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.

Systems and methods for anticipating shutdown alarms for a boiler system by way of one or more machine learning (ML) or artificial intelligence (AI) models are disclosed herein. In an example embodiment, a method for anticipating shutdown alarms with respect to a boiler by way of a ML model includes receiving and storing, at one or more storage devices, a plurality of types of boiler-related data that are received at least indirectly from a plurality of internet of things (IoT) devices. The method also includes preprocessing and feature engineering the plurality of types of boiler-related data to arrive at a training data set, training the ML model, and deploying the trained model. The method further includes receiving additional boiler-related data concerning the boiler and, by way of the model, determining an alarm prediction concerning an anticipated alarm, and taking at least one action based at least upon the prediction.

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.

A method of alarm notification includes providing data for an industrial process including stored alarm event data and stored Key Performance Indicator (KPI) data, and an alarm event-KPI correlation and operator notification system. Patterns of relationships are discovered between the stored alarm event and KPI data to provide a reference pattern database that identifies KPI violation events in the KPI data as a function of the alarm event data or alarm events in the alarm event data as a function of the KPI data. Pattern matching uses a real-time alarm event and real-time KPI data to determine a pattern similarity by comparing a current sequence spanning a predetermined time of the real-time alarm event and KPI data to the patterns. When the pattern matching identifies a current alarm event or KPI violation event, an operator is notified and a predicted KPI value or feature or a predicted alarm event.

A method of alarm notification includes providing data for an industrial process including stored alarm event data and stored Key Performance Indicator (KPI) data, and an alarm event-KPI correlation and operator notification system. Patterns of relationships are discovered between the stored alarm event and KPI data to provide a reference pattern database that identifies KPI violation events in the KPI data as a function of the alarm event data or alarm events in the alarm event data as a function of the KPI data. Pattern matching uses a real-time alarm event and real-time KPI data to determine a pattern similarity by comparing a current sequence spanning a predetermined time of the real-time alarm event and KPI data to the patterns. When the pattern matching identifies a current alarm event or KPI violation event, an operator is notified and a predicted KPI value or feature or a predicted alarm event.

An actuator system includes a motor, a ballscrew assembly coupled to the motor, a no back brake device coupled to the ballscrew assembly, and a sensor coupled to the ballscrew assembly. The sensor is configured to acquire load data regarding a load applied to the no back brake device. A control module is configured to determine an estimated coefficient of friction for the no back brake device based on the load data, and transmit an alert signal based on determining that the estimated coefficient of friction is outside a predetermined range. The control module is coupled with the sensor and includes a processor coupled with a non-transitory processor-readable medium storing processor executable code.