The present disclosure provides a system for ticket generation based on anomalies in equipment installed in a facility. An anomaly recognition engine receives a first-set of data from a facility management system. The anomaly recognition engine analyses the first-set of data associated with a plurality of devices. In addition, the anomaly recognition engine detects one or more anomalies in at least one device of the plurality of devices based on the analysis of the first-set of data. Further, a ticket generation module generates a ticket in an event of detection of the one or more anomalies in the at least one device of the plurality of devices associated with the facility. Furthermore, the ticket generation module prioritises the one or more tickets based on the severity of the one or more anomalies.

The present disclosure provides a method and system for predicting a maintenance time of a plurality of equipment used in a facility. A facility management system receives a sensor data from one or more sensors. A cloud platform collects the sensor data. In addition, a defect diagnostic engine analysis the sensor data for detection of one or more defects in the one or more sensors and the plurality of equipment. Further, the defect diagnostic engine detects the one or more defects in the one or more sensors and the plurality of equipment. Furthermore, the defect diagnostic engine creates a planned maintenance chart. Moreover, the defect diagnostic engine sends the planned maintenance chart to a user in real time.

A food safety system for food items in cooled environments includes a temperature sensor unit having a temperature sensor, a power supply and a data transmission element. The temperature sensor unit is positioned in a cooler, wherein the cooler has a plurality of predefined food item positions. A control center unit having a computer processor and a memory is adapted to execute a deterministic mode function to predict the core temperature change of such a food item on a predefined food item position in said cooler. The deterministic mode function depends on heat transfer parameters related to the predefined food item position of the cooler used, food specific coefficients related to the kind of food item taken from a group of food types, the environment temperature measured by the temperature sensor, and the predicted current core temperature of the food item.

Upon receipt of a signal indicating occurrence of anomalies, an information processor displays the nature of the anomalies. The information processor accepts for each anomaly, an input operation for assignment of a worker who is to handle an anomaly. Based on the assignment, the information processor notifies a terminal device of the worker of the nature of the anomaly to be handled by the worker. The terminal device displays contents of a remedy for the anomaly. The terminal device transmits progress information to the information processor. The information processor displays the progress information. The information processor further accepts an input operation for updating the assignment of a worker who is to handle the anomaly. Based on the assignment updated, the information processor notifies the terminal device of the worker of the nature of the anomaly to be handled by the worker.

A device including: a sensor for monitoring a pressure of a fluid system to produce pressure signals over a period; and a controller configured for: receiving the pressure signals over the period; establishing an operating pressure zone corresponding to the pressure signals over the period, the operating pressure zone is representative of a normal operation zone of the fluid system, the normal operation zone defined by an area bounded by a low pressure level and high pressure level, wherein the high pressure level is disposed at a level at least at a maximum pressure of the pressure signals over the period and the low pressure level is disposed at a level at most at a minimum pressure of the pressure signals over the period.

The present invention relates to a precise predictive maintenance method of a driver and the configuration includes: collecting slope information for a peak value between drive periods by connecting the peak value in a respective drive period in a driving state of the driver before a failure of the driver occurs; setting an alarm slope value for the peak value between the drive periods based on the collected slope information; and detecting, in a case where an average slope value for the peak value between the drive periods measured at a unit time interval set in a real-time driving state of the driver is more than the alarm slope value, the case as an abnormal state of the driver.

The unexpected failure of a turbomachine can be costly and dangerous. Processes may collect data from a turbomachine, calculate durations of machine events from the collected data, and apply a model to those machine-event durations to predict future machine-event durations and/or detect trends in the machine-event durations. This predictive output may be utilized to inform downstream functions regarding the health of the turbomachine. For example, a downstream function may utilize the predictive output to detect degradation or a potential future failure in the turbomachine and trigger remedial functions, such as alerts and/or controls, to prevent or mitigate the degradation or failure of the turbomachine.

A monitoring device includes: an operation record acquisition unit configured to acquire operation records indicating a transition in a load factor or a load change factor with respect to operation time leading up to failure in failure cases; a threshold setting unit configured to set a threshold to be contrasted with the load factor or the load change factor in the operation records of the failure cases; a wear rate acquisition unit configured to acquire a wear rate that is a value derived from a relation between the load factor or the load change factor and the threshold and indicates a degree of progress of wear of a device according to operation time; and a failure rate cumulative frequency acquisition unit configured to acquire a transition in a failure rate cumulative frequency of the failure cases with respect to the wear rate.

The present invention relates to the technical field of industrial networks and information security, and in particular to an industrial control system and a network security monitoring method therefor, for effectively monitoring the network security of an industrial control system. The method comprises: selecting at least one first data source related to an industrial control system and acquiring first data therefrom; counting time-varying features of the first data to serve as a behavior model for the industrial control system; acquiring second data from some or all of the at least one first data source; and determining whether the second data has the features described by the behavior model, and if so, determining that the industrial control system exhibits normal behavior, and if not, determining that the industrial control system exhibits abnormal behavior. In consideration of the certainty of the behavior of the industrial control system, a system behavior model is obtained by means of counting. A judgement regarding an abnormal system behavior is made based on the relatively determined behavior model, so that the obtained determination result is more accurate.

A method for reducing and/or managing energy-related stress in an electrical system includes processing electrical measurement data from or derived from energy-related signals captured by at least one intelligent electronic device (IED) in the electrical system to identify and track at least one energy-related transient in the electrical system. An impact of the at least one energy-related transient on equipment in the electrical system is quantified, and one or more transient-related alarms are generated in response to the impact of the at least one energy-related transient being near, within or above a predetermined range of the stress tolerance of the equipment. The transient-related alarms are prioritized based in part on at least one of the stress tolerance of the equipment, the stress associated with one or more transient events, and accumulated energy-related stress on the equipment. One or more actions are taken in the electrical system in response to the transient-related alarms to reduce energy-related stress on the equipment in the electrical system.