Method for setting substrate processing conditions, substrate processing method, substrate processing condition setting system, and substrate processing system

Abstract

To provide a substrate processing condition-setting method which enables the setting of a processing condition suitable for mass production, a substrate processing method, a substrate processing condition-setting system and a substrate processing system.SOLUTION: A substrate processing condition-setting method comprises steps of: inputting a plurality of processing conditions into a learned model M learned mechanically on a learning processing condition and a processing result in processing a substrate W according to the learning processing condition to gain a plurality of probable processing results (step S24); displaying, by a display part 105, an image based on the plurality of probable processing results (step S26); and setting, as an execution processing condition in processing the substrate W, one processing condition corresponding to one of the plurality of probable processing results on the image displayed on the display part 105 (step S27 and step S28).SELECTED DRAWING: Figure 16

Description

Technical Field

[0001] The present invention relates to a method for setting substrate processing conditions, a substrate processing method, a substrate processing condition setting system, and a substrate processing system.

Background Art

[0002] There is known a substrate processing apparatus that processes a wafer body or a wafer having a film formed on its surface and adjusts the film thickness of the object to be processed by liquid processing. As one type of such a substrate processing apparatus, there is a single-wafer type substrate processing apparatus provided with a nozzle for supplying a processing liquid for etching to the wafer surface (see, for example, Patent Document 1). In the substrate processing system of Patent Document 1, a learned model is generated by machine learning based on a data set including substrate processing conditions and performance data related to quality, and recommended processing conditions for substrate processing are derived based on the learned model.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the method of deriving optimal processing conditions using a learned model as in the substrate processing apparatus described in Patent Document 1, for example, when the range of processing conditions allowed to obtain a predetermined etching profile (also referred to as a process window) is narrow, it may not be possible to stably process the substrate during mass production. Further, in the method described in Patent Document 1, for example, the amount of the processing liquid used may significantly increase under the processing conditions under which a predetermined etching profile can be obtained.

[0005] That is, in the method described in Patent Document 1, processing conditions that are not suitable for mass production may be derived by the learned model.

[0006] The present invention has been made in view of the above problems, and an object thereof is to provide a method for setting substrate processing conditions, a substrate processing method, a substrate processing condition setting system, and a substrate processing system capable of setting processing conditions suitable for mass production.

Means for Solving the Problems

[0007] A method for setting substrate processing conditions according to an aspect of the present invention includes: inputting a plurality of processing conditions to a learned model that is machine-learned based on learning processing conditions and a processing result when a substrate is processed under the learning processing conditions, and obtaining a plurality of estimated processing results; causing a display unit to display an image based on the plurality of estimated processing results; and setting, as an execution processing condition when processing the substrate, one processing condition corresponding to one of the plurality of estimated processing results based on the image displayed on the display unit.

[0008] In one aspect of the present invention, the method for setting substrate processing conditions may further include, prior to the obtaining step, a step of setting an input condition range including predetermined processing conditions. In the obtaining step, a plurality of processing conditions included in the input condition range may be input to the learned model to obtain the plurality of estimated processing results.

[0009] In one aspect of the present invention, each of the processing conditions may at least include a concentration condition indicating the concentration of a processing liquid supplied to the substrate, a temperature condition indicating the temperature of the processing liquid supplied to the substrate, a supply amount condition indicating the supply amount of the processing liquid supplied to the substrate, a rotation speed condition indicating the rotation speed of the substrate, and a speed condition indicating the scan speed of a nozzle for supplying the processing liquid to the substrate.

[0010] In one aspect of the present invention, the method for setting substrate processing conditions may further include a step of selecting the one processing condition by a user based on the image displayed on the display unit prior to the step of setting as the execution processing conditions. In the step of setting as the execution processing conditions, the selected one processing condition may be set as the execution processing conditions.

[0011] In one aspect of the present invention, the image may include a distribution diagram. Each of the processing conditions may have a plurality of parameters. The distribution diagram may be displayed in three dimensions using two types of parameters specified by the user and the estimated processing result.

[0012] In one aspect of the present invention, the display unit may display a selection unit that allows the user to select the types of parameters as variables of the distribution diagram.

[0013] In one aspect of the present invention, the display unit may display a plurality of marks that can be selected by the user on the distribution diagram. In the step of selecting, the one processing condition may be selected by the user selecting one of the plurality of marks.

[0014] In one aspect of the present invention, the plurality of marks may include a first mark displayed within a predetermined range including a position corresponding to a target processing result in the distribution diagram, and a second mark displayed outside the predetermined range in the distribution diagram and different from the first mark.

[0015] A substrate processing method according to one aspect of the present invention includes a step of setting the one processing condition as the execution processing conditions according to the above-described method for setting substrate processing conditions, and a step of processing the substrate under the one processing condition.

[0016] A substrate processing condition setting system according to an aspect of the present invention includes a storage unit, a display unit, and a control unit. The storage unit stores learning processing conditions and a learned model that has been machine-learned based on processing results when a substrate is processed under the learning processing conditions. The control unit inputs a plurality of processing conditions to the learned model to obtain a plurality of estimated processing results. The control unit causes the display unit to display an image based on the plurality of estimated processing results. The control unit sets one processing condition corresponding to one of the plurality of estimated processing results as an execution processing condition when processing the substrate.

[0017] In one aspect of the present invention, the control unit may input a plurality of processing conditions included in an input condition range including a predetermined processing condition to the learned model to obtain the plurality of estimated processing results.

[0018] In one aspect of the present invention, each of the processing conditions may at least include a concentration condition indicating the concentration of the processing liquid supplied to the substrate, a temperature condition indicating the temperature of the processing liquid supplied to the substrate, a supply amount condition indicating the supply amount of the processing liquid supplied to the substrate, a rotation speed condition indicating the rotation speed of the substrate, and a speed condition indicating the scan speed of the nozzle for supplying the processing liquid to the substrate.

[0019] In one aspect of the present invention, the substrate processing condition setting system may further include an operation unit that receives an operation by a user. The control unit may set the one processing condition selected by the user using the operation unit as the execution processing condition.

[0020] In one aspect of the present invention, the image may include a distribution diagram. Each of the plurality of processing conditions may have a plurality of parameters. The control unit may display the distribution diagram in three dimensions using two types of parameters specified by the user and the estimated processing results.

[0021] In one aspect of the present invention, the display unit may display a selection unit that allows a user to select the type of the parameter as a variable of the distribution diagram.

[0022] In one aspect of the present invention, the display unit may display a plurality of marks that can be selected by the user on the distribution diagram. When one mark is selected from the plurality of marks by the user using the operation unit, the control unit may set the one processing condition corresponding to the one mark as the execution processing condition.

[0023] In one aspect of the present invention, the plurality of marks may include a first mark displayed within a predetermined range including a position corresponding to a target processing result in the distribution diagram, and a second mark displayed outside the predetermined range in the distribution diagram and different from the first mark.

[0024] A substrate processing system according to one aspect of the present invention may include the above-described substrate processing condition setting system and a processing unit that processes a substrate under the one processing condition.

Advantages of the Invention

[0025] According to the present invention, it is possible to provide a substrate processing condition setting method, a substrate processing method, a substrate processing condition setting system, and a substrate processing system capable of setting processing conditions suitable for mass production.

Brief Description of the Drawings

[0026]

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Embodiments for Carrying Out the Invention

[0027] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, the present invention is not limited to the following embodiments, and can be implemented in various aspects without departing from the gist thereof. Note that, for parts where the description overlaps, the description may be omitted as appropriate. Also, in the drawings, the same or corresponding parts are denoted by the same reference numerals and the description will not be repeated.

[0028] (First Embodiment) Referring to FIGS. 1 to 19, a substrate processing system 1000 according to a first embodiment of the present invention will be described. FIG. 1 is a diagram showing the overall configuration of the substrate processing system 1000 of the present embodiment. FIG. 2 is a schematic diagram showing the overall configuration of the substrate processing system 1000 of the present embodiment.

[0029] As shown in FIGS. 1 and 2, the substrate processing system 1000 includes a substrate processing condition setting system 500 and a processing unit 1. The setting system 500 includes a first control unit 102, a second control unit 210, and a storage unit 220. The setting system 500 further includes a display unit 105 and an input unit 104. Note that the first control unit 102 and the second control unit 210 are examples of the "control unit" of the present invention. Also, the input unit 104 is an example of the "operation unit" of the present invention. Hereinafter, the substrate processing system 1000 will be specifically described.

[0030] In the present embodiment, the substrate processing system 1000 includes a substrate processing apparatus 100 and a server 200. The substrate processing apparatus 100 includes a processing unit 1 and a control apparatus 101. The control apparatus 101 and the server 200 constitute a substrate processing condition setting system 500.

