Method for calculating the number of data points and method for evaluating substrate processing device

Abstract

To calculate the number of pieces of equipment data required to evaluate the equipment state.SOLUTION: A method for calculating the number of data items includes a first step of obtaining a first number of process data items, which are information indicating the performance of processing performed on a substrate by a substrate processing device, the first number being two or more, a second step of performing statistical calculations on a second number of process data items, which are two or more and not more than the first number, to calculate, as a third number, the number of process data items required to determine that the first number of process data items satisfy a given condition, and a third step of determining whether the second number is equal to or greater than the third number.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a method for calculating the number of data points and a method for evaluating a substrate processing apparatus. [Background technology]

[0002] Substrate processing apparatuses that perform processing on substrates, such as semiconductor substrates commonly referred to as wafers, are known. For example, a substrate processing apparatus includes a plurality of processing units that each perform a processing operation (hereinafter also tentatively referred to as "substrate processing"). The substrate processing is performed, for example, through a plurality of steps according to a predetermined procedure commonly referred to as a recipe.

[0003] A technique for evaluating the state of a substrate processing apparatus (hereinafter tentatively referred to as "apparatus state") by measuring the processing performed in the substrate processing apparatus and analyzing time-series data based on the results is known. An example of the apparatus state is the presence or absence of an abnormality in a processing unit. An example of the evaluation is the identification of a processing unit in which an abnormality has occurred and the identification of the cause of the abnormality. Patent documents 1 to 6 are prior art documents disclosing techniques related to such evaluation. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6959879 [Patent Document 2] Patent No. 7090430 [Patent Document 3] Patent No. 7074489 [Patent Document 4] Patent No. 7074490 [Patent Document 5] Patent No. 7075771 [Patent Document 6] Patent No. 7080065 Summary of the Invention [Problem to be solved by the invention]

[0005] Generally, the evaluation requires data obtained from the equipment (hereinafter also referred to as "equipment data"), such as multiple time-series data in the above example. The reliability of the evaluation may improve if there is a large amount of equipment data. On the other hand, excessive reliability is not necessary.

[0006] For example, the amount of equipment data that needs to be introduced into the evaluation in order to determine the significant difference required to determine whether or not an abnormality exists has relied on the experience of the engineer performing the evaluation, such as the operator of the substrate processing apparatus.

[0007] The present disclosure has been made in view of the above-mentioned problems, and aims to provide a method for calculating the number of pieces of device data necessary to evaluate the device state. Another aim is to provide a method for performing the evaluation. [Means for solving the problem]

[0008] The method for calculating the number of data items according to the first aspect includes a first step of obtaining a first number of process data items, which are information indicating the performance of processing performed on a substrate by a substrate processing apparatus, of two or more; a second step of performing statistical calculations on a second number of process data items, which are two or more and less than the first number, to calculate a third number of process data items required to determine that the first number of process data items satisfy a given condition; and a third step of determining whether the second number is greater than or equal to the third number.

[0009] The method for calculating the number of data items according to the second aspect is the method for calculating the number of data items according to the first aspect, and after a negative judgment result is obtained in the third step, the second step and the third step are additionally performed by increasing the second number with the first number as an upper limit.

[0010] The method for calculating the number of data according to the third aspect is the method for calculating the number of data according to the second aspect, wherein the second step includes a first substep of determining the third number using the probability of a type I error, the probability of a type II error, and an effect size corresponding to the given condition.

[0011] A method for calculating the number of data items according to a fourth aspect is the method for calculating the number of data items according to the third aspect, wherein the second step is executed prior to the first sub-step and further includes a second sub-step of determining whether the first number of process data has normality, and the first sub-step and the third step are executed only if the determination result of the second sub-step is positive.

[0012] A method for evaluating a substrate processing apparatus according to a fifth aspect is a method for evaluating a state of the substrate processing apparatus by performing statistical calculations using a fourth number of apparatus data, the fourth number being equal to or greater than the third number, obtained by the method for calculating the number of data according to any one of the first to fourth aspects. The fourth number is equal to or less than the second number of apparatus data passed through the second step until a positive determination result is obtained in the third step. The apparatus data is information indicating parameters used when the substrate processing apparatus performs the processing.

