Server, Semiconductor Device Manufacturing System, and Manufacturing Method

Abstract

The purpose of the present invention is to provide a technique for accurately controlling an etching parameter by detecting a shape defect that cannot be obtained only by planar dimension data obtained from a top view.　Therefore, the server of the present invention controls the etching parameter so that the processing result of a desired semiconductor manufacturing device can be obtained on the basis of the correlation data between the amounts of change in the feature amount of the etching shape formed in a sample and a target value and the etching parameter of a semiconductor manufacturing device, wherein the feature amount uses a value obtained from the secondary electron data from the surface of the sample or the interfering light data from the surface of the sample. The feature amount may be a value obtained from the dimension of the etching shape of the sample on the basis of the secondary electron data or the interfering light data. As the amount of change in the feature amount, there is a spatial or temporal change value.

Description

Technical Field

[0001] The present invention relates to a server, a semiconductor device manufacturing system, and a manufacturing method.

Background Art

[0002] Currently, plasma etching systems are part of semiconductor manufacturing tools for manufacturing semiconductor devices approaching atomic-level miniaturization. One of the requirements for device manufacturing equipment is improvement in uniformity. It has been known that for manufacturing semiconductor devices close to the atomic level, it is insufficient to only measure the lateral dimensions of semiconductor devices when observed from the top surface of a wafer and achieve uniformity based on the obtained measurement data. For example, the above-mentioned measurement apparatus includes CD-SEM, but only top-view geometric planar dimension data obtained from CD-SEM can only provide the dimension of the pattern surface, so it cannot measure the bowing shape or notch shape at a position slightly deeper from the pattern surface. As a result, even if the CD (Critical Dimension) value is the same, three-dimensional geometric defects of the pattern cannot be detected. If such defects cannot be detected, it is obvious that problems will occur in the ion implantation process and CVD process after etching. In addition, these defective shapes are related not only to the temperature of the electrostatic chuck during etching but also to the plasma density, so complicated etching parameter control is required. As disclosed in Patent Document 1, the prior art feeds back the temperature value of an electrostatic chuck based on variations in CD values within a wafer surface, wherein the CD values are top-view geometric dimension data, to achieve uniform CD values within the wafer surface and improve the in-wafer yield.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problem to be Solved by the Invention

[0004] However, conventional technology is designed to make the CD value uniform, and therefore cannot address defects such as bowing or notch shapes occurring in the depth direction, even though the CD value is the same. Furthermore, because it is a technology that feeds back the electrostatic chuck temperature, it cannot address defects in pattern shape caused by plasma density. Therefore, the present invention aims to provide a technology that can detect shape defects that cannot be obtained solely from planar dimensional data obtained from a top view, and to accurately control etching parameters. [Means for solving the problem]

[0005] To solve the above problems, one representative example of the present invention is a server characterized in that the etching parameters are controlled based on correlation data between the change in characteristic quantities of the etching shape formed on a sample and a target value, and the etching parameters of the semiconductor manufacturing apparatus, so as to obtain the desired processing result of the semiconductor manufacturing apparatus, and the characteristic quantities are values ​​obtained from secondary electron data from the surface of the sample or interference light data from the surface of the sample. [Effects of the Invention]

[0006] According to the present invention, it is possible to detect shape defects that cannot be obtained solely from planar dimensional data obtained from a top view, and to accurately control etching parameters. Furthermore, users can optimize etching process recipes to prevent device defects non-destructively, without observing the cross-section of the wafer, either when or before a device defect occurs. Issues, structures, and effects other than those mentioned above will be clarified by the following explanation of the implementation methods. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 is a schematic diagram of a semiconductor device manufacturing system according to the first embodiment. [Figure 2A]Figure 2A is a correlation diagram between pattern shape and secondary electron profile when the acceleration voltage is high. [Figure 2B] Figure 2B is a correlation diagram between pattern shape and secondary electron profile when the acceleration voltage is low. [Figure 3] Figure 3 is a correlation diagram between pattern shape and secondary electron profile at given etching parameters. [Figure 4] Figure 4 is a flowchart of an example of a method for controlling etching parameters in the first embodiment. [Figure 5] Figure 5 is a flowchart showing an example of a method for controlling etching parameters in the second embodiment. [Figure 6] Figure 6 is a correlation diagram between pattern shape and secondary electron profile for a predetermined number of etched wafers. [Figure 7] Figure 7 is a flowchart illustrating an example of a method for extracting combinations of features with high correlation coefficients to etching parameters. [Figure 8] Figure 8 is a schematic diagram of the feature map in the fourth embodiment. [Figure 9] Figure 9 is a flowchart showing an example of a method for controlling etching parameters in the fourth embodiment. [Figure 10] Figure 10 is a correlation diagram between features and etching parameters. [Modes for carrying out the invention]

