Plasma processing / control device and plasma processing / control method

Abstract

The purpose of the present invention is to make it possible to estimate the thickness of an object to be processed, which is subjected to plasma etching processing, with high accuracy even if a spectral pattern prepared in advance and a spectral pattern measured during actual processing deviate from each other. Therefore, this plasma processing / control device compares a measurement spectrum obtained by receiving plasma reflected light from a processing chamber at any time during etching with an estimation spectrum obtained in advance in association with the thickness of the same object to be processed. Spectral errors are calculated between the measured spectrum and the plurality of spectrums for estimation, and the thickness of the object to be processed at the arbitrary point in time is estimated using the spectrum for estimation that takes at least a first minimum value among the plurality of spectral errors and the spectrum for estimation that takes a second minimum value among the plurality of spectral errors.

Description

Technical Field

[0001] This invention relates to a plasma processing / control apparatus and a plasma processing / control method. Background Technology

[0002] In semiconductor device manufacturing, dry etching using plasma is widely used as a process to remove unwanted parts. When the etched shape deviates from the design, the manufactured semiconductor may not achieve the desired performance. Therefore, process monitoring techniques are needed to monitor and stabilize the etching process. A process monitor that measures the residual film thickness and pattern depth on the wafer by measuring the reflected light from the wafer during processing is called a film thickness / depth monitor, used for endpoint determination of the etching process, etc.

[0003] In Patent Document 1, in order to monitor the film thickness and depth during the etching process, a spectrometer is used to detect the spectrum of plasma light reflected from the surface of the wafer being etched. Using pattern recognition techniques such as principal component analysis, the detected spectral data is compared with principal component analysis data of spectral data obtained in previous etching processes, and the endpoint of the plasma etching process is determined based on the current film thickness information obtained therefrom.

[0004] Furthermore, in Patent Document 2, a standard deviation pattern corresponding to multiple thicknesses is prepared using a pre-prepared wafer. The interference light obtained by etching the wafer is compared with the standard deviation pattern to calculate the deviation. The thickness of the film during the etching process is recorded based on this deviation, and the endpoint is determined when a given etching amount is reached. Moreover, in order to cope with the variation of interference light during etching, the film thickness is corrected using a regression line approximation or the like when the deviation does not meet the given conditions.

[0005] Prior art literature

[0006] Patent documents

[0007] Patent Document 1: Japanese Patent Application Publication No. 2001-244254

[0008] Patent Document 2: Japanese Patent Application Publication No. 2007-234666 Summary of the Invention

[0009] -The problem the invention aims to solve-

[0010] In recent years, with the development of miniaturization, new miniaturization processes for semiconductor devices have increased. Furthermore, there is a push for higher performance based on new materials and structures. Therefore, the development of mass production stabilization technologies for these new device manufacturing processes is essential, and the demand for high-precision monitoring of film thickness / depth is increasing.

[0011] However, both Patent Documents 1 and 2 are methods for monitoring the etching amount by comparing a pre-prepared spectral pattern with a measured spectral pattern of the wafer to be processed. If the timing of the spectral detection is different, the spectra will not be completely consistent and will deviate. Therefore, the calculated etching amount will also deviate. Furthermore, even if the etching conditions are the same, due to certain factors, such as changes in the environment of the processing chamber or changes in the etching rate, the spectral shape in the pre-prepared spectral pattern and the measured spectral pattern of the wafer to be processed will deviate at each etching time, resulting in changes in the calculated etching amount.

[0012] Therefore, the purpose of this invention is to provide a technique that, for objects subjected to plasma etching, can accurately estimate the thickness of the object to be processed and determine the endpoint of the processing even when the spectral pattern prepared in advance and the spectral pattern measured during the actual processing deviate due to differences in detection timing, etc.

[0013] -Methods for solving problems-

[0014] To address the aforementioned issues, a representative plasma processing / control apparatus of the present invention is a plasma processing / control apparatus that uses plasma formed in a processing chamber inside a vacuum container to etch a workpiece disposed in the processing chamber to a given thickness. This apparatus compares a measured spectrum obtained by receiving plasma reflected light from the processing chamber at any time during etching with an estimated spectrum obtained in advance for establishing a correspondence between the workpiece and the thickness, and calculates a spectral error between the measured spectrum and multiple estimated spectra. The apparatus includes a thickness estimation / determination unit that estimates the thickness of the workpiece at the given arbitrary time using an estimated spectrum (referred to as a "first minimum spectrum") that takes at least the first minimum value (first minimum value) of the multiple spectral errors, and an estimated spectrum (referred to as a "second minimum spectrum") that takes the second minimum value (second minimum value).

[0015] -Invention Effects-

[0016] According to the present invention, even if the spectral pattern prepared in advance and the spectral pattern measured during actual processing deviate due to differences such as detection timing, the thickness of the object to be processed can be estimated with high accuracy and the endpoint of the processing can be determined.

