CN117242402A

CN117242402A - Analysis system, exposure apparatus, device manufacturing method, display manufacturing method, and analysis method

Info

Publication number: CN117242402A
Application number: CN202280030171.1A
Authority: CN
Inventors: 宫崎圣二; 武藤贵和; 樋口洁; 小池哲也; 高桥哲大; 大谷直也; 柏村庆基
Original assignee: Nikon Corp
Current assignee: Nikon Corp
Priority date: 2021-04-28
Filing date: 2022-04-25
Publication date: 2023-12-15
Also published as: WO2022230788A1; KR20240004363A; TW202303302A; JPWO2022230788A1

Abstract

The invention provides an analysis system capable of specifying which of a plurality of substrate processing apparatuses generates a deformation amount of a substrate. The analysis system (10) comprises: a first processing device (21) which has a first device (110) and a second device (111) and performs a first process on a substrate; and a second processing device (22) that has a third device (121) and a fourth device (122) and performs a second process on the substrate, wherein when the substrate passes through any one of a first path through which the first device and the third device pass, a second path through which the second device and the third device pass, or a fourth path through which the second device and the fourth device pass, and the analysis system analyzes Measurement Information (MI) that is information from an inspection device (220) that measures the processing results of the first substrate to the fourth substrate that pass through the first path to the fourth path, the path being a first path through which the first device and the third device pass, a second path through which the first device and the fourth device pass, and the analysis system includes: a path information acquisition unit (310) that acquires substrate identification information (SID) and path identification information (RID); a measurement information acquisition unit (320) that acquires the substrate identification information and the measurement information; and a calculating unit (330) for calculating first to fourth device characteristics generated by the first to fourth substrates by processing in the first to fourth devices, respectively, based on the route identification information and the measurement information.

Description

Analysis system, exposure apparatus, device manufacturing method, display manufacturing method, and analysis method

Technical Field

The application relates to an analysis system, an exposure apparatus, a device manufacturing method, a display manufacturing method, and an analysis method.

The present application claims priority based on japanese patent application publication No. 2021-076855 of japanese patent application laid-open at 28 of 2021, the contents of which are incorporated herein by reference.

Background

Conventionally, in the field of semiconductor device manufacturing technology, there is a technology of projecting and exposing an image of a fine pattern formed on a photomask or the like onto a substrate such as a semiconductor wafer coated with a photosensitive agent such as a photoresist using an exposure apparatus. In such an exposure technique, a photomask and a wafer are aligned with high accuracy, and a projection exposure is performed by overlapping an exposure pattern with a pattern formed on the wafer. High overlay accuracy is required for the formed pattern when the exposure device performs overlay exposure. For example, the variation in the exposure result due to the difference between the film forming apparatus and the etching apparatus for processing the wafer cannot be ignored. Specifically, when a wafer is deformed by a processing device such as a film forming device or an etching device, and the deformed wafer is exposed by an exposure device, the pattern is exposed to a position offset from the pattern formed on the wafer, and the patterns are not superimposed with good precision. Further, the deformation amount of the wafer varies depending on which processing apparatus is used for processing. Therefore, the exposure result, that is, the overlapping of the patterns, is deviated. In order to correct the deviation, a technique of calculating a superimposition prediction correction value based on a process history and the like and performing correction at the time of exposure processing is known (for example, refer to patent document 1).

However, in the prior art as described above, it is impossible to specify which one of the processing apparatuses causes the wafer to be deformed by the deformation amount. In addition, when a specific processing apparatus is replaced, there is a problem that the conventional stored data cannot be used, and correction of the exposure pattern cannot be performed.

Prior art literature

Patent literature

Patent document 1: japanese patent laid-open No. 2020-34682

Disclosure of Invention

In the analysis system according to the present invention, the analysis system is configured to analyze measurement information, which is information from an inspection device that measures a result of processing of each of a first substrate passing through the first path, a third substrate passing through the third path, and a fourth substrate passing through the fourth path, among a first processing device that includes the first device and the second device and performs a first process on a substrate, and a second processing device that includes the third device and the fourth device and performs a second process on the substrate, the second substrate passing through the second path, the third substrate passing through the third path, and the fourth substrate passing through the fourth path, and the analysis system includes: a path information acquisition unit that acquires substrate identification information for identifying each substrate and path identification information for each path; a measurement information acquisition unit configured to acquire the substrate identification information and the measurement information measured by the inspection device; and a calculating unit configured to calculate a first device characteristic generated by the first substrate subjected to the first process by the first device, a second device characteristic generated by the second substrate subjected to the first process by the second device, a third device characteristic generated by the third substrate subjected to the second process by the third device, and a fourth device characteristic generated by the fourth substrate subjected to the second process by the fourth device, based on the path identification information, the substrate identification information, and the measurement information.

In the exposure apparatus according to the present invention, the fifth substrate is exposed using the correction conditions obtained by the analysis apparatus.

The device manufacturing method of the present invention comprises: exposing the fifth substrate with the exposure device; and developing the exposed fifth substrate.

The display manufacturing method of the invention comprises the following steps: exposing the fifth substrate with the exposure device; and developing the exposed fifth substrate.

In the analysis method according to the present invention, in the analysis method, one of a first processing apparatus including a first apparatus and a second apparatus for performing a first process on a substrate and a second processing apparatus including a third apparatus and a fourth apparatus for performing a second process on the substrate is subjected to the first process and the second process through any one of measurement information from an inspection apparatus for measuring a result of the process of the first substrate, the second substrate, the third substrate, and the fourth substrate, the third path, or the fourth path, and the analysis method includes: a path information acquisition unit that acquires substrate identification information for identifying each substrate and path identification information for identifying a path through which each substrate passes; a measurement information acquisition step of acquiring the substrate identification information and measurement information, which is a processing result of each substrate measured by the inspection device; and calculating, based on the path identification information and the measurement information, a first device characteristic of the first substrate subjected to the first process by the first device, a second device characteristic of the third substrate subjected to the first process by the second device, a third device characteristic of the first substrate subjected to the second process by the third device, and a fourth device characteristic of the second substrate subjected to the second process by the fourth device.

In the analysis system according to the present invention, the analysis system is provided with an analysis system which analyzes information from an inspection device that measures a first substrate passing through the first path, a second substrate passing through the third path, and a fourth substrate passing through the fourth path, the analysis system including a first processing device that performs a first process on the first substrate, the second substrate, the third substrate, and the fourth substrate, and a second processing device that performs a second process on the first substrate, the second substrate, the third substrate, and the fourth substrate, and any one of the first processing device, the second processing device, the third substrate, and the fourth substrate, the second processing device, and the fourth processing device that performs a second process on the first substrate, the second substrate, the third substrate, and the fourth substrate, the inspection system including: a path information acquisition unit that acquires substrate identification information for identifying each substrate and path identification information for identifying a path through which each substrate passes; a measurement information acquisition unit configured to acquire the substrate identification information and measurement information, which is a processing result of each of the substrates measured by the inspection device; a classification unit configured to classify the measurement information into predetermined classification items based on the substrate identification information and the route identification information; and a display unit for displaying the result classified by the classification unit.

In the analysis system according to the present invention, the analysis system is configured to analyze measurement information, which is information from an inspection device that measures a result of processing of each of a first substrate passing through the first path, a third substrate passing through the third path, and a fourth substrate passing through the fourth path, among a first processing device that includes the first device and the second device and performs a first process on a substrate, and a second processing device that includes the third device and the fourth device and performs a second process on the substrate, the second substrate passing through the second path, the third substrate passing through the third path, and the fourth substrate passing through the fourth path, and the analysis system includes: a path information acquisition unit that acquires path identification information, which is information on a path through which each substrate passes; a measurement information acquisition unit that acquires the measurement information measured by the inspection device; and a calculating unit configured to calculate a first device characteristic, which is a characteristic of the first device, a second device characteristic, which is a characteristic of the second device, a third device characteristic, which is a characteristic of the third device, and a fourth device characteristic, which is a characteristic of the fourth device, based on the path identification information and the measurement information of the first substrate, the second substrate, the third substrate, and the fourth substrate.

Drawings

Fig. 1 is a diagram showing an example of a processing apparatus according to the first embodiment.

Fig. 2 is a diagram showing an example of the measurement result of the first embodiment.

Fig. 3 is a diagram showing an example of a functional configuration of the analysis system according to the first embodiment.

Fig. 4 is a flowchart showing a series of operations related to calculation of the correction value according to the first embodiment.

Fig. 5 is a diagram showing an example of the correspondence relationship between the path and the measurement result in the first embodiment.

Fig. 6 is a flowchart showing a series of operations related to the visualization of the error amount in the first embodiment.

Fig. 7 is a diagram showing an example of visualizing the error amount by using the coordinate system of the calibration Plate (Plate) according to the first embodiment.

FIG. 8 is a diagram showing an example of visualizing the error amount by using the orthogonal coordinate system according to the first embodiment.

Fig. 9 is a diagram showing an example of visualizing the error amount by using the heat map of the first embodiment.

Fig. 10 is a diagram showing an example of the correction value for each lens module according to the first embodiment.

Fig. 11 is a diagram showing an example of the correspondence relationship between the processing device and the correction value in the first embodiment.

Fig. 12 is a diagram showing an example of the correspondence relationship between the paths and the correction values in the first embodiment.

Fig. 13 is a diagram showing an example of a functional configuration of an analysis system related to application of the correction value according to the first embodiment.

Fig. 14 is a flowchart showing a series of operations related to the application of the correction value according to the first embodiment.

Fig. 15 is a diagram for explaining an example of selecting correction values according to the first embodiment, and selecting the correction values based on registered correction values for each device 100.

Fig. 16 is a diagram for explaining an example of selecting a correction value according to the first embodiment, and selecting the correction value based on a registered route correction value.

Fig. 17 is a diagram showing an example of a functional configuration of an analysis system according to the second embodiment.

Fig. 18 is a diagram showing an example of a functional configuration of an analysis system according to the third embodiment.

Fig. 19 is a diagram showing an example of the correspondence relationship between the path and the measurement result in the third embodiment.

Fig. 20 is a diagram showing an example of a functional configuration of an analysis system according to the fifth embodiment.

Fig. 21 is a diagram showing an example of a change with time in the result of statistical calculation of the measurement result of the eighth embodiment.

Fig. 22 is a diagram showing an example of a change in the measurement result with time for each condition according to the eighth embodiment.

Fig. 23 is a diagram showing an example of a functional configuration of an analysis device according to the eighth embodiment.

Fig. 24 is a diagram for explaining effects in the case of classifying measurement results for each tray of the eighth embodiment.

Fig. 25 is a diagram showing an example of a functional configuration of an analysis device according to the ninth embodiment.

Fig. 26 is a diagram for explaining the correction simulation of the ninth embodiment.

Fig. 27 is a diagram for explaining the average difference in the ninth embodiment.

Fig. 28 is a diagram for explaining calculation of a correction value of an unknown path according to a modification of the first embodiment.

Detailed Description

First embodiment

An embodiment of the present invention will be described below with reference to the drawings. Fig. 1 is a diagram showing an example of a processing apparatus according to the first embodiment. An example of the processing device 20 will be described with reference to fig. 1. The processing apparatus 20 is an apparatus that performs a predetermined process on a substrate (hereinafter, collectively referred to as a substrate) such as a semiconductor wafer or a glass plate in a predetermined process P. The processing apparatus 20 may be, for example, a film forming apparatus such as a sputtering apparatus, a CVD (Chemical Vapor Deposition) apparatus, a coating apparatus for coating a photosensitive material such as a photoresist, an exposure apparatus, a developing apparatus, an etching apparatus, a thermal processing apparatus such as an annealing apparatus, or the like. The processing device 20 has a plurality of devices and portions for performing processing, one of which will be referred to as a device 100. In the example shown in fig. 1, the apparatus 110, the apparatus 111, the apparatus 121, and the apparatus 122 will be described as an example of the apparatus 100 of the processing apparatus 20 in the process P.

