Patent Publication Number: US-2019170653-A1

Title: Plasma processing apparatus, plasma processing method and plasma processing analysis method

Description:
BACKGROUND 
     The present invention relates to a plasma processing apparatus, plasma processing method, and plasma processing analysis method for processing a semiconductor wafer using a plasma. 
     In order to obtain a fine pattern for a semiconductor device, etc. formed on a wafer, etching may be performed using a substance in an ionized state (plasma state) to remove a substance on the wafer by action of the ionized substance (reaction on the wafer surface). 
     The width and depth of the semiconductor device fine pattern and the processing speed of an etching apparatus for the fine pattern (etch rate) will be hereinafter called “etching result”. Due to various disturbances or change in the plasma state over time, it is difficult for the etching apparatus to achieve the same etching result even when processing is performed under the same etching conditions (hereinafter called “recipe”). For this reason, in order to stabilize the etching result, the etching apparatus adopts a control technique to change the recipe using apparatus monitor data obtained by measurement during etching (APC: Advanced Process Control). The monitor data is spectroscopic measurement data which is obtained by measuring the light emitted from the plasma during etching and the reflected light on the wafer surface by a spectroscope. The methods described in Japanese Unexamined Patent Application Publication No. 2013-105923 and Japanese Unexamined Patent Application Publication No. 2013-161913 are known as methods for adjusting the recipe using spectroscopic measurement data. 
     Japanese Unexamined Patent Application Publication No. 2013-105923 describes a method which uses, among apparatus monitor data including spectroscopic measurement data, a data parameter highly correlated with the etching result and adjusts the recipe based on the difference between the monitor data value and the target value for that data parameter. 
     Japanese Unexamined Patent Application Publication No. 2013-161913 describes a method which uses spectroscopic measurement data for data parameters highly correlated with the etching result (wavelength and time interval) among spectroscopic measurement data to estimate the etching result and adjusts the recipe using the estimation result. 
     SUMMARY 
     However, in both the methods described in Japanese Unexamined Patent Application Publication Nos. 2013-105923 and 2013-161913, the data parameters (wavelength and time interval for spectroscopic measurement data) to be used for APC are determined only according to the correlation between spectroscopic measurement data and etching result, and change in the correlation which is caused by change of the recipe is not taken into consideration. Since plasma light emission and the wafer surface condition change depending on the changed recipe parameter, the correlation between spectroscopic measurement data for the data parameters and the etching result may change. In APC, since change of the recipe is repeated using spectroscopic measurement data with a changed recipe, the correlation between spectroscopic measurement data with the data parameters used in APC and the etching result must be stabilized even with a changed recipe. 
     The present invention has an object to provide a plasma processing apparatus, plasma processing method, and plasma processing analysis method which determine a combination of a changed recipe parameter and data parameters (wavelength and time interval for spectroscopic measurement data) which ensures that change in the correlation is small even when the recipe is changed. 
     In order to achieve the above object, according to one aspect of the invention, there is provided a plasma processing apparatus which performs plasma processing on a specimen under APC as control to suppress fluctuations in plasma processing by feedback control or feedforward control and has an analysis unit to find a suitable combination for APC of emission wavelength, time interval for the emission wavelength, and a parameter (recipe) for plasma processing. The analysis unit obtains a first regression equation representing the correlation between emission intensity and plasma processing result, from temporal change data of the plasma processing, obtains a second regression equation representing the correlation between emission intensity and plasma processing result by changing the parameter, and finds a combination of wavelength, time interval for the wavelength, and a parameter for the plasma processing which is suitable for APC, based on a coefficient of correlation of the first regression equation, and a difference between a gradient of the first regression equation and a gradient of the second regression equation. 
     In order to achieve the above object, according to a second aspect of the invention, there is provided a plasma processing apparatus which performs plasma processing on a specimen under APC as control to suppress fluctuations in plasma processing by feedback control or feedforward control and is connected with an analysis unit to find a suitable combination for APC of emission wavelength, time interval for the emission wavelength, and a parameter for the plasma processing. The analysis unit obtains a first regression equation representing the correlation between emission intensity and plasma processing result, from temporal change data of the plasma processing, obtains a second regression equation representing the correlation between emission intensity and plasma processing result by changing the parameter, and finds a combination of wavelength, time interval for the wavelength, and a parameter for the plasma processing which is suitable for APC, based on a coefficient of correlation of the first regression equation, and a difference between a gradient of the first regression equation and a gradient of the second regression equation. 
     In order to achieve the above object, according to a third aspect of the invention, there is provided a plasma processing method using a plasma processing apparatus which performs plasma processing on a specimen under APC as control to suppress fluctuations in plasma processing by feedback control or feedforward control and has an analysis unit to find a suitable combination for APC of emission wavelength, time interval for the emission wavelength, and a parameter for the plasma processing. The method includes the steps of: obtaining a first regression equation representing the correlation between emission intensity and plasma processing result from temporal change data of the plasma processing by using the analysis unit; obtaining a second regression equation representing the correlation between emission intensity and plasma processing result by changing the parameter by using the analysis unit; finding a combination of wavelength, time interval for the wavelength, and a parameter for the plasma processing which is suitable for APC, based on a coefficient of correlation of the first regression equation, and a difference between a gradient of the first regression equation and a gradient of the second regression equation by using the analysis unit; and performing plasma processing by using the plasma processing apparatus on the specimen under APC which uses the combination of wavelength, time interval for the wavelength, and a parameter for the plasma processing as found by the analysis unit. 
     In order to achieve the above object, according to a fourth aspect of the invention, there is provided an analysis unit which finds a combination of wavelength, time interval for the wavelength, and a parameter for plasma processing which is suitable for control to suppress fluctuations in the plasma processing by feedback control or feedforward control. In the analysis unit, a first regression equation representing the correlation between emission intensity and plasma processing result is obtained from temporal change data of the plasma processing; a second regression equation representing the correlation between emission intensity and plasma processing result is obtained by changing the parameter; and a combination of wavelength, time interval for the wavelength, and a parameter for the plasma processing which is suitable for the control is found based on a coefficient of correlation of the first regression equation, and a difference between a gradient of the first regression equation and a gradient of the second regression equation. 
     Furthermore, in order to achieve the above object, according to a fifth aspect of the invention, there is provided an analysis method which finds a combination of wavelength, time interval for the wavelength, and a parameter for plasma processing which is suitable for control to suppress fluctuations in the plasma processing by feedback control or feedforward control. The method includes the steps of: obtaining a first regression equation representing the correlation between emission intensity and plasma processing result from temporal change data of the plasma processing; obtaining a second regression equation representing the correlation between emission intensity and plasma processing result by changing the parameter; and finding a combination of wavelength, time interval for the wavelength, and a parameter for the plasma processing which is suitable for the control, based on a coefficient of correlation of the first regression equation, and a difference between a gradient of the first regression equation and a gradient of the second regression equation. 
     According to the present invention, it is possible to determine a combination of wavelength and time interval and a changed recipe parameter for spectroscopic measurement data which ensures that change in the correlation between spectroscopic measurement data and etching result is small even when the recipe is changed, so that etching results are stabilized. 
     These features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention, as illustrated in the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram showing the general configuration of an etching apparatus according to an embodiment of the present invention; 
         FIG. 2  is a block diagram showing the general configuration of the etching module of the etching apparatus according to an embodiment of the present invention; 
         FIG. 3  is a graph for explaining an example of spectroscopic measurement data; 
         FIG. 4  shows an example of an APC setup data table according to an embodiment of the present invention; 
         FIG. 5  is a flowchart for explaining an example of control (APC) in which the recipe is changed; 
         FIG. 6  is a scatter diagram showing an example of the correlation between emission intensity monitor value and etching result; 
         FIG. 7A  is a diagram showing an example of change in emission intensity monitor value when APC is executed; 
         FIG. 7B  is a diagram showing an example of change in etching result when APC is executed; 
         FIG. 8A  is a scatter diagram showing an example of the correlation between emission intensity monitor value and etching result when the recipe is fixed; 
         FIG. 8B  is a scatter diagram showing an example of the correlation between emission intensity monitor value and etching result when the recipe is changed; 
         FIG. 9A  is a scatter diagram showing an example of the correlation between emission intensity monitor value and etching result when the recipe is fixed, in which the difference between the correlation with the fixed recipe and the correlation with the changed recipe is small; 
         FIG. 9B  is a scatter diagram showing the correlation between emission intensity monitor value and etching result when the recipe is changed, in which the difference between the correlation with the fixed recipe and the correlation with the changed recipe is small; 
         FIG. 10  shows an example of a fixed-recipe etching result data table according to an embodiment of the present invention; 
         FIG. 11  shows an example of a fixed-recipe spectroscopic measurement data table according to an embodiment of the present invention; 
         FIG. 12  shows an example of a changed-recipe etching result data table according to an embodiment of the present invention; 
         FIG. 13  shows an example of a changed-recipe recipe data table according to an embodiment of the present invention; 
         FIG. 14  shows an example of a changed-recipe spectroscopic measurement data table according to an embodiment of the present invention; 
         FIG. 15  shows an example of an APC setup data candidate table according to an embodiment of the present invention; 
         FIG. 16  is a flowchart showing the steps to be carried out by an apparatus manager according to an embodiment of the present invention; 
         FIG. 17  is a flowchart showing analysis steps to be taken in an arithmetic processing section according to an embodiment of the present invention; 
         FIG. 18  shows an example of an emission intensity monitor value data table according to an embodiment of the present invention; 
         FIG. 19  shows an example of an emission intensity monitor value data table in which data with a changed recipe is stored; 
         FIG. 20  is a scatter diagram showing an example of the regression equation between emission intensity monitor value and etching result; 
         FIG. 21A  is a scatter diagram showing an example that the coefficient of the regression equation provides a high estimation accuracy; 
         FIG. 21B  is a scatter diagram showing an example that the coefficient of the regression equation provides a low estimation accuracy; 
         FIG. 22A  is a diagram showing an example of change in emission intensity monitor value with a fixed recipe; 
         FIG. 22B  is a diagram showing an example of change in etching result with a fixed recipe; 
         FIG. 23  is a front view of the input display screen for analysis processing according to an embodiment of the present invention; and 
         FIG. 24  is a front view of the display screen which shows analysis results according to an embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     The present invention concerns a plasma processing apparatus, plasma processing method, and plasma processing analysis method for performing etching, in which spectroscopic measurement data indicating emission intensity at different wavelengths and times in the etching process and the etching result are acquired, and as for different combinations of wavelength and time interval for spectroscopic measurement data and a changeable recipe parameter, comparison is made between the regression equation between average emission intensity and etching result with a fixed recipe and the regression equation between average emission intensity and etching result with a changed recipe for each combination of wavelength and time interval, and the combination of wavelength, time interval, and a changed recipe parameter for spectroscopic measurement data to be used for APC is determined based on the difference between the coefficients of the two regression equations. The combination thus determined is applied to the plasma processing method and plasma processing apparatus for etching or the like. 
     Specifically, according to the present invention, in the plasma processing apparatus, plasma processing method, and plasma processing analysis method, the following processes (1) to (3) are carried out: 
     (1) Combinations of wavelength indicating the emission wavelength band of spectroscopic measurement data obtained by a spectroscope, time interval indicating the time when the spectroscopic measurement data is obtained, and the recipe parameter to be changed are created.
 