[0031] Next, referring to FIGS. 3 and 4, the substrate processing apparatus 100 will be described. FIG. 3 is a schematic diagram of the substrate processing apparatus 100 of the present embodiment. Specifically, FIG. 3 is a schematic plan view of the substrate processing apparatus 100. The substrate processing apparatus 100 is a single-wafer type apparatus that processes substrates W one by one. In the present embodiment, the substrate W is a semiconductor wafer. The substrate W is substantially disk-shaped.

[0032] As shown in FIG. 3, the substrate processing apparatus 100 includes a plurality of processing units 1, a fluid cabinet 100A, a plurality of fluid boxes 100B, a plurality of load ports LP, an indexer robot IR, a center robot CR, and a control device 101.

[0033] Each of the load ports LP stacks and accommodates a plurality of substrates W. The indexer robot IR transports the substrate W between the load port LP and the center robot CR. The center robot CR transports the substrate W between the indexer robot IR and the processing unit 1. Each of the processing units 1 supplies a processing liquid to the substrate W and executes processing on the substrate W. The fluid cabinet 100A accommodates the processing liquid.

[0034] The plurality of processing units 1 form a plurality of towers TW (four towers TW in FIG. 3) arranged so as to surround the center robot CR in plan view. Each tower TW includes a plurality of processing units 1 (three processing units 1 in FIG. 3) stacked vertically. The fluid boxes 100B respectively correspond to the plurality of towers TW. The processing liquid in the fluid cabinet 100A is supplied to all the processing units 1 included in the tower TW corresponding to the fluid box 100B via one of the fluid boxes 100B.

[0035] The control device 101 controls the operations of each part of the substrate processing apparatus 100. For example, the control device 101 controls the load port LP, the indexer robot IR, and the center robot CR.

[0036] Subsequently, referring to FIG. 4, the processing unit 1 of the present embodiment will be described. FIG. 4 is a schematic diagram of the processing unit 1 of the present embodiment. Specifically, FIG. 4 is a schematic cross-sectional view of the processing unit 1.

[0037] As shown in FIG. 4, the processing unit 1 processes an object constituting the substrate W with a processing liquid. Hereinafter, the object to be processed by the processing liquid is referred to as "object TG". The object TG is, for example, a substrate body (for example, a substrate body made of silicon) or a substance formed on the surface of the substrate body. The substance formed on the surface of the substrate body is, for example, a substance of the same material as the substrate body (for example, a layer made of silicon) or a substance of a different material from the substrate body (for example, a silicon oxide film, a silicon nitride film, or a resist). The "substance" may constitute a film.

[0038] In the present embodiment, the processing liquid includes an etching liquid, and the processing unit 1 executes an etching process. The object TG is processed (etched) with the etching liquid. The etching liquid is a chemical solution. The etching liquid is, for example, hydrofluoric acid and nitric acid (a mixed solution of hydrofluoric acid (HF) and nitric acid (HNO3)), hydrofluoric acid, buffered hydrofluoric acid (BHF), ammonium fluoride, HFEG (a mixed solution of hydrofluoric acid and ethylene glycol), phosphoric acid (H3PO4), SC1 (a mixed solution of ammonia and hydrogen peroxide), SC2 (a mixed solution of hydrochloric acid and hydrogen peroxide), SPM (a mixed solution of sulfuric acid and hydrogen peroxide), or ammonia, etc.

[0039] The processing unit 1 includes a chamber 2, a spin chuck 3, a spin motor unit 5, a nozzle moving mechanism 6, a measurement unit 8, a probe moving mechanism 9, a plurality of guards 10 (two guards 10 in FIG. 4), a first nozzle 41, and a second nozzle 71. Further, the substrate processing apparatus 100 includes an etching liquid supply unit 4 and a rinse liquid supply unit 7. The etching liquid supply unit 4 has a first supply pipe 42, and the rinse liquid supply unit 7 has a second supply pipe 72. Note that the first nozzle 41 is an example of the "nozzle" of the present invention.

[0040] The chamber 2 has a substantially box shape. The chamber 2 houses the substrate W, the spin chuck 3, the spin motor unit 5, the nozzle moving mechanism 6, the plurality of guards 10, the measurement unit 8, the probe moving mechanism 9, the first nozzle 41, the second nozzle 71, a part of the first supply pipe 42, and a part of the second supply pipe 72.

[0041] The spin chuck 3 holds the substrate W horizontally. Specifically, the spin chuck 3 includes a plurality of chuck members 32 and a spin base 33. The plurality of chuck members 32 are provided on the spin base 33 along the periphery of the substrate W. The plurality of chuck members 32 hold the substrate W in a horizontal posture. The spin base 33 is substantially disc-shaped and supports the plurality of chuck members 32 in a horizontal posture.

[0042] The spin motor unit 5 rotates the substrate W and the spin chuck 3 integrally about the first rotation axis AX1. The first rotation axis AX1 extends in the vertical direction. In the present embodiment, the first rotation axis AX1 extends in a substantially vertical direction. Specifically, the spin motor unit 5 rotates the spin base 33 about the first rotation axis AX1. Accordingly, the spin base 33 rotates about the first rotation axis AX1. As a result, the substrate W held by the plurality of chuck members 32 provided on the spin base 33 rotates about the first rotation axis AX1.

[0043] Specifically, the spin motor unit 5 includes a motor body 51, a shaft 53, and an encoder 55. The shaft 53 is coupled to the spin base 33. The motor body 51 rotates the shaft 53. As a result, the spin base 33 rotates.

[0044] The encoder 55 measures the rotation speed of the substrate W. The encoder 55 generates a signal indicating the rotation speed of the substrate W. Specifically, the encoder 55 generates a rotation speed signal indicating the rotation speed of the motor body 51.

[0045] The first nozzle 41 supplies an etching solution to the substrate W. Specifically, the first nozzle 41 discharges the etching solution toward the rotating substrate W. The etching solution supply unit 4 supplies the etching solution to the first nozzle 41. Specifically, the first nozzle 41 is connected to one end of the first supply pipe 42. The etching solution is supplied to the first nozzle 41 through the first supply pipe 42. The first supply pipe 42 is a tubular member through which the etching solution flows.

[0046] The nozzle moving mechanism 6 moves the first nozzle 41. In the present embodiment, the nozzle moving mechanism 6 moves the first nozzle 41 in a substantially horizontal direction. Specifically, the nozzle moving mechanism 6 pivots the first nozzle 41 about a second axis of rotation AX2 along a substantially vertical direction. While moving (while pivoting), the first nozzle 41 discharges the etching liquid toward the substrate W. The first nozzle 41 may be referred to as a scan nozzle.

[0047] Specifically, the nozzle moving mechanism 6 includes a nozzle arm 61, a first rotating shaft 63, and a first driving unit 65. The nozzle arm 61 extends along a substantially horizontal direction. The first nozzle 41 is disposed at the tip of the nozzle arm 61. The nozzle arm 61 is coupled to the first rotating shaft 63. The first rotating shaft 63 extends along a substantially vertical direction. The first driving unit 65 rotates the first rotating shaft 63 about the second axis of rotation AX2, and rotates the nozzle arm 61 along a substantially horizontal plane about the first rotating shaft 63. As a result, the first nozzle 41 moves along a substantially horizontal plane. Specifically, the first nozzle 41 pivots around the first rotating shaft 63 about the second axis of rotation AX2. The first driving unit 65 includes, for example, a stepping motor.

[0048] The second nozzle 71 supplies a rinse liquid to the substrate W. Specifically, the second nozzle 71 discharges the rinse liquid toward the rotating substrate W. The rinse liquid supply unit 7 supplies the rinse liquid to the second nozzle 71. Specifically, the rinse liquid is supplied to the second nozzle 71 through a second supply pipe 72. The second supply pipe 72 is a tubular member through which the rinse liquid flows. The rinse liquid is, for example, deionized water, carbonated water, electrolyzed ion water, hydrogen water, ozone water, or hydrochloric acid water with a dilution concentration (for example, about 10 ppm to 100 ppm). The second nozzle 71 discharges the rinse liquid in a stationary state. The second nozzle 71 may be referred to as a fixed nozzle. Note that the second nozzle 71 may be a scan nozzle.

[0049] Each of the guards 10 has a substantially cylindrical shape. The plurality of guards 10 receive the etching liquid and the rinse liquid discharged from the substrate W.

[0050] The measurement unit 8 acquires surface information regarding the surface of the substrate W. The surface information includes, for example, information indicating the thickness distribution of the substrate W. Further, the surface information includes, for example, information indicating the surface shape (profile) of the substrate W. Note that, based on one of the information on the thickness distribution of the substrate W and the information on the surface shape of the substrate W, the other can be obtained. That is, acquiring the information on the thickness distribution of the substrate W and acquiring the information on the surface shape of the substrate W are substantially the same.

[0051] In the present embodiment, the measurement unit 8 measures the thickness of the object TG in a non-contact manner and generates a thickness detection signal indicating the thickness of the object TG. The thickness detection signal is input to the control device 101.