[0008] Embodiments of the present invention will be described below with reference to the drawings. However, the present invention is not limited to these embodiments. Furthermore, in the drawings, identical parts are denoted by the same reference numerals.

[0009] In one embodiment of the present invention, a server may be provided that calculates the temporal change or spatial change of feature quantities based on feature quantities obtained from a secondary electron profile obtained from a top view of a wafer of a CD-SEM, or calculates the geometric dimensional difference (change) between the feature quantities of the etching shape and the feature quantities of the target shape, and the integral value of said geometric dimensional difference (change) in the etching depth direction, and controls etching parameters in a semiconductor manufacturing apparatus based on this correlation data. The following will be described based on embodiments.

[0010] (First Embodiment) A first embodiment of the present invention will be described with reference to Figure 1. Figure 1 is a schematic diagram of a semiconductor device manufacturing system according to the first embodiment. The semiconductor device manufacturing system 10 includes a semiconductor manufacturing apparatus (etching apparatus) 105, a PC 101 for CD-SEM, a PC 102 for semiconductor manufacturing apparatus, a semiconductor inspection apparatus 104 (e.g., CD-SEM), and a server 103. The purpose of this figure is to explain the performance improvement of a semiconductor device manufacturing system, which is important in semiconductor manufacturing.

[0011] The processing recipe for etching is entered into the PC 102 for the semiconductor manufacturing equipment, or transferred from the server 103 to the PC 102 and executed. After execution, the etching equipment 105 transmits the instruction values ​​according to the processing recipe to each device in the etching equipment, and the etching process is performed. Figure 1 shows only the main devices and elements, but it illustrates the wafer temperature control power supply, temperature control electrodes (heater / Peltier), RF power supply for high frequency application, microwave power supply for plasma generation, plasma generation gas, magnetic field generating coil for plasma density adjustment, electrostatic adsorption electrodes (electrostatic chuck), and lower electrodes. The wafer sample is placed on the electrostatic adsorption electrodes and etched by plasma processing. The executed processing recipe can be saved to the server 103 via the PC 102 for the semiconductor manufacturing equipment. Unless otherwise specified, "in-plane" hereafter refers to the surface of the sample (wafer). The wafer shape will be described as having a circular shape with radial and circumferential directions.

[0012] The etched wafer is transported to a semiconductor inspection apparatus 104 (e.g., a CD-SEM). In FIG. 1, a recipe for the CD-SEM is input to a PC 101 for CD-SEM, and predetermined measurement is performed. In the measurement herein, an electron beam is used, and feature quantity calculation is performed based on the amount of secondary electrons (secondary electron data) after electron beam irradiation. Here, description will be given using, as a representative feature quantity, a feature quantity obtained from an intensity profile of the amount of secondary electrons (secondary electron profile). As other feature quantities, there are various types such as those using illuminance data and those obtained by differentiating the above intensity profile (a feature quantity obtained from a secondary electron profile derived from an etched shape of a sample may also be referred to as a profile feature quantity.). The measurement result can be stored in the server 103 via the PC 101.

[0013] Using the stored measurement data described above, wafer yield is visualized based on the feature quantity distribution in the wafer plane, and if the required yield value cannot be satisfied, a processing recipe for re-performing etching processing is corrected. Even if CD values are the same, if there is a difference in feature quantity, it is considered that there is a defect in the pattern shape of the device. This will be described in further detail below.