The first processing device 21, i.e., the device 110 and the device 111, perform the process P1. The apparatus 110 is also referred to as a first apparatus, the apparatus 111 is referred to as a second apparatus, and the process P1 is referred to as a first process. The apparatuses 110 and 111 may be, for example, film forming apparatuses that perform a film forming process on a substrate.

The second processing device 22, that is, the device 121 and the device 122, perform the process P2. The device 121 is also referred to as a third device, the device 122 is referred to as a fourth device, and the process P2 is referred to as a second process. Devices 121 and 122 may be photoresist coating devices that perform the coating of photoresist.

In the example shown in fig. 1, the process P1 is performed by the apparatus 110 or the apparatus 111, and the process P2 is performed by either the apparatus 121 or the apparatus 122. That is, in the example shown in fig. 1, the substrate is processed by any one of the following paths: the path R1 processed by the devices 110 and 121, the path R2 processed by the devices 110 and 122, the path R3 processed by the devices 111 and 121, and the path R4 processed by the devices 111 and 122. The path R1 is also referred to as a first path, the path R2 is referred to as a second path, the path R3 is referred to as a third path, and the path R4 is referred to as a fourth path. The substrate subjected to the first process and the second process by the first path is referred to as a first substrate, the substrate subjected to the first process and the second process by the second path is referred to as a second substrate, the substrate subjected to the first process and the second process by the third path is referred to as a third substrate, and the substrate subjected to the first process and the second process by the fourth path is referred to as a fourth substrate.

Fig. 2 is a diagram showing an example of measurement results of the first embodiment. An example of the measurement result MR of the first embodiment will be described with reference to fig. 2. The measurement result MR is a result obtained by measuring the amount of error generated in the substrate after a predetermined process is performed on the substrate MR.

Fig. 2 (a) shows a measurement result (processing result) MR1 as an example of the measurement result MR. The measurement result MR1 is a result of measuring the amount of error generated in the substrate after the processing is performed through the path R1. The measurement result MR1 is a measurement result of the entire substrate. Exposing a pattern of a plurality of articles on a substrate, the exposure of one article is referred to as a scan. In fig. 2 (a), 4 articles were exposed. The measurement result MR1 collectively shows the measurement results of each scan, namely, measurement result MR1-1, measurement result MR1-2, measurement result MR1-3, and measurement result MR1-4. Fig. 2 (B) shows a measurement result MR2 as an example of the measurement result MR. The measurement result MR2 is a result of measuring the amount of error generated in the substrate after the processing is performed through the path R2. The measurement result MR2 is a measurement result of the entire substrate. The measurement result MR2 collectively shows the measurement results of each scan, namely measurement result MR2-1, measurement result MR2-2, measurement result MR2-3, and measurement result MR2-4. The measurement result MR1 is different from the measurement result MR 2. That is, the amount of error generated by the substrate varies depending on the path through which the substrate passes. Here, the error amount refers to a difference between a design value of a pattern formed on a substrate and a processing result (measurement result) MR obtained from the inspection device 220, and is also referred to as a pattern shift amount. Here, the design value of the pattern refers to a position to be exposed when the substrate is processed by the processing apparatus 20 (apparatus 100) and the substrate is not deformed. The error amount may be an amount of deformation of the entire substrate before the substrate is processed by the processing apparatus 20 and after the substrate is processed by the processing apparatus 20.

[ calculation of Path Difference correction value ]

The calculation of the path difference correction value according to the first embodiment will be described with reference to fig. 3 to 12.

Fig. 3 is a diagram showing an example of the functional configuration of the analysis system 10 according to the first embodiment. An example of the functional configuration of the analysis system 10 will be described with reference to fig. 3.

The analysis system 10 analyzes the device identification information DID, which is information from the plurality of processing devices 100, and the measurement information MI, which is information from the inspection device 220.

The inspection device 220 inspects the substrate. Specifically, the inspection apparatus 220 measures the processing results of the first substrate, the second substrate, the third substrate, and the fourth substrate. Here, the first to fourth substrates are sometimes referred to as sample substrates. The sample substrate refers to a substrate that has been exposed to light in order to calculate device characteristics (error amounts) that vary from one processing device 100 to another. More specifically, the inspection device 220 measures the amount of error generated in the substrate after a predetermined process is performed on the substrate by the processing device 20 (after the predetermined process is performed on the substrate and the substrate is exposed to light by the exposure device). The inspection device 220 outputs measurement information MI including the measurement result MR after the substrate is processed, together with the substrate identification information SID for identifying the substrate, to the analysis device 300.

The inspection device 220 may acquire the measurement result MR by performing measurement after performing individual processing on the substrate by the individual processing devices 20, or may acquire the measurement result MR by performing measurement after performing a plurality of processing on the substrate by the plurality of processing devices 20.

The analysis device 300 includes: a path information acquisition unit 310, a measurement information acquisition unit 320, a calculation unit 330, and a storage unit 340. The analyzer 300 calculates the amount of error (device characteristics) that each device 100 (device 110, device 111, device 121, and device 122) causes to occur on the substrate. The analysis device 300 may acquire information related to the process performed on the substrate by combining the device identification information DID and the substrate identification information SID from the device 100. The information related to the process performed on the substrate may be, for example, a process condition related to the process performed on the substrate. The analysis device 300 may calculate the amount of error that the processing device 20 causes to occur in the substrate by using the same method as the method described below.

The path information acquisition unit 310 acquires the device identification information DID and the substrate identification information SID from the processing apparatus 20 or the apparatus 100 (apparatus 110, apparatus 111, apparatus 121, and apparatus 122) in the processing apparatus. The path information acquisition unit 310 acquires the device identification information DID and the substrate identification information SID, obtains the path identification information RID, and outputs the path identification information RID to the calculation unit 330. The path identification information RID is information for identifying the plurality of processing apparatuses 100 that have performed the processing with respect to a predetermined substrate to which the plurality of processing is performed. Specifically, the route identification information RID is information for identifying which route of the substrate is processed through the route R1, the route R2, the route R3, and the route R4. That is, the path information acquisition unit 310 acquires the substrate identification information SID for identifying the substrate, and the path identification information RID of the first, second, third, and fourth paths through which the substrate passes.

The measurement information acquisition unit 320 acquires the substrate identification information SID and the measurement information MI measured by the inspection device 220. The measurement information acquisition unit 320 acquires measurement information MI from each of the plurality of substrates. That is, the measurement information acquisition unit 320 acquires the substrate identification information SID, and measurement information, which is a result of processing the first substrate, a result of processing the second substrate, a result of processing the third substrate, and a result of processing the fourth substrate, which are measured by the inspection device 220.

The calculating unit 330 calculates the device characteristics CI of each device 100 based on the acquired route identification information RID, measurement information MI, and substrate identification information SID. The device characteristics of each device 100 may be an amount of error caused by the processing of the device 100 to the substrate, which is generated when the device 100 performs the processing to the substrate. In the present embodiment, the first device and the second device perform the first process, and the third device and the fourth device perform the second process. That is, the calculating unit 330 calculates the first device characteristic generated by the first device on the first processed substrate, the second device characteristic generated by the second device on the first processed substrate, the third device characteristic generated by the third device on the second processed substrate, and the fourth device characteristic generated by the fourth device on the second processed substrate based on the route identification information RID and the measurement information MI.

The storage unit 340 stores the characteristics calculated by the calculation unit 330. The storage unit 340 stores the first device characteristic, the second device characteristic, the third device characteristic, and the fourth device characteristic.

Fig. 4 is a flowchart showing a series of operations related to calculation of the correction value according to the first embodiment. A series of operations when the analysis system 10 calculates the correction value will be described with reference to fig. 4.

The analyzer 300 collects measurement information MI, device identification information DID, and substrate identification information SID (step S110). Specifically, the route information acquisition unit 310 acquires the device identification information DID and the substrate identification information SID, and the measurement information acquisition unit 320 acquires the measurement information MI and the substrate identification information SID. The route information acquisition unit 310 acquires route information RID corresponding to each substrate from the substrate identification information DID and the substrate identification information SID. The route information acquisition unit 310 may directly acquire the route identification information RID from an external device or the like, instead of acquiring the route identification information DID.

The analysis device 300 collates measurement information MI (error amount) for each path (R1, R2, R3, and R4) and information of the device 100 through which the substrate passes (step S120).

Specifically, the analyzer 300 collates the information of the device 100 in each path through which the substrate passes with the measurement information MI of the substrate after passing through each path. More specifically, the analysis device 300 associates the route identification information RID with the measurement information MI based on the obtained correspondence I1 between the route identification information RID and the substrate identification information SID and the obtained correspondence between the measurement information MI and the substrate identification information SID.

Fig. 5 is a diagram showing an example of the correspondence relationship between the path and the measurement result in the first embodiment. The arrangement of information by the analysis device 300 will be described with reference to fig. 5.

In the example shown in fig. 5, information I1, which is information of the apparatus 100 after each path, and information I2, which is measurement information MI including the measurement result MR of the substrate after each path, are associated with each other. The measurement information MI is information related to measurement including measurement result MR, which is a result of measurement of the substrate processed through step 1+step 2+step 3+ … step N. Accordingly, the influence of each process is specified. Further, when a plurality of apparatuses 100 (for example, the apparatus 110 and the apparatus 111) are present in 1 step, the influence of each apparatus on the substrate is different. Therefore, the influence of the device 110 on the substrate and the influence of the device 111 on the substrate are specified. This information indicating the degree of influence of the device 110 (first device characteristic) or the information indicating the degree of influence of the device 111 (second device characteristic) is referred to as a device characteristic.

Specifically, regarding the information I1 that is the information of the apparatus 100 after each path, the first substrate having the substrate identification information SID "S01" and the path having the path identification information RID "R01" is processed as the process P1 by the apparatus 110, the substrate identification information SID "S03" and the process as the process P2 by the apparatus 121, the second substrate having the path identification information RID "R02" is processed as the process P1 by the apparatus 110, the process as the process P2 by the apparatus 122, the third substrate having the substrate identification information SID "S03" and the path having the path identification information RID "R03" is processed as the process P1 by the apparatus 111, the process as the process P2 by the apparatus 121, the fourth substrate having the substrate identification information SID "S04" and the path having the path identification information RID "R04" is processed as the process P1 by the apparatus 111, and the process as the process P2 by the apparatus 122. Regarding the information I2, which is the measurement information MI of the substrate after passing through each path, the correspondence is established with the measurement information MI of the first substrate after passing through the path R1, the correspondence is established with the measurement information MI of the second substrate after passing through the path R2, the correspondence is established with the measurement information 3, the correspondence is established with the measurement information MI of the third substrate after passing through the path R3, and the correspondence is established with the measurement information MI of the fourth substrate after passing through the path R4. Here, the route identification information RID is associated with the measurement information MI, but the measurement result MR may be associated with the route identification information RID alone.

(step S130) returning to fig. 4, the analysis device 300 calculates the device characteristics (error amounts) of each device based on the sorted information. As an example, the analysis device 300 calculates the device characteristics of each device 100 by the least squares method.

Here, an example of the case where the analysis device 300 calculates the device characteristics of each device 100 by the least squares method will be described. The calculation unit 330 uses simultaneous equations or least squares to calculate the path identification information RID and measurement information MI of each path in an analytical manner. The specific method of the minimum flattening method is that the calculating unit 330 calculates the device characteristics of each device 100 by minimizing the objective function of the square error shown in the following expression (1).

[ number 1]

Here, i is the path identification information RID, and j represents the j-th measurement point of the measurement coordinates of the substrate. Beta represents the error amount of each device at the j-th measurement point. x is a condition Vector (Vector) of the path i, i.e., path information.