[0013] A method for evaluating a substrate processing apparatus according to a sixth aspect is a method for evaluating a substrate processing apparatus according to the fifth aspect, wherein the fourth number of pieces of apparatus data indicate the parameters when the processing was performed that yielded the fourth number of pieces of process data out of the second number of pieces of process data that were provided to the second step when a positive judgment result was obtained in the third step. [Effects of the Invention]

[0014] The method for calculating the number of pieces of data according to the present disclosure contributes to automatically determining the number of pieces of equipment data to be introduced into the evaluation process without relying on the experience of the operator.

[0015] The method for evaluating a substrate processing apparatus according to the present disclosure contributes to reducing the amount of statistical calculation. [Brief explanation of the drawings]

[0016] [Figure 1] 10 is a flowchart illustrating an example of a method for calculating the number of data items according to the present disclosure. [Figure 2] 10 is a graph showing an etching amount. [Figure 3] 3 is a graph showing the results shown in FIG. 2 in the form of a frequency distribution. [Figure 4] FIG. 1 is a block diagram illustrating a method for evaluating the device state. [Figure 5] FIG. 1 is a plan view schematically showing an example of the configuration of a substrate processing apparatus. [Figure 6] FIG. 1 is a block diagram illustrating a configuration of a computer. [Figure 7] FIG. 1 is a block diagram illustrating a schematic configuration of a data processing device. DETAILED DESCRIPTION OF THE INVENTION

[0017] <1. Determining the sample size of equipment data using process data> <1-1. Explanation of process data> In this disclosure, the term "process data" is introduced. Process data is information that indicates the performance of a substrate processing. For example, when the substrate processing is etching of a wafer, examples of the process data include the etching amount and the etching profile (aspect ratio).

[0018] <1-2. Relationship between process data and equipment data> The present disclosure presents a technique for using process data to set the number of pieces of equipment data required to evaluate the equipment state, that is, the sample size required by statistics for the equipment data used in the evaluation.

[0019] Generally, substrate processing depends on given parameters. For example, when the substrate processing is etching of a wafer, examples of parameters for performing the etching include the amount of etchant supplied, the supply time, and the rotation speed and rotation time of the wafer when the etchant is supplied. The recipe described above can be said to be target values ​​or a set of target values ​​for these parameters. Equipment data can be said to be information indicating the parameters in the process executed based on the recipe.

[0020] Therefore, it can be estimated that the minimum number of process data items at which it is determined that the process data has converged in probability is the minimum sample size required in the evaluation using the equipment data.

[0021] 2. Statistical calculations using process data 1 is a flowchart showing an example of a method for calculating the number of data items according to the present disclosure. The sample-size amount of device data obtained at the end of the flowchart is input to and subjected to the above-mentioned evaluation step (hereinafter tentatively referred to as the "evaluation step").

[0022] The flowchart includes steps S101, S102, S103, S201, S202, S203, S204, S205, S206, S301, S302, and S303.

[0023] <2-1. Preparation for statistical calculations> Step S101 is a process of inputting numerical values ​​to be supplied to a program (hereinafter also tentatively referred to as a "statistical program") that performs statistical calculations used in the calculation method. Specifically, in step S101, the significance level and detection power for the statistical calculations are input to the statistical program. The inputs may be input by an operator to a computing device (described later) that executes the statistical program, or may be stored as given constants in a calculation table (described later) that is used for the statistical calculations. In the latter case, step S101 is omitted.

[0024] As is well known in statistics, significance level and power are important factors in statistical calculations. The significance level indicates the probability of a type I error, and power indicates the value obtained by subtracting the probability of a type II error from the value 1.

[0025] Step S102 is a process of inputting given conditions to be used in the statistical calculations used in the calculation method. Specifically, in step S102, the given conditions are input into a statistical program.

[0026] The given condition may be, for example, the processing performance required for the substrate processing apparatus. For example, the given condition may be an allowable range for the performance indicated by the process data. A specific example of this is an allowable range for the deviation of the etching amount from a target value.

[0027] Step S103 is a step of acquiring process data. Two or more pieces of process data are required for statistical calculations on the process data. Step S103 can be said to be a first step of acquiring a first number of process data, which is two or more pieces, prior to statistical calculations.

[0028] Process data obtained for processes performed based on the same recipe is acquired in the first step because process data for processes performed based on different recipes cannot be said to be related to equipment data for processes performed based on the same recipe and is not suitable for statistical calculations to determine the sample size of the equipment data.

[0029] The order of execution of steps S101, S102, and S103 does not matter, and these steps can be collectively considered as step S1, which is a preparation step for statistical calculation.