[0017] Other issues, structures, and effects not mentioned above will be clarified through the following description of the implementation methods. Attached Figure Description

[0018] Figure 1 This is a schematic diagram illustrating an example of the structure of the plasma processing / control apparatus in this embodiment.

[0019] Figure 2 This is a diagram illustrating an example of a spectrum obtained by detecting reflected light from plasma.

[0020] Figure 3 This is a schematic diagram showing an example of the structure of the thickness estimation / determination unit in this embodiment.

[0021] Figure 4 This is an example of a data list used when determining the thickness of an object being processed through previous spectral matching.

[0022] Figure 5 This is a graph that schematically illustrates the time dependence of film thickness errors generated in previous spectral matching.

[0023] Figure 6 This is an example of a data list of spectral errors for each estimated spectrum for a given measured spectrum.

[0024] Figure 7 It is a graph showing the relationship between film thickness and spectral error distribution.

[0025] Figure 8 This is a graph illustrating the method for estimating thickness based on the mixing ratio of the synthesized spectrum according to Example 1.

[0026] Figure 9 This is a flowchart of the thickness estimation process in Example 1.

[0027] Figure 10 This is a graph schematically illustrating the time dependence of the film thickness error generated when estimating the thickness in Example 1.

[0028] Figure 11 This is a graph illustrating the method of estimating thickness based on the approximate curve of Example 2-1.

[0029] Figure 12 This is a flowchart of the thickness estimation process in Example 2-1.

[0030] Figure 13 This is a diagram illustrating the method for estimating thickness using resampling processing according to Example 2-2.

[0031] Figure 14 This is a flowchart of the thickness estimation process in Example 2-2.

[0032] Figure 15 This is a graph representing outliers (white circles) and approximate curves generated by excluding outliers in Variation 1 of Example 2-1.

[0033] Figure 16This is a graph representing outliers (white circles) and approximate curves (solid lines) generated by excluding outliers in Variation 2 of Example 2-1.

[0034] Figure 17 This is an example of a data list supplemented by interpolation of film thickness and estimated spectral data in Example 3. Detailed Implementation

[0035] Hereinafter, embodiments of the present invention will be described using the accompanying drawings. However, the present invention is not limited to these embodiments. Furthermore, in the accompanying drawings, the same reference numerals are used to indicate the same parts.

[0036] <Structure of the Plasma Processing / Control Unit>

[0037] Figure 1 This is a schematic diagram illustrating a structural example of the plasma processing / control apparatus in this embodiment. The plasma processing apparatus 10 includes a processing chamber 11 capable of achieving a vacuum. Etching gas introduced into the chamber from a gas introduction unit (not shown) is excited and decomposed using electricity or microwaves generated by a high-frequency power supply (not shown), etc., to become plasma 12. This plasma 12 is used to etch a semiconductor wafer or other object to be processed, which is disposed on a sample stage 13 inside the processing chamber 11. The object to be processed, 14, is not particularly limited as long as it is an object to be etched; for example, an etch film (including a laminate) formed on a semiconductor wafer can be envisioned. In this disclosure, when describing the thickness of the object to be processed, it is sometimes referred to as the film thickness of the object to be processed. The gas introduction into the processing chamber 11, the generation and control of the plasma 12, and the application of voltage to the object to be processed, etc., are controlled by the control unit 23 (described later). Synchronization / timing adjustments are made between the various devices to achieve the desired etching process.

[0038] In the plasma processing apparatus 10, plasma light emitted from the plasma 12 during etching irradiates the workpiece 14. The irradiated light interferes with and is reflected depending on the surface structure of the workpiece. The plasma reflected light 15 emitted from the processing chamber is focused by a detection lens 16 and detected by a detection unit 17 via an optical fiber or the like. In the detection unit, the plasma reflected light 15 is split by a spectrometer that divides the light into a given wavelength band, and the amount (light intensity) of light at each wavelength is detected to obtain a spectrum (also called a "spectrum", "spectral pattern", etc.) with wavelength as the parameter. In the detected spectrum, a spectral pattern that varies depending on the film thickness is obtained. Alternatively, the wavenumber can be set as the parameter instead of the wavelength.

[0039] Figure 2 This is a diagram illustrating an example of a spectrum obtained by detecting reflected light from plasma. Figure 2(a) is a contour plot with the film thickness (nm) of the object to be treated on the horizontal axis and the wavelength (nm) on the vertical axis, and the spectral intensity (light intensity) divided by a pattern. Figure 2 (b) indicates dependence on a certain film thickness for cutting. Figure 2 A graph showing the spectral pattern of the wavelength at time (a). Spectral intensity, for example, the amount of light received per unit area by the detection unit 17 (W / cm²). 2 The measurement can be performed using one of these methods, but it is not limited to this; other methods, such as converting the detected total light intensity into the number of electrons, can also be used. This allows for confirmation of the correlation between film thickness and spectral pattern.

