Hitachi-high-technologies Corporation

Hitachi, Ltd.

Hitachi High-tech Corporation

Ryo Nakagaki

Yuji Takagi

Minoru Harada

Takehiro Hirai

Kenji Obara

Toshifumi Honda

Chie Shishido

Masaki Kurihara

Hiroki Kawada

Yasuhiko Ozawa

Seiji Isogai

Toshiei Kurosaki

Yohei Minekawa

Maki Tanaka

Atsushi Miyamoto

Kenji Watanabe

Mayuka Oosaki

Naoki Hosoya

Kenji Nakahira

Hisafumi Iwata

Junko Konishi

Fumihiko Fukunaga

Yuya Toyoshima

Yoko Ikeda

Minori Noguchi

Takashi Hiroi

Hidetoshi Morokuma

Masahiro Watanabe

Kazuo Aoki

Tadashi Otaka

Osamu Komuro

Atsushi Shimoda

Masakazu Takahashi

Hirohito Okuda

Hiroshi Kakibayashi

Kohei Yamaguchi

Hirohiko Kitsuki

Go Kotaki

Yasuhiro Ozawa

Katsuhiro Kitahashi

Yuuji Takagi

Chle Shishido

Hideka Bamba

A method for measuring overlay at a semiconductor device on which circuit patterns are formed by a plurality of exposure processes is characterized in including an image capturing step for capturing images of a plurality of areas of the semiconductor device, a reference image setting step for setting a reference image based on a plurality of the images captured in the image capturing step, a difference quantifying step for quantifying a difference between the reference image set in the reference image setting step and the plurality of images captured in the image capturing step, and an overlay calculating step for calculating the overlay based on the difference quantified in the difference quantifying step.

Method for measuring overlay and measuring apparatus, scanning electron microscope, and GUI

Provided is a GUI including: an unadded pane region that hierarchically displays folders which are sets of images having no class information added thereto; an image pane region that displays the images displayed in the unadded pane region, the displayed images having no classification added thereto; and a class pane region that displays images having classification added thereto, wherein by externally inputting class information for one image having the class information added thereto, the input class information is displayed.

Defect classification apparatus and defect classification method

The purpose of the present invention is to easily extract, from samples to be observed, defect candidates that can be labeled as a defect or 'nuisance' (a part for which a manufacturing tolerance or the like is erroneously detected) and to allow parameters pertaining to observation processing to be easily adjusted. This defect observation method comprises: an imaging step to image, on the basis of defect information from an inspection device, an object to be inspected and obtain a defect image and a reference image corresponding to the defect image; a parameter determining step to determine a first parameter to be used in the defect extraction by using a first feature set distribution acquired from the reference image and the defect image captured in the imaging step and a second feature net distribution acquired from the reference image; and an observing step to observe using the first parameter determined in the parameter determining step. The present invention can be applied to a method of observing defects generated during the manufacturing of semiconductor wafers.

Defect observation method and defect observation device

The present invention provides a charged-particle radiation apparatus with a defect observation device for observing defects on a sample, the apparatus including a control unit and a display unit. The control unit is configured to execute a drift correction process on one or more images acquired with the defect observation device under a plurality of correction conditions, and display the plurality of correction conditions and a plurality of corrected images obtained through execution of the drift correction process in association with each other, as a first screen on the display unit.

Charged-particle radiation apparatus

Conventionally, there was no method for automatically selecting the layers to be overlaid, so when the number of layers to be overlaid was large, there was a problem that much time was required for selecting the layers. It is an object of the present invention to provide a defect image analysis method capable of specifying patterns and layers in which a defect occurs by overlaying defect images to be analysis targets and design layout data, and a defect image analysis system capable of improving the efficiency to select the layers from the design layout data. The present invention is characterized in dividing analysis target images for each hierarchy corresponding to a manufacturing process and generating a plurality of layers; calculating a degree of matching between each of the layer division images and each design layer of the design layout data; and specifying a design layer with a highest degree of matching of the each design layer as a design layer corresponding to the layer division image.

Defect analysis assistance device, program executed by defect analysis assistance device, and defect analysis system

Cases in which defects are analyzed in a manufacturing process stage in which a pattern is not formed or in a manufacturing process in which a pattern formed on a lower layer does not appear in the captured image are increasing. However, in these cases, there is a problem of not being able to synthesize a favorable reference image and failing to detect a defect when a periodic pattern cannot be recognized in the pattern. In the present invention, a defect occupation rate, which is the percentage of an image being inspected occupied by a defect region, is found, it is determined whether the defect occupation rate is higher or lower than a threshold, and, in accordance with the determination results, it is determined whether to create, as the reference image, an image comprising pixels having the average luminance value of the luminance values of a plurality of pixels contained in the image being inspected. In particular, when the defect occupation rate is low, an image comprising pixels having the average luminance value of the luminance values of a plurality of pixels contained in the image being inspected is used as the reference image.

