JP6649073B2 - Substrate processing apparatus and quality assurance method thereof - Google Patents

Description

  The present invention relates to a substrate processing apparatus for processing a substrate and a quality assurance method thereof.

  In recent years, the quality assurance requirements of customers for equipment have become strict, and there has been an increasing demand for the delivery of equipment capable of realizing advanced equipment quality assurance (EEQA) based on data. . For example, in a substrate processing apparatus, it is necessary to manage the turntable torque, the number of revolutions, the flow rate of the polishing liquid, and the like as Equipment Engineering System (EES) data.

  Conventional EEQA is generally performed by a process of performing a test using an EEQA recipe, a process of extracting EES data from an apparatus, a process of sending EES data to the outside, and a process of analyzing the EES data with dedicated software. Met.

JP 2013-176828 A

  In the conventional method, the number of man-hours is large, and in particular, since EES data is taken out from the apparatus and sent, there is a problem that work efficiency is extremely poor. In addition, there is another problem that the security application procedure is complicated in order to take the EES data out of the factory.

  The present invention has been made in view of such a problem, and an object of the present invention is to provide a substrate processing apparatus capable of efficiently performing EEQA and a quality assurance method thereof.

According to one aspect of the present invention, a substrate processing unit that processes a substrate, and a device quality that acquires device operation data of the substrate processing unit and performs abnormality determination based on the device operation data while performing device quality assurance operation And a guarantee processing unit.
According to such an aspect, the abnormality is determined while performing the apparatus quality assurance operation. Further, since the substrate processing apparatus includes the apparatus quality assurance control unit, there is no need to send apparatus operation data to the outside. Therefore, EEQA can be efficiently realized.

Preferably, the device quality assurance control unit may perform the abnormality determination based on the device operation data and predetermined reference data.
More preferably, the reference data is data acquired by another substrate processing apparatus serving as a reference, latest data acquired by the substrate processing apparatus itself, or predetermined data.
Thereby, appropriate abnormality determination can be performed.

  Further, the device quality assurance control unit compares the average value, the standard deviation, the rise time, the fall time, the maximum value and the minimum value of the device operation data with the reference value based on the reference data as the abnormality determination. And an abnormal alarm may be issued.

Further, the device quality assurance control unit may issue a prediction alarm when a ratio of the device operation data when it is not determined to be abnormal to the acquired device operation data exceeds a predetermined value.
Thus, when the acquired device operation data is significantly different from the normal device operation data, a prediction alarm for predicting a failure can be issued.

At the end of the apparatus quality assurance operation, it is desirable that the abnormality determination has been completed.
Thereby, EEQA can be performed more efficiently.

  According to another aspect of the present invention, there is provided a quality assurance method for a substrate processing apparatus including a substrate processing unit for processing a substrate, wherein the apparatus operation data of the substrate processing unit is acquired while performing an apparatus quality assurance operation. Then, a quality assurance method for the substrate processing apparatus, which performs an abnormality determination based on the apparatus operation data, is provided.

  According to another aspect of the present invention, a substrate processing unit for processing a substrate, and while performing a device quality assurance operation, obtains device operation data of the substrate processing unit, and based on the device operation data, There is provided a substrate processing apparatus including: a device quality assurance control unit that adjusts a processing unit.

  According to such an embodiment, the substrate processing apparatus is adjusted while performing the apparatus quality assurance operation. Further, since the substrate processing apparatus includes the apparatus quality assurance control unit, there is no need to send apparatus operation data to the outside. Therefore, EEQA can be realized efficiently.

  The apparatus quality assurance control unit may adjust a substrate processing recipe of the substrate processing unit or an apparatus parameter of the substrate processing unit.

  According to another aspect of the present invention, there is provided a quality assurance method for a substrate processing apparatus including a substrate processing unit for processing a substrate, wherein the apparatus operation data of the substrate processing unit is acquired while performing an apparatus quality assurance operation. Further, there is provided a quality assurance method for a substrate processing apparatus, wherein the method adjusts the substrate processing unit based on the apparatus operation data.

  EEQA can be realized efficiently.