[0040] The spectrum detected by the detection unit 17 is processed by the signal processing unit 20 into a shape that is easy to monitor. Specifically, processing such as light intensity shift and high-frequency noise removal is performed. The signal-processed spectrum is used as an indicator for the thickness estimation / determination unit 21 to determine the film thickness and depth of the film to be processed, estimating the film thickness, depth, and etching amount corresponding to the spectrum. The values ​​estimated by the thickness estimation / determination unit 21 are not particularly limited as long as the dimension of the thickness direction (the direction perpendicular to the horizontal plane of the upper surface of the sample stage 13) of the object to be processed can be directly or indirectly known. The values ​​can be the thickness (i.e., remaining thickness), depth, etching amount, etc. of the film to be processed. In this disclosure, unless otherwise specified, the thickness (remaining thickness), depth, and etching amount of the object to be processed are collectively referred to as "thickness".

[0041] The estimated thickness value is displayed by the display unit 22, such as a monitor or printer. Furthermore, if the value estimated by the thickness estimation / determination unit 21 is determined to be the target etching film thickness, the etching process of the object 14 is terminated by the control unit 23.

[0042] In addition to the plasma processing unit 10, the plasma processing / control apparatus 30 also includes a signal processing unit 20, a thickness estimation / determination unit 21, and a control unit 23.

[0043] Further explanation of the thickness estimation / judgment unit 21. Figure 3This is a schematic diagram illustrating a structural example of the thickness estimation / determination unit in this embodiment. Plasma reflected light 15 from the object whose thickness is to be measured is transmitted via the detection unit 17 and the signal processing unit 20 as a wavelength-dependent spectrum (referred to as the "measurement spectrum") to the thickness estimation / determination unit 21. In the comparison / calculation unit 25, as described later, a comparison of the spectra is performed, and a calculation is performed to estimate the thickness of the object to be processed, determining whether the target etch film thickness has been achieved. The spectra used for comparison are stored in the database unit 24. For example, the database unit 24 prepares a test wafer identical to the semiconductor wafer of the object to be processed 14, performs an etching process under the same conditions beforehand, and thereby stores multiple spectra (collectively referred to as "estimated spectra"). Furthermore, by pre-measuring the film thickness of the test wafer before and after etching, a correspondence between the spectra and film thickness stored in the database unit 24 is established. Alternatively, multiple pre-measured test wafers can be prepared, and a database of spectra obtained from different etching conditions (formulas) can be created and added to the database unit 24. The thickness data of the object to be processed, estimated by the comparison / calculation unit 25, or the determination data based on the thickness, is sent to the display unit 22 and the control unit 23.

[0044] In the comparison / computation unit 25, program processing by a processor such as a CPU is executed. The database unit 24 includes a random access semiconductor memory, storage device, or storage medium (either volatile or non-volatile) for storing data or programs (applications). The processor and memory of the thickness estimation / determination unit 21 can be installed as a single unit, or they can be designed to be integrated with the processors and memories of other functional units included in the ion processing / control device, such as the signal processing unit 20 and the control unit 23, and execute each function via software. These functional units are connected via wired or wireless means.

[0045] <Previous Spectral Matching>

[0046] First, the method of determining thickness through spectral matching, which has been performed in the past, is described. Figure 4 This is an example of a data list previously used to determine the thickness of an object being processed through spectral matching. Figure 4 (a) The estimated spectrum data list stored in the database section 24 is used to represent the time T characterized by the detection timing interval ΔT. n Nearby, the corresponding film thickness data were established using spectra (I). Figure 4 (b) presents a list of measured spectra at actual measurement times to represent the measured spectra (I') and actual film thickness data near time T'j, characterized by detection timing intervals ΔT'. Furthermore, Figure 4(c) represents the measured spectrum and the estimated spectrum for which spectral matching is established, the film thickness determined through matching, and the film thickness error at that time. However, data at time T or T' are not required.

[0047] There are no particular limitations on the method of spectral matching; for example, the measured spectrum I'j at the search and measurement time T'j (refer to...) Figure 4 When matching the estimated spectrum of (b)), it is compared with all estimated spectra recorded in the data list library (refer to...). Figure 4 The values ​​obtained by comparing (a) with each other by summing the absolute value of the difference or the square of the difference with respect to wavelength, are considered a match when the minimum value is reached. Figure 4 In example (c), the film thickness Dn of the spectrum In is used to determine the film thickness at time T'j, which is the presumption that the match is true.

[0048] but, Figure 4 The thickness determined in (c) is inaccurate relative to the actual thickness. The actual film thickness measured during the experiment is as follows: Figure 4 The film thickness error expressed as in (b) can be as follows Figure 4 It is schematically represented by ΔD as in (c). Figure 5 This is a graph schematically illustrating the time dependence of film thickness error generated in previous spectral matching. It shows that the film thickness error varies in a stepwise manner due to different detection timings.