[0030] <2-2. Distribution convergence of process data> After steps S101, S102, and S103 are executed, step S201 is executed, in which process data is input.

[0031] Step S201 is a step of sequentially inputting the process data acquired in step S103 into the statistical program. For example, the input is realized by an operator operating a computing device (described later) on which the statistical program is executed.

[0032] Alternatively, step S201 can be implemented by storing the process data acquired in step S103 in a storage device and the statistical program itself sequentially reading the process data from the storage device. In this case, step S302 (described later) for prompting input of new process data can be omitted.

[0033] When step S201 is executed for the first time, two pieces of process data are input to the statistical program. When step S201 is executed again via execution of step S206, as described below, one additional piece of process data is input to the statistical program.

[0034] Before determining the sample size of the equipment data by the probability convergence of the process data, it is confirmed whether the process data satisfies the assumptions sufficient for determining the sample size. In the following, if it is confirmed that the variability of the process data converges to a normal distribution, the probability convergence of the process data is calculated using the significance level and power input in step S101.

[0035] After step S201 is executed, step S202 is executed. In step S202, a statistical calculation is performed using, for example, the Anderson-Darling test. The statistical calculation uses a statistical calculation table DB1 for determining distribution convergence. For example, in the statistical calculation, a normality test is performed on the process data input in step S201.

[0036] For example, when a normality test using the Anderson-Darling test is used, the null hypothesis is presented as "the process data follows a normal distribution." In this case, in step S202, for example, if the probability p of a type I error for the process data exceeds 0.05, it is determined that the process data has converged to a normal distribution. At this time, the mean value and standard deviation of the process data are calculated.

[0037] The probability p used in the Anderson-Darling test does not have to match the significance level entered in step S101.

[0038] After step S202 is executed, step S203 is executed, in which it is determined whether or not the distribution of the process data has converged as a result of execution of step S202.

[0039] If the determination result in step S203 is affirmative, that is, if the process data distribution has converged as a result of execution of step S202, step S204 is executed.

[0040] Figure 2 is a graph showing the etching amount when semiconductor substrate wafers W1, W2, W3, W4, W5, W6, W7, W8, W9, and W10 are etched based on the same recipe. The horizontal axis shows the symbol for each wafer, and the vertical axis shows the etching amount.

[0041] In the graph, multiple circles on the same wafer represent the etching amount at four different locations on the same wafer using the same etching recipe. Crosses represent a representative, e.g., average, etching amount for each wafer. A line connects the crosses across the different wafers. The line in Figure 2 indicates that the etching process that produced the results shown in Figure 2 exhibited little wafer dependency.

[0042] Figure 3 is a graph showing the frequency distribution of the results shown in Figure 2. The total frequency is 40, which is the product of the number of wafers (10) and the number of locations (4) where the etching amount was measured per wafer.

[0043] The probability of the first error for this result is 0.388, which is greater than 0.05. Therefore, this example shows a case where the result is judged to converge to a normal distribution. The graph also shows the normal distribution curve to which the result converges. In this example, the mean of the normal distribution is 3.47 nm and the standard deviation is 0.008 nm.

[0044] If the determination result in step S203 is negative, that is, if the process data distribution has not converged as a result of execution of step S202, step S206 is executed.

[0045] <2-3. Probability convergence of process data> In step S204, the number of pieces of equipment data required for the evaluation process is calculated (abbreviated as "calculation of required data number" in the figure). For reasons described later, the sample size of the process data determined in this disclosure is used as the sample size of the equipment data used in statistical processing of the equipment data.

[0046] In step S204, the sample size of the process data is determined using the significance level and power input in step S101, the given conditions input in step S102, and the mean value and standard deviation determined in step S202.

[0047] For example, suppose a given condition is that the allowable deviation of the etching amount from the target value is 1%. When the process data converges to a normal distribution, the mean value of the normal distribution can be used as the target value. In the above example, in step S203, the mean value of the etching amount is 3.47 nm, and the range is selected to be 0.0347 nm.

[0048] For example, by adopting this range as the statistical effect size, the sample size of the sample population required for testing to determine whether the first number of process data as the population satisfies a given condition is calculated. As is well known, once the significance level, power, and effect size are determined, the sample size can be calculated. In this calculation, the standard deviation calculated in step S203, which is 0.008 nm in the above example, is used.

