JP2003264179A - Method for detecting end of seasoning and plasma treatment method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To solve the problem of prior art analytic data that it is difficult to ascertain whether a variation becoming the decision criterion of the end of seasoning is a variation due to seasoning, i.e., a variation based on the state change in a treatment container, or a variation based on the temperature variation between dummy wafers and thereby it is difficult to make a decision whether seasoning has ended or not. <P>SOLUTION: The method for detecting the end of seasoning when seasoning is performed by supplying dummy wafers W into the treatment container 2 of a plasma treatment system 1 comprises a step for supplying the dummy wafers W into the treatment container 2, cooling the inside of the treatment container 2, and performing multivariate analysis using a plurality of data obtained when a plurality of dummy wafers W are supplied again into the treatment container 2 to formulate a formula for predicting the end of seasoning, and a step for detecting the end of seasoning when seasoning is performed based on the prediction formula. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a seasoning completion detecting method for a processing apparatus such as an etching processing apparatus and a plasma processing method using the seasoning completion detecting method.

[0002]

2. Description of the Related Art A processing apparatus such as an etching processing apparatus comprises a processing container having an airtight structure and a holder arranged in the processing container for holding an object to be processed, and plasma is generated in the processing container. Then, the object is subjected to a predetermined process. When the processing of the object to be processed is continued, the inside of the processing container is contaminated with by-products and the like, and the internal parts are consumed. Therefore, the processing apparatus is temporarily stopped, and maintenance such as cleaning of the inside of the processing container and replacement of consumables is performed. Then, after the maintenance is completed, the processing device is restarted.

For example, in the case of an etching processing apparatus, when restarting, a predetermined number of dummy wafers are supplied into the processing container and the etching cycle is repeated to arrange the inside of the processing container to a state required at the time of production, so-called seasoning. To do. After the completion of seasoning, the etching rate and the uniformity of etching on the wafer surface are examined. Measurement data obtained from multiple dummy wafers during seasoning,
For example, data analysis is performed using the measurement data of the emission spectrum obtained by the end point detector. Then, by observing the change in the analysis data, it is determined whether or not the seasoning is completed.

[0004]

However, in the conventional analysis data, whether the change which is the criterion for judging the end of seasoning is the change due to the seasoning, that is, the change due to the state change in the processing container, or the temperature between the dummy wafers is changed. There is a problem that it is difficult to determine whether the change is based on the change, and it is difficult to judge whether the seasoning is finished.

That is, the present inventors analyzed the measured data, for example, by using the principal component analysis, which is one of the multivariate analysis, as described later, and in the analysis result, a large peak showing a change was found. Two things are recognized, and it is difficult to judge whether the seasoning has ended. Therefore, this principal component analysis will be described. In this case, the measurement data is collected by the same method as the conventional one. For example, 130 dummy wafers were supplied on the first day, and on the second day, the production process was started and 30 dummy wafers were supplied to perform etching. A principal component analysis was performed using measurement data of emission spectra obtained from the 51st to 60th dummy wafers and the 121st to 130th dummy wafers on the first day, respectively, and FIG.
The analysis results shown in (b) and (a) and (b) of FIG. 9 were obtained. In this principal component analysis, 19 of the emission spectra
Using 297 kinds of wavelengths in the short wavelength region of 3 nm to 419 nm, each wavelength intensity was measured 18 times every 3 seconds for 1 minute for one dummy wafer, and principal component analysis was performed based on these measurement data. It was Then, the principal component scores and residuals at each measurement are obtained, respectively, and the HOTELLINGS TSQUARE
A plot of (sum of squares of principal component scores) is shown in (a) of each figure, and a plot of sum of squares of residuals (residual scores) is shown in (b) of each figure. As is clear from the results of these analyses, a large peak is observed in both the data on the first day and the data on the second day in any of the graphs, making it difficult to judge the end of seasoning. The horizontal axis of each graph shows the number of measurements.

The present invention has been made to solve the above problems, and an object of the present invention is to provide a seasoning end detection method and a plasma processing method capable of clearly determining the end of seasoning.