(2) As for each of the combinations of wavelength, time interval and changed recipe thus created, using the data with a fixed recipe, regression equation 1 representing the correlation between spectroscopic measurement data at the relevant wavelength and time interval and the etching result and regression equation 2 representing the correlation between spectroscopic measurement data at the relevant wavelength and time interval and the etching result with a changed recipe parameter are created.
 
(3) As for each of the combinations of wavelength, time interval and changed recipe parameter, the difference between the coefficient of the regression equation 1 and the coefficient of the regression equation 2 is calculated, and among the combinations, the combination for which the difference is small is presented as the combination of wavelength, time interval and changed recipe parameter to be used for APC.
 
     In order to solve the above problem, according to the present invention, in the plasma processing method for etching, the above processes (1) to (3) are carried out and using the wavelength and time interval in the above-determined combination of wavelength, time interval and changed recipe parameter, an emission intensity monitor value as spectroscopic measurement data at the wavelength and time interval is calculated and the value of the changed recipe parameter determined in the above processes is changed according to the difference between the calculated emission intensity monitor value and the target emission intensity monitor value. 
     Furthermore, in order to solve the above problem, according to the present invention, in the plasma processing apparatus which performs etching, the above processes (1) to (3) are carried out, and using the wavelength and time interval in the above-determined combination of wavelength, time interval and changed recipe parameter, an emission intensity monitor value as spectroscopic measurement data at the wavelength and time interval is calculated and the value of the changed recipe parameter determined in the above processes is changed according to the difference between the calculated emission intensity monitor value and the target emission intensity monitor value. 
     Next, the preferred embodiments of the present invention will be described referring to the accompanying drawings. In all the drawings that illustrate the preferred embodiments, basically the same members are designated by the same reference signs and descriptions thereof are not repeated. 
     Etching Apparatus 
     As an example of a plasma processing apparatus according to an embodiment of the invention, an etching apparatus will be described below. As shown in the block diagram of  FIG. 1 , the etching apparatus  1  in this embodiment includes an etching module  10 , an analysis module  20 , an input module  30 , an output module  31 , and a communication interface module (communication IF module)  32  which are interconnected through a bus  33 . 
     The etching module  10  includes a plasma processing section  11 , a spectroscope  12 , a control section  13 , a storage  14 , and an interface section (IF section)  110 . The plasma processing section  11  generates plasma to process a wafer and the spectroscope  12  acquires spectroscopic measurement data including plasma light emission data and reflected light on the wafer surface while etching is under way. The spectroscopic measurement data is stored in the storage  22  of the analysis module  20  through the IF sections  110  and  210 . The control section  13  controls processing which is performed in the plasma processing section  11 . The storage  14  has an APC setup data storage area  15  which stores the wavelength, time interval and changed recipe parameter to be used for control (APC) by the control section  13  to change the recipe. Details of the etching module  10  will be given later, referring to  FIG. 2 . Also, the APC process by the control section  13  will be described in detail later. 
     The analysis module  20  performs processing to determine the combination of wavelength, time interval, and changed recipe parameter which is used for APC as control to suppress fluctuations in plasma processing by feedback control or feedforward control. The analysis module  20  includes an arithmetic processing section  21  for data analysis, a storage  22 , and an interface section (IF section)  210 . 
     The storage  22  includes a fixed-recipe etching result data storage area  23  for storing results of etching with a fixed recipe, a fixed-recipe spectroscopic measurement data storage area  24  for storing spectroscopic measurement data obtained during an etching process with a fixed recipe, a changed-recipe etching result data storage area  25  for storing results of etching with a changed recipe, a changed-recipe recipe data storage area  26  for storing recipe setting values in an etching process with a changed recipe, a changed-recipe spectroscopic measurement data storage area  27  for storing spectroscopic measurement data obtained during an etching process with a changed recipe, and an APC setup data candidate storage area  28  for storing candidates for the combination of wavelength, time interval, and changed recipe parameter to be used for APC, and evaluation results thereof. 
     The arithmetic processing section  21  compares the regression equation between emission intensity and etching result with a fixed recipe with the regression equation between emission intensity and etching result with a changed recipe for each combination of wavelength, time interval, and changed recipe parameter, using the etching result data stored in the fixed-recipe etching result data storage area  23  of the storage  22 , the spectroscopic measurement data stored in the fixed-recipe spectroscopic measurement data storage area  24 , the etching result data stored in the changed-recipe etching result data storage area  25 , and the spectroscopic measurement data stored in the changed-recipe spectroscopic measurement data storage area  27 , and performs processing to determine the combination of wavelength, time interval, and changed recipe parameter to be used in APC, based on the difference in coefficient between the two regression equations. The analysis processing by the arithmetic processing section  21  will be described in detail later. 
     The input module  30  includes devices to receive information entered by a user, such as a mouse and a keyboard. The output module  31  includes devices to output information to the user, such as a display and a printer. The communication IF module  32  is an interface which is connected to another apparatus (connectable to an inspection device for measuring the etching result, etc.) or system (connectable to an existing production management system, etc.) through the bus  33  or an external network, etc. to transmit and receive information. The bus  33  interconnects the various modules ( 10 ,  20 ,  30 ,  31 ,  32 ). The IF sections ( 110 ,  210 , etc.) are interfaces to transmit and receive information through the bus  33 . The analysis module  20  may be an independent analysis unit which is connected to the etching apparatus including the etching section  10  through the IF section  210 . 
     Etching Module 
     The etching module  10  includes a plasma processing section  11 , a spectroscope  12 , a control section  13 , a storage  14 , and an IF section  110 . As shown in  FIG. 2 , the plasma processing section  11  includes a chamber  111  the inside of which is air-evacuated by a vacuum exhaust means (not shown), a pair of electrodes  112   a  and  112   b  which generates a plasma in the air-evacuated chamber  111  supplied with radio frequency power from a power source (not shown), a window  115  for observing the inside of the chamber  111  from outside, and a gas supply section  117  for supplying etching gas for etching a wafer  114  into the air-evacuated chamber  111 . The gas supply section  117  can supply several types of gas (CF4, CHF3, Ar, etc.), in which the flow rate of each type of gas is controlled. 
     In this structure, according to a command from the control section  13 , the plasma processing section  11  is supplied with etching gas from the gas supply section  117  while the wafer  114  is set inside the chamber  111  and the inside of the chamber  111  is air-evacuated by the exhaust means (not shown). Then, the etching gas is supplied into the chamber  111  and a radio frequency discharge is generated between the electrodes  112   a  and  112   b  by applying radio frequency power from the power source (not shown) to the electrodes  112   a  and  112   b  to generate plasma. The wafer  114  is processed by collision of the plasma gas  113  against the wafer  114 . 
     The plasma gas  113  contains elements of the etching gas supplied from the gas supply section  117  and elements generated during processing of the wafer  114  and generates light  116  with wavelength corresponding to the elements contained in the plasma gas  113 . The generated light  116  is measured by the spectroscope  12  through the window  115 . 
     And the measured data is stored in the fixed-recipe spectroscopic measurement data storage area  24  of the storage  22  of the analysis module  20  through the IF section  110 . Alternatively, an external light source (not shown) may be used to irradiate the wall surface of the chamber  111  and the wafer  114  with light so that the reflected light is measured by the spectroscope  12 . 
     The control section  13  gives commands to the plasma processing section  11  and receives spectroscopic measurement data obtained by the spectroscope  12  and performs processing to change the recipe as described later in recipe change control (Advanced Process control: APC). 
