Hitachi High-Tech Corporation

Hitachi, Ltd.

Hitachi-High-Technologies Corporation

Nec Corporation

Takeshi Ohmori

Hyakka Nakada

Masaru Kurihara

Tatehito Usui

Yutaka Okuyama

Satomi Inoue

Naoyuki Kofuji

Masayoshi Ishikawa

Kenji Maeda

Daisuke Satou

Junichi Tanaka

Masaru Izawa

Yasutaka Toyoda

Naoto Takano

Naoki Yasui

Soichiro Eto

Kenji Oguma

Hitoshi Kobayashi

Masamichi Sakaguchi

Miyako Matsui

Kenichi Kuwahara

Hiroaki Ishimura

Yasuhiro Nishimori

Kohei Matsuda

Satoshi Sakai

Hikaru Koyama

Pushe Zhao

Masashi Egi

Hiroyuki Kobayashi

Takashi Dobashi

Yuyao Wang

Shunya Tanaka

Target processing conditions are searched while reducing a process development time and process development costs. A processing condition search device includes a learning database including a processing database storing target processing data for a target process and a reference processing database storing reference processing data for a reference process, a teachered learning execution unit that estimates an I/O model of the target process, which is an I/O model between a target description variable and a target objective variable, a transfer learning execution unit that estimates the I/O model of the target process using a reference I/O mode between a reference description variable and a reference objective variable, and the target processing data, and a transferability determination unit that determines whether the teachered learning execution unit or the transfer learning execution unit is used to estimate the I/O model of the target process.

Processing condition search device and processing condition search method

For a machine learning model that receives control parameters of a semiconductor processing device and outputs shape parameters that express a processed shape of a semiconductor sample processed by the semiconductor processing device, an experiment point obtaining learning data is recommended. A contribution of each control parameter to the prediction of the machine learning model is evaluated from feature quantity data that is a value of a control parameter of the learning data used for learning of the machine learning model, and the experiment point is recommended based on a stability evaluation and an uncertainty evaluation of the prediction by the machine learning model in a space defined by the control parameters selected based on the contribution as axes.

Experiment point recommendation device, experiment point recommendation method, and semiconductor device manufacturing device

There are provided a charged particle beam device capable of appropriately setting a tilt angle of a sample stage even if an observation surface is larger than the field of view, and a sample observation method using the same. The charged particle beam device is a device for obtaining an observation image of a sample by irradiating the sample with a charged particle beam, and is characterized by including: a sample stage that tilts with respect to each of two tilt axes intersecting with each other and holds the sample as well; a boundary detection unit that detects a boundary between an upper surface and a cleavage surface of the sample from each observation image obtained while changing a tilt angle of the sample stage, and calculates a tilt of the boundary with respect to the scanning direction of a charged particle beam; an upper surface detection unit that detects the upper surface from the observation image for each tilt angle, and calculates an upper surface vanishing angle that is a tilt angle of the sample stage at which the upper surface vanishes from the observation image; and a calculation processing unit that calculates an initial sample direction, which is a direction of the cleavage surface when the tilt angle is zero, on the basis of the tilt of the boundary for each tilt angle and the upper surface vanishing angle.

Charged particle beam device, and sample observation method employing same

A computer system providing a function for: extracting, from image data of a semiconductor pattern, coordinate information of a base point for measuring a dimension of a desired location of the semiconductor pattern; and measuring the dimension using the coordinate information of the base point. The computer system includes a training device in which a pose estimation model for outputting coordinate information of at least two base points as a training result is implemented. The training device is trained in advance using teacher data having the image data of the semiconductor pattern as an input and the coordinate information of at least two base points as an output, and extracts, for new image data input into the training device, the coordinate information of at least two base points and a dimension.

Computer system, dimension measurement method, and storage medium

A dimension measurement apparatus that automatically corrects a deviation of a contour without operator determination. The dimension measurement apparatus includes: a model learning unit that obtains a learning cross-sectional image and learning labels attached to different regions of the learning cross-sectional image and generates a deep learning model for image region division using the learning cross-sectional image and the learning labels; a model estimation unit that applies the model to a newly input target image and labels each independent region; a contour correction unit that detects a contour of each region using the target image and the labels, sets a representative point on the contour of the region, moves each representative point according to a movement rule, and repeats movement of the representative point until contour correction is complete; and a dimension measurement unit that measures a dimension of a device cross-sectional structure using the corrected contour.

Dimension measurement apparatus, semiconductor manufacturing apparatus, and semiconductor device manufacturing system

To facilitate evaluation of a predicted process shape in process recipe development using machine learning, a process recipe search apparatus that searches for an etching recipe that is a parameter of a plasma processing apparatus set so as to etch a sample into a desired shape displays, on a display device, the predicted process shape of the sample by a candidate etching recipe predicted by using a machine leaning model, by highlighting a difference between the predicted process shape and a target shape.

