JP5302634B2 - Substrate processing management device - Google Patents

Description

  The present invention relates to a substrate processing apparatus that performs processing such as thin film formation on a substrate such as a semiconductor wafer for forming a semiconductor device or a glass substrate for forming an LCD, and in particular, is processed by the substrate processing apparatus. The present invention relates to a technology for managing board quality.

  In general, in a substrate processing apparatus, set values such as temperature and gas flow rate and processing time thereof are specified as data in a recipe, and substrate processing is executed based on the data specified in the recipe. ing. And when adjusting the processing amount (for example, film-forming thickness) of a board | substrate, recipe data are changed and a substrate processing apparatus is made to perform a process based on the said recipe data.

In the substrate processing apparatus using such recipe data, in order to manage the quality of the processed substrate, the processed substrate is set on a measuring instrument and the processing amount is measured. After registering, it is inspected later whether the measured data is within the normal range.
And when quality is bad, the operator changes the recipe data which processed the to-be-processed object based on an empirical rule, and makes the substrate processing apparatus perform the next process using the changed recipe data.

  As described above, in the conventional quality management, the operator manually registers the measurement data of the substrate processing amount, the operator judges the quality based on the registered data, and further changes the recipe data. There was a problem like this.

Because many engineers who are familiar with the relationship between the recipe data and the processing amount for each processing type are necessary, and the relationship between the recipe data and the processing amount is slightly different due to changes over time, even for the same processing type. Since a large number of skilled engineers are required, a great amount of labor and cost are required to stabilize the processing quality.
In addition, since it takes a certain amount of time each time the measurement data is registered and the quality is judged based on the measurement data and the recipe data is changed, a waiting time until the next processing occurs. The occupancy rate has declined. Alternatively, when the next process is executed without waiting for a quality inspection based on the measurement data, it is easy to make a defective product, and the productivity is lowered.

In addition, since it is difficult to predict the processing amount in the next and subsequent processing, there is a risk that the processing amount will be an abnormal value, and the recipe data is changed after measuring the abnormal value. As a result, the treatment turned to the back, and the productivity was reduced.
In addition, LCDs and semiconductor manufacturing lines require extremely high cleanliness, so it is strongly desired to eliminate paper that is a source of particle generation. However, paper for saving measurement data, recipe data, etc. Therefore, productivity has been reduced due to quality deterioration caused by particles.

  The present invention has been made in view of the above-described conventional circumstances, and an object thereof is to reduce the burden of substrate processing quality management work and to continuously stabilize the substrate quality.

In addition to the function of causing the substrate processing apparatus to execute processing based on the data specified in the recipe, the substrate processing management apparatus according to the present invention further includes processing result data measured from the substrate processed by the substrate processing apparatus. Is received from the measuring instrument via the communication path, and the received measurement data is stored in association with the recipe data obtained by processing the substrate.
This automatically collects data for grasping how a substrate is processed according to recipe data without generating particles or missing necessary data. can do.

Further, the substrate processing management apparatus according to the present invention includes means for calculating a relational expression between recipe data and substrate processing result data from a plurality of measurement data, a graph of the calculated relational expression, and the plurality of measurement data. Display means for displaying on the same graph screen.
Thereby, the processing amount according to the recipe data is statistically analyzed, and the operator can grasp at a glance a variation in the actually measured processing amount with respect to the processing amount that is statistically originally obtained.

  Further, the substrate processing management apparatus according to the present invention includes means for calculating a relational expression between recipe data and substrate processing result data from a plurality of measurement data, a quality control rule inputted by an operator, and a target value of the substrate processing result. Means for receiving, means for calculating recipe data corresponding to the target value by back-calculating the relational expression calculated using the target value when the measurement data received by the receiving means deviates from the quality control rule; Control means for causing the substrate processing apparatus to execute processing based on the calculated recipe data.