     The APC setup data storage area  15  of the storage  14  stores data which the control section  13  uses for APC. 
       FIG. 4  shows an APC setup data table  15   a  as an example of the APC setup data storage area  15 . The table contains a wavelength 1 field  15   b , a time interval 1 field  15   c , a wavelength 2 field  15   d , a time interval 2 field  15   e , and a changed recipe parameter field  15   f.    
     The wavelength 1 field  15   b  stores information to identify the wavelength for spectroscopic measurement data to calculate the average emission intensity. 
     The time interval 1 field  15   c  stores information to identify the time interval for spectroscopic measurement data to calculate the average emission intensity. 
     The wavelength 2 field  15   d  stores information to identify the wavelength for spectroscopic measurement data to calculate the average emission intensity. 
     The time interval 2 field  15   e  stores information to identify the time interval for spectroscopic measurement data to calculate the average emission intensity. 
     The changed recipe parameter field  15   f  stores information to identify the recipe parameter (gas flow rate, etc.) to be changed in APC. 
     After etching is finished, the processed wafer  114  is taken out from the chamber  111  and transported to another device (inspection device or the like), and then another wafer  114  is set in the etching module  10  and the wafer  114  is processed by etching. The processed wafer  114  is measured in another device (inspection device or the like) to obtain pattern dimensions as the result of etching. The measured pattern dimensions are stored in the etching result data storage area  23  of the storage  22  as etching result data. 
     Spectroscopic Measurement Data 
       FIG. 3  shows a waveform signal  301  as an example of spectroscopic measurement data of plasma emission measured by the spectroscope  12 . The waveform signal  301  as spectroscopic measurement data has two-dimensional factors, wavelength and time, and represents the value of emission intensity measured at each wavelength and each time. The value of emission intensity at each wavelength and each time is stored in the spectroscopic measurement data storage area  24  (described later) together with the ID of the wafer corresponding to the spectroscopic measurement data. 
     Recipe Change Control (APC) 
       FIG. 5  shows an example of APC processing which is performed in the control section  13 . 
     When the execution of APC is programmed, upon completion of wafer etching the control section  13  loads the information on wavelength, time interval, and changed recipe parameter stored in the APC setup data storage area  15  of the storage  14  (S 101 ). In an example of APC processing, a plurality of wafers are processed sequentially using the wavelength, time interval, and changed recipe parameter stored in the APC setup data storage area  15 , except for the first wafer for which the preset conditions are used. 
     Next, the following calculation is made (S 102 ): the average emission intensity calculated from the waveform signal  301  stored in the fixed-recipe spectroscopic measurement data storage area  24  based on the combination of wavelength and time interval stored in the spectroscopic measurement data wavelength 1 field  15   b  and time interval 1 field  15   c  of the APC setup data table  15   a  is divided by the average emission intensity calculated from the waveform signal  301  stored in the fixed-recipe spectroscopic measurement data storage area  24  based on the combination of wavelength and time interval stored in the spectroscopic measurement data wavelength 2 field  15   d  and time interval 2 field  15   e . The result of dividing the average emission intensity by the other average emission intensity as mentioned above will be hereinafter called an emission intensity monitor value. Alternatively the average emission intensity calculated from the waveform signal  301  stored in the fixed-recipe spectroscopic measurement data storage area  24  based on the combination of wavelength and time interval stored in the wavelength 1 field  15   b  and time interval 1 field  15   c  may be directly taken as an emission intensity monitor value. Furthermore, the maximum or median value of emission intensity extracted from the waveform signal  301  stored in the fixed-recipe spectroscopic measurement data storage area  24  based on the combination of wavelength and time interval stored in the wavelength 1 field  15   b  and time interval 1 field  15   c  may be taken as an emission intensity monitor value. 
     Next, the control section  13  calculates the difference between the emission intensity monitor value calculated at S 102  and the target emission intensity monitor value preset by the apparatus manager is calculated (S 103 ). 
     Furthermore, the control section  13  calculates the amount of recipe change, for example, the flow rate of etching gas supplied from the gas supply section  117  (gas flow rate) according to the difference between the emission intensity monitor value calculated at S 103  and the target emission intensity monitor value (S 104 ). The recipe parameter which is changed here is the recipe parameter stored in the changed recipe parameter field  15   f.    
     The graph A 101  on the right in  FIG. 5  shows an example of calculation of the amount of recipe change which is made at S 104 . A 101  is a scatter diagram in which the value of each wafer (A 102 ) is plotted on the horizontal axis representing the recipe setting value and the vertical axis representing the emission intensity monitor value. The example shown in A 101  reveals that the recipe setting value and the emission intensity monitor value are correlated. Line A 103  is a regression line which represents the relation between the emission intensity monitor values obtained from a plurality of points A 102  and the recipe setting value. For example, the line A 103  is drawn so that the sum of squares of the distance from each of the points A 102  is minimum. In the graph A 101 , ei 1  denotes the emission intensity monitor value calculated at S 102  and eit denotes the target emission intensity monitor value. 
     At the step of S 104 , the amount of recipe change (drc) for the recipe parameter stored in the changed-recipe parameter field  15   f  is calculated from the difference between the emission intensity monitor value (ei 1 ) and the target emission intensity monitor value (eit) using the regression line A 103  as indicated by dotted lines. The control section  13  changes the recipe by the amount of recipe change calculated here for etching the next wafer. As a result of this recipe change, the emission intensity monitor value becomes closer to the target emission intensity monitor value (eit). 
     Next, an example of control of the emission intensity monitor value and etching result will be described referring to  FIG. 6 ,  FIG. 7A , and  FIG. 7B . 
       FIG. 6  is a scatter diagram in which the value of each wafer (A 201 ) is plotted on the horizontal axis representing the emission intensity monitor value and the vertical axis representing the etching result. As shown in the diagram, when the emission intensity monitor value and etching result are correlated, the etching result (for example, er 1 ) can be made closer to the target value (ert) by controlling the emission intensity monitor value (for example, ei 1 ) to make it closer to the target value (eit). Taking advantage of this feature, even if the emission intensity monitor value or etching result deviates from the target value due to temporal change or disturbance, the etching result can be made closer to the target value (ert) by executing APC so as to make the emission intensity monitor value closer to the target value (eit). 
       FIGS. 7A and 7B  show changes in emission intensity monitor value and etching result when etching is performed under APC, respectively. Points (A 301 , A 401 ) in  FIGS. 7A and 7B  represent the emission intensity monitor value and etching result for each etched wafer respectively and from the figures, it is known that the points converge around the target values (eit, ert). 
     However, if the correlation between change in emission intensity monitor value and change in etching result with a fixed recipe, attributable to temporal change, is different in tendency from the correlation between change in emission intensity monitor value and change in etching result with a changed recipe, attributable to recipe change, it may be difficult to perform control so that the points representing the etching result converge around the target value. The reason will be explained below referring to  FIGS. 8A and 8B . 
       FIG. 8A  is a scatter diagram in which the value of each wafer (A 501 ) is plotted on the horizontal axis representing the emission intensity monitor value and the vertical axis representing the etching result when the recipe is fixed.  FIG. 22A  (to which reference will be made later) is a diagram in which the emission intensity monitor value with a fixed recipe is plotted for each wafer. The figure suggests that the emission intensity monitor value changes over time.  FIG. 22B  plots the etching result with a fixed recipe for each wafer. It also suggests temporal change.  FIG. 8A  indicates the relation between emission intensity monitor value and etching result when temporal change occurs as shown in  FIGS. 22A and 22B . Line A 502  is a regression line which expresses the correlation between the emission intensity monitor values obtained from a plurality of points A 501  and the etching result. For example, the line A 502  is drawn so that the sum of squares of distance from each of the points A 501  is minimum. 