[0052] The measurement unit 8 measures the thickness of the object TG by, for example, spectroscopic interference method. Specifically, the measurement unit 8 includes an optical probe 81, a signal line 83, and a measuring instrument 85. The optical probe 81 has a lens. The signal line 83 connects the optical probe 81 and the measuring instrument 85. The signal line 83 includes, for example, an optical fiber. The measuring instrument 85 has a light source and a light receiving element. The light emitted from the light source of the measuring instrument 85 is emitted to the object TG via the signal line 83 and the optical probe 81. The light reflected by the object TG is received by the light receiving element of the measuring instrument 85 via the optical probe 81 and the signal line 83. The measuring instrument 85 analyzes the light received by the light receiving element and calculates the thickness of the object TG. The measuring instrument 85 generates a thickness detection signal indicating the calculated thickness of the object TG. Note that the measurement method of the measurement unit 8 is not limited to the spectroscopic interference method, and other measurement methods may be used as long as the thickness of the object TG can be measured.

[0053] The probe movement mechanism 9 moves the optical probe 81 in a substantially horizontal direction. Specifically, the probe movement mechanism 9 pivots the optical probe 81 about a third axis of rotation AX3 along a substantially vertical direction. The optical probe 81 emits light toward the substrate W while moving (while pivoting). Therefore, the thickness detection signal indicates the thickness distribution of the object TG.

[0054] Specifically, the probe movement mechanism 9 includes a probe arm 91, a second rotation shaft 93, and a second drive unit 95. The probe arm 91 extends along a substantially horizontal direction. An optical probe 81 is disposed at the tip of the probe arm 91. The probe arm 91 is coupled to the second rotation shaft 93. The second rotation shaft 93 extends along a substantially vertical direction. The second drive unit 95 rotates the second rotation shaft 93 about a third rotation axis AX3, and rotates the probe arm 91 along a substantially horizontal plane with the second rotation shaft 93 as the center. As a result, the optical probe 81 moves along a substantially horizontal plane. Specifically, the optical probe 81 revolves around the second rotation shaft 93 about the third rotation axis AX3. The second drive unit 95 includes, for example, a stepping motor.

[0055] During the manufacture of the semiconductor product, the control device 101 may calculate a target throughput (target etching amount) based on the thickness detection signal input from the measurement unit 8 (measuring device 85).

[0056] FIG. 5 is a diagram for explaining the target throughput. In FIG. 5, Pa shows the thickness distribution of the object TG before processing detected using the measurement unit 8. Pb shows the target thickness distribution of the object TG after processing. Region Pc shows the difference between the thickness distribution Pa of the object TG before processing and the target thickness distribution Pb of the object TG after processing. The difference (region Pc) is the target throughput. That is, the first control unit 102 can calculate the target throughput by calculating the difference between the actually measured thickness distribution Pa using the measurement unit 8 and the target thickness distribution Pb.

[0057] In addition, a rotation speed signal is input to the control device 101 from the encoder 55. Note that the rotation speed of the substrate W during processing is, for example, constant. Specifically, as will be described with reference to FIG. 9, the control device 101 stores a recipe 131 for controlling each part of the substrate processing apparatus 100, and the recipe 131 indicates, for example, a set value of the rotation speed of the motor main body 51. The control device 101 controls the processing executed by the processing unit 1 with reference to the recipe 131.

[0058] The etching solution supply unit 4 is configured to be able to adjust the temperature of the etching solution. For example, the etching solution supply unit 4 may have a thermometer and a heater. Further, the etching solution supply unit 4 is configured to be able to adjust the supply amount of the etching solution.

[0059] Subsequently, referring to FIG. 6, the scan processing of the substrate W by the first nozzle 41 will be described. FIG. 6 is a plan view showing the scan processing of the present embodiment. As shown in FIG. 6, the scan processing is a process in which the first nozzle 41 moves while discharging the processing liquid (etching solution) onto the surface of the object TG so that the liquid landing position of the processing liquid (etching solution) on the surface of the object TG forms an arc-shaped locus TJ1 in a plan view. The locus TJ1 passes through the central portion CT of the substrate W. The central portion CT indicates a portion of the substrate W through which the first rotation axis AX1 passes. The scan processing is executed while the substrate W is rotating.

[0060] In the present embodiment, the first nozzle 41 discharges the processing liquid (etching solution) toward the rotating substrate W while moving from the first position X1 to the ninth position X9. Each position X1 to X9 included in the first position X1 to the ninth position X9 is included in the locus TJ1. The section from the first position X1 to the ninth position X9 indicates the moving section where the first nozzle 41 moves.

[0061] Among the first position X1 to the ninth position X9, the first position X1 indicates the discharge start position of the processing liquid (etching solution), and the ninth position X9 indicates the discharge stop position of the processing liquid (etching solution). The moving speed of the first nozzle 41 at the first position X1 is 0 mm / s, and the moving speed of the first nozzle 41 at the ninth position X9 is 0 mm / s. Therefore, the first position X1 is the start position of the scan processing, and the ninth position X9 is the end position of the scan processing. Also, the first position X1 is the moving start position of the first nozzle 41, and the ninth position X9 is the moving end position of the first nozzle 41. In the following description, the moving speed of the first nozzle 41 during the scan processing may be described as the "scan speed".

[0062] During the scanning process, the first nozzle 41 passes through each intermediate position (each position X2 to X8 from the second position X2 to the eighth position X8) between the first position X1 and the ninth position X9.

[0063] Subsequently, referring to FIG. 7, the scanning speed information will be described. The scanning speed information indicates a set value of the moving speed of the first nozzle 41 during the scanning process (the set value of the scanning speed). FIG. 7 is a diagram showing the scanning speed information of the present embodiment. Specifically, FIG. 7 shows the relationship between each position X1 to X9 included in the moving section of the first nozzle 41 described with reference to FIG. 6 and the set value of the scanning speed.

[0064] In FIG. 7, the upper column indicates each position X1 to X9 included in the moving section of the first nozzle 41, and the lower column indicates the set value of the scanning speed. Each position X1 to X9 included in the moving section of the first nozzle 41 is defined by the radial position of the substrate W. Specifically, the upper column indicates the start position of the moving section of the first nozzle 41 (the moving start position of the first nozzle 41), the end position of the moving section of the first nozzle 41 (the moving end position of the first nozzle 41), and a plurality of intermediate positions between the start position and the end position of the moving section of the first nozzle 41 (a plurality of positions through which the first nozzle 41 passes).

[0065] As shown in FIG. 7, the scanning speed information indicates the set value of the scanning speed for each of the positions X1 to X9 included in the moving section of the first nozzle 41. Hereinafter, each of the positions X1 to X9 included in the moving section of the first nozzle 41 may be referred to as a "speed setting position". In the present embodiment, the scanning speed information indicates nine speed setting positions. Note that the scanning speed information may indicate dozens or more (for example, 20 or more) speed setting positions.

[0066] Specifically, each speed setting position corresponds to each position X1 to X9 from the first position X1 to the ninth position X9 described with reference to FIG. 6. As described with reference to FIG. 6, the scan speed set at the start position (first position X1) of the movement section of the first nozzle 41 is 0 [mm / s], and the scan speed set at the end position (ninth position X9) of the movement section of the first nozzle 41 is 0 [mm / s]. When the first nozzle 41 reaches one end (first position X1) and the other end (ninth position X9) of the movement section of the first nozzle 41, the first nozzle 41 may move back by scan processing.

[0067] The control device 101 described with reference to FIGS. 3 and 4 controls the nozzle movement mechanism 6 (first drive section 65) based on the scan speed information. As a result, the first nozzle 41 moves along the locus TJ1 described with reference to FIG. 6 so that the scan speed at each speed setting position becomes the scan speed defined by the scan speed information.

[0068] Subsequently, with reference to FIG. 8, the thickness measurement process by the measurement section 8 will be described. FIG. 8 is a plan view showing the thickness measurement process of the present embodiment. As shown in FIG. 8, the thickness measurement process is a process of measuring the thickness of the object TG while the optical probe 81 moves so that the measurement position of the thickness with respect to the object TG forms an arc-shaped locus TJ2 in a plan view. The locus TJ2 passes through the edge portion EG of the substrate W and the center portion CT of the substrate W. The edge portion EG indicates the peripheral portion of the substrate W. The thickness measurement process is executed while the substrate W rotates.

[0069] Specifically, the optical probe 81 emits light toward the object TG while moving between the center portion CT and the edge portion EG of the substrate W in a plan view. As a result, the thickness of the object TG is measured at each measurement position included in the locus TJ2. Each measurement position corresponds to each radial position of the substrate W. Therefore, the thickness distribution of the object TG in the radial direction RD of the substrate W is measured by the thickness measurement process. Note that the surface shape (profile) of the object TG coincides with the shape indicating the thickness distribution of the object TG.

