Computer program, information processing method, and information processing device

Abstract

Provided are a computer program, an information processing method, and an information processing device that can be expected to assist in formulation of an experimental plan by a user.　A computer program according to an embodiment of the present invention causes a computer to execute processing for displaying, side by side, a plurality of bars indicating possible values of a plurality of factors in an experimental plan, and displaying lines connecting combinations of the values of experimented factors by superimposing the lines on the plurality of bars. The bars may be circular- or arc-shaped. The bars having different sizes for the respective factors may be concentrically arranged and displayed.

Description

Computer Program, Information Processing Method, and Information Processing Apparatus

[0001] The present disclosure relates to a computer program, an information processing method, and an information processing apparatus.

[0002] In Patent Document 1, a recipe for controlling a substrate processing apparatus is stored, at least one level value (processing condition) of each of a plurality of control factors is acquired, combination information indicating a combination of the acquired level values is generated by a statistical method such as an experimental design method, and an evaluation recipe is created for each combination of level values based on the stored recipe and the generated combination information. A parameter design support apparatus has been proposed.

[0003] Japanese Patent Application Laid-Open No. 2019-29445

[0004] The present disclosure provides a computer program, an information processing method, and an information processing apparatus that can be expected to assist a user in formulating an experimental plan.

[0005] A computer program according to an embodiment causes a computer to execute a process of arranging and displaying a plurality of bars indicating values that can be taken by each of a plurality of factors in an experimental plan, and superimposing and displaying a line connecting combinations of values of the factors for which experiments have been performed on the plurality of bars.

[0006] According to the present disclosure, it can be expected to assist a user in formulating an experimental plan.

[0007] This is a schematic diagram illustrating the overview of the information processing system according to this embodiment. This is a schematic diagram showing an example of the visualization of experimental information by the information processing system according to this embodiment. This is a block diagram showing an example of the configuration of an information processing device according to this embodiment. This is a schematic diagram showing an example of the visualization of experimental information by the information processing system according to this embodiment. This is a schematic diagram showing an example of the visualization of experimental information by the information processing system according to this embodiment. This is a schematic diagram showing an example of the visualization of experimental information by the information processing system according to this embodiment. This is a flowchart showing an example of the procedure for the experimental information visualization processing performed by the information processing device according to this embodiment. This is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to this embodiment. This is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to this embodiment. This is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to this embodiment. This is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to modification 1. This is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to modification 2. This is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to modification 3. This is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to modification 4.

[0008] Specific examples of information processing systems according to embodiments of this disclosure will be described below with reference to the drawings. However, this disclosure is not limited to these examples and is intended to include all changes within the meaning and scope of the claims as indicated by the claims.

[0009] <System Overview> Figure 1 is a schematic diagram illustrating the overview of the information processing system according to this embodiment. The information processing system according to this embodiment is configured to include an information processing device 1 and a substrate processing device 3, etc. The substrate processing device 3 is a device that performs various substrate processing on semiconductor substrates (wafers), such as CVD (Chemical Vapor Deposition), sputtering, or etching. The information processing device 1 controls the substrate processing by the substrate processing device 3 and provides the user with various information obtained in connection with the substrate processing. The information processing device 1 causes the substrate processing device 3 to perform the desired substrate processing based on setting information (so-called recipes) related to substrate processing that the user has prepared in advance. The information processing device 1 and the substrate processing device 3 may be an integrated device or separate devices. If they are separate devices, the information processing device 1 and the substrate processing device 3 can exchange information by, for example, wired or wireless communication.

[0010] The information processing system according to this embodiment experimentally performs substrate processing by changing various conditions such as the temperature, pressure, gas type combination, gas flow rate, voltage applied to the power supply, type of installed components, and hardware driving conditions in the chamber of the substrate processing apparatus 3. It then performs various measurements on the processed substrate, such as etching rate, film deposition rate, shape, film thickness, and electrical characteristics, and the information processing apparatus 1 stores and accumulates the obtained measurement values ​​as experimental results information related to substrate processing. By performing substrate processing with the substrate processing apparatus 3 using various combinations of experimental conditions and collecting experimental results, the information processing system according to this embodiment can determine the optimal substrate processing conditions based on the obtained substrate processing results. However, since the substrate processing performed by the substrate processing apparatus 3 takes a certain amount of time, performing all possible substrate processing combinations for multiple conditions requires a long time and high cost. For this reason, the user needs to decide in what order to perform substrate processing for multiple combinations of conditions and collect information, and which conditions to use for the next substrate processing based on the results of the completed substrate processing.

[0011] In the information processing system according to this embodiment, in order to support the user in determining experimental conditions as described above, the information processing device 1 visualizes and provides to the user information related to the experiment, such as which combinations of conditions for previously experimented substrate processing are available, which combinations of conditions are candidates for experimentation, and / or which combination of conditions for the next substrate processing to be performed is optimal, based on the information obtained from experimental substrate processing. Based on the visualized experimental information, the user can determine the combination of experimental conditions for the next substrate processing to be performed. The information processing device 1 controls the operation of the substrate processing device 3 based on the experimental conditions determined by the user, performs substrate processing according to the experimental conditions, and acquires and stores the experimental results. The information processing device 1 visualizes and provides to the user information related to past experiments, including newly acquired experimental conditions and experimental results.

[0012] Figure 2 is a schematic diagram showing an example of the visualization of experimental information by the information processing system according to this embodiment. The information processing system according to this embodiment displays a graph representing combinations of experimental conditions as concentric circles, and a table showing multiple numerical information such as the coverage rate of experimentally tested combinations for all combinations of experimental conditions, side by side. The illustrated example shows a case where there are three types of experimental conditions (factors) that the user can set, factors A, B, and C, and the experiment is conducted by selecting one of three values ​​for each factor (i.e., each factor has three levels).

[0013] The graph shown above consists of three circular bars of different sizes arranged concentrically, with each circle corresponding to one factor. In this example, the bar in the inner small circle corresponds to factor A, the bar in the middle medium circle corresponds to factor B, and the bar in the outer large circle corresponds to factor C. The number of bars in the concentric circle graph corresponds to the number of experimental conditions that can be set in the experiment. In this example, one of three values, 1, 2, or 3, can be set for factor A, and the labels 1, 2, and 3 are shown at positions that divide the circle bar for factor A into three equal parts. These three labels are arranged in order, for example, clockwise, with the values ​​increasing. The bars in each circle of the concentric circle graph are displayed with a gradient, where the color gradually changes from small to large factor values. In this example, a portion of the circle bar for factor A, the arc-shaped portion connecting label 3 to label 1, is shown with a dashed line because it exceeds the range of values ​​that can be set for factor A.