At this time, the minimization objective function (normal equation) is expressed by the following formula (2).

[ number 2]

That is, the processing result (error amount) of the path i can be obtained by solving the following equation (3).

[ number 3]

In the case of calculating the device characteristics (error amount) by the least squares method, the device characteristics can be obtained by solving the following equation (4).

[ number 4]

Specifically, the device characteristic β is represented by the following formula (5).

[ number 5]

The analysis device 300 may visualize the calculated device characteristics of each device 100 by a predetermined method.

Fig. 6 is a flowchart showing a series of operations related to the visualization of the device characteristics of the first embodiment. A series of actions for visualizing the device characteristics will be described with reference to fig. 6.

(step S131) the calculating unit 330 compares the calculated device characteristics of each device 100 with the state of the substrate before the substrate is processed by the device 100 (i.e., calibrates the board coordinate system) and then visualizes the result. More specifically, the calibration plate coordinate system displays the amount of shift (error amount) of the pattern from each position of the substrate. The shift amount of the pattern at each position of the substrate is calculated based on the state before processing by the apparatus 100 and the state after processing the substrate by the apparatus 100. The calculating unit 330 visualizes β, which is a result obtained by the least squares method, using a calibration plate coordinate system, for example.

Fig. 7 is a diagram showing an example of the device characteristics visualized by using the coordinate system of the calibration plate according to the first embodiment. An example of the calibration plate coordinate system PC will be described with reference to fig. 7. In fig. 7, 4 calibration plate coordinate systems PC are shown as an example of the calibration plate coordinate systems PC. The calibration plate coordinate system PC1 shows the amount of shift of the pattern generated by the device 110 (hereinafter referred to as the device characteristic (error amount) of the device 110), the calibration plate coordinate system PC2 shows the device characteristic of the device 111, the calibration plate coordinate system PC3 shows the device characteristic of the device 121, and the calibration plate coordinate system PC4 shows the device characteristic of the device 122.

Here, the processing apparatus 20 has two or more apparatuses 100 (for example, the apparatus 110 and the apparatus 111 of the apparatus 21 in the process P1), but the unit of the apparatus 100 may be arbitrarily set. For example, when 2 processing apparatuses are provided for the processing step P1, 2 apparatuses are collectively referred to as the processing apparatus 20, one of the 2 apparatuses is referred to as the apparatus 100 (115), and the other is referred to as the apparatus 100 (118). Further, when two processing units are provided in the apparatus 100 (115) and the modes of influence of the two processing units on the substrate are different, the apparatus 100 (115) may be further subdivided, the processing unit 1 of the apparatus 100 may be the apparatus 100 (116), the processing unit 2 of the apparatus 100 may be the apparatus 100 (117), and even if the same apparatus 100 (for example, the apparatus 110) is used, the apparatus 110 may be subdivided as long as the influence of the processing conditions (processing temperature, processing time, etc.) on the substrate is different, the apparatus 110 may be the apparatus 1101 in the processing condition a, and the apparatus 1102 in the processing condition B.

By visualizing the device characteristics (errors) using the calibration plate coordinate system PC and displaying the visualized results using the characteristic display unit 331, the trend of the device characteristics (errors) of each device 100 can be visualized, and the trend of the device characteristics (errors) can be easily recognized. The calculation unit 330 may also be visualized by other methods that can quantitatively determine the device characteristics, such as by the method of step S132 or step S133. Here, the characteristic display unit 331 may be, for example, a liquid crystal display, an organic EL (Electroluminescence) display, or the like as long as the device characteristics can be displayed.

(step S132) returning to fig. 6, the calculating unit 330 may use the orthogonal function system to develop the device characteristics (error amounts) of each device 100. The calculation unit 330 develops the device characteristics on the substrate obtained in step S131 using, for example, an orthogonal function system.

Fig. 8 is a diagram showing an example of visualizing the device characteristics (error amounts) by using the orthogonal coordinate system according to the first embodiment. An example OF the orthogonal coordinate system OF will be described with reference to fig. 8.

Fig. 8 shows an example OF the case where coefficients are spread by the orthonormal function system, as an example OF the orthonormal function system OF. Fig. 8 a and 8B show the device characteristics of the predetermined device 100 when Legendre polynomials (Legendre polynomials) are used.

In the example shown in fig. 8, values obtained when the coefficients are developed into the coefficients of each of 1 to 18 by the orthonormal function system are shown.

By visualizing the amounts OF deformation components (error amounts) in the respective items using the orthogonal function system OF, the difference in trend OF the device characteristics (error amounts) OF the respective devices 100 can be quantitatively determined. For example, it can be easily determined whether or not the device characteristics between any two devices 100 (for example, the device 110 and the device 111) as shown in fig. 8 (a) and 8 (B) have the same tendency. In a specific example, when the calculating unit 330 determines that the trends of the error amounts of the devices 110 and 111 are common under the coefficients of L14 and L15 based on fig. 8 a and 8B, the correction values for correcting the L14 and L15 may be applied to the devices 100 (the devices 110 and 111) in a unified manner without obtaining the correction values for correcting the L14 and L15 for each of the devices 100 (the devices 110 and 111). The specific examples are also similar to the heat maps described below. In the case OF visualizing using the orthogonal function system OF, the calculation unit 330 may visualize the plurality OF devices 100 by other methods that facilitate the comparison between the plurality OF devices 100 by the method OF step S133 or the like.

(step S133) returning to fig. 6, the calculating unit 330 classifies the device characteristics (error amounts) of each device 100 by color in the order of the error amounts from high to low, and by color shade (Heat Map). By arranging them on a matrix, the coefficients of the orthogonal function system can be easily compared, and visualization can be achieved. The calculation unit 330 visualizes the result of the coefficient expansion using the orthonormal function in step S132 using a heat map, for example, and displays the visualized result using the characteristic display unit 331.

Fig. 9 is a diagram showing an example of visualizing the device characteristics (error amounts) using the heat map of the first embodiment. An example of the heat map HM will be described with reference to fig. 9.

Fig. 9 shows an example of the case where the coefficients 1 to 18 are expanded by the orthonormal function system in the heat map HM with respect to "device 110", "device 111", "device 121" and "device 122". The calculation unit 330 brings the coefficient of each device 100 to a value from +3 to-3, for example, and displays the value.

By visualizing using the heat map HM, differences in trend among the plurality of devices 100 can be easily compared.

(step S140) returning to fig. 4, calculating unit 330 calculates a correction value PM for each device 100 (calculates a first correction value PM1 for device 110, calculates a second correction value PM2 for device 111, calculates a third correction value PM3 for device 121, and calculates a fourth correction value PM4 for device 122). The calculating unit 330 may calculate a correction value for each lens module 370 included in the exposure apparatus, or may calculate a correction value for driving an actuator or the like mounted in the projection optical system, for example, in order to apply the device characteristic (error amount) of each device 100, which is calculated by the minimum flatness method, to the correction value when the substrate is exposed by the exposure apparatus. The correction value of the device characteristic of each device 100 may be calculated by driving the stage on which the substrate is mounted. That is, the correction conditions may include driving conditions of the driving section of the substrate stage holding the substrate.

Fig. 10 is a diagram showing an example of the correction value of the first embodiment. The calculation of the correction value will be described with reference to fig. 10.

Fig. 10 shows an example of the device characteristics (error amounts) of each device 100. The device characteristics of each device 100 may also be the result obtained by the least squares method, for example, in step S131.

The correction value of each device 100 is calculated based on the device characteristics of each device 100 shown in fig. 10. The calculating unit 330 calculates the correction value of each lens module 371 among the plurality of lens modules 370 by the correction value calculating function. More specifically, the calculating unit 330 calculates a correction value 411 for correcting the exposure region 401 to be exposed by the lens module 371 in the exposure region 400 of the entire substrate.

(step S150) returning to fig. 4, the analysis device 300 stores the information of the device 100 and the correction value corresponding to the device 100. The analysis device 300 stores information of the device 100 and information of the correction value PM corresponding to the device 100 in the storage unit 340 as the correspondence information CI, for example.

The analysis device 300 may store the first processing device 20 and/or the second processing device 21 in association with the correction value PM, or may store the path in association with the correction value PM.

Fig. 11 is a diagram showing an example of the correspondence relationship between the correction value and the processing device according to the first embodiment. Fig. 11 shows an example of the case where the device 100 (device 110, device 111, device 121, device 122) is stored in association with the correction value PM. Fig. 11 shows the correspondence information CI1, the correspondence information CI2, the correspondence information CI3, and the correspondence information CI4 as the correspondence information CI. The device 100 is identified by the device identification information DID. In the example shown in fig. 11, the correction value is a correction value PM calculated for each device 100. The correspondence information CI1 is to make 1 device 100, i.e. "device 110", correspond to the correction value PM "first correction value", the correspondence information CI2 is to make 1 device 100, i.e. "device 111", correspond to the correction value PM "second correction value", the correspondence information CI3 is to make 1 device 100, i.e. "device 121", correspond to the correction value PM "third correction value", and the correspondence information CI4 is to make 1 device 100, i.e. "device 122", correspond to the correction value PM "fourth correction value". The storage unit 340 stores these pieces of correspondence information CI.

Fig. 12 is a diagram showing an example of the correspondence relationship between the paths and the correction values in the first embodiment. Fig. 12 shows an example of storing the device 100 in association with a path. Fig. 12 shows the correspondence information CI11, the correspondence information CI12, the correspondence information CI13, and the correspondence information CI14 as the correspondence information CI. The path is identified by the path identification information RID. In the example shown in fig. 12, the process P1 is processed by the "apparatus 110", the process P2 is processed by the "apparatus 121", the process P1 is processed by the "apparatus 110", the process P2 is processed by the "apparatus 122", and the process P1 is processed by the "apparatus 111", the process P2 is processed by the "apparatus 121", with respect to the substrate passing through the path R3. Regarding the substrate passing through the path R4, the process P1 is processed by the "apparatus 111", and the process P2 is processed by the "apparatus 122". The path R1 corresponds to the path correction value RPM, i.e. "path correction value 1", the path R2 corresponds to the path correction value RPM, i.e. "path correction value 2", the path R3 corresponds to the path correction value RPM, i.e. "path correction value 3", and the path R4 corresponds to the path correction value RPM, i.e. "path correction value 4". The storage unit 340 may store the correspondence information CI.

[ application of Path Difference correction value ]

The application of the path difference correction value of the first embodiment will be described with reference to fig. 13 to 16. The analyzer 300 transmits the correction value calculated by the above method to the exposure apparatus, and the exposure apparatus applies the correction value corresponding to the path through which the substrate passes.

Fig. 13 is a diagram showing an example of a functional configuration of an analysis system related to application of the correction value according to the first embodiment. An example of the functional configuration of the analysis system 10 will be described with reference to fig. 13. In the description of the analysis system 10, the same reference numerals are given to the components already described with reference to fig. 3, and the description thereof may be omitted. The analysis system 10 further includes a selection unit 350 and an output unit 360.

The correction condition calculating unit 351 calculates correction conditions for exposing the substrate. The correction condition calculating unit 351 includes the selecting unit 350, and based on the substrate identification information SID and the route identification information RID of the substrate, selects the correction value related to the two devices through which the substrate passes, among the first correction value, the second correction value, the third correction value, and the fourth correction value calculated by the calculating unit 330 and stored in the storage unit 340. The correction condition calculating unit 351 calculates a correction condition when exposing the substrate, based on correction values associated with the two selected devices.