Thereby, the substrate processing amount is automatically managed according to the quality control rule designated by the operator. When the actual processing amount deviates from this rule, recipe data that should achieve the target processing amount (target value) specified by the operator is automatically calculated, and based on the recipe data. As a result of the subsequent processing performed by the substrate processing apparatus, the production of defective products is quickly suppressed, and quality stabilization is performed automatically and in real time.
In the substrate processing management apparatus according to the present invention, the operator can also input and specify the relational expression between the recipe data and the substrate processing result data, and the recipe data can be corrected according to the rule of thumb. .

Further, in the substrate processing management apparatus according to the present invention, the upper limit value and the lower limit value of the processing result data are set as the quality control rule, and the measurement data received from the measuring instrument is between these upper limit value and lower limit value. In the case of deviating, a rule for calculating corresponding recipe data using the target value is used.
As a result, the actual processing amount can be automatically stored between the upper limit value and the lower limit value specified by the operator, and substrate processing with a certain quality can be realized.

Further, in the substrate processing management apparatus according to the present invention, as a quality control rule, when a plurality of continuous measurement data received from the measuring device are all above or below the target value, the corresponding recipe data is calculated using the target value. Use the rule that
Accordingly, it is possible to predict that the actual processing amount tends to exceed or fall below the target value, and it is possible to correct the recipe data and realize substrate processing with a certain quality before a large deviation occurs. .

  In addition, the present invention connects a substrate processing management apparatus to a substrate processing apparatus and a measuring instrument via a communication line, causes the substrate processing apparatus to execute processing based on data specified in a recipe by the substrate processing management apparatus, and performs measurement. The present invention is also realized as a substrate processing management system that manages the quality of the substrate processed by the substrate processing apparatus based on the measurement data obtained from the container. Then, the measuring instrument measures predetermined processing result data from the substrate processed by the substrate processing apparatus, and the substrate processing management apparatus has the above-described functional units, and automatically collects measurement data and stores recipe data. Achieves stable board quality through automatic correction.

  In particular, in the stabilization of the substrate quality in the present invention, the measurement result data of the substrate is measured by measuring the substrate processed by the substrate processing apparatus with a measuring instrument, and a plurality of substrates obtained by the measuring instrument are measured. Calculate the relational expression between the recipe data and the substrate processing result data from the measurement data, and back-calculate the relational expression using the preset target value when the measurement data obtained from the measuring instrument deviates from the quality control rules Thus, a substrate processing management method is performed in which recipe data corresponding to the target value is calculated, and the substrate processing apparatus executes processing based on the calculated recipe data.

  As described above, according to the present invention, the measurement data of the processing amount can be automatically collected by communication, so that the labor and labor costs of the worker can be saved and registered for quality control. Error and registration omission can be prevented. In addition, since it is possible to achieve paperless demand that is strongly desired in the semiconductor manufacturing line, it is possible to reduce particles, improve the quality (yield) of the object to be processed, and increase the production efficiency.

Further, according to the present invention, the operator can easily grasp the relationship between the processing amount and the recipe data, and can easily know the recipe data for obtaining the required processing amount. Therefore, it is possible to easily and appropriately adjust the processing amount of the new processing type.
Further, according to the present invention, it is possible to perform quality control according to a quality control rule desired by the operator. Moreover, since the recipe data can be changed automatically and in real time to stabilize the quality, the burden of quality control work can be reduced, the occurrence of defective products can be suppressed, and the production efficiency can be greatly improved.

The present invention will be specifically described by the following embodiments.
1 and 2 each show an example of a substrate management system to which the present invention is applied.
The system shown in FIG. 1 is a so-called job shop type, and includes a plurality of semiconductor manufacturing apparatuses 1 that perform film formation processing on a semiconductor wafer as a substrate of an object to be processed, and film formation processing performed on the semiconductor wafer. Measuring device 2 for measuring the amount (in this example, film thickness), and group management device 3 for managing a plurality of semiconductor manufacturing devices 1 using recipe data and managing the film quality applied to the semiconductor wafer And a LAN line 4 for connecting each semiconductor manufacturing apparatus 1 and measuring instrument 2 to the group management apparatus 3.