       FIG. 8B  is a scatter diagram in which the value of each wafer (A 601 ) is plotted on the horizontal axis representing the emission intensity monitor value and the vertical axis representing the etching result when the recipe is changed.  FIG. 8B  is created from data collected by experiments before execution of APC. The figure indicates the relation between the emission intensity monitor value and etching result which have changed due to recipe change, in which line A 603  is a regression line which expresses the correlation between emission intensity monitor value and etching result by the change of recipe. A 602  represents the target emission intensity monitor value (eit) and the target etching result (ert). Line A 502 ′ represents the regression line (A 502 ) with a fixed recipe as explained above in reference to  FIG. 8A , which is included in this scatter diagram. 
     When the emission intensity monitor value and etching result with a fixed recipe change to ei 1  and er 1  due to temporal change respectively, if the recipe is changed so as to make the emission intensity monitor value (ei 1 ) equal to the target value (eit), the etching result (er 1 ) changes as indicated by line A 603 ′ parallel to line A 603  and the etching result under control becomes er 2 . When the difference between the gradients of the lines A 603 ′ and A 502 ′ is smaller, the difference between the target etching result value (ert) and the etching result (erg) at the emission intensity monitor value equal to the target value is smaller. Therefore, when APC is executed, it is necessary to ensure that the correlation between emission intensity monitor value and etching result with a fixed recipe has the same gradient as that with a changed recipe (the regression lines have the same gradient) as shown in  FIGS. 9A and 9B . 
     The effectiveness of APC in making the emission intensity constant has been explained so far. However, even when control to make the emission intensity constant is not performed but the etching result is estimated using emission intensity data and the recipe is controlled according to the estimated etching result, it is desirable that the difference between the gradient of the regression line (A 502 ) representing the correlation between emission intensity monitor value and etching result with a fixed recipe and the gradient of the regression line (A 603 ) representing the correlation between emission intensity monitor value and etching result with a changed recipe be small. This is because when the difference in gradient and intercept between the two regression lines is small, the etching result can be estimated using the same regression line when the recipe is fixed as when the recipe is changed, and the etching result can be estimated stably with a smaller amount of calculation. 
     Analysis Module 
     The information about the etching performed without changing a predetermined standard recipe is stored in the fixed-recipe etching result data storage area  23  and fixed-recipe spectroscopic measurement data storage area  24  of the storage  22  shown in  FIG. 1 . 
       FIG. 10  shows a fixed-recipe etching result data table  23   a  as an example of the fixed-recipe etching result data storage area  23 . The table includes a wafer ID field  23   b  and an etching result field  23   c.    
     The wafer ID field  23   b  stores information which identifies the wafer  114 . The value stored in the wafer ID field  23   b  is associated with the value stored in the wafer ID field  24   b  of the spectroscopic measurement data table  24   a  (described later) so that the spectroscopic measurement data obtained during etching of each wafer is associated with the etching result. 
     The etching result field  23   c  stores information which identifies the etching result. For example, it stores the result of surface pattern measurement of the etched wafer  114  identified in the wafer ID field  23   b  measured by an inspection device connected to the etching apparatus  1  (for example, the dimensions of patterns formed on the wafer  114  and inter-pattern distances as measured by a measuring SEM). For each wafer, the surface pattern dimensional information is stored in the etching result data storage area  23  through the communication IF module  32 . 
       FIG. 11  shows a fixed-recipe spectroscopic measurement data table  24   a  as an example of the fixed-recipe spectroscopic measurement data storage area  24 . The table includes a wafer ID field  24   b , a wavelength field  24   c , a time field  24   d , and an emission intensity value field  24   e . This table is provided in the same number as the number of wafers. 
     The wafer ID field  24   b  stores information which identifies the wafer  114 . The value stored in the wafer ID field  24   b  is associated with the value stored in the wafer ID field  23   b  of the fixed-recipe etching result data table  23   a  described above in reference to  FIG. 10 . 
     The emission intensity value field  24   e  stores measured emission intensity values at wavelengths in the wavelength field  24   c  and at times in the time field  24   d.    
     The changed-recipe etching result data storage area  25 , changed-recipe recipe data storage area  26 , and changed-recipe spectroscopic measurement data storage area  27  of the storage  22  shown in  FIG. 1  store information about etching performed with the predetermined standard recipe partially changed. 
       FIG. 12  shows a changed-recipe etching result data table  25   a  as an example of the changed-recipe etching result data storage area  25 . The table includes a wafer ID field  25   b  and an etching result field  25   c.    
     The wafer ID field  25   b  stores information which identifies the wafer  114 . The value stored in the wafer ID field  25   b  is associated with the value stored in the wafer ID field  26   b  of the changed-recipe recipe data table  26   a  (described later) and the value stored in the wafer ID field  27   b  of the spectroscopic measurement data table  27   a  (described later) so that the amount of recipe change used for etching each wafer is associated with the spectroscopic measurement data and etching result obtained by etching. 
     The etching result field  25   c  stores information which identifies the etching result. For example, it stores the result of surface pattern measurement of the etched wafer  114  identified in the wafer ID field  25   b  measured by an inspection device connected to the etching apparatus  1  (for example, the dimensions of patterns formed on the wafer  114  and inter-pattern distances as measured by a measuring SEM). The information stored here is the result of measurement of a spot on the wafer as information which is the same as or comparable to the information in the etching result field  23   c  of the fixed-recipe etching result data table  23   a . For example, if the etching result field  23   c  stores the inter-pattern distance in the center of the wafer, the etching result field  25   c  also stores the inter-pattern distance in the center of the wafer. 
       FIG. 13  shows a changed-recipe recipe data table  26   a  as an example of the changed-recipe recipe data storage area  26 . The table includes a wafer ID field  26   b  and a recipe change amount field  26   c.    
     The wafer ID field  26   b  stores information which identifies the wafer  114 . The value stored in the wafer ID field  26   b  is associated with the value stored in the wafer ID field  25   b  of the changed-recipe etching result table  25   a  (described above in reference to  FIG. 12 ) and the value stored in the wafer ID field  27   b  of the changed-recipe spectroscopic measurement data table  27   a  (described later). 
     The recipe change amount field  26   c  stores the amount of change from the standard recipe for each recipe parameter (for example, flow rate for each gas type) which is used to etch the wafer identified in the wafer ID field  26   b . Although  FIG. 13  shows gas flow rates in the recipe change amount field  26   c  as an example, the parameter stored in this field is not limited to gas flow rates but the field may store recipe data such as processing chamber internal pressure, processing time, and voltage applied to the electrodes  112   a  or  112   b  as well. 
       FIG. 14  shows a changed-recipe spectroscopic measurement data table  27   a  as an example of the changed-recipe spectroscopic measurement data storage area  27 . The table includes a wafer ID field  27   b , a wavelength field  27   c , a time field  27   d , and an emission intensity field  27   e . This table is provided in the same number as the number of wafers for which spectroscopic measurement data has been obtained. 
     The wafer ID field  27   b  stores information which identifies the wafer  114 . The value stored in the wafer ID field  27   b  is associated with the value stored in the wafer ID field  25   b  of the changed-recipe etching result data table  25   a  described above in reference to  FIG. 12  and the value stored in the wafer ID field  26   b  of the changed-recipe recipe data table  26   a  described above in reference to  FIG. 13 . 
     The emission intensity field  27   e  stores measured emission intensity values at wavelengths in the wavelength field  27   c  and at times in the time field  27   d.    
