Abstract: Anomaly sign detection methods such as those found in plants cannot detect anomalies when relevant sensor information is not acquired, and while it is possible to detect anomalies through changes in sensor output when manual operations are performed, it is difficult to distinguish between anomalies such as those caused only by the sensor signal and actual anomalies which should be detected. The disclosed method uses event signals, which contain a signal based on the status of a unit unable to acquire sensor information and a signal based on human operations. An event sequence is extracted from an event signal outputted from a piece of equipment and grouped by clustering, then a frequency matrix is created for the alarms generated within a prescribed interval of an event sequence, and a prediction of alarms with a high probability of occurring for an event sequence is output on the basis of the frequency matrix.

Abstract: An apparatus for inspecting pattern defects, the apparatus including: an image acquisition unit which acquires an image of a specimen and stores the acquired image in an image memory; a defect candidate extraction unit which performs a defect candidate extraction process by using the acquired image, which is read from the image memory; and a defect detection unit which performs a defect detection process based on a partial image containing a defect candidate that is extracted by the defect candidate extraction unit, wherein the defect detection process performed by the defect detection unit is performed asynchronously with an image acquisition process that is performed by the image acquisition unit.

Abstract: In an inspection subject substrate, there is a problem that a defect signal is overlooked due to scattered light from a pattern and sensitivity decreases in an irregular circuit pattern part. The inventors propose a defect inspection method, characterized by comprising: an illumination step of guiding light emitted from a light source to a predetermined area on an inspection subject substrate under a plurality of predetermined optical conditions; a detection step of obtaining an electric signal by guiding scattered light components propagating in a predetermined range of azimuthal angle and in a predetermined range of elevation angle to a detector for each of a plurality of scattered light distributions occurred correspondingly to the plurality of optical conditions in the predetermined area; and a defect determination step of determining a defect based on the plurality of electric signals obtained in the detection step.

Abstract: According to the present invention, for a pattern inspection apparatus that compares images in corresponding areas of two patterns that are identical and that determines an unmatched portion between the images is a defect, a plurality of detection systems and a plurality of corresponding image comparison methods are provided. With this configuration, the affect of uneven brightnesses for a pattern that occurs due to differences in film thicknesses can be reduced, a highly sensitive pattern inspection can be performed, a variety of defects can be revealed, and the pattern inspection apparatus can be applied for processing performed within a wide range. Furthermore, the pattern inspection apparatus also includes a unit for converting the tone of image signals of comparison images for a plurality of different processing units, and when a difference in brightness occurs in the same pattern of the images, a defect can be correctly detected.

Abstract: A pattern inspection method and apparatus in which a deep ultraviolet light or an ultraviolet light is irradiated onto a specimen on which a pattern is formed, an image of the specimen which is irradiated with the deep ultraviolet light or the ultraviolet light is formed and the formed image is detected with a rear-surface irradiation type image sensor, which is sensitive to wavelengths of no greater than 400 nmm. A signal outputted from the image sensor is processed so as to detect a defect of the specimen by converting an analog image signal outputted from the image sensor to a digital image signal with an A/D converter, and a display displays information of the defect detected.

Abstract: A fault inspection method and apparatus in which the scattergram is separated or objects of comparison are combined in such a manner as to reduce the difference between an inspection object image and a reference image. As a result, the difference between images caused by the thickness difference in the wafer can be tolerated and the false information generation prevented without adversely affecting the sensitivity.

Abstract: A method and apparatus for detecting defects are provided for detecting defects or foreign matter on an object to be inspected. The apparatus includes a movable stage for mounting a specimen, an illumination system for irradiating a circuit pattern with light from an inclined direction, and an image-forming optical system for forming an image of an irradiated detection area on a detector from the upward and oblique directions. With this arrangement, diffracted light and scattered light caused on the circuit pattern through the illumination by the illumination system is collected. A spatial filter is provided on a Fourier transform surface for blocking the diffracted light from a linear part of the circuit pattern. The scattered and reflected light received by the detector is converted into an electrical signal. The converted electrical signal of one chip is compared with that of the other adjacent chip.

Abstract: A defect inspection apparatus includes an illumination optical system, a detection optical system which includes a reflecting objective lens, and wavelength separation optics for conducting wavelength separation, and after the wavelength separation, branching the scattered light into at least a first detection optical path and a second detection optical path. The detection optical system further includes, on the first detection optical path, a first sensor, and on the second detection optical path, a second sensor. A signal processor is provided which, in accordance with at least one of a first signal obtained from the first sensor and a second signal obtained from the second sensor, discriminates defects or defect candidates present on a surface of a sample.