[0014] Furthermore, in the concentric circle graph, the circles from the second innermost circle onward (the circles corresponding to factors B and C) are divided into multiple arc-shaped bars. In this example, the second circle corresponding to factor B is divided into three equal parts, resulting in three arc-shaped bars. The number of divisions in this circle is equal to 3, which is the number of possible values ​​for factor A in the innermost circle. Similarly, the third (outermost) circle corresponding to factor C is divided into nine equal parts, resulting in nine arc-shaped bars. The number of divisions in this circle is equal to the number of possible combinations of factors A and B in the two innermost circles, i.e., 3 × 3 = 9. If factor A can have four possible values ​​and factor B can have five possible values, then the circle for factor B is divided into four parts, and the circle for factor C is divided into 4 × 5 = 20 parts. Each divided arc-shaped bar is assigned, for example, one end to the minimum value of the factor and the other end to the maximum value of the factor. Each arc-shaped bar is displayed with a gradually changing color gradient to indicate that the factor values ​​change from small to large in a clockwise direction.

[0015] In the concentric circle graph, multiple lines extending outward from the center are displayed. Each of these lines represents a combination of experimentally tested conditions for factors A, B, and C. Each line is a straight line or a broken line passing through the center of the concentric circle, one bar in the first circle, one bar in the second circle, and one bar in the third circle. In this example, experiments have already been conducted with seven sets of conditions, and seven lines are displayed in the graph. However, if there is overlap in the combination of experimental conditions, parts of multiple lines may be displayed overlapping.

[0016] In this example, the table displayed alongside the graph includes a first table showing information on orthogonality and overall coverage for the entire experiment, and a second table showing the coverage for each factor. These two tables are displayed side-by-side, one above the other. The "orthogonality" in the first table is a value indicating the independence of each experimental condition (the degree to which combinations of experimental conditions do not influence each other), and in this example, the D optimal design score criterion is used. The "overall coverage" in the first table is the proportion of all combinations of factors A, B, and C that have been experimented with. In this example, since factors A, B, and C can each be set to three values, there are 3 × 3 × 3 = 27 experimental combinations, and currently 7 combinations have been experimented with, so the overall coverage is 7 / 27 = 25.9%.

[0017] The second table is a table that associates multiple "factors" with the "coverage rate" for each factor. In the second table shown in the illustration, the coverage rates of factors A, B, and C are displayed from top to bottom, and the coverage rate of factor A is 100%. In this example, factor A can be set to three values, and since the experiment was conducted with all three values ​​set at least once, the coverage rate is 3 / 3 = 100%. Also in the second table shown in the illustration, the coverage rate of factor B is 55.6%, and the coverage rate of factor C is 25.9%. The coverage rate of factor B shown in the second table in this example is not the coverage rate of factor B alone, but strictly speaking, the coverage rate of factor B considering combinations with factor A. Therefore, the coverage rate of factor B is 5 / 9 = 55.6%, because there are 3 × 3 = 9 possible combinations of factors A and B, and 5 combinations have been experimented with. Similarly, the coverage rate of factor C shown in the second table in this example is not the coverage rate of factor C alone, but strictly speaking, the coverage rate of factor C considering combinations with factors A and B. Therefore, the coverage rate for factor C is 7 / 27 = 25.9%, since there are 7 experimental combinations out of 3 × 3 × 3 = 27 possible combinations of factors A, B, and C. Thus, the factor coverage rate shown at the bottom of the second table is the same as the overall coverage rate in the first table.

[0018] In the information processing system according to this embodiment, the information processing device 1 provides the user with information about the experiment by displaying the graph and table shown in Figure 2. Based on the displayed graph, the user can confirm whether the combination of conditions has been experimented with or not. The user can also grasp the progress of the experiment based on the numerical information in the table displayed along with the graph. Based on this information, the user can decide on the next combination of experimental conditions and perform substrate processing with the substrate processing device 3 to obtain experimental results.

[0019] Furthermore, the information processing system according to this embodiment can propose to the user combinations of experimental conditions to be implemented next, for example, using methods such as experimental design. The information processing system can also predict experimental results for untested combinations of experimental conditions using a learning model created in advance through processing such as machine learning, and provide the predicted experimental results to the user.

[0020] <Device Configuration> Figure 3 is a block diagram showing an example configuration of the information processing device 1 according to this embodiment. The information processing device 1 according to this embodiment can be realized by installing a predetermined application program on a general-purpose information processing device such as a personal computer or a server computer. The information processing device 1 according to this embodiment is configured to include a processing unit 11, a storage unit 12, a communication unit 13, a display unit 14, and an operation unit 15, etc.

[0021] The processing unit 11 is composed of a arithmetic processing unit such as a CPU (Central Processing Unit), MPU (Micro-Processing Unit), GPU (Graphics Processing Unit), or quantum processor, as well as ROM (Read Only Memory) and RAM (Random Access Memory). The processing unit 11 reads and executes a program 12a stored in the storage unit 12, performing various processes such as displaying and providing experimental information to the user, and controlling substrate processing by the substrate processing device 3 according to experimental conditions determined by the user.

[0022] The storage unit 12 is configured using a large-capacity storage device such as a hard disk or an SSD (Solid State Drive). The storage unit 12 stores various programs executed by the processing unit 11, and various data necessary for the processing of the processing unit 11. In this embodiment, the storage unit 12 stores the program 12a executed by the processing unit 11. The storage unit 12 is also provided with an experimental information storage unit 12b that stores various information such as experimental conditions and experimental results of substrate processing performed by the substrate processing device 3.

[0023] In this embodiment, the program (computer program, program product) 12a is provided in a form recorded on a recording medium 99 such as a memory card or optical disc, and the information processing device 1 reads the program 12a from the recording medium 99 and stores it in the storage unit 12. However, the program 12a may also be written to the storage unit 12 during the manufacturing stage of the information processing device 1, for example. Alternatively, the program 12a may be distributed by a remote server device or the like and acquired by the information processing device 1 via communication. For example, the program 12a may be read from the recording medium 99 by a writing device and written to the storage unit 12 of the information processing device 1. The program 12a may be provided by distribution via a network, or it may be provided in a form recorded on the recording medium 99.