     The APC setup data candidate storage area  28  of the storage  22  shown in  FIG. 1  stores information as candidates for APC setup data to be stored in the APC setup data storage area  15  of the storage  14  and information on results of estimation of candidates. 
       FIG. 15  shows an APC setup data candidate table  28   a  as an example of the APC setup data candidate storage area  28 . The table includes an ID field  28   b , an APC setup candidates field  281 , and an evaluation result field  282 . The APC setup candidates field  281  includes a monitor 1 field  281   a , a monitor 2 field  281   b , and a changed recipe parameter field  28   g . The monitor 1 field  281   a  includes a wavelength 1 field  28   c  and a time interval 1 field  28   d , and the monitor 2 field  281   b  includes a wavelength 2 field  28   e  and a time interval 2 field  28   f . The evaluation result field  282  includes a fixed-recipe residual field  28   h , a changed-recipe residual field  28   i , a model difference field  28   j , and an overall evaluation field  28   k.    
     Information obtained by analysis processing which will be described later is stored in these fields. 
     The ID field  28   b  stores information which identifies the combination of data stored in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , time interval 2 field  28   f , and changed-recipe parameter field  28   g.    
     The wavelength 1 field  28   c  stores information which identifies the candidate for the wavelength to be used for APC. The value stored in row i of the wavelength 1 field (column)  28   c  is called WL 1  for later explanation. 
     The time interval 1 field  28   d  stores information which identifies the candidate for the time interval to be used for APC. The information stored in the time interval 1 field  28   d  is associated with the information stored in the wavelength 1 field  28   c . The value stored in row i of the time interval 1 field (column)  28   d  is called WLT1 for later explanation. 
     The wavelength 2 field  28   e  stores information which identifies the candidate for the wavelength to be used for APC. The value stored in row i of the wavelength 2 field (column)  28   e  is called WL 2  for later explanation. 
     The time interval 2 field  28   f  stores information which identifies the candidate for the time interval to be used for APC. The information stored in the time interval 2 field  28   f  is associated with the information stored in the wavelength 2 field  28   e . The value stored in row i of the time interval 2 field (column)  28   f  is called WLT2 for later explanation. 
     The changed-recipe parameter field  28   g  stores information which identifies the candidate for the recipe parameter to be used for APC. The value stored in row i of the changed-recipe parameter field (column)  28   g  is called Rcp for later explanation. 
     The values in each row represent a combination of APC setting values. In other words, using the values stored in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , and time interval 2 field  28   f , the average emission intensity at wavelength WL 1  in the wavelength field  24   c  of the spectroscopic measurement data table  24   a  shown in  FIG. 11  at time interval WLT1 in the time interval field  24   d  is divided by the average emission intensity at wavelength WL 2  in the wavelength field  24   c  at time interval WLT2 in the time interval field  24   d  and the result of the division (quotient) is defined as an emission intensity monitor value. Using this emission intensity monitor value, the recipe parameter specified by changed-recipe parameter Rcp stored in row i of the changed-recipe parameter field  28   g  is changed. 
     Similarly, the result of dividing the average emission intensity at wavelength WL 1  in the wavelength field  27   c  of the spectroscopic measurement data table  27   a  shown in  FIG. 14  at time interval WLT1 in the time interval field  27   d  by the average emission intensity at wavelength WL 2  in the wavelength field  27   c  at time interval WLT2 in the time interval field  27   d  is also defined as an emission intensity monitor value. 
     The fixed-recipe residual field  28   h  stores information which identifies the degree of correlation between emission intensity monitor value and etching result for data with a fixed-recipe when the values stored in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , and time interval 2 field  28   f , and the emission intensity monitor value calculated from the values in the spectroscopic measurement data table  24   a  shown in  FIG. 11  are used. In this embodiment, the smaller the value is, the stronger the correlation is. 
     The changed-recipe residual field  28   i  stores information which identifies the degree of correlation between emission intensity monitor value and etching result for data with a changed recipe when the values stored in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , and time interval 2 field  28   f , and the emission intensity monitor value calculated from the spectroscopic measurement data table  27   a  shown in  FIG. 14  are used. In this embodiment, the smaller the value is, the stronger the correlation is. 
     The model difference field  28   j  stores information which identifies the magnitude of difference between the following two functions: the function representing the relation between emission intensity monitor value and etching result when the values stored in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , and time interval 2 field  28   f  and the emission intensity monitor value calculated from the spectroscopic measurement data table  24   a  shown in  FIG. 11  are used, and the function representing the relation between emission intensity monitor value and etching result when the values stored in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , and time interval 2 field  28   f  and the emission intensity monitor value calculated from the spectroscopic measurement data table  27   a  shown in  FIG. 14  are used. In this embodiment, the smaller the value is, the smaller the difference between the two functions is. 
     The overall evaluation field  28   k  stores information which indicates the degree of suitableness for APC of the combination of the wavelengths, time intervals, and recipe as stored in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , time interval 2 field  28   f , and changed-recipe parameter field  28   g . In this embodiment, the field stores the weighted sum of the values stored in the relevant row of the fixed-recipe residual field  28   h , changed-recipe residual field  28   i , and model difference field  28   j . A combination for which the value in the overall evaluation field  28   k  is relatively small is presented to the apparatus manager and used for APC. 
     Analysis Processing by the Analysis Module  20   
     The analysis method according to this embodiment is an analysis method which determines the combination of wavelength, time interval, and recipe parameter for spectroscopic measurement data to be used for APC in the semiconductor etching process for etching a semiconductor wafer using plasma. 
     In the analysis method according to this embodiment, for each of candidates for the wavelength, time interval and recipe parameter to be used for APC, an evaluation is made of the degree of correlation between emission intensity monitor value and etching result with a fixed recipe, the degree of correlation between emission intensity monitor value and etching result with a changed recipe, and the difference between the correlation between emission intensity monitor value and etching result with a fixed recipe and the correlation between emission intensity monitor value and etching result with a changed recipe, and a suitable combination of wavelength, time interval, and recipe parameter for APC is determined. 
     This analysis method is used not only to determine the combination of wavelength, time interval and recipe but also can be used to determine the wavelength for use in APC, the time interval for use in APC, or the recipe for use in APC. For example, if one candidate is previously selected for any one factor (for example, time interval and recipe), the value of the other factor (for example, wavelength) for use in APC can be determined. 
     Next, how analysis processing according to this embodiment is performed will be described concretely. 
     In the production process, as a step prior to the step of sequentially etching wafers using the etching apparatus  1 , the apparatus manager who operates the etching apparatus  1  carries out analysis using the analysis module  20  to determine the combination of wavelength, time interval, and recipe parameter to be used in APC. 
     Since the combination of wavelength, time interval, and recipe parameter which is suitable for APC varies depending on the structure of the surface film of the semiconductor wafer to be etched, it is necessary to carry out this analysis as appropriate at the start of etching. In the production process (mass production process), a plurality of wafers are sequentially etched by the etching apparatus  1  under the etching conditions determined by this analysis. 
       FIG. 16  shows the steps which the apparatus manager carries out for analysis by the analysis module  20 . 
     First, the apparatus manager collects spectroscopic measurement data and etching result data by etching a plurality of wafers sequentially with a fixed standard recipe (S 201 ). Data is thus stored in the fixed-recipe etching result data table  23   a  shown in  FIG. 10  and the fixed-recipe spectroscopic measurement data table  24   a  shown in  FIG. 11 . 