The selecting unit 350 selects the correction condition AR at the time of exposing the substrate based on the plurality of correction values stored in the storage unit 340. Specifically, the selecting unit 350 acquires the route identification information RID and the substrate identification information SID from the route information acquiring unit 310, and acquires the correction value corresponding to the route identification information RID from the storage unit 340. The correction value corresponding to the route identification information RID is a correction value corresponding to the device characteristic of the device 100 included in each route. Each path has two or more steps (for example, a first process and a second process). Accordingly, the correction value corresponding to the path identification information RID is based on at least the correction value related to the first processing means (the first correction value related to the means 110 or the second correction value related to the means 111), the correction value related to the second processing means (the third correction value related to the means 121 or the fourth correction value related to the means 122). That is, the selecting unit 350 selects the correction condition AR to be applied when performing exposure on the substrate on which the first process and the second process are performed on the route identified based on the acquired route identification information RID, based on two correction values out of the 4 correction values (first to fourth correction values) stored in the storage unit 340.

The output unit 360 acquires the correction condition AR selected by the selection unit 350. The output unit 360 outputs the acquired correction condition AR to the exposure device 230. Specifically, the output unit 360 outputs the correction condition AR to the exposure device 230 that exposes the substrate corresponding to the correction condition AR.

The exposure device 230 exposes the substrate corresponding to the correction condition AR based on the acquired correction condition AR.

Fig. 14 is a flowchart showing a series of operations related to the application of the correction value of the first embodiment. A series of operations when the correction value is applied to the analysis system 10 will be described with reference to fig. 14.

The analyzing apparatus 300 collects path information of the substrates under production (step S210). Here, the substrate in production is a substrate (fifth substrate) different from the substrates (first to fourth substrates) used in determining the correction value PM in steps S110 to S150. The fifth substrate may be referred to as a target substrate. More specifically, the target substrate does not refer to a substrate for calculating the device characteristics of each processing device 100, but refers to a substrate exposed using the calculated device characteristics of each processing device 100. The route information acquisition unit 310 acquires the device identification information DID and the substrate identification information SID from the substrate under production, and acquires the route identification information RID. The route information acquisition unit 310 may directly acquire the route identification information RID from the substrate under production. The substrate in production identified by the substrate identification information SID is a substrate that has been subjected to a predetermined process by the apparatus 100 and has not been subjected to an exposure corresponding to the predetermined process.

The analyzing apparatus 300 collates path information of each substrate in production (step S220). Specifically, the analysis device 300 specifies information of the device 100 included in each path through which the substrate passes. Information of the device 100 in each path through which the substrate passes (passes) may be included in the path identification information RID.

The analysis device 300 checks (step S230) the path information of each substrate in production with the path information of the registered path. Specifically, the selecting unit 350 included in the correction condition calculating unit 351 obtains the correction value PM corresponding to the apparatus 100 in each path through which the substrate under production passes by comparing the correction value PM stored in the storage unit 340 and the apparatus 100, which are specified in step S220. For example, when the route R1 is a route through the devices 110 and 121, the selecting unit 350 acquires the first correction value, which is the correction value PM corresponding to the device 110, and the third correction value, which is the correction value PM corresponding to the device 121, from the storing unit 340.

The analyzer 300 determines (step S240) the correction value PM for the substrate under production. Specifically, the correction condition calculating unit 351 may calculate the correction value PM corresponding to the route R1 identified by the route identification information RID based on the correction value PM, the first correction value, and the third correction value selected in step S230, or may select the route correction value RPM for each route stored in the storage unit 340 as the route correction value RPM based on the route identified by the route identification information RID.

Fig. 15 is a diagram for explaining an example of selecting the correction value according to the first embodiment, and selecting the correction value based on the registered correction value PM for each device 100. An example of the case where the correction value PM is selected based on each registered device 100 will be described with reference to fig. 15.

Fig. 15 shows an example of the case where the substrate identification information SID is "S01" and an example of the case where the substrate identification information SID is "S02". The substrate having the substrate identification information SID "S01" is processed by a path having the path identification information RID "R01". For a path for which the path identification information RID is "R01", the information of the apparatus 100 included in the path is specified in step S220. Specifically, the path including the device 110 and the device 121 is specified for the path having the path identification information RID of "R01". The first correction value, which is the correction value of the device 110, and the third correction value, which is the correction value of the device 121, stored in the storage unit 340 are selected by the selection unit 350 included in the correction condition calculation unit 351, and the correction condition calculation unit 351 calculates the path correction value RPM by adding the first correction value and the third correction value. In the example shown in fig. 15, the value obtained by adding the correction value PM of the device 110, that is, "first correction value", and the correction value PM of the device 121, that is, "third correction value", is the path correction value RPM, and is applied to the substrate having the substrate identification information SID "S01". Similarly, the value obtained by adding the correction value PM of the device 110, i.e., the "first correction value" to the correction value PM of the device 122, i.e., the "fourth correction value" becomes the path correction value RPM, and is applied to the substrate having the substrate identification information SID of "S02", the value obtained by adding the correction value PM of the device 111, i.e., the "second correction value" to the correction value PM of the device 121, i.e., the "third correction value" becomes the path correction value RPM, and is applied to the substrate having the substrate identification information SID of "S03", and the value obtained by adding the correction value PM of the device 111, i.e., the "second correction value" to the correction value PM of the device 122, i.e., the "fourth correction value" becomes the path correction value RPM.

Fig. 16 is a diagram for explaining an example of selecting a correction value according to the first embodiment, and selecting the correction value based on a registered route correction value. An example of the case where the selection is made based on the registered path correction value will be described with reference to fig. 16. The configuration described in fig. 16 may be denoted by the same reference numerals, and the description thereof may be omitted.

In this example, the selecting unit 350 selects the route correction value RPM based on the route correction value RPM stored in the storing unit 340, and the correction condition calculating unit 351 sets the route correction RPM selected by the selecting unit 350 as the correction condition. In the example shown in fig. 16, the "path correction value 1" corresponding to the path having the path identification information RID of "R01" is the path correction value RPM, and is applied to the substrate having the substrate identification information SID of "S01". Similarly, "path correction value 2" corresponding to the path having the path identification information RID of "R02" is set as the path correction value RPM, applied to the substrate having the substrate identification information SID of "S02", the "path correction value 3" corresponding to the path having the path identification information RID of "R03" is set as the path correction value RPM, applied to the substrate having the substrate identification information SID of "S03", and the "path correction value 4" corresponding to the path having the path identification information RID of "R04" is set as the path correction value RPM, and applied to the substrate having the substrate identification information SID of "S04".

By previously calculating and storing the path correction value RPM, the time required for calculating the path correction value RPM can be omitted, and thus the processing time can be shortened.

(step S250) returning to fig. 14, the analysis device 300 transmits the substrate information in production and the path correction value RPM to the exposure device 230. Specifically, the output unit 360 receives information including the substrate identification information SID and the path correction value RPM from the correction condition calculation unit 351, and outputs the information to the exposure device 230 as the correction condition AR. In addition, the correction condition AR may include conditions concerning exposure application, and the like. In order to apply the correction condition AR as a correction value when exposing the substrate by the exposure apparatus, the correction condition may be output for each lens module 370 provided in the exposure apparatus, or may be output as a correction condition for driving an actuator or the like mounted in the projection optical system. The correction conditions may be calculated by driving the stage on which the substrate is mounted to correct the substrate.

(step S260) the substrate in production identified by the substrate identification information SID is carried into the exposure device 230.

The exposure device 230 adds the path correction value RPM included in the correction condition AR acquired from the analysis device 300 to the correction value of the Recipe (Recipe) (step S270) to perform exposure. Here, the correction value of the recipe refers not to the error amount depending on the apparatus 100, but to the correction value applied to any path as long as the processing conditions for the substrate are the same. Even if the paths R1 to R4 are passed, if the processing conditions (including the processing time and the processing temperature) are the same, the correction value of the recipe is applied to the same correction value irrespective of the path identification information RID being "R01", "R02", "R03", and "R04". In addition, when the output unit 250 outputs the path correction value RPM to the exposure device 230 in step S250, the correction condition to which the correction value of the recipe is added may be output to the exposure device 230 in addition to the path correction value RPM.

As a modification of the first embodiment, as shown in fig. 28, the first processing apparatus 21 in the process P1 includes not only the apparatuses 110 and 111 but also the apparatus 112, and this embodiment is also useful for the case where there is an unknown path through which the substrate does not pass in the processes P1 and P2, or the case where the apparatus 112 is newly added to the first processing apparatus 21 in the process P1. More specifically, when the path R5 passing through the device 112 in the process P1 and the path R5 passing through the device 121 in the process P2 is provided, the calculating unit calculates the fifth device characteristic, which is the device characteristic (error amount) related to the device 112, and calculates a fifth correction value for correcting the fifth device characteristic. Here, even if the substrate does not pass through the path R6 passing through the device 112 in the process P1 and the device 122 in the process P2, the path correction value related to the path R6 can be calculated. The fifth correction value of the device 112 and the fourth correction value of the device 122 are selected by the selecting unit 350, and the fifth correction value and the fourth correction value are added by the correction condition calculating unit 351 to calculate the correction condition of the path R6.

Summary of effects of the first embodiment

As described above, according to the present embodiment, the analysis device 300 includes the route information acquisition unit 310 to acquire information identifying a route through which a substrate passes, and includes the measurement information acquisition unit 320 to identify the substrate. The analysis device 300 further includes a calculation unit 330 to calculate the error amounts of the respective devices 100 (devices 110, 111, 121, 122) included in the path, and to calculate a correction value PM for correcting the error amounts of the respective devices 100. Therefore, according to the present embodiment, the error that occurs in the substrate for each apparatus 100 that performs the processing on the substrate can be calculated. According to the present embodiment, the error amount can be calculated on a device-by-device basis, and thus the exposure pattern can be corrected according to the device 100.

Further, according to the present embodiment, since the correction value of each device 100 (device 110, device 111, device 121, device 122) can be calculated, even in a novel route, the correction value can be predicted by combining the correction values of the known devices 100. According to the present embodiment, the path correction value can be represented by adding correction values for each device 100, and therefore, for a novel path (a combination of known devices 100), the error amount can also be calculated by adding correction values.

Further, according to the present embodiment, the correction condition calculating unit 351 calculates the correction condition by adding the characteristics of two devices through which the substrate passes among the first device, the second device, the third device, and the fourth device. Therefore, according to the present embodiment, the correction condition can be easily calculated.

Further, according to the present embodiment, the analysis device 300 calculates the error amount of each device 100 (device 110, device 111, device 121, device 122) based on the measurement information MI acquired from the plurality of substrates, and calculates the correction value PM for correcting the error amount of each device 100. Therefore, according to the present embodiment, the error amount of each device 100 can be calculated more accurately and with higher reliability. Therefore, according to the present embodiment, the analysis device 300 can correct the exposure pattern according to the device 100 based on the more accurate and reliable error amount.

Further, according to the present embodiment, the measurement information acquisition unit 320 acquires measurement information MI measured after performing at least the first and second processes, and the calculation unit 330 calculates device characteristics (first and second device characteristics) of the devices 110 and 111 of the two or more first processing devices 21, device characteristics (third and fourth device characteristics) of the devices 121 and 122 of the two or more second processing devices 22, and calculates correction values (first to fourth correction values) for correcting the respective device characteristics based on the plurality of measurement information MI. That is, according to the present embodiment, correction values relating to the respective devices 100 (110, 111, 121, 122) can be calculated from the measurement information MI after a plurality of processes are performed.

Here, according to the prior art, the error amount generated by each device 100 (device 110, device 111, device 121, device 122) cannot be calculated from the result of measurement for each path. Therefore, although the error amount per path is stored, even when the apparatus 100 included in the path is changed, the correction value based on the stored error amount cannot be applied.

According to the present embodiment, since the error amount of each device 100 can be calculated, even when one device 100 among the plurality of devices 100 included in the path is changed, the error amount of the other device can be continuously used. Therefore, according to the present embodiment, data of the error amount of each device can be stored more, and therefore, the exposure pattern can be corrected according to the device 100 based on the error amount with higher accuracy and reliability.