[0049] The sample size calculated in step S204 is based on the process data used in the calculations in steps S202 and S204, but it is unclear whether the number of process data items is equal to or greater than the sample size, because, as described above, the number of process data items is ignored in the calculations of the mean value and standard deviation calculated in step S203.

[0050] After step S204 is executed, step S205 is executed. In step S205, it is determined whether the process data that has already been input is equal to or greater than the sample size calculated in step S204. In the figure, this determination is abbreviated as "Is the input process data equal to or greater than the required number of data?"

[0051] Hereinafter, the number of process data used in the statistical calculations in steps S202 and S204 is referred to as the second number, and the sample size obtained by the statistical calculations in step S204 is referred to as the third number. Steps S202 and S204 can be considered as a second step of performing statistical calculations on the second number of process data to obtain the number of process data necessary to determine that the first number of process data satisfies a given condition, as the third number. Step S205 can be considered as a third step of determining whether the third number is equal to or less than the second number.

[0052] <2-4. Additional input of process data> From the above viewpoint, the third number may be greater than the second number, and in this case, the validity of the third number itself may be doubted because the third number itself was calculated using the second number, which is smaller than the third number. Therefore, in this case, the determination in step S205 is negative, and step S206 is executed.

[0053] In step S206, it is determined whether the number of process data input in step S201 is equal to or greater than the number (first number) of process data acquired in step S103. Using the above-mentioned terminology, it is determined whether the second number is equal to or greater than the first number.

[0054] If the second number is less than the first number, the determination result in step S206 is negative. In this case, step S201 is executed again, and the process data acquired in step S103 that has not been input in the previous step S201 is input.

[0055] Even if a negative determination result is obtained in step S203, there is a possibility that distribution convergence can be achieved by inputting new process data, and therefore step S201 is executed again in this case as well.

[0056] If a negative determination result is obtained in step S206 or step S203, step S302 is executed before step S201 is newly executed. In step S302, a prompt to input new process data to be added is displayed (abbreviated as "addition display" in the figure).

[0057] <2-5. Process data sufficiency / insufficiency> If the determination result in step S205 is affirmative, step S301 is executed.

[0058] In step S301, a message is displayed indicating that no further input of process data is required, i.e., that the input process data satisfies the number required to execute the flowchart (abbreviated as "satisfied display" in the figure). This means that the operator does not need to execute step S201 again, and the flowchart ends.

[0059] If step S201 is performed by a statistical program, step S301 may be omitted. Alternatively, in step S301, a third number may be displayed as the sample size.

[0060] If the first number of process data items have been input in step S201, the determination in step S206 is affirmative. In this case, step S201 cannot be executed again to input new process data. Therefore, in this case, step S303 is executed, and a message is displayed indicating that the acquired process data items are insufficient for executing the flowchart (abbreviated as "insufficient display" in the figure). As a result, the flowchart ends without the operator having to execute step S201 again.

[0061] If step S201 is performed by a statistical program, step S303 may be omitted, or step S303 may display a message indicating that an appropriate sample size was not calculated.

[0062] <2-6. General explanation of flowcharts> The above flowchart can be said to show a method for calculating the number of data items, which includes the following first, second, and third steps.

[0063] First step: Obtain a first number of process data, which is two or more. The first step is exemplified as step S103. The process data is information indicating the performance of the substrate processing.

[0064] Second step: A third number is obtained by performing statistical calculations on a second number of process data, which is equal to or greater than two and equal to or less than the first number. The third number is the number of process data necessary to determine that the first number of process data satisfies a given condition. The second step is exemplified by steps S202 and S204.

[0065] Third step: Determine whether the second number is equal to or greater than the third number. The third step is exemplified by step S205.

[0066] The above-described flowchart includes a procedure in which, after a negative determination result is obtained in step 3, step 2 and step 3 are additionally performed by increasing the second number up to the first number, as exemplified by step S205, followed by step S201 via step S206.

[0067] The second step includes a first substep of determining a third number using the probability of a type I error, the probability of a type II error, and the effect size corresponding to a given condition. The first substep is exemplified in step S204.

[0068] The second step is executed prior to the first sub-step and further includes a second sub-step of determining whether the first number of process data are normal. Only when the determination result of the second sub-step is positive, the first sub-step and the third step are executed. The second sub-step is exemplified by step S203.

[0069] <3.Evaluation of equipment condition> 4 is a block diagram illustrating a technique employed in the evaluation process of the equipment state, for example, an evaluation method of the equipment state. The diagram illustrates an equipment data group V, a process data group P, an evaluation unit 500, a database DB3, and evaluation data Q indicating the equipment state.

