A system processes historical facility data that relate to facility states and modes of operation. The historical facility data are clustered into groups representing the facility states and the modes of operation. The groups are used to determine a current state and mode of the facility. When the facility is in a normal state, the system determines whether an event in the facility is an abnormality. If an abnormality is identified, the system transmits a signal indicating the abnormality.

A system for a marine vessel includes a first peripheral device including a controller, and a second peripheral device. A first serial bus connects the controller to the second peripheral device. At least one sensor is coupled to the controller via a second serial bus. The first peripheral device's controller can do one or more of the following: automatically control switches in the first peripheral device in response to information from the sensor; stage the first peripheral device upon start-up of the system; diagnose a malfunction of the first peripheral device and control the second peripheral device in response to determining that the first peripheral device is malfunctioning; and/or report a status of the first peripheral device over the serial bus.

A plurality of potential fault scenarios are accessed, wherein a given potential fault scenario of the plurality of potential fault scenarios has at least one corresponding root cause, and a representation of the given potential fault scenario comprises a don't care value. An actual fault scenario from telemetry received from a monitored system is generated. The actual fault scenario is matched against the plurality of potential fault scenarios. One or more matched causes are output as one or more probable root cause failures of the monitored system.

A system for monitoring a piece of equipment is provided to enable determination of a fault state of the piece of equipment based on data about the piece of equipment and data about other equipment. Also provided are a method of monitoring a piece of equipment and a computer-readable medium including instructions for monitoring a piece of equipment.

An equipment failure diagnosis apparatus, an equipment failure diagnosis method, a smart factory system, and an application agent configured to generate a virtual abnormal signal based on a normal signal data stored in the database, determine whether an equipment signal is an abnormal signal based on a virtual abnormal signal data for the virtual abnormal signal, and output a determination result information. Accordingly, the present disclosure can quickly and accurately diagnose a failure of equipment in a factory, even under conditions where labeling data is not present or insufficient.

The invention relates to marine vessel safety system which ensures that a marine vessel enters a safe state in the event of at least one malfunction in any vessel operation systems and components of the marine vessel. The marine vessel safety system comprises at least one vessel monitoring system, at least one malfunction evaluation system and a safe-state control system.

According to at least one aspect of the present invention, a system for automatically generating a data-center network mapping for automated alarm consolidation is provided comprising a plurality of devices, and at least one computing device communicatively coupled to each of the devices, the at least one computing device being configured to receive operational data from each of the devices, the operational data being indicative of at least one of a power path, cooling or temperature zones, or communications paths, determine, based on the operational data, device relationships between each of the devices, receive, from each of the devices, a respective alarm of a plurality of alarms, determine alarm relationships between at least two of the plurality of alarms, consolidate, based on the determined device relationships and based on the determined alarm relationships, the plurality of alarms into a consolidated alert, and provide the consolidated alert to a user.

The present disclosure belongs to the technical field of semiconductors, and provides a method and apparatus for monitoring an operating status of a machine, a storage medium, and an electronic device. The method includes: monitoring a product fabrication process in real time and obtaining a monitoring data set; extracting abnormal data points of a machine based on the monitoring data set; performing screening on the abnormal data points of the machine and obtaining target abnormal data points; presetting a quantity threshold corresponding to the target abnormal data points; and determining, based on a quantity of the target abnormal data points and the quantity threshold, whether to generate an alarm signal.

The disclosure is a method and a system for root cause identification (RCI) of faults in manufacturing and process industries. With complex interrelated multivariate data in manufacturing and process industries, the process of root RCI of faults is challenging. Further, the existing techniques for RCI have significant dependency on manual inputs and subject matter knowledge/experts. The disclosure is method and a system for root cause identification of a fault based on causal maps. The root cause of fault is identified in several steps including: generation of casual maps using data received from a manufacturing and process industry and root cause identification from the causal maps based on a Fault Traversal and Root Cause Identification (FTRCI) technique. The FTRCI identifies root cause from the causal map by identifying a fault traversal pathway from a leaf node in the causal map, wherein the fault traversal pathway is identified for even cyclic paths.

A building management system for monitoring equipment status is provided. The building management system includes a processing circuit configured to generate one or more diagnostics for a piece of building equipment based on one or more faults. The processing circuit is further configured to generate a work order based on the one or more diagnostics. The processing circuit is further configured to cause the work order to include task details for resolving the one or more faults. The task details are based on the one or more diagnostics associated with the one or more faults.