[0070] Next, referring to FIG. 9, the control device 101 will be described. FIG. 9 is a block diagram of the control device 101 of the present embodiment. As shown in FIG. 9, the control device 101 includes a first control unit 102, a storage unit 103, an input unit 104, and a display unit 105.

[0071] The first control unit 102 has a processor. The first control unit 102 has, for example, a CPU (Central Processing Unit), or an MPU (Micro Processing Unit). Alternatively, the first control unit 102 may have a general-purpose arithmetic unit or a dedicated arithmetic unit. The first control unit 102 may further have an NPU (Neural Network Processing Unit).

[0072] The storage unit 103 stores data and computer programs. The storage unit 103 has a main storage device. The main storage device is, for example, a semiconductor memory. The storage unit 103 may further have an auxiliary storage device. The auxiliary storage device is, for example, a semiconductor memory and / or a hard disk drive. The storage unit 103 may have a removable medium. The first control unit 102 controls the operations of each part of the substrate processing apparatus 100 based on the data and computer programs stored in the storage unit 103.

[0073] Specifically, the storage unit 103 stores a recipe 131 and a control program 132. The recipe 131 defines the processing content and processing procedure of the substrate W. Also, the recipe 131 indicates processing conditions and various setting values.

[0074] The first control unit 102 controls the operations of each part of the substrate processing apparatus 100 based on the recipe 131 and the control program 132. In the present embodiment, the first control unit 102 causes the display unit 105 to display an image based on a plurality of estimation processing results described later. Also, the first control unit 102 sets, as an execution processing condition when processing the substrate W, one processing condition corresponding to one of the plurality of estimation processing results.

[0075] The input unit 104 receives input from the operator and outputs information indicating the input result to the first control unit 102. For example, the input unit 104 receives an input for selecting one processing condition corresponding to one of a plurality of estimation processing results described later. Also, for example, the input unit 104 receives an input within an input condition range including a predetermined processing condition described later. Also, for example, the input unit 104 receives an input of the type of parameter as a variable of the distribution diagram described later. Note that the estimation processing result, the input condition range, and the distribution diagram will be described later. Also, the input unit 104 includes, for example, a touch panel and a pointing device. The touch panel is disposed, for example, on the display surface of the display unit 105. The input unit 104 and the display unit 105 constitute, for example, a graphical user interface.

[0076] The display unit 105 displays various information. In the present embodiment, the display unit 105 displays, for example, various setting screens (input screens). Also, the display unit 105 displays, for example, a distribution diagram. Also, the display unit 105 displays, for example, a selection unit that allows a user to select the type of parameter as a variable of the distribution diagram. Also, the display unit 105 displays, for example, a plurality of marks that can be selected (by the user) on the distribution diagram. The marks include a first mark and a second mark different from the first mark. Also, the display unit 105 displays a plurality of first marks within a predetermined range including the position corresponding to the target processing result in the distribution diagram. Also, the display unit 105 displays a plurality of second marks outside the predetermined range in the distribution diagram. That is, the plurality of marks include a first mark displayed within a predetermined range including the position corresponding to the target processing result in the distribution diagram and a second mark displayed outside the predetermined area in the distribution diagram and different from the first mark. Note that the selection unit and the marks that can be selected by the user will be described later. Also, the display unit 105 has, for example, a liquid crystal display or an organic EL (electroluminescence) display.

[0077] Next, referring to FIG. 10, the server 200 will be described. FIG. 10 is a block diagram of the server 200 of the present embodiment. As shown in FIG. 10, the server 200 includes a second control unit 210 and a storage unit 220. Note that the server 200 may further include an input unit and a display unit, similar to the control device 101.

[0078] The second control unit 210 has a processor. The second control unit 210 has, for example, a CPU or an MPU. Alternatively, the second control unit 210 may have a general-purpose arithmetic unit or a dedicated arithmetic unit. The second control unit 210 may further have an NPU.

[0079] The storage unit 220 stores data and computer programs. The storage unit 220 has a main storage device. The main storage device is, for example, a semiconductor memory. The storage unit 220 may further have an auxiliary storage device. The auxiliary storage device is, for example, a semiconductor memory and / or a hard disk drive. The storage unit 220 may have a removable medium. The second control unit 210 controls the operations of each part of the server 200 based on the data and computer programs stored in the storage unit 220. Further, the second control unit 210 executes various arithmetic processes based on the data and computer programs stored in the storage unit 220.

[0080] Specifically, the storage unit 220 stores a plurality of learned models M and a control program 231. The learned model M is provided for each combination of the type of the object TG and the type of the processing liquid (etching liquid). The learned model M is generated by a learning device 900 (see FIG. 2) described later and then transmitted to and stored in the server 200.

[0081] The second control unit 210 executes arithmetic processing based on the control program 231 and outputs the estimation processing result to the control device 101. Specifically, the storage unit 220 stores processing condition information 232 indicating the processing conditions of the substrate W. The second control unit 210 inputs a plurality of processing conditions to the learned model M and obtains a plurality of estimation processing results. The learned model M outputs an estimation processing result based on the processing conditions that are the input data. The storage unit 220 stores estimation processing result information 233 indicating the estimation processing result. The second control unit 210 outputs the estimation processing result to the control device 101.

[0082] Each of the processing conditions includes, for example, at least a concentration condition, a temperature condition, a supply amount condition, a rotation speed condition, and a speed condition. In other words, the processing conditions have a plurality of parameters. The plurality of parameters include, for example, at least a concentration condition, a temperature condition, a supply amount condition, a rotation speed condition, and a speed condition. That is, the concentration condition, the temperature condition, the supply amount condition, the rotation speed condition, and the speed condition indicate the types of parameters. The concentration condition indicates the concentration of the processing liquid (etching liquid) supplied to the substrate W. The temperature condition indicates the temperature of the processing liquid supplied to the substrate W. The supply amount condition indicates the supply amount of the processing liquid supplied by the first nozzle 41 to the substrate W at each position. The rotation speed condition indicates the rotation speed of the substrate W. The speed condition indicates the position of the first nozzle 41 and the speed at each position. Also, each of the processing conditions may include the presence or absence of discharge of the processing liquid (for example, pure water) with respect to the lower surface of the substrate W.

[0083] As described above, each of the processing conditions includes at least a concentration condition, a temperature condition, a supply amount condition, a rotation speed condition, and a speed condition. Therefore, since the estimation processing result can be obtained using the processing conditions with many types of parameters, a highly accurate estimation processing result can be obtained.

[0084] The estimated processing result is the processing result estimated to be obtained when the substrate W is processed with a processing liquid (etching liquid) under predetermined processing conditions. The estimated processing result may be a result directly estimated from the processing conditions, such as a processing amount profile, or may be a result estimated from the processing conditions and a target value, such as the difference between the processing amount profile and the target processing amount profile.

[0085] The estimated processing result includes, for example, the uniformity of the processing amount or the degree of coincidence of the processing amount profile. The uniformity of the processing amount is the uniformity of the processing amount within the plane of the substrate W. For example, when the processing amount is constant regardless of the position in the radial direction of the substrate W, it can be said that the uniformity of the processing amount is high. The degree of coincidence of the processing amount profile is the degree of coincidence of the processing amount at each position in the radial direction of the substrate W between the target processing amount profile and the processing amount profile obtained by the learned model M, and is calculated based on, for example, the average value of the difference in the processing amount.

[0086] The storage unit 220 stores a plurality of estimated processing results obtained using the learned model M. The storage unit 220 stores the estimated processing results in association with the corresponding processing conditions.

[0087] Next, with reference to FIGS. 11 and 12, the learning device 900 (see FIG. 2) will be described. FIG. 11 is a block diagram of the learning device 900 of the present embodiment. The learning device 900 executes machine learning. The machine learning is, for example, any one of supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, and deep learning. As shown in FIG. 11, the learning device 900 includes a control unit 910, a storage unit 920, an input unit 930, and a display unit 940.

[0088] The control unit 910 has a processor. The control unit 910 has, for example, a CPU or an MPU. Alternatively, the control unit 910 may have a general-purpose arithmetic unit or a dedicated arithmetic unit. The control unit 910 may further have an NPU.

[0089] The storage unit 920 stores data and computer programs. The storage unit 920 has a main storage device. The main storage device is, for example, a semiconductor memory. The storage unit 920 may further have an auxiliary storage device. The auxiliary storage device is, for example, a semiconductor memory and / or a hard disk drive. The storage unit 920 may have a removable medium. The control unit 910 controls the operations of each part of the learning device 900 based on the data and computer programs stored in the storage unit 920. Further, the control unit 910 executes machine learning based on the data and computer programs stored in the storage unit 920.

[0090] Specifically, the storage unit 920 stores a learning data set 931, a control program 932, a learning program 933, and a learned model M.