FIG. 2 is a block diagram schematically showing the substrate processing apparatus 100. FIG. 2 is a side view showing a main part of the polishing module 1. FIG. 1 is a block diagram showing an example of a system configuration for performing EEQA. 5 is a flowchart illustrating an EEQA procedure according to the first embodiment. The figure which shows an example of the screen which shows the determination result of reproducibility. Screen showing trend chart and histogram. The figure which shows an example of the screen which shows the determination result of stability. The figure which shows an example of the screen which shows the determination result of the transient characteristic. The screen which shows the time change of EES data. The figure which shows an example of the screen which shows the determination result of a temporal change. 9 is a flowchart illustrating an EEQA procedure according to the second embodiment.

  Hereinafter, embodiments of the present invention will be specifically described with reference to the drawings.

(First Embodiment)
FIG. 1 is a block diagram schematically showing the substrate processing apparatus 100. The substrate processing apparatus 100 includes one or a plurality of polishing modules 1 and cleaning modules 2, a transport module 3 for transporting a substrate between these modules, and an EEQA control unit 50 (device quality assurance control unit). The substrate to be processed is polished by the polishing module 1, and is cleaned and dried by the cleaning module 2. Hereinafter, the polishing module 1, the cleaning module 2, and the transport module 3 are collectively referred to as a substrate processing unit 10 in the sense that the substrate is processed.

  The EEQA control unit 50 obtains EES data of the substrate processing unit 10 and performs quality assurance. By providing the EEQA control unit 50 in the substrate processing apparatus 100, it is not necessary to extract the EES data from the outside, and the EEQA can be realized by a self-contained system in the substrate processing apparatus 100.

  Hereinafter, the polishing module 1 will be described in detail in order to mainly describe the polishing module 1 as an example. FIG. 2 is a side view showing a main part of the polishing module 1. As shown in FIG. 2, the polishing module 1 includes a polishing unit 10, a dressing unit 20, a turntable unit 30, and a polishing liquid supply nozzle 40. The polishing unit 10 includes a polishing head 11, a shaft 12 connected to the polishing head 11, an arm 13 rotatably supporting the shaft 12, and a support shaft 14 supporting the arm 13. The turntable unit 30 includes a turntable 31, a polishing pad 32, and a table shaft 33. The polishing pad 32 is mounted on the turntable 31. The turntable 31 is rotatable around a table axis 33.

  The polishing head 11 holds the substrate W. The shaft 12 connected to the polishing head 11 is connected to a motor (not shown). As the shaft 12 rotates, the polishing head 11 rotates about the axis of the shaft 12. The polishing head 11 is movable on the polishing pad 32 by the rotation of the support shaft 14. The polishing unit 10 polishes the substrate W by rotating the polishing head 11 about the axis of the shaft 12 and bringing the substrate W held by the polishing head 11 into sliding contact with the polishing pad 32 on the rotating turntable 31. . At this time, the polishing liquid is dropped from the polishing liquid supply nozzle 40.

  The dressing unit 20 includes a dresser 21, a dresser shaft 22 connected to the dresser, a dresser arm 23 that rotatably supports the dresser shaft 22, and a support shaft 24 that supports the dresser arm 23.

  The dresser 21 includes a diamond disk 211 in which diamond particles are fixed to a lower surface, and a disk holding portion 212 that holds the diamond disk 211, and is connected to a lower end of the dresser shaft 22. The dresser shaft 22 is connected to one end of the dresser arm 23 so as to be rotatable around an axis. The other end of the dresser arm 23 is connected to a rotatable support shaft 24. The diamond disk 211 is connected to the dresser shaft 22 by a flexible joint (not shown) inside the disk holding portion 212, so that the parallelism between the diamond disk 211 and the polishing pad 32 is maintained to some extent. ing.

  The dresser shaft 22 connected to the dresser 21 is connected to a motor (not shown). The rotation of the dresser shaft 22 causes the dresser 21 to rotate about the axis of the dresser shaft 22. The dresser 21 can move on the polishing pad 32 by rotating the support shaft 24. The dressing unit 20 rotates the dresser 21 by rotating the dresser shaft 22 and reciprocates the dresser arm 23 in the radial direction of the polishing pad 32, and moves the dresser 21 to the polishing pad 32 on the rotating turntable 31. And dressing is performed.