In such a job shop type system, an operator or an automatic transport vehicle (not shown) transports a semiconductor wafer to the semiconductor manufacturing apparatus 1 that is in charge of different processing, and performs the processing. Is repeatedly transferred to the measuring device 2 to measure the processing amount, and a predetermined film is formed on the semiconductor wafer.
In such a series of steps, as will be described later, the group management apparatus 3 communicates with the semiconductor manufacturing apparatus 1 and the measuring instrument 2 via the LAN line 4 to collect data measured by the measuring instrument 2, Display of collected measurement data, statistical analysis, download of recipe data to the semiconductor manufacturing apparatus 1 so as to achieve a stable processing amount based on quality control rules, and the like are performed.

  The system shown in FIG. 2 is called a so-called cluster type, and is applied to a plurality of processing chambers 5 for performing a film forming process on a semiconductor wafer as a substrate of an object to be processed, a cleaning device 6 for cleaning the semiconductor wafer, and a semiconductor wafer. The units such as the measuring device 7 for measuring the processing amount of the film forming process (film thickness in this example) and the load lock chamber 8 for loading / unloading the semiconductor wafer are arranged so as to face the center of the polygon. A cluster tool configuration is provided in which a transfer device 9 for transferring a semiconductor wafer between the units is disposed in the part. Further, in this system, a controller 10 for managing each unit 5 to 8 and the transfer device 9 using recipe data and managing a film forming quality applied to a semiconductor wafer, and a cluster tool and the controller 10 are connected. A LAN line 11 to be connected.

In such a cluster type system, the transfer device 9 transfers the semiconductor wafers to units that are in charge of different processes and performs the processing, and transfers the processed semiconductor wafers to the measuring device 7 to measure the processing amount. This is repeated to form a predetermined film on the semiconductor wafer.
In such a series of steps, as will be described later, the controller 10 communicates with the cluster tool via the LAN line 11 to collect data measured by the measuring instrument 7, display of the collected measurement data, and statistics. Based on the analysis and quality control rules, the recipe data is downloaded to the cluster tool so that the processing amount is stable.

FIG. 3 shows a functional configuration of an automatic quality management apparatus (substrate processing management apparatus) according to an example of the present invention. The automatic quality management apparatus is realized as the group management apparatus 3 in the system shown in FIG. 1, and is realized as the controller 10 in the system shown in FIG.
This automatic quality control apparatus statistically analyzes the relationship between the communication control unit 20 that communicates with the outside via a communication path, the processing amount data (measurement data) measured from the semiconductor wafer, and the recipe data, and the regression equation And a statistical analysis unit 30 for correcting the recipe data so as to satisfy the target value of the processing amount, a storage unit 40 for storing various data such as recipe data and measurement data, and an input / output interface for the operator And a screen control unit 50.

  The communication control unit 20 includes a communication interface, necessary hardware resources, and software. The communication control unit 20 communicates with the processing apparatus communication unit 21 that communicates with the substrate processing apparatus via the communication path, and communicates with the measuring instrument via the communication path. Measuring instrument communication means 22 for performing In other words, in the system of FIG. 1, communication with each semiconductor manufacturing apparatus 1 is performed by the processing apparatus communication means 21 via the LAN line 4, and communication with the measuring instrument 2 is performed by the measuring instrument communication means 22. In the system of FIG. 2, communication with each processing chamber unit 5 is performed by the processing device communication means 21 via the LAN line 11, and communication with the measuring instrument unit 7 is performed by the measuring instrument communication means 22.

  The statistical analysis unit 30 includes necessary hardware resources and software. The statistical analysis unit 30 statistically analyzes the relationship between the measurement data of the semiconductor wafer transmitted from the measuring instrument and the recipe data on which the processing is performed. Corresponding to satisfy the target value by reversely calculating the regression equation using the target value of the processing amount when the received measurement data deviates from the quality control rule. And statistical analysis means 32 for calculating recipe data.