[0014] (Secondary Electron Profile) FIG. 2A is a correlation diagram between a pattern shape and a secondary electron profile when an acceleration voltage is high. FIG. 2B is a correlation diagram between a pattern shape and a secondary electron profile when an acceleration voltage is low. For convenience below, FIG. 2A and FIG. 2B may be collectively referred to as FIG. 2. In FIG. 2, a schematic diagram of the pattern shape of the device is shown on the left, and a schematic diagram of a profile of secondary electron amount intensity (secondary electron profile) is shown on the right. All TopCD values of the pattern shapes in FIG. 2 are the same. Differences in the amount of secondary electrons occur depending on whether the acceleration voltage is high or low, so there exists an optimal acceleration voltage that facilitates extraction of defective shapes. Here, a bowing shape is taken as an example of a defective shape, and the concept of how the secondary electron profile changes between a high acceleration voltage and a low acceleration voltage, and which voltage is optimal, will be described. Note that, when the pattern shape of a device is a shape formed by etching, it may also be referred to as an etched shape.

[0015] Fig. 2A is an explanation when the acceleration voltage is high (acceleration voltage: Vh1). (a-1) shows the case where there is a bowing shape (defective shape), and (a-2) shows the case where the shape is a target shape. Since the penetration depth of primary electrons at the acceleration voltage is large, when the etching depth is DL at the initial etching stage, the amount of secondary electrons leaking out from the sidewall of the pattern is small, and accordingly the amount of detected secondary electrons is also reduced. Therefore, both the feature quantity of the pattern shape when there is a bowing shape with a reduced width (secondary electron intensity at the center of the top surface of the pattern) and the feature quantity of the target shape with a normal width (hereinafter, the feature quantity of the target shape is simply referred to as a target value) are a, with no difference (variation), so detection of the bowing shape is difficult.

[0016] When etching proceeds to the final etching depth DH, as shown in (a-1), the amount of secondary electrons leaking out to the pattern sidewall increases, so that the value of the feature quantity (secondary electron intensity at the center of the top surface of the pattern) increases to b. Therefore, it shows a larger value compared to c which is the target value, so detection of the bowing shape is easy. That is, when b - a > c - a (i.e., b > c), it can be determined that a bowing shape is present.

[0017] On the other hand, as shown in Fig. 2B, when the acceleration voltage is low (acceleration voltage: Vl1), the penetration depth of primary electrons is small. Therefore, at the initial etching depth DL, even if the bowing shape is small as shown in (b-1), a large amount of secondary electrons leak out from the pattern sidewall, and accordingly the value of the feature quantity (secondary electron intensity at the center of the top surface of the pattern) becomes as large as d. Therefore, d - e, which is the difference (variation) from the target value e, is large, so detection of the bowing shape is easy even in the initial etching stage. Naturally, also at the final etching depth DH after the progress of the etching process, f - g, which is the difference (variation) between the feature quantity and the target value, is similarly large, and detection of the bowing shape is also easy at this time. As described above, the ease of detecting pattern shape defects changes depending on the adjustment of the acceleration voltage applied to primary electrons during electron beam irradiation, so optimal adjustment of the acceleration voltage is important.

[0018] As explained above, since the profile features include information in the etching depth direction of the etching shape, calculating the difference in profile features within the wafer surface makes it possible to identify defects such as bowing shapes in the etching depth direction, which cannot be obtained from planar dimensional data obtained from the top view alone. Alternatively, this can be done by tilting the wafer using the tilt function of a CD-SEM and calculating the change in features to obtain a more detailed calculation of the change in features.

[0019] (Features and etching parameters) Next, we will explain the correlation between feature quantities and etching parameters. Figure 3 is a correlation diagram between pattern shape and secondary electron profile at given etching parameters. As an example, it shows the pattern shape and feature quantities at the wafer edge, the pattern shape and feature quantities at the wafer center, and the etching parameters at each location, namely the temperature environment and plasma density environment. Here, as an example, the device at the wafer center is the pattern target shape, the wafer center temperature is T2, and the plasma density is P2. The device at the wafer edge is a bowing shape where a defect has occurred, the wafer edge temperature is T1, and the plasma density is P1. Figure 3 shows a schematic graph of the pattern shapes at the wafer edge and wafer center, with z on the vertical axis and B on the horizontal axis. L1 to L4 are the film type switching lines. The shaded area shows the shape difference between the wafer edge and the wafer center. The area of ​​the shape difference (area difference) is ∫ΔBdz. Here, there are two methods for optimizing the etching parameters: calculating ∫ΔBdz or optimizing without calculating it, which will be explained below.