The analyzer 300 further includes a correction condition calculating unit 351 for calculating correction conditions when exposing the substrate. Further, the correction condition calculating unit 351 includes the selecting unit 350, and based on the substrate identification information SID and the route identification information RID, uses the selecting unit to select the correction value of the two devices through which the substrate passes, of the first correction value, the second correction value, the third correction value, and the fourth correction value stored in the storage unit 340. The correction condition calculation unit 351 calculates a correction condition based on the correction values of the two selected devices. Therefore, according to the present embodiment, the analysis device 300 can calculate the correction condition corresponding to the path through which the substrate passes.

Further, according to the present embodiment, the analyzer 300 includes the storage unit 340 to store at least the first correction value, the second correction value, the third correction value, and the fourth correction value, and the selector 350 to select correction conditions to be applied when exposing the substrate subjected to the first process and the second process in the path identified by the path identification information RID based on the stored first correction value, second correction value, third correction value, and fourth correction value. That is, the analyzer 300 calculates the exposure conditions applied to the substrate based on the error amounts of the respective devices 100. Therefore, according to the present embodiment, the error amount of each path through which the substrate identified by the substrate identification information SID passes can be selected.

Further, according to the present embodiment, the analysis device 300 includes the output unit 360, and outputs the correction condition selected by the selection unit 350 to the exposure device 230. Accordingly, the analysis device 300 can apply the selected error amount as a correction value when performing exposure.

In the present embodiment, the exposure device 230 exposes the substrate using the correction conditions obtained by the analysis device 300. Accordingly, the exposure device 230 can correct the exposure pattern according to the error amount calculated by the processing device 100 for each device 100.

The processing apparatus 20 may be a Tray (Tray) or a photomask used when the substrate is placed on the exposure apparatus, an electronic photomask (DMD, SLM) having a plurality of micromirrors, or the like. More specifically, in the case of a tray, when a plurality of trays on which substrates are placed are provided in the exposure apparatus, the entire tray is set as the processing apparatus 20, one of the trays is set as the apparatus 100, and when a plurality of photomasks having the same pattern are provided, the plurality of photomasks are set as the processing apparatus 20, one of the photomasks is set as the apparatus 100, and when the photomask is an electronic photomask, the plurality of electronic photomasks are set as the processing apparatus 20, and one of the electronic photomasks is set as the apparatus 100.

In the present embodiment, the analysis device 300 calculates the error amount and the correction value for each device 100, but the same analysis may be performed by calculating the error amount and the correction value for each processing device 20.

Second embodiment

Fig. 17 is a diagram showing an example of an analysis system according to the second embodiment. An example of the analysis system 10A will be described with reference to fig. 17. In the description of the analysis system 10A, the same components as those of the analysis system 10 may be denoted by the same reference numerals, and the description thereof may be omitted. The analysis system 10A is different from the analysis system 10 in that the analysis device 300 is connected to a plurality of factories M via a predetermined network NW. The predetermined network NW may be, for example, the internet. The plurality of factories M each include a plurality of processing apparatuses 100, inspection apparatuses 220, and exposure apparatuses 230.

The processing device 20 or the device 100 (or the device 110, the device 111, the device 121, or the device 122) in the processing device 20 outputs the device identification information DID and the substrate identification information SID to the analysis device 300 via the network NW.

The inspection device 220 outputs measurement information MI and substrate identification information SID to the analysis device 300 via the network NW.

The exposure device 230 outputs the calculated correction condition AR to the exposure device 230 via the network NW.

The path information acquisition unit 310 acquires path identification information RID and substrate identification information SID based on the device identification information DID and substrate identification information SID output by the processing apparatus 20 or the processing apparatus 100 in the processing apparatus 20 via the network NW.

In the analysis system 10A, the factories M1, M2, and M3 are connected to the network NW. The analyzer 300 calculates the correction conditions AR based on the information acquired from each of the factories M, and outputs the correction conditions AR to the exposure device 230 provided in each of the factories M.

For example, when the processing apparatus 20 or the apparatus 100 in the processing apparatus 20 provided in the plant M1 is similar to the processing apparatus 20 or the apparatus 100 in the processing apparatus 20 provided in the plant M2, the analysis system 10A may use the error amount of the processing apparatus 20 or the apparatus 100 calculated based on the information acquired from the plant M1 as the error amount of the processing apparatus 20 or the apparatus 100 provided in the plant M2 different from the plant M1. The analysis system 10A can estimate the error amount of the processing device 20 or the device 100 in the novel plant M by acquiring information from a plurality of plants M.

Summary of effects of the second embodiment

As described above, according to the present embodiment, the analysis system 10A is connected to the plurality of factories M via the network NW. That is, the analysis system 10A can acquire the error amounts of the devices 100 included in the plurality of factories M. Accordingly, the analysis system 10A can calculate the correction value based on the error amounts of the plurality of devices 100 transmitted from the plurality of factories M. Accordingly, the analysis system 10A may correct the exposure pattern based on a more accurate, more reliable amount of error.

Further, according to the present embodiment, since the correction value can be calculated based on the error amounts of the plurality of devices 100 (the device 110, the device 111, the device 121, and the device 122) transmitted from the plurality of factories M, the error amounts of the respective devices 100 can be quantitatively expressed by expanding the coefficients of the error amounts of the respective devices 100 by using the orthonormal function system, and comparison with the error amounts of the respective devices 100 in large numbers can be easily performed. Therefore, according to the present embodiment, since the tendency of the error amount can be quantitatively expressed, it is possible to judge the error component of the apparatus 100, compare the apparatuses 100, or detect an abnormal apparatus 100.

In the present embodiment, the analysis device 300 calculates the error amount and the correction value for each device 100, but the same analysis as described above may be performed by calculating the error amount and the correction value for each processing device 20.

Third embodiment

Fig. 18 is a diagram showing an example of an analysis system according to the third embodiment. An example of the analysis system 10B will be described with reference to fig. 18. In the description of the analysis system 10B, the same components as those of the analysis system 10 may be denoted by the same reference numerals, and the description thereof may be omitted. The analysis system 10B is different from the analysis system 10 in that it includes, as the first layer L1, the steps P41, P42, P43, P44, and P45, and includes, as the second layer L2, the steps P46, P47, and P48. For example, the process P41 is a sputtering process, the process P42 is an exposure process, the process P43 is an etching process, the process P44 is an inspection process, the process P45 is an annealing process, the process P46 is a CVD process, the process P47 is an exposure process, and the process P48 is an inspection process.

In fig. 18, 3 different substrates are processed through different paths. Specifically, 3 different substrates are processed through the paths R41, R42, and R43, respectively.

The process P41 includes the apparatuses 411 and 412, and the apparatuses 411 and 412 process the substrates, respectively, and then output the substrate identification information SID of the substrates and the device identification information DID of the substrates to the analyzer 300B.

The step P42 includes an exposure device 421 and an exposure device 422, and the exposure device 421 and the exposure device 422 acquire the correction conditions AR from the analysis device 300B, respectively, and perform exposure based on the acquired correction conditions AR.

When the influence of each exposure apparatus on the substrate is calculated as the error amount, the apparatus identification information DID of the exposure apparatus and the substrate identification information SID of the processed substrate are output to the analyzer 300A, and the analyzer 300B can calculate the error amount of each exposure apparatus for the substrate based on the substrate identification information SID obtained from the exposure apparatus and the subsequent measurement result.

The process P43 includes the apparatuses 431, 432, and 433, and the apparatuses 431, 432, and 433 process the substrates, respectively, and then output the substrate identification information SID of the substrates and the device identification information DID of the substrates to the analyzer 300B.

The process P44 includes an inspection device 440. The inspection device 440 performs predetermined measurement on the substrate, and outputs the substrate identification information SID and measurement information MI of the substrate subjected to the measurement to the analysis device 300B.

The step P45 includes the apparatuses 451, 452, and 453, and the apparatuses 451, 452, and 453 process the substrates, respectively, and then output the substrate identification information SID of the substrates and the device identification information DID of the substrates to the analyzer 300B.

The step P46 includes the devices 461 and 462, and the devices 461 and 462 process the substrates, respectively, and then output the substrate identification information SID of the substrates and the device identification information DID of the substrates to the analyzer 300B.

Step P47 includes an exposure device 470. The exposure device 470 acquires the correction condition AR from the analysis device 300B, and performs exposure based on the acquired correction condition AR.

Step P48 includes an inspection device 480. The inspection device 480 performs predetermined measurement on the substrate, and outputs the substrate identification information SID and measurement information MI of the substrate subjected to the measurement to the analysis device 300B.

Fig. 19 is a diagram showing an example of the correspondence relationship between the path and the measurement result in the third embodiment. An example of the correspondence relationship between the paths and the measurement results in the third embodiment will be described with reference to fig. 19.

In the example shown in fig. 19, the information of the apparatus 100 through which each path passes is associated with measurement information MI including the measurement result MR of the substrate after passing through each path. Specifically, the path having the path identification information RID "R41" is the path in which the process as the process P41 is performed by the apparatus 411, the process as the process P42 is performed by the apparatus 421, the process as the process P43 is performed by the apparatus 431, the process as the process P45 is performed by the apparatus 452, the process as the process P46 is performed by the apparatus 461, the process as the process P47 is performed by the apparatus 470, the path having the path identification information RID "R42" is the path in which the process as the process P41 is performed by the apparatus 412, the process as the process P42 is performed by the apparatus 421, the process as the process P43 is performed by the apparatus 433, the process as the process P45 is performed by the apparatus 453, the process as the process P46 is performed by the apparatus 462, the process as the process P47 is performed by the apparatus 470, the path having the path identification information RID "R43" is the process as the process P41 is performed by the apparatus 412, the process as the process P42 is performed by the apparatus 422, the process as the process P47 is performed by the apparatus 451, the process as the process P45 is performed by the process P46, the process as the process P46 is performed by the apparatus 461. The inspection device 480 in the step P48 inspects the substrates passing through the steps P41 to P47. "measurement.41" is associated with the measurement result of the substrate passing through the path R41, "measurement.42" is associated with the measurement result of the substrate passing through the path R42, and "measurement.43" is associated with the measurement result MR of the substrate passing through the path R43.

In fig. 19, the substrate is measured by the step P44 of the first layer L1, but in the table of fig. 19, the measurement result MR of the step P44 may be correlated with the paths R1 and R2, and the correlation is not necessarily established. It is sufficient to measure the substrate again in the step P48 of the second layer L2, and at least the latest measurement result MR of the substrate is correlated with the paths R1 and R2. The same applies to the third layer and the second layer. The reason for this is that whether or not the substrate is exposed with high accuracy is checked by grasping the error amounts of the paths (R41, R42) from the latest measurement result MR of the substrate.

Summary of effects of the third embodiment

As described above, according to the present embodiment, the analysis system 10B includes a plurality of processing steps, and each processing step includes 1 or more devices. Therefore, there are paths in which the number of devices included in each processing step is multiplied. Here, in the case of calculating the error amount for each path by the conventional technique, the number of error amounts to be stored becomes large, and the number of measurement results required to calculate the error amount for one path becomes small. In addition, in the case of calculating the error amount for each path by the conventional technique, there may be paths for which the error amount is not measured. However, according to the present embodiment, since the error amount is calculated for each device, the error amount to be stored becomes small, and the number of measurement results required to calculate the error amount for one device becomes large. Therefore, according to the present embodiment, the error amount can be calculated more accurately and with higher reliability. Further, according to the present embodiment, the error amount can be calculated for each device, and thus the error amount can be calculated for all paths.

Further, according to the present embodiment, it is possible to detect a device having a large error amount and a device having a small error amount among a plurality of devices. Therefore, according to the present embodiment, a path having a small error amount among a plurality of paths can be detected.