Abstract: A defect inspection apparatus and method includes utilizing an irradiation optical system that focuses a beam flux emitted from a laser light source and formed into a slit-shaped beam so as to irradiate the beam onto the surface of the substrate to be inspected, utilizing a detection optical system that detects light from the substrate that has been irradiated with the slit-shaped beam, and utilizing a signal processor that processes a signal output from the detection optical system. The irradiation optical system includes a cylindrical lens for focusing the beam that has been emitted from the laser light source onto the substrate to be inspected, as the slit-shaped beam, wherein the cylindrical lens is disposed so as to obtain a distance between an incidence surface or emitting surface thereof and the slit-shaped beam upon the substrate to be inspected to be equal to a focal distance of the cylindrical lens.

Abstract: Provided is an anomaly detection method and system capable of constructing determination condition rules of anomaly detection from case-based anomaly detection by way of multivariate analysis of a multi-dimensional sensor signal, applying the rules to design-based anomaly detection of individual sensor signals, and also appropriately executing setting and control of threshold values for highly sensitive, early, and clearly visible detection of anomalies. Anomaly detection on the basis of a case base by way of multivariate analysis controls design-based anomaly detection. That is to say, (1) anomaly detection on the basis of a case base performs selection of sensor signals and anomaly detection according to various types of anomalies. Specifically, anomaly detection (characteristic conversion), evaluation of level of effect of each signal, construction of determination conditions (rules), and display and selection of sensor signals corresponding to the anomaly are performed.

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.

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: 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: An inspection method, including: illuminating a light on a wafer on which plural chips having identical patterns are formed; imaging corresponding areas of two chips formed on the wafer to obtain inspection images and reference images with an image sensor; and processing the obtained inspection image and the reference image to produce a difference image which indicates a difference between the inspection image and the reference image and detect a defect by comparing the difference image with a threshold, wherein a threshold applied to a difference image which is produced by comparing the inspection image and the reference image obtained by imaging peripheral portion of the wafer is different from a threshold applied to a difference image which is produced by comparing the inspection image and the reference image obtained by imaging central portion of the wafer.

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 pattern inspection method and apparatus are provided for sequentially imaging plural chips formed on a substrate to be inspected to and obtaining inspection images and reference images, calculating a position gap between the inspection images and the reference images using a recipe created in advance by using another substrate of the same kind or type as the substrate, the recipe including information for determining which pattern sections are to be selected and discarded, aligning the inspection images and the reference images using information of the position gap from the calculating step, and comparing the inspection images with the reference images aligned by the aligning step and extracting a defect candidate.

Abstract: To inspect a substrate such as a semiconductor substrate for surface roughness at high precision. The surface roughness of the substrate is measured in each frequency band of the surface roughness by applying a light to the substrate surface and detecting a scattered light or reflected light at a plurality of azimuth or elevation angles.

Abstract: An image feature is calculated based on the image of a detected defect, a coordinate feature is calculated based on position coordinates of the detected defect, and false alarm judgment is performed according to a decision tree constructed by threshold processing to the image feature or the coordinate feature.

Abstract: (1) A compact set of learning data about normal cases is created using the similarities among data as key factors, (2) new data is added to the learning data according to the similarities and occurrence/nonoccurrence of an anomaly, (3) the alarm occurrence section of a facility is deleted from the learning data, (4) a model of the learning data updated at appropriate times made by the subspace method, and an anomaly candidate is detected on the basis of the distance between each piece of the observation data and a subspace, (5) analyses of event information are combined and an anomaly is detected from the anomaly candidates, and (6) the deviance of the observation data is determined on the basis of the distribution of histograms of use of the learning data, and the abnormal element (sensor signal) indicated by the observation data is identified.

Abstract: Arrangements for inspecting a specimen on which plural patterns are formed; capturing a first image of a first area; capturing a second image of a second area in which patterns which are essentially the same with the patterns formed in the first area; creating data relating to corresponding pixels of the first and second images, for each pixel; determining a threshold for each pixel for detecting defects directly in accordance with the first and second images; and detecting defects on the specimen by processing the first and second images by using the threshold for each pixel and information of a scattered diagram of brightness of the first and second images, wherein the threshold is determined by using information of brightness of a local region of at least one of the first and second images, with the local region including an aimed pixel and peripheral pixels of the aimed pixel.