[0049] <Related assumptions about the implementation method>

[0050] Next, the method for estimating thickness in an embodiment of the present invention will be described. In this embodiment, when estimating the thickness when the measured spectrum is I'j(λ), the thickness estimation / determination unit 21 calculates the spectral error ΔSn between I'j(λ) and the estimation spectrum In(λ) stored in the database unit 24. ΔSn is calculated, for example, by the following formula (1).

[0051] [Mathematical Expression 1]

[0052]

[0053] However, the definition of spectral error is not limited to anything that is useful as an indicator. For example, it could be the value obtained by summing the absolute values ​​of the differences with respect to wavelength. Alternatively, it could be their square root or logarithm.

[0054] Figure 6 This is an example of a data list showing the spectral error of each estimated spectrum relative to a given measured spectrum. Figure 6 In this process, the data list is temporarily stored in the database section 24, from which the distribution relationship between film thickness and spectral error corresponding to each estimated spectrum is obtained. Figure 7This is a graph showing the relationship between film thickness and spectral error distribution. In Figure 7 The following relationship can be observed in the example: the spectral error ΔSn is minimal when the film thickness Dn is small compared to the estimated spectrum In(λ), and the spectral error increases as the film thickness becomes larger (or smaller).

[0055] In this embodiment, the correlation between film thickness and spectral error is estimated based on the discrete distribution relationship between the two. The ΔSmin value, which minimizes the spectral error under the relevant correlation, is then calculated, and the thickness Dmin at this point is estimated as the thickness relative to the measured spectrum I'j(λ). The specific estimation method is illustrated through the following examples.

[0056] [Example 1]

[0057] In Example 1, the thickness was estimated based on the spectral error between the synthesized spectrum obtained by estimating the mixing ratio and the measured spectrum. Figure 8 This is a graph illustrating the method for estimating thickness based on the mixing ratio of the synthesized spectrum according to Example 1. Figure 7 Under the distribution relationship shown, the synthesized spectrum when the estimated spectrum In(λ) and the estimated spectrum In+1(λ), ​​which are the first minimum value (first minimum value) ΔSn and the second minimum value (second minimum value) ΔSn+1, are synthesized at a mixing ratio α, is obtained by the following formula (2).

[0058] [Mathematical Expression 2]

[0059]

[0060] Therefore, the spectral error between the synthesized spectrum and the measured spectrum I'j(λ) is represented by the following equation (3), and it is expected that the spectral error ΔSmin will be smaller than the first minimum value ΔSn and the second minimum value ΔSn+1.

[0061] [Mathematical Expression 3]

[0062]

[0063] Then, by differentiating ΔSmin with α using the following equation (4), the minimum value α0 of α is obtained.

[0064] [Mathematical Expression 4]

[0065]

[0066] Therefore, as shown in Equation (5) below, the thickness Dmin, which is the film thickness Dn of the estimated spectrum In (λ) and the film thickness Dn+1 of the estimated spectrum In+1 (λ), is calculated with the minimum value α0 and estimated as the thickness of the measured spectrum I'j (λ).

[0067] [Mathematical Expression 5]

[0068]

[0069] Thus, it is possible to estimate the thickness with high precision corresponding to a synthetic spectral pattern whose spectral error is smaller than the first minimum value.

[0070] The processing steps for estimating the thickness of the object to be processed in Example 1 are explained. Figure 9 This is a flowchart of the thickness estimation process in Example 1.

[0071] First, the etching process of the target wafer is evaluated, and the thickness estimation process is also started (S101).

[0072] Next, the spectrum of the plasma reflected light 15 from the processing chamber 11 is measured using the detection unit 17 (S102).

[0073] Next, the signal processing unit 20 processes the signal of the measured spectrum for monitoring (S103).

[0074] Next, in the thickness estimation / judgment unit 21, the spectral error ΔS between the measured spectrum and the estimation spectrum is calculated, and the result is obtained. Figure 7 The data showing the relationship between spectral error and thickness distribution (S104).

[0075] Next, in the thickness estimation / determination unit 21, a synthetic spectrum of the mixing ratio α is synthesized based on the estimated spectrum with the first and second minimum spectral errors, and the estimated film thickness value Dmin is calculated based on the minimum value of α (S105).

[0076] Next, in the thickness estimation / determination unit 21, it is determined whether the estimated film thickness reaches the target film thickness (S106). If it does not reach the target, the process returns to S102, and the thickness estimation is repeated with a new measurement spectrum.

[0077] If the target film thickness is determined to be reached in S106, the etching process is stopped by the control unit 23, and the thickness estimation process also ends (S107).