  The storage unit 40 is configured by a memory that holds data in a readable and writable manner, and stores a recipe storage file 41 that stores recipe data that defines processing conditions by the substrate processing apparatus, and a measurement that stores measurement data received from a measuring instrument. It has a data file 42, a regression equation file 43 for storing the determined regression equation coefficients, and a quality control rule file 44 for storing target values (film thickness in this example) and quality control rules. .

  The screen control unit 50 is configured by a known input / output interface device such as a display device, a pointing device, and a key device, and includes an input means 51 that receives an input from the operator, and a screen that displays data to the operator. Display means 52.

  In this example, the measurement data from the measuring device is collected according to the procedure shown in FIGS. 4 to 7, the regression equation indicating the relationship between the processing amount and the processing time of the recipe data is determined, and the quality control set in advance is performed. Based on the rule, it is determined whether or not the measured data value is management-out. If it is management-out, the recipe data processing time is corrected to satisfy the target value based on the regression equation and downloaded to the substrate processing apparatus. Is automatically executed.

Here, in this example, the temperature setting value that defines the heating temperature and the processing time of heating by the temperature setting value are defined as recipe data. A plurality of types of recipe data are identified by the recipe name and stored in advance in the recipe storage file 41. As shown in FIG. 13 as an example in the case of the dry oxidation process, the temperature setting value is associated with the recipe name. A set with the processing time is set in advance as recipe data.
Further, the quality control rule and the target value are inputted by the operator as described later and stored in advance in the quality control rule file 44. As shown in FIG. A plurality of quality control rules and target values are set in advance in association with.

The contents of the quality control rule file 44 will be described. The target value is the target value of the film thickness that is the processing amount, and the upper limit value and the lower limit value are the limit value film thicknesses that can be regarded as normal in quality control. The specified number of data is each rule No. This is the number of measured data read in the process of No. Indicates whether is currently specified.
Rule No. 1 shown in FIG. The rule No. 1 is a rule for changing the recipe data subjected to the processing so as to satisfy the target value for the next processing when the measurement data of the current processing exceeds the upper limit value or falls below the lower limit value. .
Also, the rule No. 2 and rule no. Rule 3 assumes that the measurement data of this process tends to deviate from the limit value when the measurement data is biased above or below the target value, and the recipe data that has undergone the process is processed for the next process. The rule is changed to satisfy the value. That is, rule no. No. 2 is a rule for changing recipe data when the film thicknesses for the number of specified data of recent measurement data including the current process exceed all target values. 3 is a rule for changing the recipe data when the film thicknesses for the specified number of recent measurement data including the current process are all below the target value.

  First, using the function that the automatic quality control device has as the group management device 3 or the controller 10, the recipe data stored in the recipe storage file 41 designated by the operator from the input means 51 is transferred to the substrate via the communication path. By downloading to the processing device, the main control process shown in FIG. 4 is started. When the recipe data is downloaded in this manner and the processing by the substrate processing apparatus is started, the automatic quality control apparatus is in a state of waiting for a processing end notification from the substrate processing apparatus (step S1). When a processing end notification is received via the communication path and the processing device communication means 21 (step S2), the recipe name and data contents (temperature set value and processing time) of the recipe data in charge of the processing are measured in the measurement data file 42. (Step S3).

Next, the automatic quality control device enters a state where it waits to receive measurement data for the substrate subjected to the processing (in this example, a semiconductor wafer) (step S4), and the processing result data (this book) measured by the measuring instrument for the substrate. In the example, when (film thickness) is received as measurement data via the communication channel and the measuring instrument communication means 22 (step S5), the measurement data is stored in the measurement data file 42 in association with the recipe data in charge of the processing. (Step S6).
That is, as shown in FIG. 9 as an example in the case of the dry oxidation process, the measurement data (that is, the film thickness value) is the name of the recipe (recipe name) and the data content (that is, the temperature setting value and the process) And stored in association with (time).