[0007]

As a result of various studies on the cause of the two peaks, the inventors of the present invention have found that the method of collecting measurement data used for data analysis has a cause. Therefore, it was discovered that by applying a specific treatment to the processing container when collecting data, the effect of temperature changes between dummy wafers can be eliminated, the changes due to seasoning can be reliably grasped, and the end of seasoning can be reliably determined. Got

The present invention has been made on the basis of the above findings, and the seasoning completion detecting method according to claim 1 of the present invention performs a seasoning by supplying a test object to be processed into a processing container of a processing apparatus. In the method of detecting the end of the seasoning in the case, after supplying the test object in the processing container, after cooling the inside of the processing container, a plurality of the test object in the processing container again Perform multivariate analysis using multiple measurement data obtained when supplying,
The method is characterized by having a step of creating a prediction formula for predicting the end of the seasoning and a step of detecting the end of the seasoning when performing the seasoning based on the prediction formula.

The seasoning completion detecting method according to a second aspect of the present invention is the method according to the first aspect, wherein:
It is characterized in that a principal component analysis is used as the multivariate analysis.

The seasoning completion detecting method according to a third aspect of the present invention is characterized in that, in the invention according to the first or second aspect, the emission spectrum of plasma is used as the measurement data. is there.

A seasoning end detecting method according to a fourth aspect of the present invention is the method according to the third aspect, wherein
Among the wavelengths of the emission spectrum, a wavelength having a high contribution rate to the residual is used.

The seasoning completion detecting method according to a fifth aspect of the present invention is characterized in that, in the invention according to the first or second aspect, a high frequency voltage obtained by a VI probe is used as the measurement data. To do.

Further, a seasoning completion detecting method according to a sixth aspect of the present invention is characterized in that, in the invention according to the first or second aspect, a high frequency current obtained by a VI probe is used as the measurement data. To do.

The seasoning end detecting method according to claim 7 of the present invention is the method according to claim 1 or 2, wherein the phase difference between a high frequency voltage and a high frequency current obtained by a VI probe as the measurement data. It is characterized by using.

The plasma processing method according to claim 8 of the present invention comprises the step of detecting the end of seasoning by using the seasoning end detecting method according to any one of claims 1 to 7. And a step of performing plasma treatment.

[0016]

BEST MODE FOR CARRYING OUT THE INVENTION The present invention will be described below based on the embodiments shown in FIGS. As shown in FIG. 1, for example, the plasma apparatus 1 of the present embodiment has a processing container 2 whose surface can be maintained at a desired high degree of vacuum and whose surface is anodized and electrically grounded, and this processing container 2. A lower electrode 3 which is disposed in the center of the bottom surface of the inside and on which an object to be processed (for example, a wafer) W is mounted; The support 4 is provided, and the upper electrode 5 is formed in a hollow shape and is disposed with a gap from the lower electrode 3. The lower electrode 3 is provided with a high frequency power source 6 of 2 MHz, for example, a matching unit 6A.
A high frequency power source 7 having a frequency higher than that of the lower electrode 3, for example 60 MHz, is connected to the upper electrode 5 via a matching unit 7A. A high-pass filter 8 is connected to the lower electrode 3, and a low-pass filter 9 is connected to the upper electrode 5. An exhaust device 11 is connected to an exhaust port 2B on the bottom surface of the processing container 2 via a gas exhaust pipe 11A. The exhaust device 11 evacuates the processing container 2 to maintain a desired degree of vacuum. In the description below, the lower electrode 3 and the support 4 will be collectively referred to as a mounting table 10 as necessary.