[0078] Figure 10 This is a graph schematically illustrating the time dependence of film thickness error generated when estimating the thickness in Example 1. The solid line represents the time dependence of Example 1, and the dashed line represents previous examples (see reference). Figure 5 The time dependence of ). According to Figure 10 It can be seen that, compared with the previous method of determining film thickness by spectral matching, the method of estimating the minimum thickness by adjusting the mixing ratio of the synthetic spectrum of the first and second minimum values ​​generally reduces the film thickness error.

[0079] [Example 2-1]

[0080] In Example 2-1, at least the distribution relationship between the spectral error of the first to third minimum values ​​(minimum 3 points) and the film thickness is used to calculate an approximate curve and estimate the thickness. Figure 11 This is a graph illustrating the method for estimating thickness based on the approximate curve of Example 2-1. Figure 11 The example shown illustrates the generation of an approximate curve F(D) based on the distribution relationship between six spectral errors (minimum 6 points) from the first to the sixth minimum values ​​and the film thickness. The approximate curve F(D) is not particularly limited and can use a function of order 2 or higher, automatically generated corresponding to parameters that are preset based on conditions such as the plasma etching process (formula), the thickness of the object being processed (film thickness), and the calculated estimation accuracy. Alternatively, a method using past data as training data to generate / update the approximate curve through machine learning can also be considered.

[0081] Based on the approximate curve F(D), the value of Dmin corresponding to the minimum spectral error ΔSmin is calculated, and Dmin is estimated as the thickness of the measured spectrum I'j(λ). Thus, a highly accurate estimation of the thickness corresponding to a spectral pattern with a spectral error smaller than the first minimum value is achieved.

[0082] The processing steps for estimating the thickness of the object to be processed in Example 2-1 are explained. Figure 12 This is a flowchart of the thickness estimation process in Example 2-1.

[0083] First, the etching process of the target wafer is evaluated, and the thickness estimation process is also started (S201).

[0084] Next, the spectrum of the plasma reflected light 15 from the processing chamber 11 is measured using the detection unit 17 (S202).

[0085] Next, the signal processing unit 20 processes the signal of the measured spectrum for monitoring (S203).

[0086] Next, in the thickness estimation / judgment unit 21, the spectral error ΔS between the measured spectrum and the estimation spectrum is calculated, and the result is obtained. Figure 7 The data showing the relationship between spectral error and thickness distribution (S204).

[0087] Next, in the thickness estimation / determination unit 21, the spectral error of the minimum N point is approximated by a curve, and the minimum spectral error ΔSmin and the film thickness estimation value Dmin associated with it are calculated (S205).

[0088] Next, in the thickness estimation / determination unit 21, it is determined whether the estimated film thickness reaches the target film thickness (S206). If it does not reach the target, the process returns to S202, and the thickness estimation is repeated with a new measurement spectrum.

[0089] If the target film thickness is determined to be reached in S206, the etching process is stopped by the control unit 23, and the thickness estimation process also ends (S207).

[0090] [Example 2-2]

[0091] In Example 2-2, the thickness is estimated by resampling, based at least on the distribution relationship between the spectral error of the first to third minimum values ​​(minimum 3 points) and the film thickness. Figure 13 This is a diagram illustrating the method for estimating thickness using resampling processing according to Example 2-2. Figure 13 In the diagram, the distribution of the six spectral errors (minimum six points) and film thickness data points (black dots) from the first to sixth minimum values ​​(minimum six points) is shown. New data points (white circles) are added between the data points marked with black dots through resampling. Figure 13 In the example, five times the number of data points are added to the data points of the black dots through resampling. The resampling method is not particularly limited; it is automatically generated based on parameters that determine the number and location of resampled points. These parameters are preset based on conditions such as the plasma etching process (formula), the thickness of the object being processed (film thickness), and the estimated accuracy. The number of data points added in the resampling can also be considered from the perspective of computational cost. Alternatively, a method could be considered that uses past data as training data to generate / update resampled data through machine learning.

[0092] Based on the resampled data points, Dmin is calculated corresponding to ΔSmin, which represents the minimum spectral error. Dmin is then used to estimate the thickness of the measured spectrum I'j(λ). This allows for the estimation of a high-precision thickness corresponding to a spectral pattern with a spectral error smaller than the first minimum.

[0093] Furthermore, the interpolation based on the curve (Example 2-1) has the following characteristics: the texture is finer compared to the point (Example 2-2), but on the other hand, the interpolation is constrained to a curve shape. After obtaining the distribution relationship between spectral error and film thickness, whether to estimate ΔSmin and ΔDmin through curve approximation (Example 2-1) or through resampling processing (Example 2-2) can be appropriately used according to their respective characteristics and distribution conditions.

[0094] The processing steps for estimating the thickness of the object to be processed in Example 2-2 are explained. Figure 14 This is a flowchart of the thickness estimation process in Example 2-2.

[0095] First, the etching process of the target wafer is evaluated, and the thickness estimation process is also started (S301).