[0070] The process data group P includes n pieces of process data P1, ..., Pn, where n is an integer equal to or greater than 2. The device data group V includes n pieces of device data V1, ..., Vn. The integer n corresponds to the first number.

[0071] The process data group P is divided into process data groups Pa and Pb. The equipment data group V is divided into equipment data groups Va and Vb. Introducing an integer m between 2 and n, the process data group Pa includes process data P1, ..., Pm, and the equipment data group Va includes equipment data V1, ..., Vm. The integer m corresponds to the fourth number.

[0072] The fourth number is equal to or greater than the third number because it is necessary to have more process data than is required by the method for calculating the number of data items described above.

[0073] The process data group Pb includes process data Pm+1, ..., Pn. The device data group Vb includes device data Vm+1, ..., Vn. However, when m=n, the process data group Pb and the device data group Vb do not exist.

[0074] The fourth number is equal to or less than the second number because if the number of process data pieces exceeds the number used in the above-described method for calculating the number of data pieces, there will inevitably be cases where the correspondence relationship described below cannot be obtained.

[0075] The equipment data group Va is sufficient to evaluate the equipment state for the given conditions input in step S102.

[0076] The number of process data included in the process data group Pa and the number of equipment data included in the equipment data group Va are both a fourth number, i.e., m. By introducing an integer j greater than or equal to 1 and less than or equal to m, the process data Pj and the equipment data Vj have a correspondence relationship. Specifically, the equipment data Vj indicates parameters when the substrate processing that yielded the process data Pj was performed.

[0077] However, each of the process data P1, ..., Pm is selected from the second number of process data that were used in the second step (steps S203 and S204 in the above example) until a positive determination result was obtained in the third step (step S205 in the above example), because the third number was calculated using these process data.

[0078] From these explanations, the evaluation method of the substrate processing apparatus in the present disclosure is as follows: An evaluation method for evaluating a state of a substrate processing apparatus by performing statistical calculations using a fourth number of apparatus data, which is equal to or greater than a third number, obtained by the method for calculating the number of data items disclosed herein; It can be said that the fourth number is equal to or less than the second number of pieces subjected to the second step until a positive determination result is obtained in the third step.

[0079] The fourth number of pieces of equipment data indicates parameters used when the substrate processing was performed to obtain the fourth number of pieces of process data among the second number of pieces of process data that were used in the second process until a positive judgment result was obtained in the third process.

[0080] The device data group Va is input to the evaluation unit 500. The input may be performed by an operator, for example. Alternatively, the input may be performed by a program that realizes a method for calculating the number of pieces of data.

[0081] The evaluation unit 500 performs known statistical calculations using a database DB3 to output evaluation data Q. The statistical calculations themselves are explained in, for example, the above-mentioned Patent Documents 1 to 6, and therefore will not be explained further in this disclosure.

[0082] <4. Substrate processing equipment> <4-1. Overview of substrate processing equipment> A substrate processing apparatus according to the present disclosure will be described with reference to Figures 5 and 6. Figure 5 is a plan view schematically showing an example of the configuration of a substrate processing apparatus 1. The substrate processing apparatus 1 is a single-wafer processing apparatus that processes substrates W, which are the targets of substrate processing, one by one. For example, the substrates W are substantially disk-shaped semiconductor substrates.

[0083] The substrate W is not necessarily limited to a semiconductor substrate. For example, various substrates such as a glass substrate for a photomask, a glass substrate for a liquid crystal display, a glass substrate for a plasma display, a substrate for an FED (Field Emission Display), a substrate for an optical disk, a substrate for a magnetic disk, and a substrate for a magneto-optical disk can be used as the substrate W. The shape of the substrate is also not limited to a disk shape, and various shapes such as a rectangular plate shape can be used.

[0084] The substrate processing apparatus 1 includes a load port 105, an indexer section 103, a processing section 102, a transfer section 104, a transport section 106, and a control device 107. The control device 107 comprehensively controls the operations of the components of the substrate processing apparatus 1 outside the control device 107.

[0085] The processing section 102 has a plurality of, for example, four towers 20. In a plan view, the four towers 20 are arranged around the transport section 106. Each tower 20 has a plurality of, for example, three processing units 2 stacked vertically in a plan view. The processing unit 2 functions as a processing chamber that performs substrate processing on the substrate W. A mechanism 9 for holding the substrate W is stored in the processing unit 2.