  Next, the automatic quality control device uses the plurality of measurement data stored in the measurement data file 42 to determine a regression equation indicating the relationship between the measurement data and the processing time of the recipe data (step S7). More specifically, in this example, as will be described later, the regression equation determination means 31 performs a calculation process using the least square method according to the procedure shown in FIG. To store.

  Next, as will be described later, the statistical analysis means 32 performs statistical analysis processing according to the procedure shown in FIGS. 6 and 7 (step S8), and evaluates the measurement data obtained by this processing using the quality control rule and the target value. If the quality control rule is not satisfied, the recipe data in charge of the current process is changed using the corresponding regression equation, and this is stored in the recipe storage file 41.

Next, the control means (not shown) attached to the recipe storage file 41 and the processing device communication means 21 determines whether or not the recipe data has been changed by the statistical analysis process (step S9), and the recipe data is changed. If changed, the changed recipe data is downloaded from the communication means 21 to the substrate processing apparatus via the communication path (step S10). As a result, the substrate processing apparatus performs the next processing on the substrate using the changed recipe data, and performs processing that satisfies the target value on the substrate of the target object.
Therefore, if the desired film thickness is not obtained as a result of processing the substrate in a certain process cycle, the processing is automatically executed in accordance with the changed recipe data in the next process cycle. Therefore, the desired film thickness processing can be realized quickly.

The regression equation determination process (step S7) will be described in detail. As shown in FIG. 5, first, the measurement data value y that is the same as the recipe name and temperature setting value of the recipe data processed this time from the measurement data file 42 is obtained. All the processing time x is read and taken into the calculation buffer of the statistical analysis means 32 (steps S11 to S14).
Next, the product sum S (xy) of the processing time x and the measured data value (film thickness) y is calculated from the data taken into the calculation buffer, and the deviation square sum S (xx) of the processing time x is calculated. Then, the regression coefficient b is calculated by dividing the product sum of the processing time and the film thickness by the deviation sum of squares of the processing time (step S15). In this example, the relationship between the processing time x and the film thickness y is y = a + bx. However, the present invention can be applied to various relationships such as a curved relationship. it can.

Next, an average value of the film thickness y is calculated, an average value of the processing time x is calculated, and a value obtained by multiplying the average value of the processing time and the regression coefficient b is subtracted from the average value of the film thickness, and the y intercept a is calculated (step S16). Then, the calculated y-intercept a of the zeroth order coefficient and the regression coefficient b of the first order coefficient are stored in the regression equation file 43 (step S17).
That is, as shown in FIG. 11 as an example in the case of the dry oxidation treatment, the regression equation file 43 stores the calculated y-intercept a and regression coefficient b in association with the name of the corresponding recipe (recipe name). In the subsequent statistical analysis process (step S8), it is used to change the processing time of the recipe data. The y-intercept a and the regression coefficient b are input by the operator through desired values from the input means 51, stored in the regression equation file 43, and used for the recipe data changing process. Good.

Here, the calculation process (steps S15 and S16) will be described in more detail. In this process, as shown in FIG. 10, the tendency is composed of a plurality of measurement data values having variations within the relationship y = a + bx. An operation is performed to determine the coefficients a and b along.
That is, in the relationship y = a + bx, a and b are determined by the least square method so that Q = Σ {y _i − (a + bx _i )} ² is minimized, and the regression coefficient b is set to x and y. Is obtained by b = S (xy) / S (xx) by the sum of products S (xy) of S and the sum of squared deviations S (xx) of x, and the y-intercept a is determined as the mean value of y, the mean value of x, and the regression coefficient b Thus, the average value of a = y−b * (average value of x) is obtained.