At the center of the upper surface of the upper electrode 5, a gas introducing pipe 5A is provided.
Is formed, and the gas introduction pipe 5A penetrates the center of the upper surface of the processing container 2 via the insulating member 2C. Then, the processing gas supply source 12 is connected to the gas supply pipe 1 in the gas introduction pipe 5A.
3, and the etching gas is supplied from the processing gas supply source 12. That is, the processing gas supply source 12 is
It has a C ₅ F ₈ gas supply source 12A, an O ₂ gas supply source 12B and an Ar gas supply source 12C, and each of these gas supply sources 1
2A, 12B and 12C are connected to branch pipes 13A, 13B and 13C of the gas supply pipe 13, respectively. A C ₅ F ₈ gas supply source 12 is provided in each of the branch pipes 13A, 13B, and 13C.
Flow rate control devices 12D, 12E, 12F and valves 12G, 12H, 12I corresponding to A, O ₂ gas supply source 12B and Ar gas supply source 12C are sequentially provided from the upstream side to the downstream side, and these flow rate control devices are provided. 12D, 12E,
The etching gas supplied into the processing container 2 via 12F and the valves 12G, 12H, and 12I is controlled to a predetermined flow rate.

A large number of holes 5B are evenly formed on the lower surface of the upper electrode 5, and the processing gas is evenly supplied into the processing container 2 through the holes 5B. Therefore, in the state where the inside of the processing container 2 is evacuated by the exhaust device 11 and a predetermined etching gas is supplied from the processing gas supply source 12 at a predetermined flow rate, high frequency power is applied to the lower electrode 3 and the upper electrode 5, respectively. Then, plasma of an etching gas is generated in the processing container 2, and the wafer W on the lower electrode 3 is subjected to predetermined etching. A temperature sensor (not shown) is attached to the lower electrode 3, and the temperature of the wafer W on the lower electrode 3 is constantly monitored via the temperature sensor.

A coolant passage 10A through which a predetermined coolant (for example, a conventionally known fluorine-based fluid, water, etc.) passes is formed in the mounting table 10, and the lower electrode 3 is cooled while the coolant flows through the coolant passage 10A. And cools the wafer W through the lower electrode 3,
The wafer W is controlled to a desired temperature. An electrostatic chuck 14 made of an insulating material is arranged on the lower electrode 3, and an electrode plate 14A in the electrostatic chuck 14 has a high-voltage DC power supply 15
It is connected to the. The electrostatic chuck 14 is a high voltage DC power supply 1
The wafer W is electrostatically attracted by the static electricity generated on the surface by the high voltage applied from 5 to the electrode plate 14A. A focus ring 16 surrounding the electrostatic chuck 14 is arranged on the outer peripheral edge of the lower electrode 3, and plasma is focused on the wafer W via the focus ring 16.

A gas channel 10B for supplying a heat conductive gas such as He gas as a backside gas is formed in the mounting table 10, and the gas channel 10B is opened at a plurality of positions on the upper surface of the mounting table 10. These openings coincide with the through holes formed in the electrostatic chuck 14 on the mounting table 10. Therefore, when the backside gas is supplied to the gas flow path 10B of the mounting table 10, the backside gas flows out from the through hole of the electrostatic chuck 13 via the gas flow path 10B, and between the electrostatic chuck 14 and the wafer W. It spreads evenly throughout the gap, increasing the thermal conductivity in the gap. In FIG. 1, reference numeral 17 denotes a gate valve that opens and closes the loading / unloading port of the wafer W formed in the processing container 2.

An end point detector 18 is attached to the plasma processing apparatus 1, for example, the end point detector 18 is used to measure the emission spectrum of plasma in the processing container 2, and the measured value is taken into the control unit 19. I have to. A program for principal component analysis, for example, is stored in the control device 19 as a multivariate analysis program, and the principal component analysis is performed through this program. This program for principal component analysis is used for analyzing the data for seasoning when seasoning the processing container 2. The measurement data of the emission spectrum of the end point detector 18 is used as the data for data analysis. The measurement data is, for example, 1024 in the range of 193 nm to 950 nm.
Use different wavelengths.

