Updating performance of a display screen in a terminal device that displays a screen for remotely monitoring an object to be controlled by a control device is appropriately maintained. An information device for factory automation connected to the control device that controls an object communicates with a terminal device having a display capable of displaying a screen for remotely monitoring the control device. The screen includes one or more components. The screen data for displaying the screen includes attributes of the respective components relating to the display, and a logic executed by the programmable indicator to determine the attribute values. When the terminal device displays a screen, the programmable indicator transmits the attributes and attribute values of the respective components in the screen data to the terminal device.

A board production management device configured to manage a board production line including an initial notification section configured to issue notification information including at least one of a contents of an error cause or a contents of countermeasures when the error cause that requires countermeasures occurs at the board production line; and an escalation notification section configured to issue the notification information after escalating in a case in which the error cause is not resolved after a specified time has elapsed since the error cause occurred. Accordingly, because when the specified time has elapsed, a notification is issued as escalating the notifyee or escalating the contents of countermeasures to resolve error causes more effectively, and compared to conventional technology in which only re-notification of the occurrence of the error cause is performed, notification is performed more efficiently, enabling an error cause that requires countermeasures to be resolved more quickly.

One embodiment of the present disclosure is a system. The system includes one or more memory devices having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations. The operations include: receiving operating data for one or more pieces of building equipment, determining one or more building faults for the one or more pieces of building equipment based on the operating data, using a fault categorization model to categorize the one or more building faults as remote fix faults or on-site fix faults based on the operating data, and performing an automated action based on a categorization of the one or more building faults as remote fix faults or on-site fix faults.

An example method includes, at a weather forecast time, determining a lag between a target renewable energy site and a first nearby site for which respective power measurements are correlated, selecting a first forecast look-ahead time, determining if the first forecast look-ahead time is less than or equal to the lag, determining a series of lagged power measurements at a time of forecast which constitute a series of correlation-based forecasts for power generation at the target site based on the lag, generating a set of ramp predictors incorporating correlation-based forecasts from the first site and the first forecast look-ahead time, receiving power forecast errors, applying sets of decision trees to the predictors and the power forecast errors to obtain predicted forecast errors, and generating second power forecasts for the set of look-ahead times of the target site based on the first power forecasts and the predicted forecast errors.

A control system, for example for an optical system, includes: an actuating element; a measuring element for acquiring actuating element measurement data of the actuating element; a regulating unit for generating a regulating signal for regulating the actuating element depending on the acquired actuating element meas-urement data; and a state monitoring unit for monitoring a state of the control system depending on the acquired actuating element measurement data. The state monitoring unit includes: a first processing unit for generating preprocessed state data depending on (i) the acquired actuating element measurement data and a physical model and/or a mathematical model of the actuating element, or (ii) the acquired actuating element measurement data, a physical model and/or a mathematical model of the actuating element and the generated regulating signal; and a second processing unit for determining the state of the control system depending on the preprocessed state data.

The present invention provides a bioreactor controller with a simple user interface comprising a microcontroller and a linear motor. The bioreactor controller is microcontroller-based, has a greater temporal accuracy, and inexpensive. The microcontroller of the bioreactor controller selects a protocol mode and a setup mode by the user, runs the protocol mode if the setup mode is not selected by the user, stops running the protocol mode for a predetermined time if the protocol mode is selected by the user until the user is completed with calculations and record-keeping, detects movement error of the bioreactor controller, and informs the error to the user.

A method includes determining, based on physical characteristics indicated by first data, a plurality of sensor operations associated with a plurality of structures. The method further includes updating a structural health management system to indicate the plurality of sensor operations and, after updating the structural health management system, sending a plurality of notifications to the plurality of portable field devices. The method further includes receiving, in response to sending the plurality of notifications, second data from the plurality of portable field devices indicating results of the plurality of sensor operations. The results are generated by a plurality of tools used to perform the plurality of sensor operations. The method further includes performing, based on the results of the plurality of sensor operations, a plurality of remote structural health monitoring operations to determine one or more structural health characteristics of each structure of the plurality of structures.

The present disclosure provides a log information obtaining system and method. The log information obtaining system includes a baseboard management controller (BMC), a storage device, a first interface, a controller and a first selector. The storage device stores log information of the electronic device. The controller obtains a first signal of the BMC and determines the working state of the BMC, the controller outputs a first selection signal when the working state of the BMC is abnormal. The first selector selects the first output terminal to output the log information received from the first input terminal to the external device. Even if the BMC cannot work normally, it can still obtain the log information of the electronic device and debug the electronic device.

A variable power generation asset may be subject to ramp events, which are large variations in power generated by the variable power generation asset within a short period of time. A variable power generation forecast system may receive or generate benchmark power forecasts and generated power measurements. Ramp predictors are based on the benchmark power forecasts and the generated power measurements. The variable power generation forecast system utilizes a feedback error correction model that predicts forecast errors for the benchmark power forecasts at various look-ahead times. The variable power generation forecast system applies sets of decision trees to the ramp predictors and last known forecast errors of the benchmark power forecasts to obtain the predicted forecast errors. The variable power generation forecast systems uses the predicted forecast errors and the benchmark power forecasts to generate more accurate power forecasts at the various look-ahead times.

The present disclosure provides a method for managing a pipe network of natural gas. The method may comprise: obtaining pipe network information of natural gas in at least one area, the pipe network information including a running time of a system of the pipe network of the natural gas and gas leakage information of the pipe network; extracting feature information based on the running time and the gas leakage information; predicting a maintenance time of the pipe network by inputting the feature information into a maintenance time prediction model.