[0024] The experimental information storage unit 12b stores various information related to the substrate processing experiments conducted in the substrate processing apparatus 3. The experimental information storage unit 12b stores information such as the date and time the substrate processing experiment was conducted, identification information attached to the substrate that underwent the experiment, combinations of experimental conditions, measured values ​​obtained during the substrate processing related to the experiment, and the results of the experiment, in association with each other. The measured values ​​stored in the experimental information storage unit 12b are, for example, values ​​such as temperature, pressure, and gas flow rate during substrate processing measured by sensors provided in the substrate processing apparatus 3. The experimental results stored in the experimental information storage unit 12b are, for example, characteristics such as film thickness, shape, or etching rate of the substrate after processing, measured by measuring instruments installed in the substrate processing apparatus 3 or measuring instruments installed outside the substrate processing apparatus 3.

[0025] The communication unit 13 is connected to the substrate processing device 3 via a wired or wireless network N and exchanges data with the substrate processing device 3. In this embodiment, the communication unit 13 transmits the substrate processing conditions and operation commands provided by the processing unit 11 to the substrate processing device 3. The communication unit 13 also receives information regarding experimental results transmitted from the substrate processing device 3 and provides it to the processing unit 11.

[0026] The display unit 14 is configured using a liquid crystal display or the like, and displays various images and characters based on the processing of the processing unit 11. The display unit 14 displays various information such as the progress of substrate processing by the substrate processing apparatus 3, whether or not there are any abnormalities, or measured values ​​measured by sensors of the substrate processing apparatus 3. In this embodiment, the display unit 14 also displays various information such as a graph showing experimental combinations of conditions shown in Figure 2, and a table showing numerical values ​​such as the coverage rate of experimental conditions.

[0027] The operation unit 15 receives user input and notifies the processing unit 11 of the received input. For example, the operation unit 15 receives user input via a mechanical button or an input device such as a touch panel provided on the surface of the display unit 14. Alternatively, the operation unit 15 may be an input device such as a mouse and a keyboard, and these input devices may be configured to be detachable from the information processing device 1.

[0028] The memory unit 12 may be an external storage device connected to the information processing device 1. The information processing device 1 may be a multicomputer comprising multiple computers, or it may be a virtual machine virtually constructed by software. Furthermore, the information processing device 1 is not limited to the above configuration, and for example, it does not have to include a display unit 14 and an operation unit 15, in which case information may be exchanged with the user via an external device equipped with a display unit and an operation unit.

[0029] Furthermore, in the information processing device 1 according to this embodiment, the processing unit 11 reads and executes the program 12a stored in the storage unit 12, thereby realizing the experiment control unit 11a, graph generation unit 11b, score calculation unit 11c, experiment candidate calculation unit 11d, experiment result prediction unit 11e, and display processing unit 11f, etc., as software-based functional units in the processing unit 11. In this figure, the functional units of the processing unit 11 that perform processing related to the experiment of substrate processing performed in the substrate processing device 3 are shown, and functional units related to other processing are omitted from the illustration.

[0030] The experimental control unit 11a controls the operation of the substrate processing device 3 by sending and receiving information via the communication unit 13, causing the substrate processing device 3 to perform substrate processing under the set experimental conditions. The experimental control unit 11a transmits control commands to the substrate processing device 3, including experimental conditions set by the user, to perform substrate processing. The experimental control unit 11a also receives various measurement values ​​related to substrate processing measured by sensors etc. of the substrate processing device 3 and stores the received information in the experimental information storage unit 12b.

[0031] The graph generation unit 11b generates a graph to visualize the experimental conditions based on the information stored in the experimental information storage unit 12b. Specifically, the graph generation unit 11b generates the concentric circle graph shown at the top of Figure 2. The graph generation unit 11b determines the number of circles to include in the graph according to the number of changeable experimental conditions (factors), and determines the number of divisions of each circle according to the number of settable values ​​for each factor. Based on the determined number of circles and the number of divisions of each circle, the graph generation unit 11b arranges multiple circles or arc-shaped bars in a concentric circle pattern, and generates lines showing combinations of experimental conditions by connecting points on the bars corresponding to the experimental conditions with lines.

[0032] The score calculation unit 11c performs a process to calculate numerical values ​​such as coverage rate and orthogonality for experimentally completed conditions as scores, based on the information stored in the experimental information storage unit 12b. In this embodiment, the calculation formulas for calculating these scores are predetermined. The score calculation unit 11c obtains the information necessary for calculation using the predetermined calculation formulas from the experimental information storage unit 12b, and calculates the scores by performing calculations using the calculation formulas based on the obtained information.

[0033] The experiment candidate calculation unit 11d calculates experiment candidates from combinations of conditions for which experiments have not yet been conducted, based on the information stored in the experiment information storage unit 12b. In this embodiment, the experiment candidate calculation unit 11d calculates the optimal combination of experimental conditions to be conducted next from among multiple combinations of unexperimented conditions, for example, by using a method such as Bayesian optimization. Since the Bayesian optimization method for calculating the optimal experimental conditions is an existing technology, a detailed explanation is omitted in this embodiment.

[0034] The experimental result prediction unit 11e performs processing to predict experimental results for combinations of conditions for which experiments have not been conducted, based on the information stored in the experimental information storage unit 12b. In this embodiment, the experimental result prediction unit 11e predicts experimental results using a learning model that has been generated in advance by machine learning. The learning model can be of various configurations, such as linear regression, SVM (Support Vector Machine), or neural network. The learning model is pre-programmed to accept experimental conditions as input and output predicted values ​​of experimental results. The information processing device 1 can generate a learning model by, for example, collecting learning data that associates experimental conditions and experimental results for substrate processing in advance and performing machine learning processing using the obtained learning data. The experimental result prediction unit 11e obtains combinations of conditions for which experiments have not been conducted, inputs these combinations of conditions into the learning model, and obtains predicted values ​​of experimental results output by the learning model, thereby predicting experimental results for unexperimented conditions.

[0035] The display processing unit 11f performs the processing of displaying various characters and images on the display unit 14. In this embodiment, the display processing unit 11f displays, for example, a graph generated by the graph generation unit 11b and a table of scores calculated by the score calculation unit 11c side by side on the display unit 14. The display processing unit 11f also displays, for example, a line or region corresponding to an experimental candidate calculated by the experimental candidate calculation unit 11d superimposed on a graph of concentric circles generated by the graph generation unit 11b. The display processing unit 11f also displays, for example, the experimental result prediction unit 11e predicts the experimental results. Furthermore, the display processing unit 11f graphs and displays sensor measurement values ​​acquired from the substrate processing unit 3 when, for example, the experimental control unit 11a is controlling the operation of the substrate processing unit 3 to perform substrate processing related to the experiment. The display processing unit 11f may also display various other information on the display unit 14.

