Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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 that measures a dimension of a device complete; and a dimension measurement unit cross-sectional structure using the corrected contour.

Abstract: 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 monito

Abstract: 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.

Abstract: 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.

Abstract: 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 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.

Abstract: 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. 2).

Abstract: 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.

Abstract: 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.

Abstract: 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 monito

Abstract: The efficiency of operation in a semiconductor processing apparatus is improved. In order to search an input parameter value to be set in a semiconductor processing apparatus for processing into a target processed shape, a predictive model indicating a relationship between an input parameter value and an output parameter value is generated based on the input parameter value and the output parameter value which is a measured value of a processing result processed by setting the input parameter value in the semiconductor processing apparatus. In this case, when the measured value of the processing result processed by the semiconductor processing apparatus is the defective data, the predictive model is generated based on the input parameter value causing defective data and defective substitute data obtained by substituting the measured value which is the defective data.

Abstract: 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.

Abstract: A sample simulates a processing state of a semiconductor sample and is measured by a measurement device. The sample includes: a first surface formed at a first height when viewed from a sample surface; a second surface formed at a second height higher than the first height; and a plurality of inflow parts which allow a particle for performing processing on the first surface to flow between the first surface and the second surface. The processing by the particle flowing from the inflow parts is superimposed in at least a part of a region to be processed on the first surface, and the region where the processing is superimposed on the first surface is measured by the measurement device.

Abstract: A system for determining a processing procedure including a plurality of processes for controlling an object, the system includes a learning unit for performing a learning process for determining a processing condition of each of a plurality of processes, and the learning unit acquires a physical quantity correlating with a state of the object on which a process has been performed under a predetermined processing condition, from a device for controlling the object on the basis of the processing procedure, calculates a pseudo state corresponding to the state of the object on the basis of the physical quantity, performs a learning process using a value function, and determines a processing condition of each of the plurality of processes to achieve a target state of the object.

Abstract: 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.

Abstract: 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.

Abstract: 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. 2).

Abstract: A search apparatus receives each input of a target value and a reference value indicated by the target value; generates a prediction model indicating a relation between the condition and the result based on a setting value of the condition inside the search area and a measured value of the result; acquires a prediction value from the prediction model by assigning the target value to the prediction model and specifies a presence area of the prediction value from the search area; determines whether the prediction value is closer to the target value than the reference value; sets the measured value of the result corresponding to the prediction value to the reference value when the prediction value is closer to the target value, and sets the prediction value presence area to the search area; and outputs a prediction value satisfying an achievement condition when the prediction value satisfies the achievement condition.