Hitachi-high-technologies Corporation

Hitachi, Ltd.

Renesas Electronics Corporation

Junko Konishi

Makoto Ono

Tomohiro Funakoshi

Takehiro Hirai

Kenji Obara

Hisafumi Iwata

Yoko Ikeda

Yuji Takagi

Ryo Nakagaki

Yasuhiko Ozawa

Seiji Isogai

Tsunehiro Sakai

Fumiaki Endo

Kozo Miyake

Yuya Isomae

Yasuhiro Yoshitake

Noritsugu Takahashi

Yohei Minekawa

Toshiharu Miwa

Natsuyo Morioka

Kazunori Nemoto

Toshihide Kawachi

Hidekimi Fudo

Yuko Kariya

Shigenori Yamashita

Takeshi Tashiro

A first object is to use both ADC (automatic defect classification) and MDC (manual defect classification) and reduce the amount of MDC operation. A second object is to prevent a DOI (defect of interest) from being missed. The first object is achieved by displaying judgment information on a screen. The judgment information is necessary when part of the classification is performed by ADC and part of the classification is performed by MDC and used to judge which classification is used, ADC or MDC. In the display operation, ADC classification results and MDC classification results are also displayed in the form of matrix. Further, a missed DOI rate is calculated for each classification threshold used in the defect classification and displayed on the screen.

Method for optimizing observed image classification criterion and image classification apparatus

Disclosed is a technique wherein an object that requires adjustment in order to increase the reliability of automatic classification can be easily identified. A device () for adjusting classification classifies defects into a first class group according to the feature amount of the defects that are obtained from image data obtained from an electron microscope (), and classifies the defects into a second class group according to the feature amount of the defects classified into the first class group. And, the device () for adjusting the classification calculates classification performance by comparing the defects that have been classified into the second class group, and outputs the calculated classification performance in a predetermined display format to an output unit ().

Device for classifying defects and method for adjusting classification

Provided is a charged particle beam device that prevents the increase in processing trouble caused by deterioration in the reviewing performance (e.g., overlooking of defects) by detecting an operation abnormality affecting the performance of the device or a possibility of such an abnormality in the middle of a processing sequence of a sample and giving a feedback in real time. In each processing step of the charged particle beam device, monitoring items representing the operating status of the device (control status of the electron beam, an offset amount at the time of wafer positioning, a defect coordinate error offset amount, etc.) are monitored during the processing sequence of a sample and stored as history information. In the middle of the processing sequence, a comparative judgment between the value of each monitoring item and the past history information corresponding to the monitoring item is made according to preset judgment criteria. When the width of fluctuation from the past history information deviates from a reference range, an alert is issued.

Charged particle beam device, defect observation device, and management server

The objective is to improve a classification standard. Classification standard data, in which is registered image data information that is the standard when image data is classified, and classification data, in which is registered image data information that is the result when newly input image data is classified using the classification standard data, are stored in a storage unit. An image classification device is characterized in that when any image data information of the image data that is registered in the classification data is selected by means of an input unit, and an instruction to additionally register the selected image data information in the classification standard data is input by means of the input unit, the selected image data information is additionally registered in the classification standard data.

Image classification standard update method, program, and image classification device

Provided is an observation condition determination support device which can improve the defect classification accuracy. The observation condition determination support device includes: a means () for acquiring a plurality of defects images which have captured the same defect under a plurality of observation conditions set in advance in an observation device () in accordance with check data relating to defects of a semiconductor device detected by an inspection device (); a means () for classifying the plurality of the same defects according to the respective defect images and determining a first category to which the same defects belong for each of the observation conditions as a result of the classification; and a means () for determining an observation condition to be used when fabricating the semiconductor device among the plurality of the observation conditions according to the ratio at which the first category is matched with a second category determined by a user of the observation device who has classified the same defects.

Observation condition determination support device and observation condition determination support method

A method for classifying defects, including: calculating feature quantifies of defect image which is obtained by imaging a defect on a sample; classifying the defect image into a classified category by using information on the calculated feature quantities; displaying the classified defect image in a region on a display screen which is defined to the classified category; adding information on the classified category to the displayed defect image; transferring the displayed defect image which is added the information on the classified category to one of the other categories and displaying the transferred defect image in a region on the display screen which is defined to the one of the other categories; and changing information on the category.

Inspecting method, inspecting system, and method for manufacturing electronic devices

In order to allow to easily specify inspection recipe with which defects desired to be detected can be detected efficiently, a defect inspection apparatus performs defect inspection of a substrate in accordance with a plurality of inspection recipes and produces defect information associated with position of defect in the substrate and attribute data of the defect for each of the inspection recipes and a defect review apparatus produces review result information specifying a kind of defect selected from defects contained in the defect information. An analyzing apparatus obtains defect information and review result information and totalizes the number of defects having attribute data similar to attribute data possessed in defects corresponding to kind of defects to be analyzed for each inspection recipe.

Analyzing apparatus, program, defect inspection apparatus, defect review apparatus, analysis system, and analysis method

A defect detected by a wafer inspection tool is reliably captured by a defect review tool. A defect review condition in the defect review tool is varied depending on defect attributes provided by the wafer inspection tool so as to optimize the review process. For example, review magnification is varied depending on the size of the defect, or the frame addition number is varied depending on the maximum gray level difference.

Wafer inspection data handling and defect review tool

In an exposure process forming a predetermined circuit pattern of a semiconductor device on a wafer, a resist dimension of the resist pattern formed on a wafer and a focus position in the exposure process at a past time are measured. A resist dimension and a focus position of a wafer to which the exposure process is secondly performed are estimated by using measurement results of the measured resist dimension and focus position, and a focus offset value is calculated by using estimated values of the estimated resist dimension and focus position. Then, an exposure dose is calculated with considering this focus offset value, and a resist pattern is formed on the wafer to which the exposure process is performed by using the calculated exposure dose and focus offset value.

Manufacturing method and manufacturing system of semiconductor device

Disclosed is a test data analyzing method and system for use in estimation of a defect cause of a product, such as, an integrated circuit, a liquid crystal display, an optical transceiver, a thin film magnetic head, etc., which is fabricated through plural processes. The estimation of a defect cause is achieved by selecting a wafer number to be analyzed, reading test data, reading fabrication line data, counting frequency of machine codes by wafers, grouping test data by machine codes or frequencies, comparing test data distributions between groups by machine codes, and comparing results between machine codes.

Test data analyzing system and test data analyzing program

The present invention has an analyzing unit including an image detection device for producing a plurality of images of a workpiece, a storage for storing detected images produced by the image detection device, and a display having a screen with a first area for displaying a plurality of detected images stored in the storage and a plurality of second areas for classifying the detected images according to features of the detected images, whereby the plurality of detected images are moved on the screen from the first area to selected second areas to classify the plurality of detected images in the second areas.

An inspection system comprises an inspection machine for inspecting a work which is processed in one of the manufacturing processes of a manufacturing line and an analysis system for outputting an inspection history list obtained by making calculations from the inspected result. The inspection history list shows a matrix of first information as the inspection processes in which the work is inspected or the manufacturing processes corresponding to the inspection processes in which the work is inspected and second information as to the works inspected by the inspection machine.

Growing community of inventors

Yokohama, Japan

Junko Konishi