[0091] FIG. 12 is a diagram showing the learning data set 931 of the present embodiment. As shown in FIG. 12, the learning data set 931 includes information #A1 to #An indicating a plurality of learning processing conditions, and information DA1 to DAn indicating a plurality of processing results when the substrate W is actually processed under the learning processing conditions. Note that "n" is a positive integer. The plurality of learning processing conditions and the plurality of processing results are associated with each other. The learning data set 931 is provided for each combination of the type of the object TG and the type of the processing liquid (etching liquid). For example, when there are 10 combinations of the type of the object TG and the type of the processing liquid, there are 10 learning data sets 931.

[0092] Note that the plurality of processing results when the substrate W is processed under the learning processing conditions may include, in addition to the processing results when the substrate W is actually processed, the processed results increased by data augmentation and the processing results based on simulation.

[0093] The learning processing conditions are the conditions for processing the substrate W. In the present embodiment, each of the learning processing conditions includes, for example, at least a concentration condition, a temperature condition, a supply amount condition, a rotation speed condition, and a speed condition. In other words, the learning processing conditions have a plurality of parameters. The plurality of parameters include, for example, at least a concentration condition, a temperature condition, a supply amount condition, a rotation speed condition, and a speed condition. The concentration condition, the temperature condition, the supply amount condition, the rotation speed condition, and the speed condition indicate the types of parameters. The concentration condition indicates the concentration of the processing liquid supplied to the substrate W. The temperature condition indicates the temperature of the processing liquid supplied to the substrate W. The supply amount condition indicates the supply amount of the processing liquid that the first nozzle 41 supplies to the substrate W at each position. The rotation speed condition indicates the rotation speed of the substrate W. The speed condition indicates the position of the first nozzle 41 and the speed at each position. In addition, each of the learning processing conditions may include whether or not the processing liquid is discharged onto the lower surface of the substrate W. Note that whether or not the processing liquid (for example, pure water) is discharged onto the lower surface of the substrate W affects the temperature of the substrate W.

[0094] As shown in FIG. 11, the control unit 910 generates a learned model M that has been machine-learned based on the learning dataset 931 using the learning program 933. One learned model M is generated using one learning dataset 931. The learning program 933 is a program for executing an algorithm that finds a certain rule from the learning dataset 931 and generates a model (learned model M) that represents the rule.

[0095] The learned model M is usually configured using a high-dimensional function. In the present embodiment, the control unit 910 may perform a dimensionality reduction process on the learned model M. That is, the learned model M of the present embodiment may be configured using a low-dimensional function. With this configuration, the calculation time for obtaining a plurality of estimation processing results using the learned model M can be shortened. For example, it is possible to reduce a calculation that takes several tens of hours to a few seconds.

[0096] The control unit 910 stores the generated learned model M in the storage unit 920. Also, the control unit 910 transmits the learned model M to the setting system 500 (here, the server 200).

[0097] The input unit 930 receives an input from the operator. For example, the input unit 930 receives an input of an execution instruction for machine learning. The input unit 930 includes, for example, a touch panel and a pointing device. The touch panel is arranged, for example, on the display surface of the display unit 940. The input unit 930 and the display unit 940 constitute, for example, a graphical user interface.

[0098] The display unit 940 displays various information. In the present embodiment, the display unit 940 displays, for example, various error screens and various setting screens (input screens). The display unit 940 has, for example, a liquid crystal display or an organic EL display.

[0099] Next, with reference to FIG. 13, the image displayed on the display unit 105 of the control device 101 will be described. FIG. 13 is a diagram showing an example of the image displayed on the display unit 105 of the present embodiment. Here, an image based on a plurality of estimation processing results will be described in detail.

[0100] As shown in FIG. 13, the display unit 105 of the control device 101 displays an image based on a plurality of estimation processing results. The image includes a plurality of estimation processing results transmitted from the server 200 and processing conditions corresponding to the plurality of estimation processing results. That is, the plurality of estimation processing results are displayed as an image in a state associated with the plurality of processing conditions.

[0101] In the present embodiment, the image displayed on the display unit 105 includes a distribution diagram. The distribution diagram is displayed using one or more types of parameters and the estimation processing results. In other words, the distribution diagram displays one or more types of parameters and the estimation processing results as variables. Note that the display unit 105 may display, for example, a graph or a table instead of the distribution diagram.

[0102] In addition, in this embodiment, the distribution map is displayed in three dimensions using two types of parameters and the estimation processing result. Note that, as will be described later, the parameters as variables of the distribution map are selected by the user. Further, the distribution map may be displayed using one type of parameter and the estimation processing result, or may be displayed using three or more types of parameters and the estimation processing result.

[0103] In addition, in this embodiment, the image displayed on the display unit 105 includes the response surface C. The response surface C is obtained based on the values at each position of the distribution map (see the black circle marks and black square marks in FIG. 13). The response surface C may be generated by interpolating between each position of the distribution map, or may be generated from an approximate function generated based on each position of the distribution map. Note that, in this embodiment, the display unit 105 displays both the distribution map and the response surface C, but only one of the distribution map and the response surface C may be displayed.

[0104] Continuing to refer to FIG. 13, the distribution map displayed on the display unit 105 will be described in detail. The distribution map is displayed, for example, using "rotation speed" and "supply amount" as two types of parameters and "uniformity of processing amount" as the estimation processing result. In the distribution map of FIG. 13, the value in the z-axis direction decreases as the "uniformity of processing amount" improves.

[0105] "Rotation speed", "supply amount", and "uniformity of processing amount" as variables of the distribution map are set by the user. When the user reselects the variables of the distribution map, the display unit 105 displays a distribution map and a response surface C based on the newly selected variables. The combination of two types of parameters is not particularly limited. For example, combinations such as "rotation speed" and "supply amount", "supply amount" and "concentration of processing liquid", "supply amount" and "presence or absence of discharge of processing liquid onto the lower surface of the substrate W", "rotation speed" and "temperature of processing liquid", "rotation speed" and "presence or absence of discharge of processing liquid onto the lower surface of the substrate W", "presence or absence of discharge of processing liquid onto the lower surface of the substrate W" and "temperature of processing liquid" can be mentioned.

[0106] Further, in FIG. 13, for example, only the regions where the estimated processing result is equal to or greater than a predetermined threshold value, the distribution diagram and the response surface C are displayed. Note that the display regions of the distribution diagram and the response surface C are set as appropriate. The distribution diagram and the response surface C may be displayed, for example, only in the regions where the estimated processing result is less than a predetermined threshold value, or only in a predetermined range (equal to or greater than a first threshold value and less than a second threshold value). Further, the distribution diagram and the response surface C may be displayed for all regions regardless of the value of the estimated processing result.

[0107] Also, for example, when "rotation speed", "supply amount", and "uniformity of processing amount" are set as variables of the distribution diagram, among the parameters as processing conditions, parameters other than "rotation speed" and "supply amount" (for example, "concentration of processing liquid", "temperature of processing liquid", and "presence or absence of discharge of processing liquid onto the lower surface of substrate W") are obtained. The number of combinations of the estimated processing results (hereinafter, may be referred to as the estimated processing results of the number of combinations) is obtained. That is, for one combination of a certain value of "rotation speed" and a certain value of "supply amount", the values of the estimated processing results are obtained as many as the number of the above combinations. Therefore, in the present embodiment, the first control unit 102 obtains one estimated processing result for one combination of a certain value of "rotation speed" and a certain value of "supply amount" by calculating, for example, the average value of the estimated processing results of the number of combinations. Note that the method of obtaining one estimated processing result for one combination of "rotation speed" and "supply amount" is not limited to the above. For example, among the estimated processing results of the number of combinations, a predetermined number of estimated processing results close to the target processing result may be extracted, and the average value of the predetermined number of estimated processing results may be obtained as the above one estimated processing result. Further, for example, among the estimated processing results of the number of combinations, a predetermined range of estimated processing results including the target processing result may be extracted, and the average value of the predetermined range of estimated processing results may be obtained as the above one estimated processing result. Note that in the present embodiment, an example of obtaining one estimated processing result by averaging at least a part of the estimated processing results of the number of combinations and displaying the obtained result is shown, but the present invention is not limited thereto. For example, a part or all of the estimated processing results of the number of combinations may be displayed.

[0108] In addition, the distribution diagram and the response surface C represent the influence degree of parameters on the estimation processing result. Specifically, for example, referring to points A1 and A3 in FIG. 13, around point A1, the change amount of the uniformity of the processing amount when the numerical value of the parameter is changed is relatively small, and around point A3, the change amount of the uniformity of the processing amount when the numerical value of the parameter (especially the rotation speed) is changed is relatively large. That is, when the substrate W is processed under the processing conditions corresponding to point A1, it can be understood that the "uniformity of the processing amount" is ensured even if the "rotation speed" and the "supply amount" vary slightly. The change amount of the uniformity of the processing amount can be read from the slope of the response surface C. Further, in association with the marks described below, the slope of the response surface C at the position of the mark may be displayed. Also, when the user selects a mark, the slope of the response surface C at the position of the mark may be displayed. In the present embodiment, the distribution diagram and the response surface C are displayed as shown in FIG. 13, and the slope of the response surface C is calculated, but this is not the only case. For example, after inputting a plurality of processing conditions included in the input condition range including a predetermined processing condition and obtaining a plurality of estimation processing results, the slope at a predetermined point may be calculated.