     Next, the apparatus manager changes the recipe and collects spectroscopic measurement data and etching result data by etching a plurality of wafers sequentially (S 202 ). For example, the flow rate of the gas type specified by the apparatus manager is changed. The amount of change may be specified by the apparatus manager or the gas flow rate may be automatically changed by a predetermined amount. In this embodiment, it is assumed that only one recipe parameter is changed at a time from the standard recipe. However, data may be collected by changing two or more recipe parameters. Furthermore, the recipe may be changed for a specific part of the etching time: for example, the gas flow rate in the latter half of the etching time may be changed. Consequently, data is stored in the changed-recipe etching result data table  25   a  shown in  FIG. 12 , the changed-recipe recipe data table  26   a  shown in  FIG. 13 , and the changed-recipe spectroscopic measurement data table  27   a  shown in  FIG. 14 . 
     Next, the apparatus manager enters candidates for wavelength, time interval, and changed recipe parameter on an input display screen shown in  FIG. 23  (S 203 ) and starts analysis processing (S 204 ). 
     As wavelength candidates, wavelengths within a specific numerical range such as 201 nm and 211 nm, the emission wavelength of an element related to the etching process, such as 251 nm (emission wavelength of Si), and 675 nm (emission wavelength of Ar) may be entered. As a time interval candidate, etching time information such as a time interval (51-100) in the latter half of the etching time or the entire etching time (1-100) is entered. As a changed recipe parameter candidate, information on the changed recipe parameter used in the etching process at S 202  is entered. 
     The apparatus manager gives a command to perform analysis processing and the analysis module  20  performs analysis processing. The apparatus manager enters settings for APC using the result of analysis by the analysis module  20  to perform etching (S 205 ). 
     Next, the flow of analysis processing steps which are performed by the analysis module  20  will be described referring to  FIG. 17 . 
     When a button D 106  to start analysis processing is clicked with a cursor (not shown) on a display D 100  shown in  FIG. 23 , the analysis module  20  starts analysis processing. First, combinations of wavelength candidates D 101  and D 103 , time interval candidates D 102  and D 104 , and changed recipe candidate D 105  are created from the information on wavelength candidates, time interval candidates and changed recipe candidates as entered on the display D 100 , and stored in the APC setup data candidate table  28   a  shown in  FIG. 15  (S 301 ). Next, using the information on the wavelength candidates D 101  and D 103  and time interval candidates D 102  and D 104  in the combinations of wavelength candidates D 101  and D 103 , time interval candidates D 102  and D 104 , and changed recipe candidate D 105  as created at S 301 , the emission intensity monitor value is calculated from data with a fixed recipe (S 302 ). Also, as information indicating the degree of correlation between emission intensity and etching result with a fixed recipe, the residual of the regression equation (regression line) between emission intensity monitor value and etching result is calculated (S 303 ). Furthermore, the coefficient of the regression equation (regression line) between emission intensity monitor value and etching result is calculated (S 304 ). 
     Next, using data obtained by changing the changed-recipe parameter candidate D 105  in the combination of wavelength, time interval, and changed recipe parameter as created at S 301 , the emission intensity monitor value with the changed recipe at the wavelength and time interval in this combination is calculated (S 305 ). As information indicating the degree of correlation between the calculated emission intensity monitor value and the etching result with the changed recipe, the residual of the regression equation (regression line) between emission intensity monitor value and etching result is calculated (S 306 ). Furthermore, the coefficient of the regression equation (regression line) between emission intensity monitor value and etching result is calculated (S 307 ) and the estimation error of the coefficient of the regression equation (regression line) is calculated ( 308 ). 
     From the coefficients of the regression equations (regression lines) and coefficient estimation error as calculated at S 304 , S 307 , and S 308 , the difference between the coefficients of the regression equations is calculated as the information indicating the difference between the correlation of emission intensity monitor value and etching result with a fixed recipe and the correlation of emission intensity monitor value and etching result with a changed recipe (S 309 ). 
     The overall evaluation value  28   k  which indicates the degree of suitableness for APC of a combination of wavelength, time interval, and changed recipe parameter is calculated from the residuals of the regression equations (regression lines) as calculated at S 303  and S 306  and the difference between the coefficients of the regression equations (equation lines) as calculated at S 309  (S 310 ). 
     The steps from S 302  to S 310  are carried out for all the combinations of wavelength candidates D 101 , D 103 , time interval candidates D 102 , D 104 , and changed recipe parameter candidate D 105  and when all calculations are finished (Yes at S 311 ), a combination of wavelength, time interval, and changed recipe parameter for which the overall evaluation value  28   k  is small is presented to the apparatus manager as the wavelength, time interval, and changed recipe parameter to be used for APC (S 312 ). 
     Next, the above steps will be described in detail. 
     (S 301 ): The arithmetic processing section  21  creates a plurality of combinations of two wavelengths, two time intervals, and a changed recipe parameter, using the wavelength candidates and time interval candidate entered in the wavelength 1 input field D 101  and time interval 1 input field D 102  of the display D 100  shown in  FIG. 23 , the wavelength candidates and time interval candidate entered in the wavelength 2 input field D 103  and time interval 2 input field D 104 , and the changed recipe parameter candidate entered in the changed recipe parameter input field D 105 , and stores each combination of wavelengths, time intervals and changed recipe parameter in the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , time interval 2 field  28   f , and changed recipe parameter field  28   g  of the APC setup data candidate table  28   a  shown in  FIG. 15 , respectively. The combinations stored there may be combinations of all wavelengths, time intervals, and changed recipe parameters entered in the input fields D 101 , D 102 , D 103 , D 104 , and D 105 . Also, the arithmetic processing section  21  assigns numbers to the first and subsequent rows in the ID field  28   b  sequentially. 
     The arithmetic processing section  21  performs steps S 302  to S 310  for the combination of wavelengths, time intervals, and changed recipe parameter which is stored in each row of the APC setup data candidate table  28   a . Hereinafter, the row for which processing is performed will be called “the row concerned”. 
     (S 302 ): The arithmetic processing section  21  creates an emission intensity monitor value data table  29   a  which includes the wafer ID field  29   b , emission intensity monitor value field  29   c , and etching result field  29   d , as shown in  FIG. 18 . 
     The wafer ID field  29   b  of the emission intensity monitor value data table  29   a  stores information which indicates the wafer for which data has been acquired, for example, information stored in the wafer ID field  23   b  of the fixed-recipe etching result data table  23   a  shown in  FIG. 10 . 
     The emission intensity monitor value field  29   c  stores the emission intensity monitor value as the first average emission intensity value (described below) divided by the second average emission intensity value (described below). The first average emission intensity value is the average of values stored in the column identified by the wavelength stored in the row concerned of the wavelength 1 field  28   c  of the APC setup data candidate table  28   a  shown in  FIG. 15  and in the time row identified by the time interval 1 field  28   d , in the emission intensity value field  24   e  of the fixed-recipe spectroscopic measurement data table  24   a  shown in  FIG. 11 . The second average emission intensity value is the average of values stored in the column identified by the wavelength stored in the row concerned of the wavelength 2 field  28   e  of the APC setup data candidate table  28   a  and in the time row identified by the time interval 2 field  28   f , in the emission intensity value field  24   e  of the fixed-recipe spectroscopic measurement data table  24   a.    
     The etching result field  29   d  of the emission intensity monitor value data table  29   a  shown in  FIG. 18  stores information stored in the etching result field  23   c  of the fixed-recipe etching result data table  23   a.    
     (S 303 ): The arithmetic processing section  21  calculates the square average (AveSe 1 ) of the residual of the regression equation as information which indicates the degree of correlation between emission intensity monitor value and etching result for data with a fixed recipe, using the data stored in the emission intensity monitor value data table  29   a  and the following equations (Equation 1) to (Equation 5). 
     