The statistical analysis process (step S8) will be described in detail. As shown in FIG. 6, first, the quality control rule No. currently designated by the operator from the quality control rule file 44 is displayed. (Step S21), the rule No. The process according to this is performed (step S22).
This rule No. The process (step S22) according to FIG. This will be described using the second process.

First, rule no. 2 is stored in the quality control rule file 44 as shown in FIG. The target value of data that matches the number of designated data 2 and the recipe name of the recipe data processed this time is read (step S31).
Next, the measurement data value and the processing time of the data matching the recipe name of the recipe data processed this time are read from the measurement data file 42 for the designated number of data (steps S32 to S34).

  Next, it is determined whether all of the read measurement data values exceed the target value (step S35). If the measurement data does not exceed the target value, the measurement data does not tend to exceed the limit value, so the recipe data remains as it is. Do not change as. On the other hand, when the target value is exceeded, the measurement data tends to exceed the limit value. In order to prevent this, the recipe data is changed so as to approach the target value.

That is, the difference Δy between the latest measurement data value obtained for the current process and the target value is calculated (step S36), and the regression of data that matches the recipe name of the recipe data used for the current process is calculated from the regression equation file 43. The coefficient b is read (step S37).
Next, the difference Δy is divided by b to calculate a change Δx in the processing time of the recipe data (step S38), and Δx is subtracted from the processing time x of the current recipe data to be used for the next processing. The processing time x is determined, and the processing time of the corresponding data in the recipe storage file 41 is changed to the determined processing time x (step S39). As a result, the changed recipe data is downloaded to the substrate processing apparatus, and even if the result actually processed by the substrate processing apparatus tends to deviate from the intended value, the target value specified by the operator is set. Modifications are made to meet.

FIG. 8 shows the procedure of input / output processing performed by the screen control unit 50.
When the automatic quality control device is started up, the screen control unit 50 enters an input standby state (step S41). When an input from the operator is received from the input means 51 (step S42), the input type of this input is determined. (Step S43).
As a result, when the input type is recipe registration (step S44), the display unit 52 displays a recipe registration screen as shown in FIG. 14 (step S45). When the recipe name, temperature set value, and processing time are input from the input means 51 by the operator, these data are accepted (step S46), and these data are stored in the recipe in association with each other as shown in FIG. Store in the file 41 (step S47).

  On the other hand, when the input type is statistical analysis (step S48), necessary measurement data is read from the measurement data file 42 (step S49), and necessary regression equation coefficients are read from the regression equation file 43 (step S50). Then, a graph of a relational expression suitable for satisfying the target value is created using the regression coefficient (step S51), and the display means 52 displays the graph and the measured data value on the same graph screen as shown in FIG. (Step S52). Thus, the operator can grasp at a glance the measurement data accumulated in the measurement data file 42 and the trend graph that can realize the target value in relation to the measurement data.

  On the other hand, when the input type is registration of a quality management rule (step S53), the display unit 52 displays a quality management rule registration screen as shown in FIG. 16 (step S54). The name (recipe name), target value, upper limit value, lower limit value, and rule number of the recipe data to which the rule is applied from the input means 51 by the operator. Is input (step S55), and these data are stored in the quality control rule file 44 in association with each other as shown in FIG. 12 (step S56). Thereby, the operator can arbitrarily set a quality control rule for a desired recipe.

In the above example, each functional unit according to the present invention is configured using the computer system that constitutes the group management device 3 and the controller 10, but in the present invention, each functional unit is configured by a dedicated circuit or device. You may make it comprise.
In the above example, the temperature setting value and the processing time are used as recipe data, and the processing time is corrected according to the film thickness of the processing result. However, in the present invention, the temperature setting value may be corrected. Alternatively, the value may be corrected as recipe data including the gas flow rate, or the measured data may be the film quality of the substrate. In short, there is no particular limitation as long as it is recipe data set in the substrate processing apparatus, and there is no particular limitation on the measurement data as long as the processing result is to be inspected.