[0109] In addition, the display unit 105 displays a plurality of marks that can be selected by the user on the distribution diagram. In other words, the distribution diagram includes marks that can be selected by the user. The marks include a first mark and a second mark different from the first mark. In FIG. 13, the first mark is indicated by a black circle, and the second mark is indicated by a black square. Also, the first mark corresponds to points A1 to A3, and the second mark corresponds to points B1 to B5.

[0110] The display unit 105 displays a plurality of first marks (points A1 to A3) within a predetermined range R including the position corresponding to the target processing result in the distribution diagram. The display unit 105 displays second marks (points B1 to B5) outside the predetermined range R in the distribution diagram. The target processing result may be, for example, the average value of the processing amount, the uniformity of the processing amount, or the degree of coincidence of the processing amount profile. In the present embodiment, the predetermined range R is the lower region in the distribution diagram of FIG. 13. That is, the first marks (points A1 to A3) indicate that the processing conditions can obtain processing results closer to the target processing result than the second marks (points B1 to B5). In FIG. 13, three first marks and five second marks are displayed, but the numbers of the first marks and the second marks are not particularly limited. For example, about 10 first marks and about 20 second marks may be displayed. For example, the processing conditions corresponding to the upper several processing results close to the target processing result may be displayed as the first marks.

[0111] As described above, the display unit 105 displays a plurality of first marks (points A1 to A3) within a predetermined range R including the position corresponding to the target processing result in the distribution diagram. The display unit 105 displays second marks (points B1 to B5) outside the predetermined range R in the distribution diagram. Therefore, the user can easily select the processing conditions that can obtain processing results closer to the target processing result.

[0112] Next, with reference to FIGS. 14 to 19, a substrate processing method using the substrate processing system 1000 will be described. FIG. 14 is a flowchart showing the substrate processing method using the substrate processing system 1000 of the present embodiment.

[0113] As shown in FIG. 14, the substrate processing method using the substrate processing system 1000 includes at least step S2 and step S3. In the present embodiment, the substrate processing method includes steps S1 to S3.

[0114] Step S1 includes the step of measuring the thickness of the object TG before processing. Step S2 includes the step of setting the substrate processing conditions. Step S3 includes the step of processing the substrate W. Note that the processing of the substrate W in steps S1 to S3 is an etching process. Hereinafter, steps S1 to S3 will be described in detail.

[0115] First, referring to FIG. 15, the step of measuring the thickness of the object TG before processing (step S1) will be described. FIG. 15 is a flowchart showing a method of measuring the thickness of the object TG before processing in the present embodiment. The step of measuring the thickness of the object TG before processing includes steps S11 and S12.

[0116] The process shown in FIG. 15 is started by an operator operating the input unit 104. At this time, a plurality of substrates W are accommodated in at least one of the plurality of load ports LP.

[0117] The first control unit 102 controls the indexer robot IR and the center robot CR so that the substrate W is carried into the chamber 2. The first control unit 102 causes the substrate W carried into the chamber 2 to be held by the spin chuck 3 (step S11).

[0118] When the substrate W is held by the spin chuck 3, the first control unit 102 causes the measuring unit 8 to measure the thickness distribution of the object TG included in the substrate W (step S12). The thickness distribution of the object TG measured here indicates the thickness distribution of the object TG before processing.

[0119] Based on the thickness distribution of the object TG obtained in steps S11 and S12 and the target surface profile of the substrate W, it is possible to obtain the target processing profile.

[0120] Next, with reference to FIGS. 16 to 18, the process of setting substrate processing conditions (step S2) will be described. FIG. 16 is a flowchart showing a method of setting substrate processing conditions according to the present embodiment. The process of setting substrate processing conditions includes steps S24, S26, and S28. In the present embodiment, the process of setting substrate processing conditions includes steps S21 to S28.

[0121] As shown in FIG. 16, in step S21, the user selects the type of the object TG and the type of the processing liquid (etching liquid) by operating the input unit 104. Thereby, the type of the object TG and the type of the processing liquid are set by the first control unit 102.

[0122] FIG. 17 is a diagram showing an example of an image displayed on the display unit 105 according to the present embodiment. Specifically, in step S21, as shown in FIG. 17, on the display unit 105, for example, a pull-down menu i1 for selecting the type of the object TG and a pull-down menu i2 for selecting the type of the processing liquid are displayed. The user selects the type of the object TG and the type of the processing liquid from the pull-down menu i1 and the pull-down menu i2 by operating the input unit 104. Note that the user may input the type of the object TG and the type of the processing liquid using a keyboard or the like without using the pull-down menu i1 and the pull-down menu i2. Further, when the user inputs the lot number or the like of the substrate W, the first control unit 102 may set the type of the object TG and the type of the processing liquid based on the lot number or the like of the substrate W.

[0123] In step S22 shown in FIG. 16, for example, the user sets an input condition range by operating the input unit 104. The input condition range is the range of the processing conditions input to the learned model 23 in a later step S24.

[0124] The input condition range includes predetermined processing conditions. The predetermined processing conditions may be, for example, the type of the object TG selected by the user and the type of the processing liquid, and may also be the processing conditions when processed in the past. Further, the predetermined processing conditions may be, for example, the processing conditions determined by the user based on past experience.

[0125] Also, the input condition range is set for each of a plurality of parameters of the processing conditions. The condition range of each parameter may be set, for example, within a predetermined range centered on the value of the predetermined processing condition. Further, the input condition range may be set by the first control unit 102 when the user inputs it, or may be automatically set by the first control unit 102 based on the predetermined processing conditions.

[0126] FIG. 18 is a diagram showing an example of an image displayed on the display unit 105 of the present embodiment. Specifically, in step S22, as shown in FIG. 18, for example, an input field i3 for inputting the lower limit value and the upper limit value of the input condition range of each parameter is displayed on the display unit 105. For example, the user inputs a numerical value into the input field i3 using the input unit 104.

[0127] In step S23, the type information of the object TG, the type information of the processing liquid, and the input condition range information are transmitted from the control device 101 to the server 200. The type information of the object TG is information indicating the type of the object TG. The type information of the processing liquid is information indicating the type of the processing liquid. The input condition range information is information indicating the input condition range.

[0128] In step S24, the second control unit 210 inputs a plurality of processing conditions to the learned model 23 and obtains a plurality of estimated processing results. The plurality of processing conditions input to the learned model 23 are the processing conditions included in the input condition range.

[0129] Specifically, in step S24, the second control unit 210 selects one learned model 23 from the plurality of learned models 23 based on the type information of the object TG and the type information of the processing liquid. That is, the second control unit 210 selects one learned model 23 corresponding to the type of the object TG and the type of the processing liquid selected in step S21.

[0130] Then, the second control unit 210 inputs the processing conditions included in the input condition range to the learned model 23 and obtains the estimated processing result. At this time, the second control unit 210 obtains a plurality of estimated processing results by, for example, loop operation. Specifically, each parameter includes several to several tens of values to be input. The values to be input are the values from the lower limit value to the upper limit value of the input condition range in each parameter. For the temperature parameter of the processing liquid, for example, it is set every several degrees, 5 degrees, or 10 degrees. As a result, the number of combinations of the values to be input for each parameter included in the input condition range is, for example, several hundreds to several thousands. Then, the same number of processing conditions as the number of combinations are input to the learned model 23, and the same number of estimated processing results are obtained. The plurality of obtained estimated processing results are stored in the storage unit 220.

[0131] In step S25, the plurality of estimated processing result information is transmitted from the server 200 to the control device 101. The plurality of estimated processing result information is transmitted from the server 200 to the control device 101 in association with the corresponding processing condition information.

[0132] In step S26, the first control unit 102 causes the display unit 105 to display an image based on the plurality of estimated processing results. Specifically, as shown in FIG. 18, on the display unit 105, a button i4 for selecting "uniformity of processing amount" as a variable of the distribution diagram and a button i5 for selecting "degree of match of processing amount profile" as a variable of the distribution diagram are displayed. The user selects "uniformity of processing amount" or "degree of match of processing amount profile" by clicking the button i4 or the button i5.

[0133] In addition, a pull-down menu i6 and a pull-down menu i7 for selecting the type of parameter as a variable of the distribution map are displayed on the display unit 105. The user selects the type of parameter as a variable of the distribution map by using the pull-down menus i6 and i7. Note that the pull-down menus i6 and i7 are an example of the "selection unit" of the present invention.

