance of the operation by the machine. Data generated by the sensor is stored for retrieval by a server in data memory storage. The server includes at least one display template for displaying the data, and the server generates a data display by populating the at least one display template with the data. The data template can be populated with data in real time, to display the data display immediate to the generation of the data. The display template includes a data feature which is differentiated for displaying the data feature in a mode determined by the data populating the data display. The data display can be displayed in real time by a user device in communication with the server.