[0086] A plurality of, for example, four carriers C are loaded into the load port 105. As the carriers C, a FOUP (Front Opening Unified Pod) that stores substrates W in an enclosed space, a SMIF (Standard Mechanical Interface) pod, or an OC (Open Cassette) that exposes substrates W to the outside air may be used.

[0087] The substrate processing apparatus 1 includes an indexer robot 109. The indexer robot 109 moves mainly along the direction in which the carriers C are lined up in the indexer section 103 (see arrow F1 in FIG. 1). The indexer robot 109 moves between the indexer section 103 and the transfer section 104 (see arrow F2 in FIG. 1). The indexer robot 109 has a function of holding a substrate W. The indexer robot 109 transports the substrate W between the carriers C in the indexer section 103.

[0088] The substrate processing apparatus 1 includes a transfer robot 108. The transfer robot 108 has a function of holding the substrate W. The transfer robot 108 moves between the delivery section 104 and the transfer section 106 (see arrow F3 in FIG. 1).

[0089] The transfer robot 108 transfers the substrate W between itself and the indexer robot 109 in the transfer section 104. The indexer robot 109 transfers the substrate W between itself and the transfer robot 108 in the transfer section 104.

[0090] The transfer robot 108 moves between the transfer section 106 and each of the processing units 2 (see arrow F4 in FIG. 1). The transfer robot 108 transfers the substrate W to and from each of the processing units 2.

[0091] The transfer robot 108 receives the substrate W from the indexer robot 109 and transfers it into one of the processing units 2. The transfer robot 108 transfers the processed substrate W from the processing unit 2 and hands it over to the indexer robot 109.

[0092] <4-2. Overview of the control device> FIG. 6 is a block diagram illustrating the configuration of a computer 3 that can be used as the control device 107.

[0093] The computer 3 includes a central processing unit (hereinafter and in the drawings, abbreviated as "CPU") 31, a main memory 32, a storage unit 33, an input unit 34, a display unit 35, and a communication unit 36. The computer 3 further includes a bus 30 that connects these units to one another.

[0094] The main memory 32 may be, for example, a volatile storage element, which functions as a working memory in the computer 3. The storage unit 33 may be, for example, a hard disk drive, which stores the data processing program 41, time-series data 47, and measurement data 48.

[0095] The input unit 34 includes, for example, a keyboard 38 and a mouse 39, and is responsible for inputting data from outside the computer 3. The display unit 35 uses, for example, a liquid crystal display, and displays, for example, confirmation of items input to the input unit 34, a recipe employed in the substrate processing apparatus 1, etc.

[0096] The communication unit 36 ​​is an interface circuit for wired or wireless communication, and is used for communication between the substrate processing apparatus 1 and other data processing apparatuses, such as evaluation apparatuses that implement the evaluation methods described above. For example, the communication unit 36 ​​receives a data processing program 41 from outside the computer 3. The data program is stored in the storage unit 33 from the communication unit 36.

[0097] The computer 3 may further include a recording medium reading unit 37. For example, the recording medium reading unit 37 is an interface circuit for a recording medium 40 that records a program that defines the operation of the computer 3. For example, a data processing program 41 is stored in the recording medium 40 via the recording medium reading unit 37 and stored in the memory unit 33.

[0098] For example, the data processing program 41 includes a recipe for substrate processing to be performed on a substrate W in the substrate processing apparatus 1, specifically in the processing unit 2. Based on the recipe, the CPU 31 instructs the processing unit 2 to perform substrate processing via the bus 30. The processing unit 2 performs the substrate processing in accordance with the instruction.

[0099] For example, the time-series data 47 is equipment data. The processing unit 2 provides actual parameters for the substrate processing executed based on the recipe, such as the amount of etchant supplied and its supply time, and the wafer rotation speed and rotation time when the etchant is supplied, to the control device 107. The computer 3 functioning as the control device 107 stores the parameters as time-series data 7 via the bus 30.

[0100] For example, the measurement data 48 is process data. For example, the process data is externally input to the storage unit 33 via the input unit 34 and stored as the measurement data 48. Specific examples include the etching amount and aspect ratio from the etching profile of the substrate W after substrate processing. These values ​​are obtained outside the substrate processing apparatus 1, for example, by observation with a microscope. The operator operates the input unit 34 to input these values ​​into the control device 107, which functions as the computer 3.