[0134] Then, the first control unit 102 causes the display unit 105 to display a three-dimensional distribution map (see FIG. 13) using the type of variable selected by the user.

[0135] Note that the user may change the variable of the distribution map after the display of the distribution map. Thereby, the user can confirm a plurality of distribution maps with different variables.

[0136] In addition, the display unit 105 displays marks (a first mark and a second mark) that can be selected by the user on the distribution map.

[0137] In step S27, the user selects one processing condition corresponding to one of the plurality of estimation processing results by using the input unit 104. Specifically, the user selects one of the first marks (points A1 to A3) on the distribution map displayed on the display unit 105. That is, the user selects one of the processing conditions corresponding to the first mark (points A1 to A3) as the execution processing condition. For example, if the first mark (point A1) in FIG. 13 is selected, it is possible to suppress the supply amount of the processing liquid and to ensure the uniformity of the processing amount even when the rotation speed varies.

[0138] In step S28, the first control unit 102 sets one processing condition corresponding to one mark selected by the user as the execution processing condition.

[0139] In this way, the substrate processing conditions are set.

[0140] In this embodiment, the user defines the input condition range by operating the input unit 104 to set the input condition range. However, this is not the only way. For example, by clicking the button i4 or button i5 in FIG. 18 and selecting the variable of the distribution diagram, the input condition range may be set by an optimization algorithm such as Bayesian optimization. As a result, the trouble of determining the input condition range is eliminated, and the usability for the user is improved.

[0141] As described above with reference to FIGS. 16 to 18, the method for setting the substrate processing conditions has been explained. In this embodiment, as described above, the second control unit 210 inputs a plurality of processing conditions to the learned model M and obtains a plurality of estimated processing results (step S24). Then, the first control unit 102 causes the display unit 105 to display an image based on the plurality of estimated processing results (step S26). Further, the first control unit 102 sets, as the execution processing conditions when processing the substrate W, one processing condition corresponding to one of the plurality of estimated processing results (step S28). Therefore, the user can easily grasp how the estimated processing results change by changing the parameters of the processing conditions. Thus, the processing conditions suitable for mass production can be set as the execution processing conditions. Specifically, for example, since the substrate W can be processed under processing conditions with a wide process window, the substrate W can be processed stably. Also, for example, the amount of the processing liquid (etching liquid) used when processing the substrate W can be suppressed.

[0142] Also, as described above, the second control unit 210 inputs a plurality of processing conditions included in the input condition range to the learned model M and obtains a plurality of estimated processing results (step S24). Therefore, compared with the case where processing conditions outside the input condition range are also input to the learned model M, it is possible to significantly reduce the number of processing conditions input to the learned model M. Thus, it is possible to significantly suppress the increase in the calculation time of the second control unit 210 when obtaining a plurality of estimated processing results. In particular, when there are many types of parameters of the processing conditions, since the number of processing conditions increases exponentially, setting the range of the processing conditions to be input is particularly effective.

[0143] Also, as described above, the user uses the input unit 104 to select one processing condition based on the image displayed on the display unit 105 (step S27). Then, the first control unit 102 sets the selected one processing condition as the execution processing condition (step S28). Therefore, for example, the substrate W can be processed under desired processing conditions such as processing conditions with a wide process window or processing conditions capable of suppressing the usage amount of the processing liquid.

[0144] Also, as described above, the first control unit 102 causes a distribution diagram to be displayed in three dimensions using two types of parameters specified by the user and the estimated processing result. Therefore, for example, compared with the case of displaying a two-dimensional distribution diagram, it becomes easier to visually grasp the degree of influence of each parameter on the estimated processing result (for example, the amount of change in the uniformity of the processing amount).

[0145] Also, as described above, the display unit 105 displays a selection unit (here, pull-down menus i6 and i7) that allows the user to select the types of parameters as variables of the distribution diagram. Therefore, since the parameters as variables of the distribution diagram can be easily selected, it is possible to easily grasp the processing conditions suitable for mass production.

[0146] Also, as described above, the display unit 105 displays marks that can be selected by the user on the distribution diagram. Then, one mark is selected from a plurality of marks by the user using the input unit 104 (step S27). After that, the first control unit 102 sets one processing condition corresponding to the one mark selected by the user as the execution processing condition (step S28). Therefore, the user can select the processing condition corresponding to the selected position as the execution processing condition by selecting a mark at a certain position on the distribution diagram while visually checking the distribution diagram. Thus, the confirmation work and selection work by the user can be facilitated.

[0147] Next, referring to FIG. 19, the process of processing the substrate W (step S3) will be described. FIG. 19 is a flowchart showing the method of processing the substrate W according to the present embodiment. The process of processing the substrate W includes steps S31 to S33.

[0148] As shown in FIG. 19, in step S31, the first control unit 102 rotates the substrate W held by the spin chuck 3 using the spin motor unit 5. Thereafter, the first control unit 102 controls the nozzle moving mechanism 6 and the etching solution supply unit 4 so that the processing solution (etching solution) is supplied from the first nozzle 41 toward the substrate W. As a result, the substrate W is etched.

[0149] In step S32, the first control unit 102 controls the rinse solution supply unit 7 to supply the rinse solution to the substrate W, thereby removing the processing solution (etching solution) from the substrate W. Specifically, the processing solution is flushed outward from the substrate W by the rinse solution and discharged around the substrate W. As a result, the liquid film of the processing solution on the substrate W is replaced with the liquid film of the rinse solution.

[0150] In step S33, the first control unit 102 controls the spin motor unit 5 to dry the substrate W.

[0151] In the above manner, the processing of the substrate W is completed.

[0152] (Second Embodiment) Referring to FIG. 20, the substrate processing system 1000 according to the second embodiment of the present invention will be described. FIG. 20 is a diagram showing an example of an image displayed on the display unit 105 according to the second embodiment of the present invention. In the second embodiment, different from the first embodiment, an example of displaying the distribution map in two dimensions will be described.

[0153] As shown in FIG. 20, the distribution map is displayed in two dimensions. The distribution map is displayed using, for example, "processing amount" and "uniformity of processing amount" as variables. Note that the variables of the distribution map are not particularly limited, and the parameters of the processing conditions may be used as in the first embodiment.

[0154] In this embodiment, the display unit 105 displays a button i8 for switching the dimension of the distribution diagram between two dimensions and three dimensions. The user can use the input unit 104 to click the button i8 to display a two-dimensional distribution diagram or a three-dimensional distribution diagram on the display unit 105.

[0155] In addition, the display unit 105 displays a plurality of marks that can be selected by the user on the distribution diagram. In this embodiment, the marks include three first marks (point A4 to point A6). For example, when the user emphasizes the uniformity of the throughput, the user selects the processing conditions corresponding to point A4. Also, for example, when the user emphasizes the target throughput (e.g., 3.05 nm), the user selects the processing conditions corresponding to point A5.

[0156] In this embodiment, without using the parameters of the processing conditions, as shown in FIG. 20 for example, by displaying a distribution diagram using variables (here, "throughput" and "uniformity of throughput") based on the estimated processing results, when the user emphasizes the target processing result, it becomes easier to select the processing conditions.

[0157] Other configurations, substrate processing methods, and other effects of the second embodiment are the same as those of the first embodiment.

[0158] As described above, the embodiments of the present invention have been described with reference to the drawings. However, the present invention is not limited to the above embodiments, and can be implemented in various aspects without departing from the gist thereof. Also, the plurality of components disclosed in the above embodiments can be modified as appropriate. For example, a certain component among all the components shown in one embodiment may be added to the components of another embodiment, or some of the components among all the components shown in one embodiment may be deleted from the embodiment.

[0159] The drawings schematically show each component mainly for facilitating the understanding of the invention. The thickness, length, number, interval, etc. of each component shown in the drawings may be different from the actual ones for the convenience of drawing preparation. Also, it goes without saying that the configuration of each component shown in the above embodiments is an example and is not particularly limited, and various modifications are possible without substantially departing from the effects of the present invention.

[0160] For example, in the above first and second embodiments, the substrate W was a semiconductor wafer, but the substrate W is not limited to a semiconductor wafer. For example, the substrate W can be a substrate for a liquid crystal display device, a substrate for a field emission display (FED), a substrate for an optical disk, a substrate for a magnetic disk, a substrate for a magneto-optical disk, a substrate for a photomask, a ceramic substrate, or a substrate for a solar cell.

[0161] Also, in the above first and second embodiments, an example where the first control unit 102 and the second control unit 210 are arranged in separate devices has been described, but the present invention is not limited to this, and they may be arranged in the same device. For example, the first control unit 102 and the second control unit 210 may be arranged in the control device 101. Also, the first control unit 102 and the second control unit 210 may be constituted by one control unit.