       
         
           
             
               
                 
                   
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     In the above equations, x i  denotes the value stored in the i-th column of the emission intensity monitor value field  29   c  of the emission intensity monitor value data table  29   a  shown in  FIG. 18 ; y i  denotes the value stored in the i-th column of the emission intensity monitor value field  29   c ; n denotes the number of columns of the emission intensity monitor value data table  29   a ; and E denotes the sum of values in all the columns of the emission intensity monitor value data table  29   a.    
     The meanings of the calculated values are explained below referring to  FIG. 20 . The graph of  FIG. 20  is a scatter diagram which plots the values stored in the emission intensity monitor value field  29   c  and the values stored in the etching result field  29   d  for each wafer ID  29   b  in the emission intensity monitor value data table  29   a  shown in  FIG. 18 . 
     In  FIG. 20 , points such as A 601 , which represent the values stored in the columns of the emission intensity monitor value field  29   c  of the emission intensity monitor value data table  29   a , are plotted with the values stored in the emission intensity monitor value field  29   c  on the horizontal axis and the values stored in the etching result field  29   d  on the vertical axis. 
     The value (X 11 ) calculated by (Equation 1) represents dispersion of plotted points in  FIG. 20  in the horizontal axis direction (emission intensity monitor value) and the value (X 12 ) calculated by (Equation 2) represents dispersion of plotted points in  FIG. 20  in the horizontal axis direction (etching result). The value (X 13 ) calculated by (Equation 3) represents the sum of products of deviation of plotted points in  FIG. 20  in the horizontal axis direction and vertical axis direction, in which when the value of a plotted point in the vertical axis direction is larger, its value in the horizontal axis direction is also larger. 
     In  FIG. 20 , line A 602  represents a line (regression equation) in which the average square sum of distances from points is minimum. The first residual square average (AveSe 1 ) calculated by (Equation 5) represents the square average of distances (residuals) between points and the line. 
     As for data with a fixed recipe, when the correlation between emission intensity monitor value and etching result is stronger, the residual square average (AveSe 1 ) is smaller. The first residual square average (AveSe 1 ) calculated by (Equation 5) is stored in the row concerned of the fixed-recipe residual field  28   h  of the APC setup data candidate table  28   a  shown in  FIG. 15  as information for evaluation of the combination of wavelengths and time intervals in the row concerned. 
     Alternatively, a value other than the residual square average thus calculated may be used, provided that it indicates the degree of correlation between emission intensity monitor value and etching result. For example, it may be the reciprocal of the absolute value of the coefficient of correlation between emission intensity monitor value and etching result or the reciprocal of the square of the coefficient of correlation. 
     (S 304 ): The arithmetic processing section  21  calculates the gradient of the regression equation (regression line) between emission intensity monitor value and etching result for data with a fixed recipe as information which indicates the direction of correlation between emission intensity monitor value and etching result. 
     The arithmetic processing section  21  calculates variable (a 1 ) on the left-hand side of (Equation 4), using (Equation 1), (Equation 3), and (Equation 4) and the values stored in the emission intensity monitor field  29   c  and etching result field  29   d  of the emission intensity monitor value data table  29   a  shown in  FIG. 18 . This variable (a 1 ) represents the gradient of line A 602  in  FIG. 20 . The arithmetic processing section  21  uses the calculated gradient (a 1 ) at the step S 310  which will be described later. 
     (S 305 ): The arithmetic processing section  21  creates a data table corresponding to the emission intensity monitor value data table  29   a  shown in  FIG. 18 , using data with a changed recipe. As an example,  FIG. 19  shows an emission intensity monitor value data table  29 - 2   a  in which data with a changed recipe is used. 
     Let&#39;s assume that Rcp denotes the value stored in the row concerned with the changed recipe parameter field  28   g  of the APC setup data candidate table  28   a  shown in  FIG. 15 . The emission intensity monitor data table  29 - 2   a  shown in  FIG. 19  stores the data on the wafer for which the recipe parameter identified by Rcp has been changed, among the wafers for which the etching result and spectroscopic measurement data have been obtained. 
     For example, the wafer ID field  29 - 2   b  stores, as information indicating the wafer for which data has been obtained, a wafer ID among wafer IDs stored in the wafer ID field  23   b  of the changed-recipe etching result data table  23   a  shown in  FIG. 10 , for which the value of the recipe parameter corresponding to Rcp in the recipe change amount field  26   c  of the changed-recipe recipe data table  26   a  shown in  FIG. 13  is not 0. 
     The emission intensity monitor value field  29 - 2   c  stores an emission intensity monitor value as the third average emission intensity value (described below) divided by the fourth average emission intensity value (described below). The third average emission intensity value is the average of values stored in the column identified by the wavelength stored in the row concerned with the wavelength 1 field  28   c  of the APC setup data candidate table  28   a  shown in  FIG. 15  and in the time row identified by the time interval 1 field  28   d , in the emission intensity value field  27   e  of the changed-recipe spectroscopic measurement data table  27   a  shown in  FIG. 14 . The fourth average emission intensity value is the average of values stored in the column identified by the wavelength stored in the row concerned with the wavelength 2 field  28   e  of the APC setup data candidate table  28   a  and in the time row identified by the time interval 2 field  28   f , in the emission intensity value field  27   e  of the changed-recipe spectroscopic measurement data table  27   a . Among these averages, the value of the wafer for which the recipe parameter identified by Rcp has been changed is stored here. 
     The etching result field  29 - 2   d  of the emission intensity monitor value data table  29 - 2   a  stores the value of the wafer for which the value of the recipe parameter corresponding to Rcp in the recipe change amount field  26   c  shown in  FIG. 13  is not 0, among the data stored in the etching result field  25   c  of the changed-recipe etching result table  25   a  shown in  FIG. 12 . 
     (S 306 ): The arithmetic processing section  21  calculates the residual square average (AveSe 2 ) of the regression equation as information which indicates the degree of correlation between emission intensity monitor value and etching result for data with a fixed recipe, using the following equations, (Equation 6) to (Equation 10), which are obtained by substituting the data stored in the emission intensity monitor value data table  29   a - 2   a  shown in  FIG. 19  in (Equation 1) to (Equation 5). 
     
       
         
           
             
               
                 
                   
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     In the above equations, x′ i  denotes the value stored in the i-th column of the emission intensity monitor value field  29 - 2   c  of the emission intensity monitor value data table  29 - 2   a  shown in  FIG. 19 ; y′ i  denotes the value stored in the i-th column of the emission intensity monitor value field  29 - 2   c ; n′ denotes the number of columns of the emission intensity monitor value data table  29 - 2   a ; and denotes the sum of values in all the columns of the emission intensity monitor value data table  29 - 2   a.    
     The second residual square average (AveSe 2 ) calculated by (Equation 10) represents the square average of distances (residuals) between the line and the regression equation as in the case of (Equation 5). 
     As for data with a changed recipe, when the correlation between emission intensity monitor value and etching result is stronger, the second residual square average (AveSe 2 ) is smaller. The second residual square average (AveSe 2 ) calculated here is stored in the row concerned of the changed-recipe residual field  28   i  of the APC setup data candidate table  28   a  shown in  FIG. 15  as information for evaluation of the combination of wavelengths and time intervals in the row concerned. 
     Alternatively, a value other than the residual square average thus calculated may be used, provided that it indicates the degree of correlation between emission intensity monitor value and etching result. For example, it may be the reciprocal of the absolute value of the coefficient of correlation between emission intensity monitor value and etching result or the reciprocal of the square of the coefficient of correlation. 
     (S 307 ): The arithmetic processing section  21  calculates the gradient of the regression equation (regression line) between emission intensity monitor value and etching result for data with a changed recipe as information which indicates the direction of correlation between emission intensity monitor value and etching result. 
     The arithmetic processing section  21  calculates variable (a 2 ) on the left-hand side of (Equation 9), using (Equation 6), (Equation 8), and (Equation 9) and the values stored in the emission intensity monitor field  29 - 2   c  and etching result field  29 - 2   d  of the emission intensity monitor value data table  29 - 2   a  shown in  FIG. 19 . This variable (a 2 ) represents the gradient of the regression equation (regression line) created from data with a changed recipe. 
     (S 308 ): The arithmetic processing section  21  calculates information which indicates a gradient estimation error of the regression equation (regression line) obtained from data with a changed recipe, using the following equation (Equation 11): 
     