  FIG. 3 is a block diagram illustrating an example of a system configuration for performing EEQA. The host PC 51 and the plurality of substrate processing apparatuses 100 are connected on the same network via Ethernet (registered trademark) or the like.

  One of the plurality of substrate processing apparatuses 100 is a golden tool 100a. The golden tool 100a is a reference substrate processing apparatus. If there is no problem in the recipe executed by the golden tool 100a, the recipe is transferred to another substrate processing apparatus 100. The golden tool 100a stores EES data (apparatus operation data) when the EEQA operation (apparatus quality assurance operation) is executed. Then, one of the substrate processing apparatuses 100 different from the golden tool 100a is a target substrate processing apparatus 100b to be subjected to EEQA (hereinafter, simply referred to as a target substrate processing apparatus 100b).

  FIG. 4 is a flowchart showing the procedure of the EEQA according to the first embodiment, in which an abnormality is determined as to whether or not the EES data in the target substrate processing apparatus 100b has an abnormality. The EEQA control unit 50 includes a non-volatile storage medium (for example, an HDD), a memory, and a processor (for example, a CPU) (not shown). At least a part of the flowchart includes a program stored in the non-volatile storage medium. It may be expanded on a memory and executed by a processor.

  The EEQA control unit 50 acquires reference data for determining whether the EES data is abnormal (step S1). As a specific example, by specifying the IP address of the golden tool 100a, the EEQA control unit 50 causes the EES data stored in the golden tool 100a, more specifically, the latest EES data obtained when the EEQA operation is performed by the golden tool 100a. May be obtained as reference data. Thus, the EES data of the substrate processing apparatus 100a actually operating on the production line can be used as a reference.

  As another example, the reference data may be data that is determined in advance by the manufacturer of the substrate processing apparatus 100 and managed by the host PC 51. As another example, the reference data may be the latest EES data acquired by the target substrate processing apparatus 100b. The reference data may be a single value or a range having a width.

  Subsequently, the EEQA control unit 50 starts the EEQA operation and also starts the EEQA process (step S2). The EEQA operation refers to applying a predetermined EEQA recipe and causing the target substrate processing apparatus 100b to process a plurality of substrates. The EEQA recipe includes operating parameters of the substrate processing apparatus 100 (for example, processing time in the polishing module 1, airbag pressure in the polishing head 11, rotation number of the top ring, rotation number of the turntable 31, rotation number of the dresser 21). And the like, and a transfer route that defines which processing module processes the processing substrate unloaded from the carrier and returns to the carrier. The EEQA recipe may be set in advance in the EEQA control unit 50 or may be set from outside (for example, the host PC 51). Here, the EEQA processing refers to acquiring the EES data in the substrate processing unit 10 at a predetermined cycle (for example, 100 ms) determined based on the time required to process one substrate. A specific example of the acquired EES data will be described later.

  Further, the start of the EEQA operation is specifically performed by allocating a recipe to a substrate in a carrier and creating a job. The number of boards and the recipe to be assigned to each board are selected by the operator when creating a job.

  Then, the EEQA control unit 50 performs the abnormality determination based on the acquired EES data while performing the EEQA operation (Step S3). As will be described in detail later, as an abnormality determination of the substrate processing unit 10, the EEQA control unit 50 determines whether the value based on the acquired EES data (such as the average value of the EES data) exceeds a predetermined range with respect to the reference data. An abnormal alarm is issued, or a predicted alarm is issued when the acquired EES data satisfies a predetermined relationship and an abnormality is predicted. Until the EEQA operation ends, the EEQA control unit 50 continues the abnormality determination (Step S4).

  As described above, in the present embodiment, instead of acquiring the EES data during the EEQA operation and analyzing the EES data after the end of the EEQA operation, the EEQA operation and the abnormality determination based on the EES data are performed in parallel. Is one feature.

  The EEQA operation ends, and if there is no particular abnormality (YES in step S5), the EEQA control unit 50 ends the EEQA operation. It is desirable that the results of the EEQA operation and the abnormality determination can be downloaded from the target substrate processing apparatus 100b, for example, in the form of a report to be submitted to the customer.