[0036] <Visualization of Experimental Information> Figures 4 to 7 are schematic diagrams showing an example of the visualization of experimental information by the information processing system according to this embodiment. In the information processing system according to this embodiment, for example, in order to find the optimal conditions for substrate processing, the user performs experimental substrate processing with various combinations of conditions in the substrate processing device 3 and collects information on the experimental results. Based on the multiple experimental results collected, the user identifies the combination of conditions that yielded the best results. The user can expect to obtain good results by performing subsequent substrate processing with the identified conditions. To support such experimental substrate processing, in the information processing system according to this embodiment, the information processing device 1 visualizes and provides to the user experimental information such as conditions that have been experimented with and conditions for candidate experiments.

[0037] To utilize the visualization function of the information processing device 1, the user pre-registers information with the information processing device 1, such as the number of conditions (factors) that can be set as an experiment in substrate processing, the number of values ​​that can be set for each factor, constraints for each factor, constraints regarding combinations of multiple factors, and settings for substrate processing that will not be changed during the experiment. Once this information is registered, the information processing device 1 can generate a concentric circle graph and table corresponding to the initial state (the state before the experiment is performed). Figure 4 shows an example of a concentric circle graph and table in the initial state.

[0038] The information processing device 1 determines the number of circles in the concentric circle graph according to the number of experimental factors, based on pre-registered information. In the example shown in Figure 4, there are three experimental factors, A, B, and C, and the information processing device 1 generates a concentric circle graph with three circular bars of different sizes (small, medium, and large) arranged concentrically. The innermost small circle corresponds to factor A, the second medium circle from the inside corresponds to factor B, and the third large circle corresponds to factor C. If there are four factors, the graph will be a quadruple concentric circle, and if there are five factors, the graph will be a quintuple concentric circle.

[0039] The information processing device 1 also divides the second and subsequent circles from the inside into multiple arc bars. The number of divisions for each circle is determined according to the number of levels of the factors corresponding to one or more circles located further inside it. For example, if the number of levels of the factors corresponding to the first circle is a, the number of levels of the factors corresponding to the second circle is b, and the number of levels of the factors corresponding to the third circle is c, then the number of divisions for the second circle is a, the number of divisions for the third circle is a × b, and the number of divisions for the fourth circle is a × b × c. In other words, the number of divisions for each circle is the total number of combinations of one or more factors corresponding to one or more circles located further inside it. In the example shown in Figure 4, the circle of the second factor B is divided into 3, which is the number of levels of factor A, and the circle of the third factor C is divided into 9 (= 3 × 3), which is the total number of combinations of factors A and B.

[0040] In the example shown in Figure 4, the circle is divided in the initial state before the experiment begins. This is because the number of levels for each factor is determined before the experiment begins. If the number of levels is not determined before the experiment begins, the information processing device 1 may not divide the circle in the initial state, but divide the circle as the experiment progresses, increasing the number of divisions in accordance with the increase in the number of factors being tested.

[0041] Furthermore, for each arc-shaped bar, if the corresponding factor changes value continuously, the information processing device 1 displays the bar with a gradient, associating one end with the minimum value and the other end with the maximum value, and gradually changing the color of the bar. However, the information processing device 1 does not have to display the arc-shaped bars with a gradient. Also, if the corresponding factor is expressed as a category, the information processing device 1 does not have to color-code the arc-shaped bars with a gradient.

[0042] Furthermore, if there are conditions under which substrate processing cannot be performed by the substrate processing device 3, or conditions under which the experiment does not need to be performed, the information processing device 1 displays arc-shaped bars corresponding to such conditions, distinguishing them from other bars. The information processing device 1 has previously received input from the user as constraints and stores them in the storage unit 12. In the example shown in Figure 4, the arc-shaped bars corresponding to such constraints are displayed with dashed lines, but this is not the only way. For example, the arc-shaped bars corresponding to constraints may be distinguished from other bars by displaying them in a different color (for example, an inconspicuous color such as light gray), or the arc-shaped bars corresponding to constraints may be hidden.

[0043] Furthermore, if the number of levels for each factor is defined, the information processing device 1 displays multiple points representing possible values ​​for each factor superimposed on the arc-shaped bar corresponding to that factor. In the example shown in Figure 4, factors A, B, and C each have 3 levels, and the information processing device 1 displays three black dots superimposed on one arc-shaped bar. The black dots are nodes corresponding to the number of levels and divide the arc-shaped bar. In this example, black dots are displayed at both ends and the center of the arc-shaped bar, indicating that the experiment is conducted on the three values ​​of the factor: minimum, maximum, and median. In this example, the minimum, maximum, and median values ​​of the factor that equally divide the bar are used as the values ​​corresponding to the black dots, but this is not limited to these, and the values ​​corresponding to the black dots may be any values ​​for which the experiment can be conducted. The information processing device 1 may or may not display these black dots on a concentric circle graph. In the display examples from Figure 2 and Figure 5 onward, these black dots are not displayed, but they may be displayed. Furthermore, the information processing device 1 may display not only black dots, but also, for example, white dots or dots of an appropriate color, or it may display various shapes such as "X", triangles, rhombuses, or stars instead of dots.

[0044] In addition, the information processing apparatus 1 displays a table showing numerical values such as the coverage rate and parallelism related to the experiment, together with a concentric circle graph. Since these numerical values cannot be calculated in the initial state before the start of the experiment, the information processing apparatus 1 displays the table with the numerical values set to "0" or not displayed, for example.

[0045] When the experiment is carried out, the information processing apparatus 1 can show the combinations of the conditions that have been experimented on by drawing a line that successively connects the points of the arc-shaped bars corresponding to the conditions implemented from the center of the concentric circles. FIG. 2 shows an example of a concentric circle graph and a table after conducting experiments in seven combinations. In this example, it can be understood that experiments have been focused on the combinations of experimental conditions where the value of factor A is "2".