Therefore, the seasoning data analysis method of the present embodiment, that is, the collection of measurement data used for creating a so-called prediction formula for predicting the end of seasoning will be described. That is, after cleaning the processing container 2 and replacing consumables such as a focus ring (not shown), the processing container 2
Seasoning is performed by the following procedure to stabilize the temperature. First, after activating the plasma processing apparatus 1 on the first day, a dummy wafer (bare silicon) W is supplied into the processing container 2, and then an etching gas is supplied from the gas supply pipe 16 into the processing container 2 so that a predetermined vacuum degree is obtained. In the held state, high-frequency power supplies 6 and 7 apply high-frequency power of 60 MHz and 2 MHz, for example, to perform etching. This processing is performed, for example, 130
The dummy wafers W are repeatedly performed. The processing of the 130th dummy wafer W completes the processing of the first day.

After that, the etching process is temporarily stopped, and the processing container 2 is left for several hours or more while the power is on, that is, in a state where it can be immediately restarted. Cool internal components such as 12 to the set temperature.

Then, on the second day, again, for example, 30 dummy wafers W are supplied into the processing container 2 one by one under the conditions of the production process, and the etching cycle is repeated for each dummy wafer W. Since the inside of the processing container 2 is cooled at the start of the etching cycle, the processing container 2 itself, the lower electrode 12 in the processing container 2, the focus ring, etc. are etched during the etching from the first dummy wafer W to the 30th dummy wafer W. The temperature of the parts of the parts gradually rises. In this embodiment, 30
Of the wafers, the emission spectrum of the dummy wafer W at the time when there is a temperature change from the first to the 20th wafer was measured 18 times in about 1 minute, and the emission intensity of 297 kinds of wavelengths described above was used as the measurement data of the principal component analysis. To use. Therefore, the temperature change in the processing container 2 is reflected in these measurement data.

Then, principal component analysis is performed using the above measurement data. For example, 20 dummy wafers are measured m times (18 × 20 = 360 times in this embodiment), and n (emission intensity of 297 wavelengths in this embodiment) measurement data exists for each measurement. Then, the matrix containing the measurement data is expressed by Equation 1. The rows of this matrix have the measurement data of the measurement wavelength obtained by one measurement as the component, and the columns have the measurement data of each wavelength that changes with time. Then, the controller 19 obtains an average value, a variance value, and a standard deviation based on the respective measurement data, and then normalizes the average value and the standard deviation value. Principal component analysis of a plurality of measurement data is performed using a correlation matrix based on these standardized values to obtain an eigenvalue and its eigenvector. The eigenvalue represents the magnitude of the variance of each measurement data, and in the order of the magnitude of the eigenvalue, the first principal component, the second principal component,
... Defined as the nth principal component. Further, each eigenvalue has an eigenvector (weight) belonging to it.
Generally, the higher the order of the principal component, the lower the contribution rate to the evaluation of data, and the less useful it is.

[Equation 1]

In this embodiment, 20 dummy wafers are measured m times, and n measurement data are taken for each measurement, and the j-th principal component corresponding to the j-th eigenvalue of the i-th measurement. Is represented by Equation 2. Then, the value obtained by substituting the measurement data (x _i1 , x _i2 , ..., x _in ) obtained by the specific i-th measurement into this j-th principal component t _ij is the value for the i-th measurement. It becomes the score of the j-th principal component. Therefore, the score t _j of the j-th principal component is defined by Equation 3, and the eigenvector P _j of the j-th principal component is defined by Equation 4. Then, using the matrix X and the eigenvector P _j , the score t _j of the j-th principal component is expressed by Equation 5. Further, the matrix X is expressed by Equation 6 using the score of the main component and each eigenvector.

[Equation 2]

[Equation 3]

[Equation 4]

[Equation 5]

[Equation 6] _{However, P} ^{n T} is the transpose matrix of the _{P n.}

Therefore, in the principal component analysis, even if there are many kinds of measurement data, the first principal component and the second principal component, and at most the third principal component are collected as a small number of statistical data, and the small number of statistical data are collected. Just by investigating, the situation of seasoning can be grasped and the end of seasoning can be judged. For example, generally, the cumulative contribution rate of the eigenvalues of the first and second principal components is 9
If it exceeds 0%, the evaluation based on the first and second principal components becomes highly reliable. As described above, the first main component indicates the direction in which the measurement data is most widely dispersed, and is suitable for grasping the temporal change in the seasoning of the processing container 2 and determining the end of seasoning. Changes that cannot be grasped by the first and second principal components can be grasped by the residual score. In this embodiment, the first principal component is obtained.