[0096] Next, the spectrum of the plasma reflected light 15 from the processing chamber 11 is measured using the detection unit 17 (S302).

[0097] Next, the signal processing unit 20 processes the signal of the measured spectrum for monitoring (S303).

[0098] Next, in the thickness estimation / judgment unit 21, the spectral error ΔS between the measured spectrum and the estimation spectrum is calculated, and the result is obtained. Figure 7 The data showing the relationship between spectral error and thickness distribution (S304).

[0099] Next, in the thickness estimation / judgment unit 21, based on the minimum N-point spectral error, the minimum spectral error ΔSmin and the associated film thickness estimation value Dmin are calculated through resampling processing (S305).

[0100] Next, in the thickness estimation / determination unit 21, it is determined whether the estimated film thickness reaches the target film thickness (S306). If it does not reach the target, the process returns to S302, and the thickness estimation is repeated with a new measurement spectrum.

[0101] If the target film thickness is determined to be reached in S306, the etching process is stopped by the control unit 23, and the thickness estimation process also ends (S307).

[0102] [Modification 1 of the embodiment]

[0103] In plasma processing equipment, the environment inside the processing chamber may become temporarily unstable due to some reason, which may cause spectral pattern distortion. In this case, outliers may sometimes be generated in the spectral error. Figure 15 This is a graph showing outliers (white circles) and approximate curves generated after excluding outliers, in Variation 1 of Example 2-1. Figure 15 The example shown is an example where the spectral error ΔSn is small due to the similarity of the accidental spectral patterns.

[0104] In Modification 1, outliers are identified, for example, by sequentially calculating the rate of change (differential) of the spectral error, and identifying outliers when their values ​​reverse or jump discontinuously. In each embodiment, spectral errors identified as outliers in Modification 1 are excluded before synthesizing the synthetic spectrum, generating approximate curves, or performing resampling.

[0105] [Modification 2 of the embodiment]

[0106] and Figure 15Similarly, Figure 16 This is a graph representing outliers (white circles) and approximate curves (solid lines) generated after excluding outliers, in Variation 2 of Example 2-1. Figure 16 The example shown is an instance where the spectral error ΔSSn-1 is large due to significant accidental distortion of the spectral pattern.

[0107] The outlier determination in Variation Example 2 is performed as follows: The fitting error between the approximate curve F(D) (solid line) generated by sequentially excluding the spectral error ΔS from ΔSn-4 and the approximate curve F'(D) (dashed line) containing the generated approximate curve is calculated. The larger ΔS (in...) represents the outlier. Figure 16 The value ΔSn-1 is identified as an outlier. The fitting error is obtained, for example, by summing the absolute value or the square of the difference between F(D) and F'(D) with respect to the film thickness D. Alternatively, in the determination of Variation 1, values ​​with large deviations can be excluded, and Variation 2 can be applied to values ​​requiring subtle determination, whereby the fitting error is used to determine whether it is an outlier. In each embodiment, spectral errors identified as outliers in Variation 2 are excluded when synthesizing synthetic spectra, generating approximate curves, or resampling.

[0108] [Example 3]

[0109] It is believed that the more film thickness and estimated spectrum data contained in the data list of estimated spectra stored in the database section 24, the higher the accuracy of the thickness estimation (the lower the film thickness error). On the other hand, there are also labor and financial constraints in preparing the same processed object to be tested in advance to measure the film thickness and spectrum. Therefore, in Example 3, data is supplemented by interpolation from existing data. Figure 17 This is an example of a data list supplemented by interpolation of the film thickness and estimated spectrum data in Example 3. Figure 17 (a) is a list of pre-measured and stored data (measured and estimated data) of film thickness and spectra in database section 24 (see reference). Figure 4 (a)). Figure 17 (b) is a list supplementing the measured estimation data with data on film thickness calculated by interpolation and estimation spectra (interpolation estimation data). Figure 17 In the example, three data points were added between the measured inference data points through interpolation. Figure 17 (b) shows an example of interpolation of film thickness using a linear approximation, but for the estimated spectrum, the value obtained by interpolating the value of the light quantity (light intensity) of the spectrum using a linear approximation can also be used for each wavelength.

[0110] Used in Figure 17The estimation data list created in (b) is used to estimate the thickness of the object being processed through the above-described embodiments 1 and 2. Therefore, by increasing the amount of data, it is expected that the estimation accuracy of each embodiment will be improved.

[0111] <Function / Effect>

[0112] Thus, in this embodiment, even if the measured spectrum deviates from the pre-prepared estimated spectrum, the film thickness of the measured spectrum is not simply considered as the film thickness of the estimated spectrum that matches the established spectrum. Instead, the correlation is found based on the distribution relationship of the spectral error, and the film thickness with the smallest possible spectral error is estimated. This allows for high-precision estimation of the thickness, and consequently, high-precision determination of the end of the etching process.