[0020] (Method 1) Method 1 is a method for controlling etching parameters without specifying ∫ΔBdz. First, ∫ΔBdz can be expressed using the function Q as shown in Equation 1. ∫ΔBdz = Q((fa)-(ga)) ···Equation 1 Next, assuming the electrostatic chuck temperature difference ΔT = T1 - T2 and the plasma density difference ΔP = P1 - P2, ∫ΔBdz can also be expressed using the function R as shown in Equation 2. ∫ΔBdz = R(ΔT, ΔP)...Equation 2 From equations 1 and 2, Q(fg) = R(ΔT,ΔP) Therefore, fg can be expressed using the function Z as shown in Equation 3. fg = Z(ΔT, ΔP) ...Equation 3 Ideally, since fg = 0, we need to find the values ​​of T and P for which Z(ΔT, ΔP) = 0 using equation 3.

[0021] (Method 2) Method 2 involves specifying ∫ΔBdz and controlling the etching parameters. First, ∫ΔBdz is determined by real-time CD measurement at L1 to L4 using OCD (Optical Critical Dimension). In this process, the measurement points in the depth direction should be for multilayer films with different film types. For identical films, the wafer can be split and measured using SEM or TEM. SEM and TEM can, of course, be used for multilayer films as well. Furthermore, ∫ΔBdz can be expressed using a predetermined function R as shown in Equation 4. ∫ΔBdz = R(ΔT, ΔP)...Equation 4 Ideally, since ∫ΔBdz = 0, we need to find the values ​​of T and P for which R(ΔT, ΔP) = 0 using equation 4. While there are no particular limitations on the derivation of the functions described in this disclosure, it is possible to obtain them inductively from experiments.

[0022] In the first embodiment, since Method 1 is employed, it is not necessary to determine the geometric dimensional difference. On the other hand, in the second embodiment, which will be described later, Method 2 is employed. The method for controlling etching parameters using Method 1 is explained in a flowchart. Figure 4 is a flowchart of an example of the method for controlling etching parameters in the first embodiment. First, after wafer etching, N measurement points are selected. N is a number greater than 1 relative to the number of parameters to be determined. For example, in this embodiment, two points are selected: the wafer center and the wafer edge. In this embodiment, to simplify the explanation, the plasma density is assumed to remain constant, and the only parameter to be determined is temperature, so the above two measurement points are sufficient. Next, the wafer temperature T and plasma density P at the selected location are measured, and characteristic quantities are also measured. Next, the wafer temperature difference ΔT and plasma density difference ΔP at the wafer center and wafer edge are calculated, and the change amount fg, which is the difference in feature quantities, is also calculated.

[0023] Next, referring to Equation 3, we set the target fg, the reference point (wafer center) T2, and P2 to calculate the value of the function Z. As explained above, if P1 at the wafer edge is the same as P2, then T1 at the wafer edge can be found from Equation 3. This is the temperature at the wafer edge that creates the target shape. As the etching parameter Ep that satisfies this T1, we adjust the temperature near the edge of the electrostatic chuck. Considering the heat input balance from the plasma, we adjust the temperature near the edge of the electrostatic chuck and etch the wafer edge so that the wafer edge temperature becomes T1.

[0024] In this embodiment, we demonstrated an example of optimizing etching parameters using the change in spatial features. Here, we explained based on features calculated from a secondary electron profile obtained from a CD-SEM as secondary electron data, but the same flow applies to features calculated from an interference light profile obtained from an OCD as interference light data.

[0025] (Second Embodiment) A second embodiment of the present invention will be explained with reference to Figure 5. The difference from the first embodiment is the use of Equation 4 in Method 2 described above, and other aspects are the same as in the first embodiment, so the differences will be explained in detail. Figure 5 is a flowchart of an example of a method for controlling etching parameters in the second embodiment. In the first embodiment, it was not necessary to determine the geometric dimensional difference between the target shape and the defective shape, but the second embodiment is an example in which the geometric dimensional difference between the target shape and the defective shape is determined.