Therefore, in this embodiment, the dummy wafer W is etched under the following conditions, and the eigenvalue can be obtained by using the correlation matrix of the measurement data by the principal component analysis of the measurement data at this time, and the largest eigenvalue is the first. It is the variance of one principal component score. The eigenvector of the first principal component can be obtained using the eigenvalue and the correlation matrix. The principal component score of each measurement data is calculated, and the sum of squares (HOTELLINGSTSQUARE) of each principal component score is plotted, which is the graph shown in (a) of FIG. As is clear from this graph, a large peak is observed only in the measurement data on the first day, and no large peak is observed in the measurement data on the second day, so that the end of seasoning can be reliably determined. Further, a plot of the sum of squares of residuals of each measurement data is the graph shown in (b) of FIG. Also in this figure, a large peak is observed only in the measurement data on the first day,
The end of seasoning can be reliably determined.
The horizontal axis of each graph shows the number of measurements. In this embodiment, one dummy wafer W is measured 18 times, and since 160 dummy wafers W have been processed in two days, there is a scale of up to 18 × 160 = 2880.

[Processing conditions] Processing device: Capacitively coupled parallel plate plasma processing device Dummy wafer (bare silicon): 300 mm High frequency and power of lower electrode: 2 MHz, 3800
W Upper electrode power supply high frequency and power: 60 MHz, 330
0 W Treatment pressure: 25 mTorr Etching gas: C ₅ F ₈ = 29 sccm, Ar = 75
0 sccm, O ₂ = 47 sccm Backside gas: He = 15 Torr (electrode center part), 40 Torr (electrode edge part) Treatment temperature: Upper electrode = 60 ° C., Side wall = 60 ° C., Lower electrode = 20 ° C.

As described above, according to the present embodiment, that is, the method of creating a prediction formula for predicting the end of seasoning,
After the plasma processing apparatus 1 is temporarily stopped in the middle of the stage where the dummy wafer W is used in the production process, the processing container 2 is left for several hours to leave the processing container 2 itself and the lower electrode 1 inside thereof.
After cooling the components such as 2 and the like, the measurement data for determining the end of the seasoning is collected while the production process is started again and 20 dummy wafers W are processed. Therefore, the processing container 2 itself and the lower electrode 3 and the like are collected. It is possible to obtain the measurement data in which the temperature change of the component is reflected, and the peak based on the temperature change can be excluded from the analysis result. Further, by using this analysis result at the time of seasoning, the end of seasoning can be surely detected and judged.
Therefore, the stable etching process can be performed on the wafer by performing the plasma process after surely detecting the seasoning.

FIG. 3 is a diagram showing a data analysis method according to another embodiment of the present invention. In the present embodiment, unlike the above embodiment, after obtaining the average value of 18 pieces of measurement data (297 kinds of wavelengths) obtained for each dummy wafer W,
Principal component analysis was performed using these average values to obtain eigenvalues and eigenvectors. Then, the graphs shown in (a) and (b) of FIG. 3 are obtained by plotting the sum of squares of the principal component scores and the sum of squares of the residuals of each dummy wafer W. As is clear from FIGS. 3A and 3B, the end of seasoning can be determined in the same manner as the graph of the embodiment shown in FIG. The numerical value on the horizontal axis indicates the number of dummy wafers.

FIGS. 4 and 5 are diagrams showing a data analysis method according to still another embodiment of the present invention. In the present embodiment, as shown in FIG. 4, for example, 10 types of wavelengths having a large contribution to the residual of the measurement data (for example, wavelengths surrounded by circles in FIG. 4) are selected, and the above-mentioned execution is performed for these 10 types of wavelengths. After obtaining an average value for each dummy wafer W as in the case of the embodiment, a principal component analysis was performed using these average values to obtain an eigenvalue and an eigenvector. Then, plots of the first principal component score and the residual score of each dummy wafer W are graphs shown in (a) and (b) of FIG. (A) of FIG.
As is clear from (b), the jaggedness of the graph is reduced and the curve becomes smoother as compared with the embodiment shown in FIG.
The end of seasoning can be determined more easily.