[0101] Alternatively, the etching profile may be input from the microscope to the computer 3 via the communication unit 36 ​​and stored in the storage unit 33 as measurement data 48 .

[0102] <4-3. Calculation of the number of data items by the control device> The method for calculating the number of pieces of data illustrated in the flowchart of FIG. 1 is executed in the computer 3 functioning as the control device 107, for example.

[0103] The significance level and detection power are input in step S101 by, for example, an operator operating the input unit 34. The same applies to the input of the given conditions in step S102. However, if one or more of the significance level, detection power, and given conditions are stored in the storage unit 33, input of the stored items may be omitted.

[0104] The acquisition of the process data in step S103 is realized, for example, by an operator operating the input unit 34. Alternatively, the process data is acquired by inputting the etching profile from the microscope to the computer 3 via the communication unit 36 ​​and storing it in the storage unit 33 as measurement data 48.

[0105] The input of the process data in step S201 is realized, for example, by an operator operating the input unit 34. The process data input each time step S201 is executed is stored in the storage unit 33 one by one.

[0106] For example, the statistical calculations in steps S202 and S204 are executed by the CPU 31 using the main memory 32 as a working memory. The statistical calculation tables DB1 and DB2 used at this time are stored in the storage unit 33, for example.

[0107] The determinations made in steps S203, S205, and S206 are performed by, for example, the CPU 31, and the respective determination results are obtained. The displays made in steps S301, S302, and S303 are performed by, for example, the display unit .

[0108] <4-4. Evaluation of equipment status by control device> The evaluation of the equipment state can be executed, for example, by the computer 3. This is because the measurement data 48 is stored as process data and the time-series data 47 is stored as equipment data in the storage unit 33. The CPU 31 can use the main memory 32 as a working memory to perform statistical calculations using equipment data corresponding to the fourth number of process data out of the second number of process data that were used in the second step until a positive determination result was obtained in the third step.

[0109] 4, the apparatus data group V, the process data group P, and the database DB3 are stored in the memory unit 33. The evaluation unit 500 is realized by the operation of the CPU 31 based on the data processing program 41. The evaluation data Q is output to the outside of the substrate processing apparatus 1 via the communication unit 36, for example. The evaluation data Q is displayed on the display unit 35, for example.

[0110] <5. Calculation of data number from outside the control device and evaluation of device status> The calculation of the number of pieces of data described above is not limited to being performed in the computer 3 functioning as the control device 107. The calculation of the number of pieces of data may be performed outside the substrate processing apparatus 1 together with the evaluation of the apparatus state.

[0111] 7 is a block diagram illustrating a schematic configuration of a data processing device 10 that exchanges data with the substrate processing apparatus 1. The data processing device 10 performs both the calculation of the number of data items and the evaluation of the apparatus state described above.

[0112] For example, the data processing device 10 can communicate with a communication unit 36 ​​(see FIG. 6) provided in a computer 3 that functions as a control device 107 included in the substrate processing device 1.

[0113] The data processing device 10 includes, for example, a data storage unit 11, statistical calculation units 12 and 16, a score storage unit 13, an input unit 14, and an evaluation display unit 15.

[0114] The data storage unit 11 stores device data 17 and process data 18 obtained from the computer 3. The score storage unit 13 stores reference data 19 used to output evaluation data Q, and functions as the database DB3 shown in FIG.

[0115] The input unit 14 has a configuration including a keyboard and a mouse, similar to the configuration exemplified as the input unit 34. The input unit 14 can be operated by an operator.

[0116] The process data 18 is a first number of process data obtained by the substrate processing apparatus 1. In accordance with FIG. 4, the process data 18 corresponds to the process data group P. At this time, the equipment data 17 is a first number of equipment data. In accordance with FIG. 4, the equipment data 17 corresponds to the equipment data group V. The statistical calculation tables DB1 and DB2 (see FIG. 1) used to calculate the number of data are also stored in the data storage unit 11.

[0117] For example, the first number of process data items are input from the substrate processing apparatus 1 to the data processing apparatus 10 in steps S103 and S201.

[0118] The data processing device 10 receives inputs from the outside via the input unit 14, such as the probability α of a type I error, which is used as the significance level, the probability β of a type II error, which is subtracted from the value 1 to obtain the detection power, and a given condition J (see steps S101 and S102 in Figure 1).