[0046] In addition, the information processing apparatus 1 can display the experimental results on the concentric circle graph. FIG. 5 shows an example of the case where the experimental results are displayed together with the concentric circle graph and the table. In this example, the information processing apparatus 1 displays small circles representing the experimental results at the positions of the intersections between the outermost factor C circle and the seven straight lines indicating the combinations of the conditions that have been experimented on. Each small circle of the experimental results is color-coded according to the experimental results (however, in FIG. 5, the color-coding is expressed by hatching). The experimental results are given as numerical values obtained by measuring characteristic values such as the etching rate or film thickness of the substrate on which the substrate processing has been performed, for example. The information processing apparatus 1 classifies these numerical values into three levels of excellent, good, and acceptable by comparing them with appropriate threshold values, and overlays small circles of the color corresponding to the classification results on the concentric circle graph as the experimental results. However, the information processing apparatus 1 may display the numerical values obtained as the experimental results, for example, inside the small circles or in the vicinity of the small circles, or may display the experimental results by other methods.

[0047] In the state where the information processing apparatus 1 according to the present embodiment displays a screen representing the combination of the experimental conditions shown in FIG. 2 or FIG. 5 etc. as a concentric circle graph, when receiving a display instruction of an experiment candidate from the user by an operation on a menu or an icon etc. not shown, the information processing apparatus 1 superimposes and displays the experiment candidate on the concentric circle graph. FIG. 6 shows an example of a display of an experiment candidate. The information processing apparatus 1 displays a line indicating a combination of untested conditions together with a line indicating a combination of tested conditions in a color different from the line indicating the combination of tested conditions (in FIG. 6, it is expressed by making it a dashed-dotted line to distinguish colors) and superimposes it on the concentric circle graph. In the case of this example, there are a total of 27 combinations of factors A, B, and C, and 7 of them are tested. Therefore, lines corresponding to 20 combinations of untested conditions are superimposed and displayed on the concentric circle graph.

[0048] Although not shown in FIG. 6, the information processing apparatus 1 may calculate the priorities for a plurality of experiment candidates and display the lines of the plurality of experiment candidates with color-coding according to the priorities. For example, the information processing apparatus 1 can display the line of an experiment candidate with a high priority as a thick line and the line of an experiment candidate with a low priority as a thin line. The priorities of the experiment candidates may be color-coded in multiple levels instead of two levels of high and low.

[0049] Also, in FIG. 6, the information processing apparatus 1 represents the combination of experimental conditions by a line, but it is not limited to this. For example, the combination of experimental conditions may be represented by a surface (area) instead of a line. The information processing apparatus 1 may represent a combination of tested conditions or a combination of untested conditions etc. by, for example, superimposing a fan-shaped area surrounding the above-mentioned one or more lines indicating the combination of experimental conditions on the concentric circle graph in a predetermined color. Also, the information processing apparatus 1 may represent the combination of experimental conditions by combining lines and surfaces, for example, representing the combination of tested conditions by an area and representing the combination of untested conditions by a line.

[0050] Furthermore, the information processing device 1 displays detailed information about the experimental conditions corresponding to a line in a pop-up window, for example, when the user moves the mouse cursor over a line of a candidate experiment by operating the mouse on the operation unit 15. In the example shown in Figure 6, the information processing device 1 displays a callout-shaped area near the mouse cursor on the line of the candidate experiment, and displays the information "A: 1, B: 3, C: 1" within this area. This display indicates that the conditions for the candidate experiment are that the value of factor A is 1, the value of factor B is 3, and the value of factor C is 1.

[0051] When the information processing device 1 displays experimental candidates, it highlights the line of one of the experimental candidates when the user selects it, for example, by operating the mouse on the operation unit 15. Figure 7 shows an example of the display when one experimental candidate is selected. In the example shown in Figure 7, the experimental candidate whose detailed information was displayed via a pop-up in Figure 6 is highlighted according to the user's selection, and this is represented by displaying the line corresponding to this experimental candidate with a thick line. Note that the highlighting method is not limited to displaying with a thick line; various methods such as displaying with a different color or flashing can be used.

[0052] Furthermore, the information processing device 1 calculates numerical values ​​such as coverage and orthogonality, assuming that the substrate processing experiment by the substrate processing device 3 was carried out under the conditions of the experimental candidate selected by the user. The information processing device 1 displays the calculated numerical values ​​such as coverage and orthogonality in a table provided below the concentric circle graph. At this time, the information processing device 1 may highlight in the table the numerical values ​​that change as a result of conducting the experiment under the conditions of the selected experimental candidate. In the example shown in Figure 7, the numerical values ​​for which the coverage has increased are highlighted by displaying them with a thick line. Note that the method of highlighting is not limited to displaying with a thick line; various methods such as displaying with a different color or flashing can be used.

[0053] Furthermore, the information processing device 1 according to this embodiment can select one potentially optimal experimental candidate from among multiple experimental candidates and present it to the user. As shown in Figures 6 and 7, when displaying experimental candidates, the information processing device 1 displays a button (or icon, etc.) labeled "Random Selection". In the example shown in Figures 6 and 7, the "Random Selection" button is displayed between the concentric circle graphs and the table arranged vertically. When the user performs an operation such as clicking or touching the "Random Selection" button, the information processing device 1 selects and displays one experimental candidate from among multiple experimental candidates. The method of displaying the experimental candidate selected by the information processing device 1 is the same as when the user selects an experimental candidate as shown in Figure 7.

[0054] In this embodiment, the information processing device 1 selects the optimal experimental candidate to be conducted next from among a plurality of experimental candidates, for example, using a Bayesian optimization method. Since the Bayesian optimization method and other methods for selecting the optimal experimental candidate are existing technologies, a detailed explanation is omitted in this embodiment. Furthermore, the method for selecting experimental candidates is not limited to Bayesian optimization; any other method may be employed. For example, the information processing device 1 may select the experimental candidate that provides the greatest increase in coverage.

[0055] The information processing device 1 also predicts the experimental results obtained when substrate processing is performed under experimental conditions corresponding to the selected experimental candidate, and may display the predicted values ​​of the experimental results superimposed on a concentric circle graph using a display method similar to that shown in Figure 5 (illustration omitted). In this case, the information processing device 1 stores a learning model generated in advance by machine learning in the storage unit 12, and uses this learning model to predict the experimental results. The learning model can be configured to accept experimental conditions as input and output predicted values ​​of the experimental results, and can be generated, for example, by machine learning using learning data that associates previously collected experimental conditions and experimental results. The information processing device 1 inputs the experimental conditions corresponding to the selected experimental candidate into the learning model, obtains the predicted values ​​of the experimental results output by the learning model, and displays the experimental results superimposed on a concentric circle graph based on the obtained predicted values.