[0162] Also, in the above-described first and second embodiments, an example is shown in which, after the user selects the type of the object TG and the type of the processing liquid (step S21) and the user sets the input condition range (step S22), the second control unit 210 inputs a plurality of processing conditions to the learned model M and acquires a plurality of estimated processing results (step S24). However, the present invention is not limited to this. For example, the second control unit 210 may input a plurality of processing conditions to the learned model M in advance and acquire a plurality of estimated processing results. Then, an image may be displayed based on the plurality of estimated processing results acquired in advance and the types of the object TG and the processing liquid selected by the user. That is, when the user selects the types of the object TG and the processing liquid, the calculation using the learned model M may already be completed. With such a configuration, an image can be displayed to the user more quickly, so that the time required for substrate processing can be shortened. When the second control unit 210 acquires a plurality of estimated processing results in advance, it is preferable to input more processing conditions to the learned model M to acquire the estimated processing results. More preferably, for example, all possible processing conditions are input to the learned model M to acquire the estimated processing results.

[0163] Also, in the above-described first and second embodiments, an example is shown in which a plurality of estimated processing results acquired using the learned model M are transmitted from the server 200 to the control device 101. However, the present invention is not limited to this. For example, information input by the user using the input unit 104 (such as information regarding the selected parameters) may be transmitted from the control device 101 to the server 200 each time, the server 200 may generate distribution map information for displaying the distribution map, and the generated distribution map information may be transmitted from the server 200 to the control device 101.

[0164] Also, in the above-described first and second embodiments, an example is shown in which the learning device 900 is provided separately from the server 200 and the control device 101. However, the present invention is not limited to this. For example, the server 200 or the control device 101 may also serve as the learning device 900.

[0165] In addition, in the above-described first and second embodiments, an example in which the control device 101 constitutes the substrate processing apparatus 100 has been shown, but the present invention is not limited to this. For example, the control device 101 may be provided separately from the substrate processing apparatus 100. And information regarding execution processing conditions may be transmitted from the control device 101 to the substrate processing apparatus 100.

[0166] In addition, in the above-described first and second embodiments, an example has been shown in which a predetermined processing condition included in the input condition range may be, for example, a processing condition when processed in the past or a processing condition determined by the user based on past experience, but the present invention is not limited to this. For example, a learned model that outputs a predetermined processing condition when a target throughput profile is input may be generated by machine learning using the learning dataset 931, and a predetermined processing condition may be acquired using the learned model.

[0167] In addition, in the above-described first embodiment, an example in which two types of parameters of processing conditions are used as variables of the three-dimensional distribution diagram has been shown, but the present invention is not limited to this. As variables of the three-dimensional distribution diagram, two or more variables based on the estimated processing result may be used for display as in the second embodiment.

[0168] In addition, in the above-described second embodiment, an example in which a two-dimensional distribution diagram can be displayed or a three-dimensional distribution diagram can be displayed has been shown, but the present invention is not limited to this. For example, the display unit 105 may display only one of the two-dimensional distribution diagram and the three-dimensional distribution diagram.

[0169] In addition, in the above-described first and second embodiments, an example in which the user selects one first mark from among a plurality of first marks displayed on the display unit 105 has been shown, but the present invention is not limited to this. For example, the display unit 105 may display one of the plurality of first marks as a candidate for the execution processing condition, and the user may approve it. Also in this case, it goes without saying that the user selects one processing condition.

[0170] Also, in the above-described first and second embodiments, the process executed by the substrate processing apparatus 100 was an etching process, but the process executed by the substrate processing apparatus 100 is not limited to the etching process. For example, the process may be a film formation process.

Industrial Applicability

[0171] The present invention is useful in the field of processing substrates.

Explanation of Signs

[0172] 1: Processing unit 41: First nozzle (nozzle) 102: First control unit (control unit) 104: Input unit (operation unit) 105: Display unit 210: Second control unit (control unit) 220: Storage unit 500: Substrate processing condition setting system 1000: Substrate processing system M: Learned model R: Predetermined range W: Substrate i6, i7: Pull-down menu (selection unit)

Claims

1. A step of inputting a plurality of processing conditions to a learned model that has been machine-learned based on learning processing conditions and processing results when processing a substrate under the learning processing conditions, and obtaining a plurality of estimated processing results; A step of causing a display unit to display an image based on the plurality of estimated processing results; A step of setting, as an execution processing condition when processing a substrate, one processing condition corresponding to one of the plurality of estimated processing results based on the image displayed on the display unit A method for setting substrate processing conditions, including the above steps.

2. The method further includes a step of setting an input condition range including predetermined processing conditions prior to the obtaining step, In the obtaining step, a plurality of processing conditions included in the input condition range are input to the learned model to obtain the plurality of estimated processing results. The method for setting substrate processing conditions according to Claim 1.

3. Each of the processing conditions includes at least a concentration condition indicating the concentration of the processing liquid supplied to the substrate, a temperature condition indicating the temperature of the processing liquid supplied to the substrate, a supply amount condition indicating the supply amount of the processing liquid supplied to the substrate, a rotation speed condition indicating the rotation speed of the substrate, and a speed condition indicating the scan speed of the nozzle for supplying the processing liquid to the substrate. The method for setting substrate processing conditions according to Claim 2.

4. Prior to the step of setting as the execution processing condition, A step of selecting the one processing condition by a user based on the image displayed on the display unit is further included, In the step of setting as the execution processing condition, the selected one processing condition is set as the execution processing condition. The method for setting substrate processing conditions according to any one of Claims 1 to 3.

5. The image includes a distribution diagram, Each of the processing conditions has a plurality of parameters, The distribution diagram is displayed three-dimensionally using two types of parameters specified by the user and the estimated processing results. The method for setting substrate processing conditions according to Claim 4.

6. The display unit displays a selection unit that allows the user to select the types of the parameters as variables of the distribution diagram. The method for setting substrate processing conditions according to Claim 5.

7. The display unit displays a plurality of marks that can be selected by the user on the distribution diagram, The method for setting substrate processing conditions according to claim 5 or claim 6, wherein in the step of selection, one of the plurality of marks is selected by the user, and the one processing condition is selected.

8. The plurality of marks include a first mark displayed within a predetermined range including a position corresponding to a target processing result in the distribution diagram; and a second mark displayed outside the predetermined range and different from the first mark in the distribution diagram The method for setting substrate processing conditions according to claim 7.

9. A substrate processing method including a step of setting the one processing condition as the execution processing condition according to the method for setting substrate processing conditions according to any one of claims 1 to 8; and a step of processing a substrate under the one processing condition.

10. A storage unit that stores learning processing conditions and a learned model that has been machine-learned based on the processing results when a substrate is processed under the learning processing conditions; a display unit; a control unit The substrate processing condition setting system is provided with The control unit inputs a plurality of processing conditions to the learned model to obtain a plurality of estimated processing results; causes an image based on the plurality of estimated processing results to be displayed on the display unit; and sets, as an execution processing condition when processing a substrate, one processing condition corresponding to one of the plurality of estimated processing results.

11. The control unit inputs a plurality of processing conditions included in an input condition range including a predetermined processing condition to the learned model to obtain the plurality of estimated processing results. The substrate processing condition setting system according to claim 10.

12. Each of the processing conditions includes at least a concentration condition indicating the concentration of the processing liquid supplied to the substrate, a temperature condition indicating the temperature of the processing liquid supplied to the substrate, a supply amount condition indicating the supply amount of the processing liquid supplied to the substrate, a rotation speed condition indicating the rotation speed of the substrate, and a speed condition indicating the scan speed of the nozzle for supplying the processing liquid to the substrate. The substrate processing condition setting system according to claim 11.

13. The substrate processing condition setting system according to any one of claims 10 to 12 further includes an operation unit that receives an operation by a user, and the control unit sets, as the execution processing condition, the one processing condition selected by the user using the operation unit.

14. The image includes a distribution diagram, and each of the processing conditions has a plurality of parameters. The substrate processing condition setting system according to claim 13, wherein the control unit causes the distribution diagram to be displayed in three dimensions using two types of parameters specified by the user and the estimation processing result.

15. The substrate processing condition setting system according to claim 14, wherein the display unit displays a selection unit that allows the user to select the types of the parameters as variables of the distribution diagram.

16. The display unit displays a plurality of marks that can be selected by the user on the distribution diagram, and the control unit sets, as the execution processing condition, the one processing condition corresponding to the one mark when one mark is selected by the user from the plurality of marks using the operation unit. The substrate processing condition setting system according to claim 14 or claim 15.

17. The plurality of marks are a first mark displayed within a predetermined range including a position corresponding to a target processing result in the distribution diagram, and a second mark displayed outside the predetermined range and different from the first mark in the distribution diagram The substrate processing condition setting system according to claim 16, including.

18. A substrate processing condition setting system according to any one of claims 10 to 17, and a processing unit that processes a substrate under the one processing condition A substrate processing system comprising.

Images