The analysis system 10B may be provided with a route recommendation unit, not shown, for example, to recommend a route. The route recommendation unit recommends a route to be passed through, for example, according to the Grade (Grade) of the product. The path recommendation unit recommends a path (Golden Route) with a smaller error, for example, in the case of a product or Layer (Layer) with a relatively strict accuracy.

Further, according to the present embodiment, since the analysis system 10B calculates the error amount for each device, the error amounts of the respective devices among the plurality of devices can be compared. As a result of comparing the error amounts of the respective devices, the analysis system 10B can detect a device having a larger error amount and a device having a smaller error amount. Therefore, according to the present embodiment, the analysis system 10B can detect a device having a large error amount abnormality as a device having an abnormality.

In addition, according to the present embodiment, even in the same apparatus, a portion having a large difference in error can be detected on the substrate. The analysis device 300 can estimate that some abnormality occurs in a portion of the substrate where the error amount is large, and can promote maintenance work such as maintenance.

Further, it is also possible to find an abnormal portion on the substrate based on the vector diagram or the coefficient of the orthonormal function included in the measurement information MI, to prompt investigation of whether or not there is an abnormality in the photomask drawing error of the abnormal portion, or to prompt investigation of whether or not it relates to the Heater (Heater) position of the heat treatment (Process).

Further, according to the present embodiment, a path through which a substrate may pass in the future among a plurality of paths may be determined in advance, and corrected to an exposure shape that, for example, counteracts a deformation amount of a Plate (Plate) generated in the processing apparatus 100 provided in the path. The "final TP (total pitch) accuracy" can be improved by performing correction such as counteracting the amount of plate deformation generated after exposure. TP refers to an absolute value of an error amount obtained from the design value of the pattern and the measurement information MI. Further, by correcting the plate deformation amount generated in the CF (color filter) step, the CF bonding accuracy can be improved.

In addition, the exposure shape can be adjusted by matching the Mask deformation and Alignment accuracy in the organic vapor deposition process in the OLED manufacturing process, thereby improving the vapor deposition accuracy.

Further, according to the present embodiment, since the correction value is weighted after the step of discriminating between the step of correcting with priority and the step of correcting with no priority is provided, the correction value may be weighted. Specifically, the correction condition calculating unit 351 may be configured to calculate the correction condition by weighting any one of the first characteristic, the second characteristic, the third characteristic, and the fourth characteristic. By weighting the correction value, the correction amount can be reduced by weighting the unstable process with a large deviation. In the case where the calculated correction value is large, the effect may be confirmed while increasing the correction value by a small amount in order to avoid the risk of error in the correction value.

In the present embodiment, the analysis device 300B calculates the error amount and the correction value for each device 100, but the same analysis as described above may be performed by calculating the error amount and the correction value for each processing device 20.

Fourth embodiment

In the above embodiment, a method of calculating the error amount of each device 100 from the measurement result of each path is described. By calculating the error amount of each device 100, the error amount of each device 100 can be added to calculate the error amount of each path. However, in the case where there is an association between processes, it may not be sufficient to merely add the error amounts of each device 100.

In the fourth embodiment, the difference from the above-described embodiment is that the error amount of each path is calculated on the premise of calculating the error amount of each apparatus 100 and considering the correlation between processes.

[ method 1: combining a plurality of processes to be regarded as 1 process ]

In the present embodiment, the analysis system 10C (not shown) uses x in the above formula (1) as a condition vector in the path i, that is, as path information, as a combination of a plurality of devices 100.

That is, in the present embodiment, by regarding a plurality of processes as one process, an error amount in consideration of the correlation between the processes can be calculated.

In the present embodiment, by regarding a plurality of processes as one process, formulation can be achieved without breaking the form of the least squares method.

On the other hand, since all conditions of the combination are covered, as the number of steps and the number of devices used in each step increase, the stored information becomes enormous. Further, as the stored information becomes huge, the number of data per condition tends to be small, and therefore, there is a possibility that the estimation result becomes unstable.

[ method 2: introduction of interaction term

In the present embodiment, the analysis system 10C considers the interactions between processes by introducing the interaction terms based on the above formula (3). Specifically, the expression (6) below.

[ number 6]

Where γ is the difference in relation to the interaction, x _int Representing the path. That is, according to the present embodiment, by adding the error amount related to the interaction to the error amount of each device 100, a more accurate error amount can be calculated.

Here, the coefficient γ of the interaction term may also be subjected to mechanical learning using a neural network or the like. The coefficient γ of the interaction term may be learned by setting a limit such as L1 regularization to a small value. Specifically, by reducing the value of λ shown by the following formula (7), the ratio contributed by the interaction term can be reduced.

[ number 7]

According to the present embodiment, formulation can be achieved without breaking the form of the least squares method. Further, according to the present embodiment, since the interaction items are simply added, even when the interaction items of all paths are not calculated (only the interaction in the paths becomes 0), the error amount in the paths can be calculated.

In the present embodiment, the analysis system 10C calculates the error amount and the correction value for each device 100, but the same analysis as described above may be performed by calculating the error amount and the correction value for each processing device 20.

Fifth embodiment

Fig. 20 is a diagram showing an example of a functional configuration of an analysis system according to the fifth embodiment. An example of the analysis system 10D will be described with reference to fig. 20. In the description of the analysis system 10D, the same components as those of the analysis system 10 may be denoted by the same reference numerals, and the description thereof may be omitted. The analysis system 10D differs from the analysis system 10 in that it includes a defective device detection unit 370 and a warning unit 380.

The defective device detection unit 370 detects a defective device 100 based on the error amount of each device 100 calculated by the calculation unit 330. For example, the defective device detection unit 370 measures a change in the error amount of the same processing device 100, and determines that the processing device 100 is abnormal when there is an abnormality in the change with time. The defective device detection unit 370 may store a correspondence relationship between the error amount stored in the storage unit 340 and the time (or the time of acquiring data) for performing the inspection of the substrate in order to detect the change with time.

The defective device detection unit 370 may correct the correction value PM for correcting the error amount based on the change with time. For example, when the temporal change in the error amount has regularity, the defective device detection unit 370 may correct the correction value PM based on the elapsed time since the current date and time or data was calculated (or acquired).

The defective device detection unit 370 may compare the error amounts of the same processing device 100 or similar devices 100 among the plurality of devices 100 that can collect data with each other, and detect a processing device 100 having an abnormality.

The defective device detection unit 370 may determine whether or not there is a tendency of the cause of the defect of the plurality of processing devices 100 by storing the generated defect, and specify the cause of the defect when there is a tendency of the cause of the defect. By specifying the cause of occurrence of the defect, the defect predicted to be likely to occur thereafter can be prevented from occurring.

When the defective device detection unit 370 detects a defective device, the warning unit 380 warns the factory provided with the defective device. For example, the warning unit 380 notifies a factory provided with the device via a predetermined communication network. When the analysis device 300D is located in the same factory as the processing device 100, the inspection device 220, or the exposure device 230, the warning unit 380 may warn of the occurrence of a defect by lighting an LED lamp, flashing, or a buzzer.

The warning unit 380 may notify the possibility of a defect together with the warning. For example, the warning unit 380 may notify the possibility of occurrence of a defect or the type of defect, based on the situation in which the error amount changes with time.

In the present embodiment, the analysis system 10D uses the error amount for each device 100, but the same analysis as described above may be performed using the error amount for each processing device 20.

Sixth embodiment

In the above embodiment, an example of the case where the error amount of each device 100 is calculated based on the path through which the substrate passes is described. In the sixth embodiment, a point different from the above embodiment is that the processing conditions of each processing apparatus 100 are regarded as path information. That is, in the present embodiment, even when the same apparatus 100 is used, the processing conditions are different, and the different paths are regarded as different paths.

Even in the case of passing through the same processing apparatus 100, when the processing conditions are different, the path information acquisition unit 310 looks at the different paths, and thus, when the error amount is calculated by the calculation unit 330, the apparatus 100 having a large influence on the error amount can be found.

The treatment conditions may be, for example, conditions such as a treatment temperature. When the processing conditions are processing temperatures, each processing temperature in a predetermined range is considered to be different from each other. By configuring in this way, the processing temperature having a large influence on the error amount can be detected. Further, by providing a proposal unit not shown, it is possible to estimate and propose a processing condition such as a reduction in the error amount based on the relationship between the obtained processing temperature and the error amount.

In the present embodiment, the analysis device 330 calculates the error amount of each device 100 and gives the processing conditions, but the same analysis as described above may be performed by calculating the error amount of each processing device 20 and giving the processing conditions.

Seventh embodiment

In the above embodiment, an example of the case where the calculating unit 330 calculates the error amount based on the measurement information MI acquired by the measurement information acquiring unit 320 is described. In the seventh embodiment, a description will be given of a method of calculating the error amount in the case where the measurement information acquisition unit 320 cannot acquire the measurement information MI for some reason.

As an example, the calculating unit 330 obtains the alignment measurement result by the exposure device 230 and the corresponding substrate identification information SID. The calculating unit 330 calculates an error amount based on the alignment measurement result of the exposure apparatus and the path of the substrate passing identified by the substrate identification information SID.

As another example, the measurement information acquisition unit 320 acquires information, which is a result after the substrate is inspected, in addition to or instead of the measurement information MI. The information, which is the result of inspecting the substrate, may be information indicating the degree to which the substrate is good or bad. The information indicating the degree to which the substrate is good or bad may be, for example, information about whether the substrate is bad or not, or information about the product grade. In this case, the calculating unit 330 calculates the defective rate based on information, which is a result of inspecting the substrate, instead of the error amount.

In the present embodiment, the calculating unit 330 calculates the error amount and the defective rate of each device 100, but the same analysis as described above may be performed by calculating the error amount and the defective rate of each processing device 20.

Eighth embodiment

Fig. 21 is a graph showing a change with time of a result of a statistical operation performed on the measurement result of the eighth embodiment. In fig. 21, the horizontal axis is time, and the change with time of the result of the statistical calculation of the measurement result of one substrate is shown. As an example of the statistical calculation result, the vertical axis represents the standard deviation. In the present embodiment, the analysis device 300 can intuitively display a change in accuracy of one substrate with time or a deviation in accuracy by displaying a change in standard deviation with time with respect to the measurement result.

In the following description, an example of the case where the result of the statistical operation is obtained on the measurement result is described, but a predetermined characteristic value or the like may be used instead of the result of the statistical operation as long as an index of the change with time of the accuracy or the deviation of the accuracy can be grasped.

Fig. 21 (a) is a diagram for explaining an example of a case where the state of the substrate gradually changes. It is found that the measurement results from 3/18 to 3/19 are stabilized around 0.6 (μm), but from 3/19 to 3/23, the accuracy gradually deteriorates.

Fig. 21 (B) is a diagram for explaining an example of a case where a sudden change in accuracy occurs. It is found that the measurement results from 3/18 to 3/20 are stabilized at about 0.9 (μm), but the accuracy is suddenly improved to about 0.2 (μm) during the period from 3/20 to 3/21. However, the accuracy was again deteriorated to about 0.9 (. Mu.m) even after this time to 3/23.

As shown in fig. 21, by observing the time-dependent change of the result of the statistical calculation of the measurement result of one substrate, the time-dependent change of the accuracy or the variation of the accuracy of one substrate can be grasped.

Fig. 22 is a diagram showing an example of a change in the measurement result with time for each condition according to the eighth embodiment. An example of a case where the time-dependent change of the measurement result under each condition is shown will be described with reference to fig. 22. In fig. 22, the horizontal axis is time, and the time-dependent change of the result of the statistical calculation of the measurement result of one substrate is shown. As an example of the statistical calculation result, the vertical axis represents the standard deviation. In fig. 22, the measurement result of "condition 1" is indicated by a solid line, and the measurement result of "condition 2" is indicated by a broken line. The conditions may be arbitrarily set. By referring to fig. 22, the difference in accuracy or deviation of each condition can be grasped.