It is a figure which shows an example of the board | substrate management system to which this invention is applied. It is a figure which shows another example of the board | substrate management system to which this invention is applied. It is a functional block diagram which shows the automatic quality control apparatus which concerns on an example of this invention. It is a flowchart which shows the procedure of the main control process which concerns on an example of this invention. It is a flowchart which shows the procedure of the determination process of the regression type which concerns on an example of this invention. It is a flowchart which shows the procedure of the statistical analysis process which concerns on an example of this invention. It is a flowchart which shows the procedure of the quality control process which concerns on an example of this invention. It is a flowchart which shows the procedure of the screen control process which concerns on an example of this invention. It is a figure which shows the measurement data file structure which concerns on an example of this invention. It is a graph explaining the regression type calculation process which concerns on an example of this invention. It is a figure which shows the regression type file structure which concerns on an example of this invention. It is a figure which shows the quality control rule file structure which concerns on an example of this invention. It is a figure which shows the recipe storage file structure which concerns on an example of this invention. It is a figure which shows the recipe registration screen which concerns on an example of this invention. It is a figure which shows the statistical analysis screen which concerns on an example of this invention. It is a figure which shows the quality management rule registration screen which concerns on an example of this invention.

Explanation of symbols

3 ... group management device, 2, 7 ... measuring instrument, 4, 11 ... LAN line,
20 ... Communication control unit, 21 ... Processing device communication means,
22 ... Measuring instrument communication means, 30 ... Statistical analysis section,
31 ... regression equation determination means, 32 ... statistical analysis means, 40 ... storage unit,
41 ... Recipe storage file, 42 ... Measurement data file,
43 ... regression equation file, 44 ... quality control rule file,
50 ... Screen control unit, 51 ... Input means, 52 ... Display means,

Claims (8)