Process recipe search apparatus, etching recipe search method and semiconductor device manufacturing system

High-accuracy dimension extraction for a complicated shape possibly appearing through semiconductor processing. A starting point and an endpoint are placed on the periphery of a graphic shape including a combination of multiple ellipses, and a curve unicursally drawn on the periphery between the two points is used as a shape mode, thereby describing a contour of an intended structure.

Contour analysis apparatus, processing condition determination system, shape estimation system, semiconductor device manufacturing system, search apparatus, and data structure used in them

A model learning unit learns a prediction model on the basis of learning data, a target setting unit sets a target output parameter value by interpolating between a goal output parameter value and an output parameter value which is the closest to the goal output parameter value in output parameter values in the learning data, a processing condition search unit estimates input parameter values which corresponds to the goal output parameter value and the target output parameter value, a model learning unit updates the prediction model by using a set of the estimated input parameter value and an output parameter value which is a result of processing that a processing device performs as additional learning data.

Plasma processing apparatus including predictive control

A parameter compression unit compresses first input parameter values so that a parameter restoration unit can restore the first input parameter values, and generates first compressed input parameter values in which the number of control parameters is reduced, a model learning unit learns a prediction model from learning data that is a set of the first compressed input parameter values and first output parameter values that are processing results obtained by giving the first input parameter values, as a plurality of control parameters, to a processing device, and a processing condition search unit estimates a second compressed input parameter values corresponding to target output parameter values by using the prediction model.

Search device, search program, and plasma processing apparatus

Provided is a system that constructs a learning database for a learning model in a short period of time. The system generates an image in which a structure image is similar to an actual image by image processing of the structure image. One or more processors acquire a first structure image and a second structure image different from the first structure image. The one or more processors create a plurality of intermediate structure images indicating an intermediate structure between the first structure image and the second structure image. The one or more processors generate an image by making each of the plurality of intermediate structure images to be similar to an actual image by image processing of each of the plurality of intermediate structure images.

Image generation system

Search device, searching method, and plasma processing apparatus

To efficiently search a processing condition of giving a desired target processing result, there is provided a processing condition determination system including a processing apparatus that processes a sample, a processing monitor system that monitors the state of the processing in the processing apparatus, and an analysis system that sets the processing condition of the processing apparatus of giving a target processing result, wherein the system includes a processing condition and result database that stores a set of an explanatory variable that is a processing condition under which the processing apparatus processes a sample and an objective variable that is the processing result obtained by the processing apparatus' processing the sample, and when the processing apparatus processes the sample under the processing condition set using the correlation model derived from the database and it is determined that a probability of failure occurrence becomes high, based on the monitor data of the processing monitor system, the processing apparatus stops the processing under the present processing condition and the analysis system resets a new processing condition.

Processing condition determination system and processing condition searching method

The disclosure relates to a dimension measurement apparatus that reduces time required for dimension measurement and eliminates errors caused by an operator. Therefore, the dimension measurement apparatus uses a first image recognition model that extracts a boundary line between a processed structure and a background over the entire cross-sectional image and/or a boundary line of an interface between different kinds of materials, and a second image recognition that output information for dividing the boundary line extending over the entire cross-sectional image obtained from the first image recognition model for each unit pattern constituting a repetitive pattern, obtains coordinates of a plurality of feature points defined in advance for each unit pattern, and measures a dimension defined as a distance between two predetermined points of the plurality of feature points.

Dimension measurement apparatus, dimension measurement program, and semiconductor manufacturing system

An object of the present invention is to provide a technique that allows automatically generating a processing recipe from an inspection image even when the inspection image varies by being affected by an imaging condition of a processing device. A processing recipe generation device according to the present invention generates a converted image in which components relying on the imaging condition of the inspection image are reduced and generates a processing recipe using a target image generated using a conversion condition same as that of the converted image (see FIG.).

Processing recipe generation device

A computer for determining a control parameter of processing to be performed on a sample includes: a memory unit configured to store a first model indicating a correlation between a first processing output obtained by measuring a first sample used for manufacturing, on which the processing is performed and a second processing output obtained by measuring a second sample that is easier to measure than the first sample and on which the processing is performed, and a second model indicating a correlation between a control parameter of the processing performed on the second sample and the second processing output; and an analysis unit configured to calculate a target control parameter of the processing performed on the first sample based on a target processing output as the target first processing output, the first model, and the second model.

Growing community of inventors

Tokyo, Japan

Takeshi Ohmori