Fig. 22 (a) is a diagram for explaining an example of a case where the accuracy is different for each condition. In contrast to the measurement result of "condition 1" which is stabilized to about 0.4 (μm) to about 0.6 (μm), the measurement result of "condition 2" is stabilized to about 0.6 (μm) to about 0.9 (μm). Therefore, "condition 1" is found to have a better accuracy than "condition 2".

Fig. 22 (B) is a diagram for explaining an example of a case where the variation in accuracy is different for each condition. In contrast to the measurement result of "condition 1" which is stable at about 0.6 (μm) to about 0.9 (μm), the measurement result of "condition 2" varies from about 0.4 (μm) to about 1.2 (μm). Therefore, "condition 1" is found to have a better deviation in accuracy than "condition 2".

Fig. 23 is a diagram showing an example of a functional configuration of an analysis device according to the eighth embodiment. The analysis device 300E will be described with reference to fig. 23. The analysis device 300E is different from the analysis device 300 in that it includes a classification information acquisition unit 390, a classification unit 391, and a display unit 392. In the description of the analysis device 300E, the same components as those of the analysis device 300 may be denoted by the same reference numerals, and the description thereof may be omitted.

The classification information acquisition unit 390 acquires classification items (grouping information) selected by the user's operation. The classification item is information including a group, which is a unit for grouping and visualizing measurement results. The group may be, for example, the processing apparatus 20, the apparatus 100, a recipe, a processing condition (processing time, processing temperature, etc.), a photomask, a tray, or product information. The apparatus 100 is a processing unit or a processing site, which is incorporated in the apparatus 20 and actually performs a predetermined process on a substrate, and is 1 or more. The product information may specifically be a product, a layer number, a Lot (Lot) number, or the like.

The classification unit 391 classifies the measurement results based on the classification items acquired by the classification information acquisition unit 390 and the measurement results included in the measurement information MI stored in the storage unit 340, and the display unit 392 displays the results classified by the classification unit 391.

The display 392 displays various information based on the classification items classified by the classification 391. The display unit 105 may be, for example, a liquid crystal display, an organic EL (Electroluminescence) display, or the like, and the same device as the characteristic display unit 331 may be used. The display unit 392 may be provided in the analysis device 300E, a factory provided with an exposure device, or the like, or a general-purpose terminal such as a personal computer or a tablet terminal. The display 392 may be connected to the analysis device 300E via a predetermined communication network.

Fig. 24 is a diagram for explaining effects in the case of classifying measurement results for each tray of the eighth embodiment. The graph shown in fig. 24 is an example of information displayed on the display 392. Fig. 24 (a) is a diagram showing an example of measurement results before classification, and fig. 24 (B) is a diagram showing an example of measurement results after classification. In fig. 24, the horizontal axis represents time, and the time-dependent change in the result of the statistical calculation of the measurement results of 1 exposure apparatus is shown. As an example of the statistical calculation result, the vertical axis represents the standard deviation.

An example shown in fig. 24 (a) is an example of measurement results before sorting, and thus shows all the results obtained by measurement with 1 exposure apparatus. From the graph of the measurement results before classification, it is clear that the measurement results deviate from about 0.4 (μm) to about 0.9 (μm). Here, the 1-stage exposure apparatus is sometimes equipped with a plurality of trays (for example, two sheets). From the graph of the measurement results before sorting, the deviation of each tray cannot be grasped.

An example shown in fig. 24 (B) is an example of the measurement result after classification. In fig. 24 (B), the measurement results are shown by dividing the "tray a" and the "tray B" provided in 1 exposure apparatus. When the classification information acquisition unit 390 acquires information classified for each "tray" as a classification item, the classification unit 391 classifies the measurement result of each "tray" and displays the classification result on the display unit 392. In fig. 24 (B), the measurement result of "tray a" is indicated by a broken line, and the measurement result of "tray B" is indicated by a solid line.

In the example shown in fig. 24 (B), the same measurement results as those shown in fig. 24 (a) are shown, but since they are classified (grouped), the trend of the measurement results for each tray can be understood. Specifically, "tray a" is deviated about 0.4 (μm) to 0.6 (μm) in the measurement result, and "tray B" is deviated about 0.6 (μm) to 0.9 (μm) in the measurement result. That is, according to the analysis device 300E, the deviation of each tray can be displayed. Further, according to the analysis device 300E, by acquiring the route information as the classification item, the accuracy and the deviation of the accuracy for each route can be displayed. Further, since the analysis device 300 can display the accuracy and the deviation of the accuracy for each path, the user can specify a path in which a failure occurs or can select a path having a good accuracy in the exposure of a pattern requiring the accuracy.

Ninth embodiment

Fig. 25 is a diagram showing an example of a functional configuration of an analysis device according to the ninth embodiment. The analysis device 300F will be described with reference to fig. 25. The analysis device 300F differs from the analysis device 300E in that it includes a simulation calculation unit 396. In the description of the analysis device 300F, the same components as those of the analysis device 300E may be denoted by the same reference numerals, and the description thereof may be omitted.

The simulation operation unit 396 performs a correction simulation (hereinafter, abbreviated as "simulation"). The simulation calculation unit 396 performs simulation based on the classification items acquired by the classification information acquisition unit 390 and measurement result selection information, which is information for selecting measurement results. The measurement result selection information may also be acquired by the classification information acquisition section 390. The simulation calculation unit 396 calculates an average value of each measurement point based on the selected measurement result. The simulation calculation unit 396 subtracts the calculated average value from each measurement point to calculate a simulation value at the time of correction. The display control unit 391 causes the display unit 392 to display the simulation result.

The simulation calculation unit 396 may perform simulation by correcting pattern information at the time of exposure by the exposure device, or the like, instead of or in addition to subtracting the calculated average value from each measurement point.

Fig. 26 is a diagram for explaining the correction simulation of the eighth embodiment. The correction simulation is described with reference to fig. 26. In fig. 26, the solid line represents "condition a", the broken line represents "condition B", and the horizontal axis represents time, and the time-dependent change of the measurement result when "condition a" is selected as the classification item is shown. The vertical axis represents standard deviation.

Fig. 26 (a) shows measurement results before simulation. The white circles shown in the figures represent the measurement results selected for simulation. The measurement result of the "condition a" is shifted about 0.8 (μm) to 1.0 (μm), and the measurement result of the "condition B" is shifted about 0.6 (μm) to 0.7 (μm). For example, the condition a is that the substrate of the device 110 used in the process P1 is the condition a, and the substrate of the device 111 used in the process P1 is the condition B. The setting of the condition is not limited to this, and may be arbitrarily set. The points shown by the white circles in the drawing are points selected by the simulation operation unit 396, and the points shown by the black circles in the drawing are points not selected by the simulation operation unit 396. In the example shown in fig. 26 (a), 4 points out of the 8-point measurement result are selected for "condition a", and 3 points out of the 10-point measurement result are selected for "condition B". The simulation calculation unit 396 calculates an average point of the selected points. By selecting some of all the measurement results, even when there is a measurement result in which the error amount is extremely deviated from other measurement results, the correction value can be calculated using only the measurement result to be considered.

Fig. 27 is a diagram for explaining the average difference in the eighth embodiment. The calculation of the average (average difference) of the selected points performed by the simulation calculation unit 396 will be described with reference to fig. 27. Fig. 27 (a) and 27 (B) are measurement results before simulation, respectively. Fig. 27 (a) shows measurement results related to "condition a", and fig. 27 (B) shows measurement results related to "condition B". Arrows in fig. 27 a and 27B indicate measurement results (solid lines) and average values (broken lines) at the time of processing each substrate.

The "condition a" shows the measurement result of 4 points in an overlapping manner since the measurement result of 4 points is selected, and the "condition B" shows the measurement result of 3 points in an overlapping manner since the measurement result of 3 points is selected. The simulation calculation unit 396 calculates an average of measurement results for each point. For example, the average of points shown in the lower right in fig. 27 (B) is indicated by a dotted arrow.

Next, the simulation calculation unit 396 performs simulation by subtracting the calculated average from each point.

Fig. 27 (C) and 27 (D) are measurement results after simulation, respectively. Fig. 27 (C) shows simulation results related to "condition a", and fig. 27 (D) shows simulation results related to "condition B". From the simulation results, it was found that the strain observed before the simulation was not observed from the simulation results.

Returning to fig. 26, fig. 26 (B) shows simulation results. The simulation calculation unit 396 applies the average value calculated from the selected points to all the points. Specifically, the simulation calculation unit 396 subtracts the average calculated from the "condition a" from the measurement result of the "condition a", and subtracts the average calculated from the "condition B" from the measurement result of the "condition B".

From the simulation results, it was found that the accuracy of both the "condition a" and the "condition B" was improved to about 0.2 (μm) to 0.4 (μm) by applying the correction.

According to the embodiment described above, the analysis device 300F includes the simulation calculation unit 396 to calculate the average value of the selected measurement results, and subtracts the calculated average value from all the measurement data to perform simulation correction. The analysis device 300F displays the simulation result on the display 392. Therefore, according to the present embodiment, simulation can be performed in the visualization tool.

Further, according to the present embodiment, since the result of applying the correction value can be simulated, the result in the case of applying the correction value can be known before the correction value is actually applied to the exposure apparatus.

Further, according to the above-described embodiment, the measurement results for each group can be classified for each selected channel and displayed on the display 392, whereby the deviation for each group can be visualized. The analysis device 300F is a simulation for each group after classification, and thus can simulate the result when correction corresponding to the deviation of each group is performed. That is, according to the present embodiment, the effect in the case of updating the correction value for each group can be easily visualized.

Further, according to the embodiment described above, the correction value calculated by the simulation calculation unit 396 is applied to all the measurement results. That is, according to the present embodiment, the change with time of the result of the correction value application can be visualized.

Here, the measurement results selected for correction are limited, and thus the correction value may not function properly for all measurement results. That is, correction may adversely affect the measurement result. According to the present embodiment, since the correction value is applied to all the measurement results, the effect of the correction value on the measurement results can be judged with time.

The simulation calculation unit 396 may not be limited to any measurement results that are not selected for calculating the correction value, and may apply to all measurement results obtained by actual measurement, and may apply to all measurement results including measurement results that are selected for calculating the correction value, for example, the simulation calculation unit 396 may select a plurality of points for calculating the correction value, calculate the correction value based on the selected measurement results, and apply the correction value to the selected measurement results and the unselected measurement results to perform simulation.

The whole or a part of the functions of each unit included in the analysis system 10 according to the above embodiment may be realized by recording a program for realizing the above functions on a computer-readable recording medium, and causing a computer system to read and execute the program recorded on the recording medium. Further, the term "computer System" as used herein includes hardware such as an Operating System (OS) or a peripheral machine.

The term "computer-readable recording medium" refers to a portable medium such as a flexible disk, a magneto-optical disk, a Read-Only Memory (ROM), a compact disk-Read Only Memory (CD-ROM), or a storage unit such as a hard disk incorporated in a computer system. Further, the "computer-readable recording medium" may include: a medium that dynamically holds a program for a short time, such as a communication line when the program is transmitted via a network such as the internet or a communication line such as a telephone line, and a medium that holds a program for a certain period of time, such as a volatile memory in a computer system that is a server or a client in the above case. The program may be a program for realizing a part of the functions, or a program capable of realizing the functions by a combination with a program recorded in a computer system.

Although one embodiment of the present invention has been described in detail with reference to the drawings, the specific configuration is not limited to the above configuration, and various design changes and the like may be made without departing from the gist of the present invention.

The method for manufacturing a display according to the present invention is suitable for the production of a display. The device manufacturing method of the present invention is applicable to the production of micro devices.