[0056] Furthermore, after the user has selected an experimental candidate themselves, or after using the "Automatic Selection" button to have the information processing device 1 select an experimental candidate, the user can discard the selection of the experimental candidate (return to an unselected state) by re-selecting the thick line of the selected experimental candidate in the display state shown in Figure 7. When this user discards the selection, the information processing device 1 stops highlighting the line of the selected experimental candidate in the concentric circle graph and returns the value in the table to the value when the experiment for the selected experimental candidate is not performed.

[0057] Furthermore, the user can select multiple experimental candidates by first selecting an experimental candidate themselves, or by using the "Automatic Selection" button to have the information processing device 1 select an experimental candidate, and then selecting yet another experimental candidate. Additional experimental candidates can be selected by the user by selecting lines on a concentric circle graph, or by using the "Automatic Selection" button. Each time an additional experimental condition is selected, the information processing device 1 calculates numerical values ​​such as the coverage rate if an experiment based on the multiple selected experimental candidates were to be conducted, and updates the table display based on the calculated values.

[0058] After selecting one or more experimental candidates, the user can instruct the information processing device 1 to perform substrate processing under experimental conditions corresponding to the selected experimental candidates in the concentric circle graph by, for example, selecting a menu item or icon (not shown). When the information processing device 1 receives an instruction from the user to perform substrate processing, it transmits information such as a substrate processing recipe with the experimental conditions of the selected experimental candidates to the substrate processing device 3, and instructs the device to perform substrate processing based on the transmitted information, thereby performing substrate processing under experimental conditions corresponding to the selected experimental candidates. The information processing device 1 acquires information related to experimental results, such as sensor measurement values, from the substrate processing device 3 that performed the substrate processing, and stores it in the experimental information storage unit 12b.

[0059] Figure 8 is a flowchart showing an example of the procedure for visualizing experimental information performed by the information processing device 1 according to this embodiment. The experiment control unit 11a of the processing unit 11 of the information processing device 1 according to this embodiment acquires information stored in the experiment information storage unit 12b, i.e., information such as combinations of experimental conditions and experimental results that have been experimented (step S1). Based on the information acquired in step S1, the graph generation unit 11b of the processing unit 11 generates a graph of concentric circles showing combinations of factors that have been experimented, and the score calculation unit 11c of the processing unit 11 calculates scores such as coverage rate and orthogonality related to the experiments that have been experimented and generates a table that notifies these (step S2). The display processing unit 11f of the processing unit 11 displays a screen including the graph of concentric circles and the score table generated in step S2 on the display unit 14 (step S3). Based on the user's operation on the operation unit 15, the processing unit 11 determines whether or not to visualize the experimental candidates, for example, based on whether or not a menu item for visualizing experimental candidates has been selected (step S4). If no operation to visualize the experimental candidates has been performed (S4: NO), the processing unit 11 returns to step S3 and continues the screen display.

[0060] If an operation to visualize experimental candidates is performed (S4: YES), the display processing unit 11f displays combinations of factors that have not been experimented with as experimental candidates on the concentric circle graph displayed in step S3 (step S5). The processing unit 11 determines whether or not an operation has been performed on the "Automatic" button displayed on the screen along with the experimental candidates (step S6). If no operation has been performed on the "Automatic" button (S6: NO), the processing unit 11 determines whether or not an operation to select one of the multiple experimental candidates displayed on the screen has been performed (step S7). If no operation to select an experimental candidate has been performed (S7: NO), the processing unit 11 returns to step S5 and continues to display the experimental candidates.

[0061] If the "Automatic" button is pressed in step S6 (S6: YES), the experimental candidate calculation unit 11d of the processing unit 11 calculates the optimal experimental candidate for the next experiment from among multiple experimental candidates based on a method such as Bayesian optimization (step S8), and proceeds to step S9. If the operation to select an experimental candidate is performed in step S7 (S7: YES), the processing unit 11 proceeds to step S9. The display processing unit 11f updates the screen by highlighting the experimental candidate selected in step S7 or the experimental candidate calculated in step S8 on a concentric circle graph and reflecting the coverage rate, etc., if the experiment for this experimental candidate were to be conducted in a table (step S9).

[0062] The processing unit 11 determines whether to conduct an experiment under the conditions of the selected or calculated experimental candidate, based on whether a menu item such as determining experimental conditions or conducting an experiment has been selected (step S10). If the experiment is not yet to be conducted (S10: NO), the processing unit 11 returns to step S5 and continues the screen display. If the experiment is to be conducted (S10: YES), the experiment control unit 11a transmits the experimental conditions related to the selected or calculated experimental candidate to the substrate processing device 3 (step S11), has the substrate processing device 3 perform the substrate processing under the transmitted experimental conditions, and then terminates the process.

[0063] <Other Display Examples> Figure 9 is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to this embodiment. The example shown in Figure 9 is a graph of concentric circles when there are four factors related to the experiment. When the number of experimental factors is four, the information processing device 1 generates a graph of concentric circles with four circles of different sizes arranged concentrically. In this example, the number of levels for each factor is three. The information processing device 1 divides the second circle from the center into three, divides the third circle into 3 x 3 = 9, and divides the fourth circle into 3 x 3 x 3 = 27, thereby creating multiple arc-shaped bars.

[0064] Figure 10 is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to this embodiment. The example shown in Figure 10 is a graph of concentric circles when there are five factors related to the experiment. When the number of experimental factors is five, the information processing device 1 generates a graph of concentric circles with five circles of different sizes arranged concentrically. In this example, the number of levels for each factor is three. The information processing device 1 divides the second circle from the center into three, divides the third circle into 3 x 3 = 9, divides the fourth circle into 3 x 3 x 3 = 27, and divides the fifth circle into 3 x 3 x 3 x 3 = 81 to create multiple arc-shaped bars.

[0065] Thus, with the experimental information visualization method according to this embodiment, even if the number of experimental factors increases, the user can visually recognize them, and the user can intuitively understand the progress of the experiment.

[0066] Furthermore, the information processing device 1 may arrange the multiple circles, which are arranged concentrically, not at equal intervals, but rather so that the spacing between them widens as you move outwards. This is expected to reduce the visibility of arc-shaped bars and straight lines connecting the circles, as the number of divisions of the circles increases towards the outside.

[0067] <Modification> (Modification 1) Figure 11 is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to Modification 1. In the example shown in Figure 11, instead of a concentric circle graph made up of multiple arc-shaped bars, the information processing device 1 displays a stepped graph made up of multiple straight lines. The experimental information shown in the stepped graph in Figure 11 (which combinations of conditions have been experimented with) is the same as the experimental information shown in the concentric circle graph shown in the upper part of Figure 2. In other words, the stepped graph shown in Figure 11 can be considered as multiple arc-shaped bars included in the concentric circle graph shown in Figure 2 extended in a straight line and arranged in a row.