[0026] First, after wafer etching, M measurement points are selected. M is a number greater than 1 relative to the number of parameters to be determined. For example, in this embodiment, two points are selected: the wafer center and the wafer edge. In this embodiment, to simplify the explanation, the plasma density is assumed to remain constant, and the only parameter to be determined is temperature, so the above two measurement points are sufficient. Next, the wafer temperature T and plasma density P are measured at the selected location. The pattern shape is also measured using secondary electron data from cross-sectional SEM and TEM, or interference light data from OCD, to obtain geometric feature quantities (feature quantities directly obtained from the geometric dimensions of the pattern shape are sometimes called shape features).

[0027] Next, the wafer temperature difference ΔT and plasma density difference ΔP at the wafer center and wafer edge are calculated, and the area difference ∫ΔBdz is also calculated. To calculate this area difference, the wafer is cut using a cross-sectional SEM or TEM to measure the shape features related to the dimensions of the pattern shape, or the OCD light source is adjusted to determine the average pattern width for each film type L1 to L4 as explained in Figure 3, thereby determining the shape features related to the dimensions of the pattern shape. Then, the change in the geometric dimensional difference (ΔB) between the shape features of the pattern shape and the target value is integrated in the etching depth direction to calculate the area difference ∫ΔBdz.

[0028] Next, referring to Equation 4, we set the target ∫ΔBdz, T2 at the wafer center (the reference point), and P2 to calculate the value of the function R. As explained above, if P1 at the wafer edge is the same as P2, then T1 at the wafer edge can be found from Equation 4. This is the temperature at the wafer edge that creates the target shape. As the etching parameter Ep that satisfies this T1, we adjust the temperature near the edge of the electrostatic chuck. Considering the heat input balance from the plasma, we adjust the temperature near the edge of the electrostatic chuck and etch the wafer so that the wafer edge temperature becomes T1. As a result, it becomes possible to control etching parameters to detect and resolve defects such as bowing shapes in the etching depth direction, which cannot be obtained solely from planar dimensional data obtained from the top view. In this embodiment, we demonstrate an example of directly determining the dimensions of the pattern shape using secondary electron data or interference light data to identify shape features and optimize etching parameters.

[0029] (Third embodiment) A third embodiment of the present invention will be described with reference to Figure 6. Figure 6 is a correlation diagram between the pattern shape and the secondary electron profile for a predetermined number of etching wafers. As an example, it shows the pattern shape and characteristic quantities at the wafer center for the 1st, 100th, and 1000th etching wafers, as well as the temperature environment and plasma density environment at each time. Here, as an example, the 1st etching wafer has the target shape, the wafer center temperature is T1, and the plasma density is P1. The 100th etching wafer has a bowing shape and a defect has occurred, the wafer center temperature is T100, and the plasma density is P100. The 1000th etching wafer also has a bowing shape and a defect has occurred, the wafer center temperature is T1000, and the plasma density is P1000. Figure 6 shows a schematic graph of the pattern shapes for the 1st and 1000th wafers, with z on the vertical axis and B on the horizontal axis. L1 to L4 are the film type switching lines. The shaded area shows the shape difference between wafer 1 and wafer 1000. The area of ​​the shape difference is ∫ΔBdz. Here, as in the first embodiment, we use an optimization method (Method 1) that does not require calculating ∫ΔBdz.

[0030] Figure 4 is used to illustrate the above using a flowchart. First, after wafer etching, N measurement points are selected. N is a number greater than 1 relative to the number of parameters to be determined. For example, in this embodiment, two points are selected: the first wafer and the 1000th wafer. In this embodiment, to simplify the explanation, the plasma density is assumed to remain unchanged, and the only parameter to be determined is temperature, so the above two measurement points are sufficient. Next, the wafer temperature T and plasma density P at the time of selection are measured, and characteristic quantities are also measured. Next, the wafer temperature difference ΔT and plasma density difference ΔP between the first wafer and the 1000th wafer are calculated, and the change amount fg, which is the difference in feature quantities, is also calculated.