Description of symbols

10: analysis system

100: processing device

110. 111, 121, 122: device and method for controlling the same

220: inspection apparatus

230: exposure apparatus

300: analysis device

310: route information acquisition unit

320: measurement information acquisition unit

330: calculation unit

331: characteristic display unit

340: storage unit

350: select part

351: correction condition calculation unit

360: output unit

P1, P2: working procedure

R1 and R2: path

MR: measurement results

DID: device identification information

SID: substrate identification information

RID: route identification information

MI: measurement information

PM: correction value

CI: correspondence information

AR: correction conditions

PC: calibration plate coordinate system

OF: orthogonal function system

HM: thermal map

Claims

1. An analysis system includes a first processing device having a first device and a second device for performing a first process on a substrate, and a second processing device having a third device and a fourth device for performing a second process on the substrate,

the substrate is subjected to the first process and the second process through any one of a first path through the first device and the third device, a second path through the first device and the fourth device, a third path through the second device and the third device, and a fourth path through the second device and the fourth device,

The analysis system analyzes measurement information, which is information from an inspection device that measures the processing results of each of the first substrate passing through the first path, the second substrate passing through the second path, the third substrate passing through the third path, and the fourth substrate passing through the fourth path,

the analysis system is characterized by comprising:

a path information acquisition unit that acquires substrate identification information for identifying each substrate and path identification information for each path;

a measurement information acquisition unit configured to acquire the substrate identification information and the measurement information measured by the inspection device; and

and a calculating unit configured to calculate a first device characteristic generated by the first substrate subjected to the first process by the first device, a second device characteristic generated by the second substrate subjected to the first process by the second device, a third device characteristic generated by the third substrate subjected to the second process by the third device, and a fourth device characteristic generated by the fourth substrate subjected to the second process by the fourth device, based on the path identification information, the substrate identification information, and the measurement information.

2. The analytical system of claim 1, wherein the analytical system comprises,

the calculating unit calculates a first correction value for correcting the first device characteristic, a second correction value for correcting the second device characteristic, a third correction value for correcting the third device characteristic, and a fourth correction value for correcting the fourth device characteristic, and

the analysis system further includes a storage unit that stores the first correction value, the second correction value, the third correction value, and the fourth correction value.

3. The analytical system of claim 2, further comprising:

a selecting unit configured to select a correction value of two devices through which the substrate passes, of the first correction value, the second correction value, the third correction value, and the fourth correction value stored in the storage unit, based on the substrate identification information and the path identification information of a fifth substrate different from the first to fourth substrates; and

and a correction condition calculating unit configured to calculate a correction condition for exposing the fifth substrate based on the correction values of the two devices selected by the selecting unit.

4. The analytical system of claim 3, wherein the analytical system comprises,

The correction condition calculation unit calculates at least one of a first correction condition as the correction condition based on the first correction value and the third correction value, a second correction condition as the correction condition based on the first correction value and the fourth correction value, a third correction condition as the correction condition based on the second correction value and the third correction value, a fourth correction condition as the correction condition based on the second correction value and the fourth correction value, and

the correction condition applied when exposing the fifth substrate is calculated based on the substrate identification information of the fifth substrate, the path identification information, and the calculated correction condition acquired by the path information acquisition unit.

5. The analytical system according to any one of claim 1 to 4, wherein,

the measurement information includes an error amount, which is information about a difference between the design values of the first to fourth substrates and the measurement values of the first to fourth substrates.

6. The analytical system of claim 5, wherein the analytical system comprises,

The calculation unit calculates, as the first device characteristic, an error amount due to processing of the first device, an error amount due to processing of the second device, an error amount due to processing of the third device, an error amount due to processing of the fourth device, and an error amount due to processing of the fourth device, based on the path identification information and the error amount.

7. The analytical system according to any one of claims 1 to 6, further comprising: a characteristic display section for displaying the characteristic of the object,

the characteristic display unit displays at least one of the first device characteristic, the second device characteristic, the third device characteristic, and the fourth device characteristic calculated by the calculation unit.

8. The analytical system of claim 7, wherein the analytical system comprises,

the characteristic display section displays the first device characteristic, the second device characteristic, the third device characteristic, or the fourth device characteristic using a heat map.

9. An analysis system according to claim 3 or any one of claims 4 to 8 when dependent on claim 3,

The correction condition calculation unit calculates the correction condition by adding device characteristics of two devices through which the substrate passes among the first device, the second device, the third device, and the fourth device.

10. An analysis system according to claim 3 or any one of claims 4 to 9 when dependent on claim 3,

the first processing device is provided with a fifth device in addition to the first device and the second device,

the path information acquisition unit acquires substrate identification information of a sixth substrate different from the first substrate to the fifth substrate among the substrates passing through a fifth path passing through the fifth device and the third device, and the path identification information of the fifth path,

the calculating unit calculates a fifth device characteristic generated by the sixth substrate subjected to the first process by the fifth device,

the storage stores the fifth device characteristic,

the correction condition calculation unit calculates a fifth correction condition, which is the correction condition of a sixth path through the fifth device and the fourth device, based on the fifth device characteristic and the fourth device characteristic.

11. The analysis system of claim 3 or any one of claims 4 to 10 when dependent on claim 3, further comprising: a route recommendation unit configured to recommend the route,

the path recommending unit recommends, as a path through which the fifth substrate passes, a device having a small error amount, which is information on a difference between a design value and a measured value, among the first device or the second device, based on the first device characteristic and the second device characteristic calculated by the calculating unit.

12. The analytical system of claim 11, wherein the analytical system comprises,

the route recommendation unit recommends a route having a small error amount, which is information on a difference between a design value and a measured value, among the first route, the second route, the third route, or the fourth route, based on the first device characteristic, the second device characteristic, the third device characteristic, and the fourth device characteristic calculated by the calculation unit.

13. The analysis system according to any one of claims 1 to 12, wherein,

the path information acquisition unit acquires path identification information as a seventh path that is a different path when a processing condition for the first substrate in the first apparatus is different from at least one of the processing conditions for the first substrate in the third apparatus, compared with the path identification information for identifying the first path.

14. An analysis system according to claim 3 or any one of claims 4 to 13 when dependent on claim 3,

the correction condition calculation unit weights at least one of the first device characteristic, the second device characteristic, the third device characteristic, and the fourth device characteristic, and calculates the correction condition.

15. An analysis system according to claim 3 or any one of claims 4 to 14 when dependent on claim 3,

the correction conditions include: the driving conditions of the driving part of the substrate stage of the substrate are maintained.

16. An analysis system according to claim 3 or any one of claims 4 to 15 when dependent on claim 3,

the correction condition calculating unit calculates the correction condition for each of the projection optical systems when the fifth substrate is exposed from the plurality of projection optical systems.

17. The analytical system according to any one of claims 1 to 16, further comprising: a defective device detecting unit configured to detect the defective device,

the defective device detection unit detects the presence or absence of occurrence of a defect with respect to the first processing device or the second processing device based on the first device characteristic, the second device characteristic, the third device characteristic, and the fourth device characteristic.

18. The analytical system of claim 17, wherein the analytical system comprises,

the defective device detection unit detects the presence or absence of occurrence of a defect in the first device, the second device, the third device, and the fourth device based on the first device characteristic, the second device characteristic, the third device characteristic, and the fourth device characteristic.

19. The analytical system according to claim 17 or 18, wherein the analytical system comprises,

the defective device detection unit further includes: and a warning unit for warning when the defect is detected.

20. The analysis system of claim 3 or any one of claims 4 to 19 when dependent on claim 3, further comprising: an output section for outputting the output signal,

the output unit outputs the correction condition calculated by the correction condition calculation unit to an exposure apparatus.

21. An exposure apparatus, characterized in that,

exposing the fifth substrate using the correction conditions obtained using the analysis system of claim 3 or any one of claims 4 to 20 depending on claim 3.

22. The exposure apparatus according to claim 21, wherein,

the exposure device acquires path information that the fifth substrate passed before being exposed by the exposure device, and exposes the fifth substrate based on the correction condition related to the path identification information.

23. A method of manufacturing a device, comprising:

exposing the fifth substrate using the exposure apparatus according to claim 21 or 22; and

developing the exposed fifth substrate.

24. A method of manufacturing a display, comprising:

developing the exposed fifth substrate.

25. In an analysis method, in a first processing device having a first device and a second device and performing a first process on a substrate, and a second processing device having a third device and a fourth device and performing a second process on the substrate,

the analysis method analyzes measurement information, which is information from an inspection apparatus that measures processing results of a first substrate passing through the first path, a second substrate passing through the second path, a third substrate passing through the third path, and a fourth substrate passing through the fourth path, among the substrates,

The analysis method is characterized by comprising the following steps:

a path information acquisition unit that acquires substrate identification information for identifying each substrate and path identification information for identifying a path through which each substrate passes;

a measurement information acquisition step of acquiring the substrate identification information and measurement information, which is a processing result of each substrate measured by the inspection device; and

a calculation step of calculating, based on the route identification information and the measurement information, a first device characteristic generated by the first substrate subjected to the first process by the first device, a second device characteristic generated by the third substrate subjected to the first process by the second device, a third device characteristic generated by the first substrate subjected to the second process by the third device, and a fourth device characteristic generated by the second substrate subjected to the second process by the fourth device.

26. An analysis system includes a first processing device having a first device and a second device and performing a first process on a first substrate, a second substrate, a third substrate, and a fourth substrate, and a second processing device having a third device and a fourth device and performing a second process on the first to fourth substrates,

The first to fourth substrates are subjected to the first and second processes through any one of a first path through the first device and the third device, a second path through the first device and the fourth device, a third path through the second device and the third device, and a fourth path through the second device and the fourth device,

the analysis system analyzes measurement information, which is information from an inspection device that measures a result of processing of a first substrate passing through the first path, a second substrate passing through the second path, a third substrate passing through the third path, and a fourth substrate passing through the fourth path,

the analysis system is characterized by comprising:

a measurement information acquisition unit configured to acquire the substrate identification information and measurement information, which is a processing result of each of the substrates measured by the inspection device;

a classification unit configured to classify the measurement information into predetermined classification items based on the substrate identification information and the route identification information; and

And a display unit for displaying the result classified by the classification unit.

27. The analytical system of claim 26, wherein the analytical system comprises,

the measurement information acquisition unit acquires an error amount of the measured value of each substrate with respect to the design value of each substrate in the measurement device.

28. The analytical system of claim 26 or 27 wherein the analytical system comprises,

the predetermined classification item is at least one of the first processing apparatus, the first apparatus, a tray for carrying the substrate into an exposure apparatus, a layer name for exposing the substrate, and a photomask having a predetermined pattern and exposed to the substrate using a projection optical system.

29. The analysis system of any one of claims 26 to 28, wherein,

a selection unit configured to select at least a part of the measurement information displayed on the display unit; and

a correction condition calculation simulation calculation unit that calculates a correction condition based on the measurement information selected by the selection unit, applies the correction condition to the measurement information, and performs simulation to calculate corrected measurement information; and is also provided with

The display unit displays the post-correction measurement information calculated by the correction condition calculation simulation calculation unit.

30. An analysis system includes a first processing device having a first device and a second device for performing a first process on a substrate, and a second processing device having a third device and a fourth device for performing a second process on the substrate,

the substrate is subjected to the first process and the second process through any one of a first path through the first device and the third device, a second path through the first device and the fourth device, a third path through the second device and the third device, and a fourth path through the second device and the fourth device, and

the analysis system is characterized by comprising:

a path information acquisition unit that acquires path identification information, which is information on a path through which each substrate passes;

A measurement information acquisition unit that acquires the measurement information measured by the inspection device; and

and a calculating unit configured to calculate a first device characteristic, which is a characteristic of the first device, a second device characteristic, which is a characteristic of the second device, a third device characteristic, which is a characteristic of the third device, and a fourth device characteristic, which is a characteristic of the fourth device, based on the path identification information and the measurement information of the first substrate, the second substrate, the third substrate, and the fourth substrate.