In automatic defect classification, a classification recipe must be set for each defect observation device. If a plurality of devices operate at the same stage, the classification class in the classification recipes must be the same. Problems have arisen whereby differences occur in the classification class in different devices when a new classification recipe is created. This defect classification system has a classification recipe storage unit; an information specification unit, the stage of a stored image, and device information. A corresponding defect specification unit specifies images of the same type of defect from images obtained from different image pickup devices at the same stage. An image conversion unit converts the images obtained from the different image pickup devices at the same stage into comparable similar images; and a recipe update unit records the classification classes in the classification recipes corresponding to the specified images of the same type of defect.

Defect classification method, and defect classification system

In performing a programmed-point inspection of a circuit pattern using a review SEM, stable inspection can be performed while suppressing the generation of a false report even when a variation in a circuit pattern to be inspected is large. SEM images that are obtained by sequentially imaging a predetermined circuit pattern using the review SEM are stored into a storage unit. Images that meet a set condition are selected from the stored SEM images, and averaged to create an average image (GP image). By performing pattern check by GP comparison using this GP image, an inspection can be performed while suppressing the generation of a false report even when a variation in the circuit patterns is large.

Method and device for testing defect using SEM

A method for reviewing defect, comprising the steps of: as an image acquisition step, imaging a surface of a sample using arbitrary image acquisition condition selected from a plurality of image acquisition conditions and obtaining a defect image; as a defect position calculation step, proceeding the defect image obtained by the image acquisition step and calculating a defect position on the surface of the sample; as a defect detection accuracy calculation step, obtaining a defect detection accuracy of the defect position calculated by the defect position calculation step; and as a conclusion determination step, determinating whether the defect detection accuracy obtained by the defect detection accuracy calculation step meets a predetermined requirement or not; wherein until it is determined that the defect detection accuracy obtained by the defect detection accuracy calculation step meets a predetermined in the conclusion determination step, the image acquisition condition is selected from the plurality of image acquisition conditions once again and the image acquisition step, the defect position calculation step, the defect detection accuracy calculation step and the conclusion determination step are repeated.

Method and apparatus for reviewing defect

A region-of-interest determination apparatus includes: a calculation unit and a region determination unit. The calculation unit calculates a degree of a defect based on at least a plurality of kinds of defect attribute information regarding defect data. The defect data includes an image corresponding to a defect position detected on a specimen by inspection thereof or an image corresponding to a defect position predicted to be likely to develop a defect on the specimen, where both images are obtained by imaging. The region determination unit extracts the defect data of which the degree is higher than a predetermined level, and determines the region to be observed or inspected on the specimen based on the extracted defect data.

Region-of-interest determination apparatus, observation tool or inspection tool, region-of-interest determination method, and observation method or inspection method using region-of-interest determination method

Disclosed is a method of inspecting an object to be inspected in a semiconductor manufacturing process, for resolving the problem to increase defect detection sensitivity. An image capture means is used to image capture a designated area of the object to be inspected; a defect is detected in the captured image; a circuit pattern is recognized from the captured image; a characteristic value is computed, relating to an image tone and shape, from the detected defect; a characteristic value is computed, relating to the image tone and shape, from the recognized circuit pattern; either a specified defect or circuit pattern is filtered and extracted from the detected defect and the recognized circuit pattern; a mapping characteristic value is determined from the characteristic value of either the filtered and extracted specified defect or circuit pattern; and the distribution of the determined characteristic values is displayed onscreen in a map format.

Inspection method and device therefor

An imaging region of a high-magnification reference image capable of being acquired in a low-magnification field without moving a stage from a position at which a defective region has been imaged at a low magnification is searched for and if the search is successful, an image of the imaging region itself is acquired and the high-magnification reference image is acquired. If the search is unsuccessful, the imaging scheme is switched to that in which the high-magnification reference image is acquired from a chip adjacent to the defective region.

Defect observation method and device using SEM

In a pattern inspection of a semiconductor circuit, to specify a cause of a process defect, not only a distribution on and across wafer of the number of defects but also more detailed, that is, the fact that how many defects occurred where on the semiconductor pattern is needed to be specified in some cases. Accordingly, the present invention aims to provide an apparatus capable of easily specifying a cause of a process defect based upon a positional relationship of a distribution of defect occurrence frequency and a pattern. The apparatus includes: a charged particle beam optical system for detecting secondary charged particles by irradiating the charged particle beam to the sample; an image processing unit for, based upon a plurality of images to be inspected that are obtained by the secondary charged particles, obtaining an occurrence frequency of defect candidates for each of predetermined regions inside the detected image; and a display unit for displaying the distribution of the occurrence frequency of the defect candidates so that a positional relationship to the pattern is recognized.

Charged particle beam apparatus

A defect observation device including an input-output unit supplied with information of a taught defect, and information of an ideal output of the taught defect, and configured to display a processing result based upon a determined image processing parameter set; and an automatic determination unit configured to: select image processing parameter sets which are less in number than the total number of all image processing parameter sets, out of all image processing parameter sets, calculate image processing results on an input defect image, by using the selected image processing parameter sets, calculate a coincidence degree for each of the selected image processing parameter sets, estimate distribution of an index value in all image processing parameter sets from distribution of the coincidence degree for the selected image processing parameter sets, and determine an image processing parameter set to have a high coincidence degree out of all image processing parameter sets.

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Kawasaki, Japan

Ryo Nakagaki