[0031] Next, referring to Equation 3, we set the target fg, the reference point T1 of the first wafer, and P1 to calculate the value of the function Z. As explained above, if P1000 of the 1000th wafer is the same as P1, then T1000 of the 1000th wafer can be found from Equation 3. This is the temperature of the 1000th wafer when the target shape is created. As the etching parameter Ep that satisfies this T1000, we adjust the temperature near the center of the electrostatic chuck. Considering the heat input balance from the plasma, we adjust the temperature near the center of the electrostatic chuck over time so that the temperature of the wafer center becomes T1000, and then etch. In this embodiment, we demonstrated an example of optimizing etching parameters using the change in temporal features. Here, we explained based on features calculated from the secondary electron profile using CD-SEM, but the same flow applies to features calculated from the interference light profile using OCD.

[0032] (Fourth embodiment) A fourth embodiment of the present invention will be illustrated with reference to Figure 7. Figure 7 is a flowchart of an example of a method for extracting combinations of features with high correlation coefficients to etching parameters.

[0033] First, set the etching parameter Ep and then perform the etching process. Next, shape features are measured after etching. These shape features can include various parameters such as etching rate, CD value, and surface roughness. The number of measurement points is greater than one. Furthermore, profile features are measured after etching. These features are not limited to the secondary electron intensity at the center of the pattern top surface obtained from the secondary electron profile described above; various other features (feature 1 / feature 2 / feature 3, etc.) are also possible. The number of measurement points is greater than one.

[0034] Next, the in-plane distribution of features is visualized to determine the heterogeneity. As an example, the heterogeneity is calculated using the maximum value of the variation in the measured feature data relative to the mean data, as (maximum value - mean value) / mean value × 100 (%). Then, features whose heterogeneity exceeds a predetermined percentage (%) are extracted (for example, if the predetermined heterogeneity for shape features is Q%, the number of extracted features is n, and if the predetermined heterogeneity for profile features is R%, the number of extracted features is m).

[0035] Next, we normalize the in-plane distribution for each extracted feature. Here, as an example, we normalize by setting the maximum value for each feature to 1. Next, the normalized data of the in-plane distribution of shape features and the normalized data of the in-plane distribution of profile features are compared, and the correlation coefficient is calculated. As an example of calculating the correlation coefficient, Figure 7 shows the relationship between the normalized data and the measurement position (x) on the wafer. Here, as an example, in the case of etching rate and feature 3, the normalized data is superimposed, and the area of ​​the differing parts (area difference) is found. As an example of the formula for calculating the correlation coefficient from the ratio of the area difference to the integral value of the etching rate normalized data, we give 100 - ratio of the area difference to the integral value of the etching rate normalized data (%) = correlation coefficient. This is calculated for all n × m combinations, and combinations with a correlation coefficient greater than L (%) are extracted and stored in the database (DB1) on the server. This makes it possible to accumulate correlation data in DB1 regarding features that have a high correlation with the etching parameter Ep. This allows for the retrieval of highly correlated etching parameters from DB1 using machine learning or other methods, and control to ensure a uniform in-plane distribution.

[0036] Let's explain a practical application example. Figure 8 is a schematic diagram of the feature map in the fourth embodiment. The map shows features 1 to 3, and we focus on feature 3, which has a difference in its in-plane distribution (high heterogeneity). Since the etching parameters highly correlated with feature 3 are stored in DB1, we search for them and adjust the etching parameters precisely so that feature 3 becomes uniform (database search). It is also possible to extract the optimal etching parameters from past experimental data and set them manually.

[0037] The above-described procedure is explained using a flowchart. Figure 9 is a flowchart of an example of a method for controlling etching parameters in the fourth embodiment. First, the in-plane distribution of features after etching is normalized for wafer 1. That is, the maximum feature value is set to 1. Next, using the in-plane distribution of the above-mentioned features, the etching parameter Ep1 with a high correlation coefficient is identified from DB1 as described above. Machine learning can also be used for identification. If there are significant spatial or temporal differences (changes) in the features and problems arise, the etching parameter Ep1 is corrected to a predetermined value, and the etching process is performed again on wafer 2. The same process is then repeated until there are no problems with the features, thereby obtaining the desired etching process recipe. Therefore, by accurately controlling the etching parameter for problematic features that are unevenly distributed in-plane, it becomes possible to achieve the target shape.

