Abstract: Disclosed is a system and method for measuring a health index of a plant in which a condition of a lower level component is reflected. The actual measurement values of lower level components are reflected to the health index such that, when an actual measurement value of a certain component deviates from a normal range, if the deviation is less likely to trip the plant, the actual measurement value of the component has a minimal influence on the health index. The condition of the plant can be more easily and conveniently monitored based on only the health index of the uppermost level layer.

Abstract: A method for predicting a plant health status, a system for predicting a plant health status, and a computer-readable storage medium in which a program for performing the method is stored are disclosed. In some embodiments, the method includes a step in which a first difference between a historical dataset and an input value is calculated, a step in which a weight based on a precision index and the calculated first difference is determined, a step in which a prediction value is determined by applying the weight to the historical data set, and a step in which a second difference between the prediction value and the input value is calculated, wherein the precision index is selected from a plurality of precision index candidates.

Abstract: Disclosed is a system and method for measuring a health index of a plant in which a condition of a lower level component is reflected. The actual measurement values of lower level components are reflected to the health index such that, when an actual measurement value of a certain component deviates from a normal range, if the deviation is less likely to trip the plant, the actual measurement value of the component has a minimal influence on the health index. The condition of the plant can be more easily and conveniently monitored based on only the health index of the uppermost level layer.

Abstract: A method for predicting a plant health status, a system for predicting a plant health status, and a computer-readable storage medium in which a program for performing the method is stored are disclosed. In some embodiments, the method includes a step in which a first difference between a historical dataset and an input value is calculated, a step in which a weight based on a precision index and the calculated first difference is determined, a step in which a prediction value is determined by applying the weight to the historical data set, and a step in which a second difference between the prediction value and the input value is calculated, wherein the precision index is selected from a plurality of precision index candidates.

Abstract: The present invention relates to a method of measuring a health index of a plant in which a condition of a lower level component is reflected and a computer-readable storage medium in which a program to perform the method is stored in which the condition of the plant is more easily and conveniently monitored based on only the health index of the uppermost level layer, in a case in which an actual measurement value of a certain component of a certain lower level layer deviates from a normal range, the actual measurement value is reflected in the health index, and, in a case in which a trip possibility of the plant due to change of an actual measurement value of a specific component is low although the actual measurement value of the component temporarily deviates from a normal range, the actual measurement value of the component has a minimal influence on the health index.

Abstract: A data collection method for a process margin monitoring system of industrial equipment includes preparing a learning data set based on data determined to be normal in an operation history of the industrial equipment so that the learning data set is sorted for each operation mode, in a case in which the industrial equipment includes equipment units performing the same functions, receiving data for each of the equipment units and processing the received data as data for the equipment units, sorting and grouping associated ones of the data in the learning data set, and sampling the collected data to reduce the amount of data.

Abstract: Disclosed is a method and an apparatus for supervising the integrated trip margin of an industrial plant facility. The apparatus includes a measurement operation value collection means for collecting a measurement operation value of a facility having a trip setting value inside the industrial plant; a trip margin calculation means for receiving the measurement operation value from the measurement operation value collection means and calculating a trip margin; and a display means for displaying a trip margin having a smallest value among trip margins of respective groups on a screen when there is a plurality of groups of objects of interest, the trip margin of which is to be supervised.