       
         
           
             
               
                 
                   
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     The meaning of the calculated value is explained below referring to  FIGS. 21A and 21B . The graphs of  FIGS. 21A and 21B  are scatter diagrams which plot the values stored in the emission intensity monitor value field  29 - 2   c  and the values stored in the etching result field  29 - 2   d  for each wafer ID  29 - 2   b  in the emission intensity monitor value data table  29 - 2   a  shown in  FIG. 19 . 
     In  FIGS. 21A and 21B , points such as A 701  and A 801 , which represent the values stored in the columns of the emission intensity monitor value field  29 - 2   c  of the emission intensity monitor value data table  29 - 2   a  shown in  FIG. 19 , are plotted with the values stored in the emission intensity monitor value field  29 - 2   c  on the horizontal axis and the values stored in the etching result field  29 - 2   d  on the vertical axis. Lines A 702  and A 802  represent lines (regression equations) in which the average square sum of distances from points is minimum. Points A 703  and A 803  represent data missing from the emission intensity monitor value data table  29 - 2   a  (due to a failure in data transfer from the inspection device, etc.) and lines A 704  and A 804  represent regression equations obtained by adding points A 703  and A  803  to points A 701  and A 801 . 
     It is known that line A 704  is smaller in change (change in gradient) from the original line A 702  than line A 804 . Dispersion (X 11 ) in the horizontal axis direction is larger in the scatter diagram of  FIG. 21A  than in the scatter diagram of  FIG. 21B  and in the case shown in  FIG. 21A , gradient estimation can be less affected by missing data, etc. Regarding the gradient estimation error (Δa 2 ) calculated by (Equation 11), when dispersion (X′ 11 ) in the horizontal axis direction is larger, the gradient estimation error is smaller. 
     (S 309 ): The arithmetic processing section  21  calculates the value of evaluation of the difference between the direction of correlation with a fixed recipe and the direction of correlation with a changed recipe from the following (Equation 12), using the variables (a 1 ) and (a 2 ) calculated by (Equation 4) and (Equation 9) and the variable (Δa 2 ) indicating the gradient estimation error calculated by (Equation 11). 
         E   a   {|a   1   −a   2   |+Δa   2 } 2   ×Δei   2   (Equation 12)
 
     (Equation 12) suggests that when the difference between the gradient of the regression equation with a fixed recipe and the gradient of the regression equation with a changed recipe is larger or the gradient estimation error is larger, the value (E a ) of evaluation of gradient difference on the left-hand side is larger. Δei on the right-hand side represents the difference between the emission intensity monitor value control target eit and the minimum emission intensity monitor value eimin with a fixed recipe as shown in  FIG. 22A . The equation suggests that when the difference from the control target is larger, the amount of recipe change is larger and the contribution of gradient difference is larger. 
     As for data with a fixed recipe as well, the gradient estimation error of the regression equation may be calculated and added to the inside of the parentheses of (Equation 12). Also, Δa 2  may be multiplied by a constant factor (1.5, 2 and so on). (X 11 ), which indicates dispersion of emission intensity monitor values with a fixed recipe, may be used instead of Δei 2 . 
     The arithmetic processing section  21  stores the value (E a ) of evaluation of gradient difference as calculated by (Equation 12) in the row concerned with the model difference field  28   j  of the APC setup data candidate table  28   a.    
     (S 310 ): The arithmetic processing section  21  calculates the degree of suitableness for APC of a combination of wavelength, time interval, and changed recipe parameter, using the following equation (Equation 13): 
         E   all =AveSe 1 ×α 1 +AveSe 2 ×α 2   +E   a ×α 3   (Equation 13)
 
     On the right-hand side of (Equation 13), the first term is a term for evaluating the degree of correlation with a fixed recipe, the second term is a term for evaluating the degree of correlation with a changed recipe, and the third term is a term for evaluating the difference in correlation tendency between a fixed recipe and a changed recipe. Coefficients α 1 , α 2 , and α 3  are weighting factors of the terms which are determined by the apparatus manager, etc. (Equation 13) suggests that when the evaluation value (E all ) calculated by (Equation 13) for a combination of wavelength, time interval, and recipe is small, it is a combination which ensures that the correlation is strong with a fixed recipe and with a changed recipe and the direction of correlation with a fixed recipe is the same as with a changed recipe. 
     The arithmetic processing section  21  stores the calculated evaluation value (E all ) in the row concerned with the overall evaluation field  28   k  of the APC setup data candidate table  28   a  shown in  FIG. 15 . 
     (S 311 ): If the arithmetic processing section  21  has finished calculating overall evaluation values (E all ) for all combinations of wavelength, time interval, and changed recipe parameter, it proceeds to step S 312  or if it has not finished, it returns to step S 302  and performs processing for the next combination of wavelength, time interval and changed recipe parameter. 
     (S 312 ): The arithmetic processing section  21  outputs the result of analysis processing on the display, specifically the values stored in the APC setup data candidate table  28   a  shown in  FIG. 15  and data related to scatter diagrams, and ends the processing sequence.  FIG. 24  shows an example of the output display screen of the output module  31  which is presented to the operator by the arithmetic processing section  21 . 
     The output display screen D 200  shown in  FIG. 24  includes a table D 201  which lists the values stored in the rows of the wavelength 1 field  28   c , time interval 1 field  28   d , wavelength 2 field  28   e , time interval 2 field  28   f , changed recipe parameter field  28   g , and overall evaluation field  28   k , in the ascending order of the value stored in the overall evaluation field  28   k  of the APC setup data candidate table  28   a  shown in  FIG. 15 . 
     As for the combination of wavelengths, time intervals and changed recipe parameter for which the value in the overall evaluation field  28   k  is the smallest, D 202  is a scatter diagram of emission intensity monitor value and etching result with a fixed recipe as obtained by calculation of emission intensity monitor values using the relevant wavelengths and time intervals. Similarly, D 203  is a scatter diagram of emission intensity monitor value and etching result for data with a changed recipe in which the value of the relevant changed recipe parameter is changed. 
     The apparatus manager can know the combination of wavelengths, time intervals and changed recipe parameter to be used for APC by checking the output display screen D 200  shown in  FIG. 24 . 
     The combination of wavelengths  2402 ,  2404 , time intervals  2403 ,  2405 , and changed recipe parameter  2406  which corresponds to the smallest value of overall evaluation  2407  and the first place of overall evaluation ranking  2401  in the table D 201  shown in  FIG. 24  is stored in the columns of the APC setup data candidate table  15   a  shown in  FIG. 4 . As the apparatus manager clicks the button D 204  for execution of APC with the cursor (not shown) on the display screen D 200  to acknowledge execution of APC with the first-ranked combination, the control section  13  of the etching module  10  controls the plasma processing section  11  using the data stored in the APC setup data table  15   a  so that the wafers  114  are etched sequentially. 
     As explained so far, the combination of wavelengths, time intervals and changed recipe parameter to be used for APC can be selected among many combinations of wavelengths, time intervals and changed recipe parameter, using the analysis method which is performed by the etching apparatus  1  (analysis module  20 ) according to this embodiment. 
     According to this embodiment, the wavelengths and time intervals for calculation of emission intensity monitor values can be appropriately determined from spectroscopic measurement data. Also, the recipe parameter to be changed for APC can be appropriately determined among a plurality of recipe parameters. Consequently, even when the recipe is changed, the correlation between emission intensity monitor value and etching result is stabilized with a constant tendency and the etching result is controlled with high accuracy. 
     The invention has been so far explained in reference to the preferred embodiment thereof. 
     The invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiment is therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims, rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.