[0038] Figure 10 shows further techniques for efficiently determining etching parameters. Figure 10 is a correlation diagram between feature quantities and etching parameters. An example of a correlation diagram between etching parameters and feature quantity 3 (for example, the secondary electron quantity intensity at the center of the pattern top surface) is shown for the wafer center and wafer edge. In etching, the gas pressure is low at the outer edge of the wafer, and the adhesion rate of reaction products is often lower than at the center. Therefore, the thickness of the reaction products attached to the pattern sidewall may differ between the wafer center and the outer edge. Also, it is thought that differences in the shape and roughness of the sidewall will result in differences in feature quantities. In that case, even if the shape is the same, the material and surface roughness inside the pattern sidewall will differ, so the amount of secondary electrons emitted from the sidewall will also differ between the wafer center and the outer edge. In Figure 10, when feature quantity 3 is f, the etching parameters Ep1 and Ep2 differ between the wafer center and the wafer edge. If the etching parameter remains Ep1, a difference in feature quantity fg will occur, which is problematic, but to bring the wafer edge closer to the center, the etching parameter Ep1 of the wafer edge should be changed to Ep2.

[0039] Although embodiments of the present invention have been described above, the present invention is not limited to the embodiments described above, and various modifications are possible without departing from the spirit of the present invention. For example, in the embodiment, a flow was described in which etching parameters are controlled to eliminate differences in features by visualizing, normalizing, and calculating correlation coefficients of the feature distribution on the wafer. However, the visualization method, normalization method, and correlation coefficient calculation method described here are just examples.

[0040] Furthermore, although the above embodiments described the server as a component that controls etching parameters, it does not have to be a server; a virtual area, PC terminal, or mobile terminal may also be used, and similar effects can be achieved with communication methods other than SMB communication, such as FTP or NFS communication. Furthermore, although the above embodiments described an etching apparatus as an example of semiconductor manufacturing equipment, similar effects and advantages can be obtained with other manufacturing equipment, such as plasma CVD apparatus, ashing apparatus, surface modification apparatus, etc. Furthermore, although the above embodiments used CD-SEM as an example of a semiconductor inspection device, similar effects and advantages can be found with other inspection devices such as OCD, TEM, and XRR.

[0041] The following describes, but is not limited to, embodiments that may constitute the present invention. (Aspect 1) Based on correlation data between the change in characteristic quantities of the etching shape formed on the sample and the target value, and the etching parameters of the semiconductor manufacturing apparatus, the etching parameters are controlled so that the desired processing result of the semiconductor manufacturing apparatus can be obtained. The server is characterized in that the aforementioned feature quantities are values ​​obtained from secondary electron data from the surface of the sample or interference light data from the surface of the sample. (Aspect 2) The server according to embodiment 1, characterized in that the aforementioned feature quantity is a value obtained from the dimensions of the etched shape of the sample based on the secondary electron data or the interference light data. (Aspect 3) The server according to embodiment 1 or 2, characterized in that the amount of change is a value of spatial or temporal change. (Aspect 4) The server according to any one of embodiments 1 to 3, characterized in that the correlation data includes a value obtained from the integral value in the etching depth direction with respect to the amount of change relating to the dimensional difference between the etching shape and the target shape. (Appendix 5) The server according to embodiment 4, characterized in that the correlation data includes the difference between the etching parameter relating to the etching shape and the etching parameter relating to the target shape, and the integral value. (Aspect 6) The server according to embodiment 1, characterized in that, when the aforementioned feature quantities are obtained from the secondary electronic data, the feature quantities are adjusted by the acceleration voltage of the electron gun of the CD-SEM. (Aspect 7) The server according to any one of embodiments 1 to 6, characterized in that the sample has multiple films deposited on it. (Pattern 8) The server according to embodiment 3, characterized in that, when the amount of change is a value of spatial change, it is a value of change in the radial direction or the circumferential direction of the sample. (Aspect 9) The server according to any one of embodiments 1 to 8, characterized in that the correlation data includes a correlation coefficient for a predetermined etching parameter calculated from the visualization and normalization of the in-plane distribution of the sample for multiple features. (Aspect 10) The server according to embodiment 9, characterized in that it includes a database that stores data relating to combinations of features with high correlation coefficients and etching parameters. (Aspect 11) The server according to embodiment 10, characterized in that a combination of a feature with a high correlation coefficient and an etching parameter is identified from the database, and if the feature differs from the target value, the etching parameter is modified. (Aspect 12) The server according to embodiment 11, characterized in that the etching parameters are controlled by controlling the temperature of the sample. (Aspect 13) A semiconductor device manufacturing system characterized by comprising a server according to any one of embodiments 1 to 12. (Aspect 14) A step of obtaining feature quantities from secondary electron data from the surface of the sample or interference light data from the surface of the sample, A step of obtaining correlation data between the change in characteristic quantities of the etching shape formed on the sample and the target value, and the etching parameters of the semiconductor manufacturing apparatus, A step of controlling the etching parameters so that the desired processing result of the semiconductor manufacturing apparatus can be obtained based on the correlation data, A semiconductor device manufacturing method characterized by having the following features. [Explanation of Symbols]