[0113] Furthermore, since no hardware changes to the plasma processing device are required in the relevant estimations, changes to the estimation method and the supplementation of the estimation data list based on interpolation can also be implemented through software, thus enabling flexible design changes and adjustments.

[0114] The embodiments of the present invention have been described above, but the present invention is not limited to the above embodiments, and various modifications can be made without departing from its spirit. For example, the above embodiments are described in detail for the purpose of easily understanding the present invention, and are not necessarily limited to having all the structures described. Furthermore, a part of the structure of one embodiment can be replaced with the structure of another embodiment, and the structure of another embodiment can be added to the structure of one embodiment. In addition, with respect to a part of the structure of each embodiment, other structures can be added / deleted / replaced.

[0115] The following description can be the content of this invention, but is not limited thereto.

[0116] (Method 1)

[0117] A plasma processing / control apparatus etches a workpiece disposed in a processing chamber inside a vacuum container to a given thickness using plasma formed in the processing chamber. It compares a measured spectrum obtained by receiving plasma reflected light from the processing chamber at any time during etching with an estimated spectrum obtained in advance to establish a correspondence between the thickness and the workpiece being processed, and calculates a spectral error between the measured spectrum and a plurality of estimated spectra. The apparatus includes a thickness estimation / determination unit that estimates the thickness of the workpiece at the given arbitrary time using an estimated spectrum that takes at least the first minimum value (referred to as a "first minimum spectrum") and an estimated spectrum that takes the second minimum value (referred to as a "second minimum spectrum") among the plurality of spectral errors.

[0118] (Method 2)

[0119] According to the plasma processing / control apparatus of method 1, the thickness estimation / determination unit uses the spectral error calculated between the synthesized spectrum synthesized from the first minimum spectrum and the second minimum spectrum, taking into account the mixing ratio, to estimate the thickness of the object to be processed at any given time.

[0120] (Method 3)

[0121] According to the plasma processing / control apparatus of method 1, the thickness of the object to be processed at any given time is estimated using an estimated spectrum (referred to as the "third minimum spectrum") that takes at least a third minimum value among a plurality of said spectral errors. The thickness of the object to be processed at any given time is estimated using an approximate curve automatically generated based at least on the first to third minimum values ​​and the thickness of the object to be processed corresponding to the first to third minimum spectra.

[0122] (Method 4)

[0123] According to the plasma processing / control apparatus of method 1, the thickness of the object to be processed at any given time is estimated using a spectra that takes at least a third minimum value (referred to as the "third minimum spectrum") of a plurality of said spectral errors, at least based on the first to third minimum values ​​and the thickness of the object to be processed corresponding to the first to third minimum spectra, by means of resampling processing.

[0124] (Method 5)

[0125] According to any one of the plasma processing / control apparatuses of methods 1 to 4, the spectral error is a value obtained by summing the squares of the differences in light intensity of the wavelength pairs being compared.

[0126] (Method 6)

[0127] A plasma processing / control method is a plasma processing / control method that uses plasma formed in the processing chamber to etch a workpiece disposed inside a vacuum container to a given thickness. In a thickness estimation / determination unit, a measurement spectrum obtained by receiving plasma reflected light from the processing chamber at any time during etching is compared with an estimated spectrum of the workpiece obtained in advance for establishing a correspondence between the thickness and the workpiece. A spectral error is calculated between the measurement spectrum and a plurality of estimated spectra. The thickness of the workpiece at the arbitrary time is estimated using an estimated spectrum that takes at least the first minimum value (first minimum value) of the plurality of spectral errors (referred to as "first minimum spectrum") and an estimated spectrum that takes the second minimum value (second minimum value) of the plurality of spectral errors (referred to as "second minimum spectrum").

[0128] (Method 7)

[0129] According to the plasma processing / control method of method 6, in the thickness estimation / determination unit, the thickness of the object to be processed at any given time is estimated using the spectral error calculated between the synthesized spectrum synthesized from the first minimum spectrum and the second minimum spectrum taking into account the mixing ratio and the measured spectrum.

[0130] (Method 8)

[0131] According to the plasma processing / control method of method 6, the thickness of the object to be processed at any given time is estimated using an estimated spectrum (also called the "third minimum spectrum") that takes at least a third minimum value among a plurality of said spectral errors. The thickness of the object to be processed at any given time is estimated using an approximate curve automatically generated based at least on the first to third minimum values ​​and the thickness of the object to be processed corresponding to the first to third minimum spectra.

[0132] (Method 9)

[0133] According to the plasma processing / control method of method 6, the thickness of the object to be processed at any given time is estimated by using a spectra that takes at least a third minimum value (referred to as the "third minimum spectrum") from a plurality of said spectral errors, at least based on the first to third minimum values ​​and the thickness of the object to be processed corresponding to the first to third minimum spectra, and by using resampling processing.