[0068] In this example, there are three factors involved in the experiment: A, B, and C, and each factor has three levels. In Modification 1, the information processing device 1 displays one linear bar related to the first factor A in the uppermost row, extending horizontally; three linear bars related to the second factor B are displayed in the second row, spaced equally apart and extending horizontally; and 3 x 3 = 9 linear bars related to the third factor C are displayed in the third row (bottom row) and extending horizontally. The number of linear bars displayed in each row is determined according to the number of combinations of levels of one or more factors displayed in the rows above. For each linear bar, if the corresponding factor has a continuously changing value, the information processing device 1 may display it with a gradient, gradually changing the color of the bar by associating one end with the minimum value and the other end with the maximum value.

[0069] The information processing device 1 also displays a number of black dots corresponding to the number of levels for each factor, superimposed on each linear bar. These black dots represent values ​​that can be set as experimental conditions for each factor. In this example, since each factor has three levels, three black dots are displayed superimposed on each linear bar. The three black dots on each bar correspond, for example, to the minimum, maximum, and median values ​​of each factor. The information processing device 1 provides the user with information indicating which combination of experimental conditions has been tested by displaying a straight line connecting the black dots that correspond to the experimental conditions for each factor.

[0070] In this example, the minimum, maximum, and median values ​​of the factor that evenly divides the bar are used as values ​​corresponding to the black dots, but this is not limited to these values, and the values ​​corresponding to the black dots may be any values ​​that allow the experiment to be conducted. Also, in this example, the information processing device 1 displays black dots superimposed on a straight bar, but this is not limited to this, and it is not necessary to display black dots, as in the graph of Figure 2. Furthermore, the information processing device 1 may display not only black dots, but also, for example, white dots or dots of an appropriate color, or various shapes such as "X", triangles, rhombuses, or stars instead of dots.

[0071] (Modification 2) Figure 12 is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to Modification 2. The information processing device 1 according to Modification 2 displays combinations of experimental conditions as a tree diagram. The example shown in Figure 12 is a tree diagram when there are four experimental factors A, B, C, and D, and each factor has three levels. The information processing device 1 generates the illustrated tree diagram by creating branches from the central root node in the order of factors A, B, C, and D according to the number of levels. The branching points and terminal nodes of the tree diagram are associated with the values ​​of each factor. The information processing device 1 connects multiple paths from the root node to the terminal leaf nodes with thin lines and highlights paths corresponding to combinations of conditions that have been experimented with using thick lines, thereby providing the user with information indicating which combinations of conditions have been experimented with.

[0072] The tree diagram relating to the modified example 2 shown in Figure 12 corresponds to, for example, the display method in which the arc-shaped bars are omitted in the concentric circle graph shown in Figure 9, and the combination of experimental factors and the number of levels are represented by the branching and nodes of the tree diagram.

[0073] (Modification 3) Figure 13 is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to Modification 3. The information processing device 1 according to Modification 3 displays experimental conditions by using a combination of multiple concentric circle graphs. This example shows the display when there are five experimental factors and each factor has three levels. The information processing device 1 displays the combination of the first and second factors in a large concentric circle graph in the center, and displays the combination of the third to fifth factors in multiple small concentric circle graphs arranged around it.

[0074] (Modification 4) Figure 14 is a schematic diagram showing another example of the visualization of experimental information by the information processing system according to Modification 4. The information processing device 1 according to Modification 4 displays experimental conditions by combining the linear bars of Modification 1 and the graph of multiple concentric circles of Modification 3. This example shows the display when there are five experimental factors and each factor has three levels. The information processing device 1 displays the combination of the first and second factors in a two-tiered stepped graph using linear bars, and displays the combination of the third to fifth factors in a graph of multiple concentric circles located below the stepped graph. The example shown in Figure 14 corresponds to the graph of multiple concentric circles shown in Figure 13, in which the central large concentric circle graph is replaced with a two-tiered stepped graph.

[0075] The information processing system may visualize experimental conditions by appropriately combining various graph shapes as illustrated in the embodiments and their modifications. Furthermore, the shape and arrangement of graphs displayed by the information processing system are not limited to those illustrated in the embodiments and their modifications, and various shapes and arrangements may be adopted. For example, the information processing system may use polygonal graphs instead of circular graphs for concentric circle graphs. Also, for example, the information processing system may use various linear bars such as curves, bent lines, or wavy lines instead of straight lines for stepped graphs.

[0076] (Modification 5) The experiments handled by the information processing system according to this embodiment may include not only actual experiments in which the substrate processing device 3 actually performs substrate processing, but also virtual experiments such as simulations performed on a computer such as the information processing device 1. The information processing system according to Modification 5 displays the combinations of factors for which actual experiments were performed and the combinations of factors for which virtual experiments were performed separately in a graph of concentric circles, etc. For example, the information processing device 1 according to Modification 5 distinguishes between actual experiments and virtual experiments by using different colors for the lines connecting the combinations of factors that have been experimented on for actual experiments and virtual experiments. Furthermore, the information processing device 1 according to Modification 5 may display numerical values ​​such as coverage rates in tables displayed together with the graph, for example, numerical values ​​for actual experiments only, numerical values ​​for virtual experiments only, and numerical values ​​that combine actual and virtual experiments.

[0077] <Summary> In this embodiment of the information processing system, the information processing device 1 displays multiple bars, such as arc-shaped or linear bars, representing the possible values ​​for each of the multiple factors in the experimental design, and displays lines connecting the combinations of experimentally tested factor values ​​superimposed on the multiple bars. As a result, the information processing system in this embodiment is expected to provide information on experimentally tested combinations of multiple factors related to the experimental design in a manner that is easy for the user to recognize, and is expected to support the user in formulating the experimental design.

[0078] Furthermore, in the information processing system according to this embodiment, the information processing device 1 displays a graph in which circular or arc-shaped bars are used, with bars of different sizes arranged concentrically for each factor. The information processing system may display each bar using color coding such as a gradient according to the magnitude of the factor values. The information processing device 1 may also display the bars corresponding to values ​​for which experiments cannot be conducted or do not need to be conducted in a predetermined color (for example, an inconspicuous color such as light gray). As a result, the information processing system according to this embodiment is expected to provide information on experimentally tested combinations in a manner that is easier for the user to understand.