[0042] 10...Semiconductor device manufacturing system, 101...PC for CD-SEM, 102...PC for semiconductor manufacturing equipment, 103...Server, 104...Semiconductor inspection equipment, 105...Semiconductor manufacturing equipment

Claims

1. Based on correlation data between the change in characteristic quantities of the etching shape formed on the sample and the target value, and the etching parameters of the semiconductor manufacturing apparatus, the etching parameters are controlled so that the desired processing result of the semiconductor manufacturing apparatus can be obtained. The aforementioned feature quantities are values ​​obtained from secondary electron data from the surface of the sample or interference light data from the surface of the sample. The server is characterized in that the correlation data includes a value obtained from the integral value in the etching depth direction of the amount of change relating to the dimensional difference between the etching shape and the target shape.

2. The server according to claim 1, characterized in that the aforementioned feature quantity is a value obtained from the dimensions of the etching shape of the sample based on the secondary electron data or the interference light data.

3. The server according to claim 1, characterized in that the amount of change is a value of spatial or temporal change.

4. The server according to claim 1, characterized in that the correlation data includes the difference between the etching parameter relating to the etching shape and the etching parameter relating to the target shape, and the integral value.

5. The server according to claim 1, characterized in that, when the feature quantities are obtained from the secondary electronic data, the feature quantities are adjusted by the acceleration voltage of the electron gun of the CD-SEM.

6. The server according to claim 1, characterized in that the sample has multiple films deposited on it.

7. The server according to claim 3, characterized in that, when the amount of change is a value of spatial change, it is a value of change in the radial direction or the circumferential direction of the sample.

8. The server according to claim 1, characterized in that the correlation data includes correlation coefficients for predetermined etching parameters calculated from the visualization and normalization of the in-plane distribution of the sample for multiple features.

9. The server according to claim 8, characterized in that it includes a database that stores data relating to combinations of features with high correlation coefficients and etching parameters.

10. The server according to claim 9, characterized in that a combination of a feature with a high correlation coefficient and an etching parameter is identified from the database, and if the feature differs from the target value, the etching parameter is modified.

11. The server according to claim 10, characterized in that the etching parameters are controlled by controlling the temperature of the sample.

12. A semiconductor device manufacturing system characterized by comprising the server described in claim 1.

13. A step of obtaining feature quantities from secondary electron data from the surface of the sample or interference light data from the surface of the sample, A step of obtaining correlation data between the change in characteristic quantities of the etching shape formed on the sample and the target value, and the etching parameters of the semiconductor manufacturing apparatus, The process includes controlling the etching parameters based on the correlation data so that a desired processing result for the semiconductor manufacturing apparatus can be obtained, A semiconductor device manufacturing method characterized in that the correlation data includes a value obtained from the integral value in the etching depth direction of the amount of change relating to the dimensional difference between the etching shape and the target shape.

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