[0134] (Method 10)

[0135] According to any one of methods 6 to 9, the plasma processing / control method wherein the spectral error is a value obtained by summing the squares of the differences in light intensity of the compared spectra.

[0136] -Explanation of Figure Markers-

[0137] 10: Plasma treatment device

[0138] 11: Processing Room

[0139] 12: Plasma

[0140] 13: Sample Stage

[0141] 14: Processing objects

[0142] 15: Plasma reflected light

[0143] 16: Detection Lens

[0144] 17: Testing Department

[0145] 20: Signal Processing Department

[0146] 21: Thickness estimation / judgment section

[0147] 22: Display Section

[0148] 23: Control Department

[0149] 24: Database Department

[0150] 25: Comparison / Arithmetic Unit

[0151] 30: Plasma treatment / control device.

Claims

1. A plasma processing / control apparatus for etching an object disposed within a processing chamber inside a vacuum container to a given thickness using plasma formed in the processing chamber. The plasma processing / control device is characterized in that... The measured spectrum, obtained by receiving plasma reflected light from the processing chamber at any moment during etching, is compared with a pre-observed spectrum that establishes a correspondence between the same processing object and thickness. The spectral error is calculated between the measured spectrum and the plurality of pre-observed spectra. The plasma processing / control apparatus includes a thickness estimation / determination unit that estimates the thickness of the object to be processed at any given time using an estimation spectrum called a "first minimum spectrum" which takes at least the first minimum value among a plurality of spectral errors, and an estimation spectrum called a "second minimum spectrum" which takes the second minimum value.

2. The plasma treatment / control apparatus according to claim 1, wherein, The thickness estimation / determination unit uses the spectral error calculated between the synthesized spectrum, which is synthesized from the first minimum spectrum and the second minimum spectrum taking into account the mixing ratio, and the measured spectrum to estimate the thickness of the object to be processed at any given time.

3. The plasma treatment / control apparatus according to claim 1, wherein, Using an estimated spectrum called the "third minimum spectrum" which takes at least a third minimum value among the plurality of spectral errors, the thickness of the object to be processed at any given time is estimated using an approximate curve automatically generated based at least on the first minimum value to the third minimum value and the thickness of the object to be processed corresponding to the first minimum spectrum to the third minimum spectrum.

4. The plasma treatment / control apparatus according to claim 1, wherein, Using an estimated spectrum called the "third minimum spectrum" which takes at least a third minimum value among the plurality of spectral errors, the thickness of the object to be processed at any given time is estimated by resampling, based at least on the first minimum value to the third minimum value and the thickness of the object to be processed corresponding to the first minimum spectrum to the third minimum spectrum.

5. The plasma treatment / control apparatus according to any one of claims 1 to 4, wherein, The spectral error is a value obtained by summing the squares of the differences in light intensity between the wavelength pairs being compared.

6. A plasma processing / control method, using plasma formed in a processing chamber inside a vacuum container to etch an object to be processed, disposed within the processing chamber, to a given thickness. In the thickness estimation / determination unit, a measurement spectrum obtained by receiving plasma reflected light from the processing chamber at any moment during etching is compared with an estimated spectrum of a processed object obtained in advance to establish a correspondence between the processed object and the thickness. The spectral error is calculated between the measurement spectrum and the plurality of estimated spectra. The thickness of the object being processed at any given time is estimated using an estimated spectrum that takes at least the first minimum value among the plurality of spectral errors, referred to as the "first minimum spectrum", and an estimated spectrum that takes the second minimum value, referred to as the "second minimum spectrum".

7. The plasma treatment / control method according to claim 6, wherein, In the thickness estimation / determination unit, the thickness of the object to be processed at any given time is estimated using the spectral error calculated between the synthesized spectrum, which is synthesized from the first minimum spectrum and the second minimum spectrum taking into account the mixing ratio, and the measured spectrum.

8. The plasma treatment / control method according to claim 6, wherein, Using an estimated spectrum called the "third minimum spectrum" which takes at least a third minimum value among the plurality of spectral errors, the thickness of the object to be processed at any given time is estimated using an approximate curve automatically generated based at least on the first minimum value to the third minimum value and the thickness of the object to be processed corresponding to the first minimum spectrum to the third minimum spectrum.

9. The plasma treatment / control method according to claim 6, wherein, Using an estimated spectrum called the "third minimum spectrum" which takes at least a third minimum value among the plurality of spectral errors, the thickness of the object to be processed at any given time is estimated by resampling, based at least on the first minimum value to the third minimum value and the thickness of the object to be processed corresponding to the first minimum spectrum to the third minimum spectrum.

10. The plasma treatment / control method according to any one of claims 6 to 9, wherein, The spectral error is a value obtained by summing the squares of the differences in light intensity between the wavelength pairs being compared.

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