Abstract: A defect classification method to classify defects by using a classifier having a binary tree structure based on features of defects extracted from detected signals acquired from a defect inspection apparatus includes a classifier construction process for constructing the classifier by setting a branch condition including defect classes respectively belonging to groups located on both sides of the branch point, a feature to be used for branching, and a discriminant reference, for each branch point in the structure based on instruction of defect classes and feature data respectively associated therewith beforehand. The process includes a priority order specification process for previously specifying target classification performance of purity and accuracy for each defect class, whole and in worst case, with priority order, and an evaluation process for evaluating whether the specified target classification performance under the branching condition is satisfied and displaying a result of evaluation, every item.

Abstract: An inspecting method and apparatus for inspecting a substrate surface includes illuminating a light to the substrate surface having a film, detection of a scattered light or reflected light from a plurality of positions of the substrate surface to obtain a plurality of electrical signals, comparison of the plurality of electrical signals and a database which indicates a relationship between the electrical signals and surface roughness, and calculation of a surface roughness value based on the result of comparison.

Abstract: In case-based anomaly detection in equipment such as a plant, it is necessary to search entire learned data for partial data close to newly observed data. Which needs a long computation time. In order to solve this problem, there is provided a method, the learned data is clustered into clusters and the centers of the clusters as well as data pertaining to the clusters are stored in advance. Data close to newly observed data is selected from only the learned data pertaining to a cluster close to the newly observed data. Then, a normal model is created from the selected data and an anomaly measure is found whereas a threshold value is determined. Subsequently, an anomaly measure is found from the newly observed data and the created normal model. Then, this anomaly measure is compared with the threshold value in order to detect an anomaly of the equipment.

Abstract: When size of a defect on an increasingly miniaturized pattern is obtained by defect inspection apparatus in the related art, a value is inconveniently given, which is different from a measured value of the same defect by SEM. Thus, a dimension value of a defect detected by defect inspection apparatus needs to be accurately calculated to be approximated to a value measured by SEM. To this end, size of the defect detected by the defect inspection apparatus is corrected depending on feature quantity or type of the defect, thereby defect size can be accurately calculated.

Abstract: Provided are a method which permits complete training data and data with added errors, and enables the early and accurate discovery of errors in facilities such as a plant, and a system thereof. To achieve the objectives, (1) the behavior of temporal data is observed over time, and the trace is divided into clusters; (2) the divided cluster groups are modeled in sub spaces, and the discrepancy values are calculated as errors candidates; (3) the training data are used (compare, reference, etc.) for reference to determine the state transitions caused by the changes over time, the environmental changes, the maintenance (parts replacement), and the operation states; and (4) the modeling is a sub space method such as regression analysis or projection distance method of every N data removing N data items, (N=0, 1, 2, . . . ) (for example, when N=1, one error data item is considered to have been added, this data is removed, then the modeling is performed), or a local sub space method.

Abstract: A visual inspection method and apparatus detecting a defect with the use of a detected signal obtained by illuminating one of a light and an electron beam onto a substrate to be inspected. The visual inspection method and apparatus includes calculation of an image feature based on an image of the detected defect, calculation of a coordinate feature based on position information of the detected defect, and outputting of real defect information by performing false alarm judgment by processing with respect to one of the image feature and the coordinate feature.

Abstract: The pattern inspection apparatus of the present invention performs comparison between images of regions corresponding to patterns formed to be same patterns, thereby determining mismatch portions across the images to be defects. The apparatus includes multiple sensors that synchronously acquire images of shiftable multiple detection systems different from one another, and an image comparator section corresponding thereto. In addition, the apparatus includes a means for detecting a statistical offset value from the feature amount to be a defect, thereby properly detecting the defect even when a brightness difference is occurring in association with film a thickness difference in a wafer.

Abstract: In order to provide a facility of a plant or the like with an anomaly detection/diagnosis method and an anomaly detection/diagnosis system which are capable of detecting an anomaly of the facility with a high degree of sensitivity at an early time, pieces of maintenance-history information composed of past examples such as a work history and information on replaced parts are associated in advance with each other by the appearance frequency (context) of a keyword and, on the basis of anomaly detection making use of signals output by a multi-dimensional sensor installed in the facility as an object, the detected anomaly is linked to the pieces of maintenance-history information which are associated with each other. Thus, at a point of time prediction is detected, it is possible to give a relationship with a countermeasure such as a replacement of a part, an adjustment or a restart.

Abstract: To allow early sensing of anomalies in a manufacturing plant or other infrastructure (plant), provided is a method that acquires data of runtime status of said plant from a plurality of sensors of said plant, makes a model from training data that corresponds to the regular runtime status of said plant, employs the training data thus modeled in computing a anomaly measure of the data acquired from the sensors, and detects anomalies. In computing the anomaly measure, the anomaly is detected by recursively carrying out: a derivation of a residual error from the training data thus modeled acquired from the plurality of sensors, a removal of a signal having a residual error that is greater than a predetermined value, and a computation of the anomaly measure for the data that is acquired from the plurality of sensors whereupon the signal having the large residual error is removed.