[0119] The statistical calculation unit 12 executes statistical calculations used to calculate the number of data items. In the above example, the statistical calculations in steps S202 and S204 are executed by the statistical calculation unit 12. The statistical calculation unit 12 also executes the determinations in steps S203, S205, and S206. As a result, the execution of steps S301 and S302 is omitted.

[0120] The statistical calculation unit 16 performs statistical calculations used to evaluate the device state. In accordance with Fig. 4, the statistical calculation unit 16 functions as the evaluation unit 500. As described with reference to Fig. 4, the device data group Va is sufficient for the statistical calculations used in the evaluation as far as device data is concerned. The device data group Va is provided to the statistical calculation unit 16 from, for example, the statistical calculation unit 12.

[0121] The statistical calculation unit 16 performs statistical calculations using the reference data 19 by a known method (see, for example, Patent Document 1) to obtain evaluation data Q, and provides the evaluation data Q to the evaluation display unit 15. The evaluation display unit 15 displays an evaluation of the device status based on the evaluation data Q.

[0122] The device data group Va may be added to the reference data 19 to aid in later evaluation of the device state, as indicated by the dashed arrow in FIG.

[0123] The apparatus data group Va may be input by the operator to the input unit 14 in accordance with the fourth number obtained by the statistical calculation unit 12, specifically by the execution of step S204.

[0124] 6. Examples of Effects of the Present Disclosure <6-1. How to calculate the number of data items> The method for calculating the number of pieces of data according to the present disclosure contributes to automatically determining the number of pieces of equipment data to be introduced into the evaluation process without relying on the experience of an operator, which contributes to a high level of economic productivity through diversification, technological improvement, and innovation.

[0125] <6-2. Equipment condition evaluation method> By using the equipment condition evaluation method according to the present disclosure in the evaluation process, the number of equipment data used in the statistical calculations is the fourth number obtained using the data number calculation method according to the present disclosure, which contributes to reducing the amount of calculation required for the statistical calculations and ultimately contributes to economic productivity.

[0126] It goes without saying that all or part of the components constituting each of the above-described embodiments and various modified examples can be combined as appropriate within the scope of not causing any contradiction. [Explanation of symbols]

[0127] 1. Substrate processing equipment 17 Equipment Data 18 Process Data 41 Data Processing Program DB1 Statistical calculation table (for determining distribution convergence) DB2 statistical calculation table (for probability convergence judgment) DB3 database P, Pa, Pb process data group P1, Pj, Pm, Pn process data Q Evaluation Data S101, S102, S103, S201, S202, S203, S204, S205, S206, S301, S302, S303 steps V, Va, Vb equipment data set V1, Vj, Vm, Vn equipment data W substrate α Probability of type 1 error β Probability of type II error

Claims

1. a first step of obtaining a first number of process data, which is information indicating performance of a process performed on a substrate by the substrate processing apparatus, the first number being two or more; a second step of performing statistical calculations on a second number of the process data, the second number being two or more and less than the first number, and calculating, as a third number, the number of the process data required to determine that the first number of the process data satisfies a given condition; a third step of determining whether the second number is equal to or greater than the third number; A method for calculating the number of data items.

2. 2. The method of claim 1, wherein after a negative determination result is obtained in the third step, the second step and the third step are additionally performed by increasing the second number with the first number as an upper limit.

3. The second step comprises: a first substep of determining the third number using the probability of a type I error, the probability of a type II error, and an effect size corresponding to the given condition; The method for calculating the number of data items according to claim 2 , comprising:

4. The second step comprises: a second sub-step that is executed prior to the first sub-step and determines whether the first number of process data pieces are normal; and 4. The method for calculating the number of data items according to claim 3, wherein the first sub-step and the third sub-step are executed only when the determination result of the second sub-step is affirmative.

5. 5. An evaluation method for evaluating a state of the substrate processing apparatus by performing statistical calculations using a fourth number of apparatus data, the fourth number being equal to or greater than the third number, obtained by the method for calculating the number of data according to any one of claims 1 to 4, the fourth number is equal to or less than the second number of pieces subjected to the second step until a positive determination result is obtained in the third step, The method for evaluating a substrate processing apparatus, wherein the apparatus data is information indicating parameters when the substrate processing apparatus performs the processing.

6. 6. The method for evaluating a substrate processing apparatus according to claim 5, wherein the fourth number of pieces of apparatus data indicate the parameters when the processing was performed that yielded the fourth number of pieces of process data among the second number of process data that were provided to the second process when a positive judgment result was obtained in the third process.

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