In the substrate processing management apparatus that causes the substrate processing apparatus to execute processing based on the recipe data defined in the recipe,
Receiving means for receiving processing result data measured from a substrate processed by the substrate processing apparatus;
Means for receiving the upper and lower limits and the target value of the processing result data;
The processing result data received by the receiving means is stored in association with the recipe data that has been processed for the substrate, and indicates the relationship between the recipe data and the processing result data from the plurality of stored processing result data. Means for calculating a regression equation;
When the processing result data received by the receiving unit deviates from between the upper limit value and the lower limit value, a difference Δy between the latest processing result data and the target value is calculated, and among the data relating to the regression equation The difference Δy is divided by the regression coefficient b using the regression coefficient b of the regression equation calculated from the data that matches the recipe name of the recipe data used for the current process to obtain the change Δx of the processing time of the recipe data. Means for subtracting the change Δx from the processing time x of the recipe data to determine the processing time x of the recipe data used for the next processing, and changing the recipe data to the determined processing time x ;
Control means for causing the substrate processing apparatus to execute a next process based on the changed recipe data;
A substrate processing management apparatus comprising: In a control method of a substrate processing apparatus for processing a substrate based on recipe data defined in a recipe,
Receiving process result data measured from a substrate processed by the substrate processing apparatus;
Receiving upper and lower limit values and target values of processing result data;
The received processing result data is stored in association with the recipe data that has been processed for the substrate, and a regression equation that indicates the relationship between the recipe data and the processing result data is calculated from the plurality of stored processing result data. And a process of
When the received processing result data falls outside the range between the upper limit value and the lower limit value, the difference Δy between the latest processing result data and the target value is calculated, and the current processing among the data relating to the regression equation is calculated. The difference Δy is divided by the regression coefficient b using the regression coefficient b of the regression equation calculated from the data that matches the recipe name of the used recipe data to obtain a change Δx in the processing time of the recipe data. Subtracting the change Δx from the processing time x to determine the processing time x of the recipe data used for the next processing, and changing the recipe data to the determined processing time x ;
A step of causing the substrate processing apparatus to execute a next process based on the changed recipe data;
A method for controlling a substrate processing apparatus, comprising: The substrate processing management apparatus according to claim 1,
The substrate processing management apparatus, wherein the processing result data is a film thickness value. The substrate processing management apparatus according to claim 1,
A substrate processing management apparatus characterized in that a processing time is defined as the recipe data. A method of manufacturing a semiconductor device having a step of causing a substrate processing apparatus to execute a process based on recipe data defined in a recipe,
Receiving process result data measured from a substrate processed by the substrate processing apparatus;
Receiving upper and lower limit values and target values of processing result data;
The received processing result data is stored in association with the recipe data that has been processed for the substrate, and a regression equation that indicates the relationship between the recipe data and the processing result data is calculated from the plurality of stored processing result data. And a process of
When the received processing result data falls outside the range between the upper limit value and the lower limit value, the difference Δy between the latest processing result data and the target value is calculated, and the current processing among the data relating to the regression equation is calculated. The difference Δy is divided by the regression coefficient b using the regression coefficient b of the regression equation calculated from the data that matches the recipe name of the used recipe data to obtain a change Δx in the processing time of the recipe data. Subtracting the change Δx from the processing time x to determine the processing time x of the recipe data used for the next processing, and changing the recipe data to the determined processing time x ;
A step of causing the substrate processing apparatus to execute a next process based on the changed recipe data;
A method for manufacturing a semiconductor device, comprising: A substrate processing management system for connecting a substrate processing management device to a substrate processing device via a communication line and managing the quality of the substrate processed by the substrate processing device based on recipe data defined in the recipe by the substrate processing management device Because
The substrate processing management apparatus is configured to receive processing result data measured from a substrate processed by the substrate processing apparatus via a communication path;
Means for receiving the upper and lower limits and the target value of the processing result data;
The processing result data received by the receiving means is stored in association with the recipe data that has been processed for the substrate, and indicates the relationship between the recipe data and the processing result data from the plurality of stored processing result data. Means for calculating a regression equation;
When the processing result data received by the receiving unit deviates from between the upper limit value and the lower limit value, a difference Δy between the latest processing result data and the target value is calculated, and among the data relating to the regression equation The difference Δy is divided by the regression coefficient b using the regression coefficient b of the regression equation calculated from the data that matches the recipe name of the recipe data used for the current process to obtain the change Δx of the processing time of the recipe data. Means for subtracting the change Δx from the processing time x of the recipe data to determine the processing time x of the recipe data used for the next processing, and changing the recipe data to the determined processing time x ;
Control means for causing the substrate processing apparatus to execute a next process based on the changed recipe data;
A substrate processing management system comprising: A recipe management method for a substrate processing apparatus for processing a substrate based on recipe data defined in a recipe,
Receiving process result data measured from a substrate processed by the substrate processing apparatus;
Receiving upper and lower limit values and target values of processing result data;
The received processing result data is stored in association with the recipe data that has been processed for the substrate, and a regression equation that indicates the relationship between the recipe data and the processing result data is calculated from the plurality of stored processing result data. And a process of
When the received processing result data falls outside the range between the upper limit value and the lower limit value, the difference Δy between the latest processing result data and the target value is calculated, and the current processing among the data relating to the regression equation is calculated. The difference Δy is divided by the regression coefficient b using the regression coefficient b of the regression equation calculated from the data that matches the recipe name of the used recipe data to obtain a change Δx in the processing time of the recipe data. Subtracting the change Δx from the processing time x to determine the processing time x of the recipe data used for the next processing, and changing the recipe data to the determined processing time x ;
A recipe management method for a substrate processing apparatus, comprising: A display method in the substrate processing management apparatus according to claim 1,
The substrate processing management apparatus performs calculation of the relational expression using a plurality of processing result data,
Furthermore, a display means for displaying the relationship between the recipe data and the processing result data is provided,
A display method in a substrate processing management apparatus, wherein the display means displays the graph of the calculated relational expression and the plurality of processing result data on the same graph screen.

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