FIG. 6 is a diagram showing a data analysis method according to still another embodiment of the present invention. In this embodiment, as in the embodiment shown in FIG. 5, ten types of wavelengths having a high contribution rate to the residual are selected. Further, in the embodiment shown in FIG. 5, the time average value of the measurement data of each wavelength is adopted for the dummy wafer W, but in the present embodiment, the measurement data itself is used, which is the same as the case shown in FIG. However, in the case of FIG. 2, the rows of the matrix have the measurement data of the measurement wavelength obtained by one measurement as the component, and the columns have the measurement data of each wavelength that changes with time. In this embodiment, rows and columns are transposed for each dummy wafer W and each wavelength. Since one row is measured 16 times for 10 wavelengths, it has 10 × 16 = 160 components. One column has 20 wafers in the training set, so the training set for principal component analysis with 20 components is 20 rows,
It is a matrix of 160 columns. Principal component analysis is performed based on this matrix in the same manner as in each of the above-described embodiments, and the square sum of principal component scores and the sum of squares of residuals are plotted in the graphs shown in (a) and (b) of FIG. 6. . As is clear from (a) and (b) of FIG. 6, compared to the graph shown in FIG. 5, jaggedness is reduced and a smoother curve is obtained, and the end of seasoning can be determined more easily. .

Further, the present invention can be applied to the plasma processing apparatus 20 shown in FIG. 7 as in the case of the plasma processing apparatus 1, and the same effects as those of the plasma processing apparatus 1 can be expected. This plasma processing apparatus 20
As shown in FIG. 7, a processing container 21 made of a conductive material such as aluminum, a lower electrode 22 disposed on the bottom surface of the processing container 21 and also serving as a mounting table on which the wafer W is mounted, A hollow grounded upper electrode 23, which is disposed above the lower electrode 22 with a predetermined interval and also serves as an etching gas supply unit, and a magnetic field forming unit 24 for applying a rotating magnetic field, are controlled. Under the control of the device 25, the magnetic field forming means 24 is applied to the electric field generated between the upper and lower electrodes of the processing container 21.
The rotating magnetic field B generated by
A uniform plasma treatment is performed on.

A gas supply pipe 26 communicating with the upper electrode 23 is connected to the upper surface of the processing container 21, and a gas supply source (not shown) into the processing container 21 through the gas supply pipe 26 and the upper electrode 23. Supply etching gas. Processing container 2
A gas exhaust pipe 27 connected to a vacuum exhaust device (not shown) is connected to a side surface of the vacuum exhaust device 1 and the gas exhaust pipe 2.
The inside of the processing container 21 is decompressed via 7 to maintain a predetermined degree of vacuum. A high frequency power supply 28 is connected to the lower electrode 22,
High frequency power is applied from the high frequency power source 28 to the lower electrode 22 to generate etching gas plasma between the electrodes 22 and 23, and the surface of the semiconductor wafer W on the lower electrode 22 is subjected to, for example, a predetermined etching process.

An end point detector 29, for example, is attached to the plasma processing apparatus 20. The end point detector 29 is used to measure the emission spectrum of the plasma in the processing container 21, and the measured value is taken into the control apparatus 25. I have to.
As the multivariate analysis program, for example, a program for principal component analysis is stored in the control device 25, and the principal component analysis is performed through this program. This main component analysis program is used to analyze the seasoning data when seasoning the processing container 21. The end point detector 29 is used as data for data analysis.
The measurement data of the emission spectrum of is used. The measurement data is, for example, 10 in the range of 193 nm to 950 nm.
Twenty-four wavelengths are used.