Abstract: In a pattern inspection apparatus, influences of pattern brightness variations that is caused in association with, for example, a film thickness difference or a pattern width variation can be reduced, high sensitive pattern inspection can be implemented, and a variety of defects can be detected. Thereby, the pattern inspection apparatus adaptable to a broad range of processing steps is realized. In order to realize this, the pattern inspection apparatus of the present invention performs comparison between images of regions corresponding to patterns formed to be same patterns, thereby determining mismatch portions across the images to be defects. The apparatus includes multiple sensors capable of synchronously acquiring images of shiftable multiple detection systems different from one another, and an image comparator section corresponding thereto.

Abstract: A defect classification method to classify defects by using a classifier having a binary tree structure based on features of defects extracted from detected signals acquired from a defect inspection apparatus includes a classifier construction process for constructing the classifier by setting a branch condition including defect classes respectively belonging to groups located on both sides of the branch point, a feature to be used for branching, and a discriminant reference, for each branch point in the structure based on instruction of defect classes and feature data respectively associated therewith beforehand. The process includes a priority order specification process for previously specifying target classification performance of purity and accuracy for each defect class, whole and in worst case, with priority order, and an evaluation process for evaluating whether the specified target classification performance under the branching condition is satisfied and displaying a result of evaluation, every item.

Abstract: An inspecting method and apparatus for inspecting a substrate surface includes illuminating a light to the substrate surface having a film, detection of a scattered light or reflected light from a plurality of positions of the substrate surface to obtain a plurality of electrical signals, comparison of the plurality of electrical signals and a database which indicates a relationship between the electrical signals and surface roughness, and calculation of a surface roughness value based on the result of comparison.

Abstract: In order to provide a method and system for anomaly detection/diagnosis that can detect anomalies quickly and with high sensitivity in a machinery such as a plant, in the present disclosures, sets of maintenance record information comprising operational records, replacement part information and other past cases are associated with each other on a keyword basis, anomalies are detected on the basis of anomaly detection that targets the output signal of a multidimensional sensor attached to the machinery, and by means of connecting the detected anomaly with the associated maintenance record information, the required diagnosis/measures with respect to the anomaly that has arisen are elucidated.

Abstract: When size of a defect on an increasingly miniaturized pattern is obtained by defect inspection apparatus in the related art, a value is inconveniently given, which is different from a measured value of the same defect by SEM. Thus, a dimension value of a defect detected by defect inspection apparatus needs to be accurately calculated to be approximated to a value measured by SEM. To this end, size of the defect detected by the defect inspection apparatus is corrected depending on feature quantity or type of the defect, thereby defect size can be accurately calculated.

Abstract: A defect inspection apparatus for inspecting defects on an inspecting object includes an illuminator which irradiates a beam of light on the inspecting object, a photo-detector which detects rays of light from the inspecting object due to the irradiation of the light beam by the illuminator, a defect detector which detects a defect by processing a signal obtained through detection by the photo-detector, a characteristic quantity calculator which calculates a characteristic quantity related to a size of the defect, and a defect size calculator which uses a relation between size and characteristic quantity which is calculated by an optical simulation and calculates a size of the detected defect.

Abstract: A method and system for detecting an anomaly or a fault in equipment such as a plant. A method of representing the state of the equipment is offered. Output signals from multidimensional sensors are treated as subjects. (1) Normal learning data is created. (2) An anomaly measurement is calculated by a subspace classifier or other method. (3) Trajectories of motions of observational data and learning data are evaluated and their errors are calculated by a linear prediction method or the like. (4) The state of the equipment is represented using the anomaly measurement and the trajectories of the motions. (5) A decision is made regarding an anomaly. A case-based reasoning anomaly detection consists of modeling the learning data by the subspace classifier and detecting candidate anomalies based on the distance relationship between the observational data and the subspace. The trajectories of the motions are based on modeling using a linear prediction method.

Abstract: This invention provides method for detecting advance signs of anomalies, event signals outputted from the facility are used to create a separate mode for each operating state, a normal model is created for each mode, the sufficiency of learning data for each mode is checked, a threshold is set according to the results of said check, and anomaly identification is performed using said threshold. Also, for diagnosis, a frequency matrix is created in advance, with result events on the horizontal axis and cause events on the vertical axis, and the frequency matrix is used to predict malfunctions. Malfunction events are inputted as result events, and quantized sensor signals having anomaly measures over the threshold are inputted as cause events.

Abstract: In the failure diagnosis system of the present invention, the maintenance case information including data ambiguity and a partially deficient portion is utilized even in the case where maintenance case information having a high similarity is not sufficiently provided.

Abstract: When size of a defect on an increasingly miniaturized pattern is obtained by defect inspection apparatus in the related art, a value is inconveniently given, which is different from a measured value of the same defect by SEM. Thus, a dimension value of a defect detected by defect inspection apparatus needs to be accurately calculated to be approximated to a value measured by SEM. To this end, size of the defect detected by the defect inspection apparatus is corrected depending on feature quantity or type of the defect, thereby defect size can be accurately calculated.

Abstract: An inspecting method and apparatus for inspecting a substrate surface includes application of a light to the substrate surface, detection of scattered light or reflected light from the substrate surface due to the applied light at a plurality of positions to obtain a plurality of electrical signals, extraction of a signal in a mutually different frequency band from each of the plurality of electrical signals, and calculation of a value regarding a state of film of the substrate through an arithmetical operation process of a plurality of extracted signals in the frequency bands.