[0079] Furthermore, in the information processing system according to this embodiment, the information processing device 1 displays the experimental results for the experimentally tested combinations of factors. As a result, the information processing system according to this embodiment is expected to provide the user with a more easily recognizable correspondence between the experimentally tested combinations of factors and their experimental results.

[0080] Furthermore, in the information processing system according to this embodiment, the information processing device 1 displays a table showing scores such as coverage or orthogonality related to the experiment, along with a graph showing combinations of experimentally tested factors using multiple bars. As a result, the information processing system according to this embodiment is expected to provide the user with a score related to the entire experiment, which is difficult to read from the graph alone.

[0081] Furthermore, in the information processing system according to this embodiment, the information processing device 1 displays lines connecting combinations of factors that are candidates for experimentation superimposed on multiple bars. The information processing device 1 may also accept the selection of one or more experimental candidates from among multiple experimental candidates and update the score displayed in the table according to the accepted selection. As a result, the information processing system according to this embodiment is expected to support the user in formulating an experimental plan by displaying experimental candidates for combinations of unexperimented conditions on a graph using multiple bars.

[0082] Furthermore, in the information processing system according to this embodiment, the information processing device 1 displays a predetermined button or icon, such as an "automatic" button, along with a graph using multiple bars. When the device receives an operation on this button or icon, it calculates and displays one or more experimental candidates that it recommends conducting from among multiple experimental candidates. The information processing device 1 can calculate the most suitable experimental candidate for implementation by performing a process such as Bayesian optimization. As a result, the information processing system according to this embodiment can present the user with an experimental candidate that is suitable for implementation from among multiple experimental candidates, and is expected to support the user in formulating an experimental plan.

[0083] Furthermore, in the information processing system according to this embodiment, the information processing device 1 displays predicted values ​​of experimental results for combinations of factors that are candidates for experiments. The information processing device 1 can predict experimental results for experimental conditions using, for example, a learning model generated in advance by machine learning. As a result, the information processing system according to this embodiment can predict and present experimental results for experiments that have not yet been conducted to the user, and is expected to support the user in formulating experimental plans.

[0084] Furthermore, in the information processing system according to this embodiment, the experiment includes both a real experiment in which substrate processing is actually performed using the substrate processing device 3 and a virtual experiment using computer simulation, etc., and the information processing device 1 displays the combination of factors related to the real experiment and the combination of factors related to the virtual experiment separately. As a result, the information processing system according to this embodiment can handle both real and virtual experiments, and can present information related to the real experiment and information related to the virtual experiment separately to the user, and is expected to support the user in formulating an experiment plan.

[0085] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of this disclosure is indicated by the claims, not in the sense described above, and all modifications within the meaning and scope equivalent to the claims are intended.

[0086] The matters described in each embodiment can be combined with each other. Furthermore, the independent and dependent claims described in the claims can be combined with each other in any combination, regardless of the form of reference. In addition, the claims use a form in which claims referencing two or more other claims (multi-claim form), but are not limited to this. A form in which multi-claims referencing at least one multi-claim (multi-multi-claim) may also be used.

[0087] 1 Information processing device (computer) 3 Board processing device 11 Processing unit 11a Experiment control unit 11b Graph generation unit 11c Score calculation unit 11d Experiment candidate calculation unit 11e Experiment result prediction unit 11f Display processing unit 12 Storage unit 12a Program (computer program) 12b Experiment information storage unit 13 Communication unit 14 Display unit 15 Operation unit 99 Recording medium N Network

Claims

1. A computer program that causes a computer to perform the following process: display multiple bars representing the possible values ​​of each factor in an experimental design, and superimpose lines connecting the combinations of experimentally tested factor values ​​onto the multiple bars.

2. The computer program according to claim 1, wherein the bars are circular or arc-shaped, and bars of different sizes for each factor are arranged concentrically.

3. The computer program according to claim 1 or claim 2, which displays the bars in different colors according to the magnitude of their values.

4. The computer program according to claim 3, which displays the portion of the bar that cannot be experimentally measured in a predetermined color.

5. A computer program according to claim 1 or 2, which displays experimental results for experimentally tested combinations of factors.

6. A computer program according to claim 1 or 2, which displays a table showing scores related to an experiment, along with the aforementioned bars.

7. A computer program according to claim 1 or claim 2, which displays lines connecting candidate combinations of factors superimposed on the plurality of bars.

8. The computer program according to claim 7, which displays a table showing scores related to an experiment along with the bar, accepts the selection of one or more experimental candidates from among multiple experimental candidates, and updates the scores in the table according to the accepted selection.

9. A computer program according to claim 7, which displays a predetermined button or icon along with the bar, and when an operation is performed on the button or icon, calculates one or more experimental candidates to recommend from among a plurality of experimental candidates, and displays the calculated experimental candidates.

10. The computer program according to claim 7, which displays predicted values ​​of experimental results for the combination of factors that are candidates for the experiment.

11. The computer program according to claim 7, which causes a substrate processing apparatus to execute a substrate processing apparatus under conditions corresponding to one or more selected experimental candidates.

12. The computer program according to claim 1 or claim 2, wherein the experiment includes a real experiment and a virtual experiment, and distinguishes between the combination of factors related to the real experiment and the combination of factors related to the virtual experiment.

13. An information processing method in which an information processing device displays multiple bars in a row, each representing a possible value for multiple factors of an experimental design, and superimposes lines connecting combinations of experimentally tested factor values ​​onto the multiple bars.

14. An information processing device comprising a processing unit, wherein the processing unit displays a plurality of bars in a row, each representing a possible value for a plurality of factors in an experimental design, and displays lines connecting combinations of experimentally tested factor values ​​superimposed on the plurality of bars.

15. A computer program that displays a tree diagram connecting the possible value combinations of each factor in an experimental design, and instructs the computer to perform a process of highlighting the lines connecting the value combinations of the factors that have already been experimented on in the tree diagram.

16. An information processing method in which an information processing device displays a tree diagram in which the possible combinations of values ​​for multiple factors of an experimental design are connected by lines, and the lines connecting the combinations of values ​​of the factors that have been experimented with are highlighted in the tree diagram.

17. An information processing device comprising a processing unit, wherein the processing unit displays a tree diagram in which the possible combinations of values ​​for each factor of the experimental design are connected by lines, and highlights the lines in the tree diagram that connect the combinations of values ​​of the factors that have been experimented with.

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