In each of the above embodiments, the principal component analysis is taken as an example of the data analysis method for determining the end of seasoning, but other multivariate analysis may be used. Further, in each of the above-described embodiments, the case where the emission spectrum of plasma is used has been described. It is possible to use measurement data that is easily affected by temperature changes in the processing container, such as current phase differences. Further, in each of the above-described embodiments, the etching processing apparatus has been described as an example, but the present invention can be applied to other plasma processing apparatuses.

[0038]

According to the invention described in claims 1 to 7 of the present invention, it is possible to provide a seasoning end detection method capable of clearly determining the end of seasoning.

Further, according to the invention described in claim 8 of the present invention, there is provided a plasma processing method capable of performing stable etching processing on a wafer by performing plasma processing after surely detecting seasoning. Can be provided.

[Brief description of drawings]

FIG. 1 is a configuration diagram showing an example of a plasma processing apparatus to which a seasoning data analysis method and a seasoning end detection method of the present invention are applied.

FIG. 2 is a diagram showing an analysis result of measurement data regarding the plasma processing apparatus shown in FIG. 1 obtained according to an embodiment of the present invention, in which (a) is a graph showing a variation of a sum of squares of main component scores of the measurement data. , (B) are graphs showing variations in the residual score of the measurement data.

3 (a) and 3 (b) are diagrams showing analysis results obtained by another embodiment of the present invention, and FIGS.
Is a graph corresponding to.

FIG. 4 is a graph showing a contribution rate to a residual of measurement data of an emission spectrum used in still another embodiment of the present invention.

5 is a diagram showing an analysis result obtained by using the average value of the wavelengths shown in FIG. 4, and is a graph corresponding to (a) and (b) of FIG.

6 is a diagram showing an analysis result obtained by using the wavelength shown in FIG. 4, and is a graph corresponding to (a) and (b) of FIG.

FIG. 7 is a configuration diagram showing another example of a plasma processing apparatus to which the seasoning data analysis method and seasoning end detection method of the present invention are applied.

FIG. 8 is a diagram showing an analysis result obtained by a conventional analysis method and is a graph corresponding to (a) and (b) of FIG. 2 when using 51st to 60th dummy wafers on the first day of seasoning. .

FIG. 9 is a diagram showing another analysis result obtained by the conventional analysis method, and is a graph corresponding to (a) and (b) of FIG. 2 when using 121st to 130th dummy wafers on the first day of seasoning. Is.

[Explanation of symbols]

10 Plasma processing device (processing device) 11 Processing container 12 Lower electrode W dummy wafer (test object)

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Satoshi Harada             TBS release, 5-3-6 Akasaka, Minato-ku, Tokyo             Sending Center Tokyo Electron Limited F term (reference) 5F004 AA16 BA04 BB18 CB15 DA00                       DA23 DA26 DB01 EA21

Claims (8)

[Claims] 1. A method for detecting the end of the seasoning when a test object is supplied into a processing container of a processing apparatus to perform seasoning, wherein the test object is supplied into the processing container. After cooling the inside of the processing container,
Performing a multivariate analysis using a plurality of measurement data obtained when supplying a plurality of the test target objects into the processing container again, a step of creating a prediction formula for predicting the end of the seasoning, and the prediction A step of detecting the end of seasoning when performing the seasoning based on an equation. 2. The seasoning end detection method according to claim 1, wherein a principal component analysis is used as the multivariate analysis. 3. The seasoning end detection method according to claim 1, wherein an emission spectrum of plasma is used as the measurement data. 4. The seasoning end detection method according to claim 3, wherein a wavelength having a high contribution to the residual is used among the wavelengths of the emission spectrum. 5. The seasoning completion detecting method according to claim 1, wherein a high frequency voltage obtained by a VI probe is used as the measurement data. 6. The seasoning end detection method according to claim 1, wherein a high frequency current obtained by a VI probe is used as the measurement data. 7. The seasoning end detection method according to claim 1, wherein a phase difference between a high frequency voltage and a high frequency current obtained by a VI probe is used as the measurement data. 8. A plasma comprising: a step of detecting the end of seasoning by using the seasoning end detecting method according to claim 1, and a step of performing a plasma treatment. Processing method.