  On the other hand, if there is an abnormality in the EEQA operation (NO in step S5), the abnormal part is adjusted by the operator (step S6), and another module (for example, if there is an abnormality in a certain polishing module 1), The polishing module 1) is operated, and the EEQA operation and the EEQA processing are started again (step S2).

  Subsequently, the abnormality determination in step S3 will be described with a specific example. In the EEQA, an abnormality determination is performed to guarantee at least one, and preferably all, of reproducibility, stability, transient characteristics, and aging.

  To determine the reproducibility, the average value of the EES data when the target substrate processing apparatus 100b processes each substrate in the EEQA operation is used. That is, the EEQA control unit 50 issues an abnormal alarm when the difference between the average value of the EES data and the set value specified in the EEQA recipe exceeds a predetermined reference value. The reference value can be determined based on the reference data obtained in step S1, for example, based on the difference between the average value of the EES data obtained by the golden tool 100a and the set value specified in the EEQA recipe. Can be determined.

  FIG. 5 is a diagram illustrating an example of a screen showing a determination result of reproducibility. This screen is displayed on a display (not shown) by the EEQA control unit 50, for example. On the screen, which of reproducibility, stability, transient characteristics, and temporal characteristics is displayed can be switched by a tab X that can be selected by an operator. In FIG. 5, reproducibility is selected. Also, which of the reproducibility of the cleaning module 2, the transport module 3 and the polishing module 1 is displayed can be switched by a tab Y which can be selected by the operator. ing. Further, which of the four polishing modules A to D included in the target substrate processing apparatus 100b is displayed can be switched by a tab Z that can be selected by the operator. Selected.

  The polishing module 1 has a unit such as a turntable 31 for polishing a substrate while rotating, and a top ring for holding a substrate and pressing the substrate against the turntable. For each unit, monitoring contents, monitoring targets, and monitoring items that are EES data are defined. For example, in the turntable 31, a rotation operation is set as monitoring content, a rotation motor is set as a monitoring target, and a motor torque and a rotation speed are set as monitoring items. In addition, the reference data acquired in step S1 of FIG. 3 is set as a QA management value.

  Then, in this EEQA operation, the processing of STEP 1 to STEP 25 is performed for each substrate. That is, the processing of STEP 1 to STEP 25 is performed on a certain substrate, and the processing of STEP 1 to STEP 25 is performed on the next substrate. Therefore, a result of processing a plurality of substrates for each STEP is obtained, and the EEQA control unit 50 records the EES data obtained when each substrate is processed.

  In the cell indicated by reference numeral 31 on the screen, the average value of the EES data (here, the number of rotations of the rotary motor of the turntable 31) of all the substrates processed in STEP 1 is displayed. Further, when the cell 31 is selected (for example, double-clicked), a screen shown in FIG. 6 is displayed. This screen is superimposed on the screen of FIG. 5, for example.

  FIG. 6 includes a trend chart, the horizontal axis of which is time (ie, corresponding to the processed substrate) and the vertical axis of which is the EES data value of each substrate processed in STEP1. That is, one point represents EES data when one substrate is processed. Also, the average value μ and μ ± 3σ (σ is the standard deviation) of the EES data are displayed together.

  FIG. 6 also includes a histogram, in which the horizontal axis is frequency and the vertical axis is EES data. Thereby, the distribution of the EES data can be grasped.

  Next, the stability will be described. To determine the stability, the standard deviation of the EES data when the target substrate processing apparatus 100b processes each substrate in the EEQA operation is used. That is, the EEQA control unit 50 issues an abnormal alarm when the standard deviation of the EES data exceeds a predetermined reference value. The reference value can be determined based on the reference data acquired in step S1, for example, based on the standard deviation of the EES data acquired by the golden tool 100a.

  FIG. 7 is a diagram illustrating an example of a screen indicating the stability determination result. This screen is displayed when stability is selected in tab X. The contents of the screen are those in which the average value of the EES data is displayed in each cell in FIG. 5 and replaced with the standard deviation. Again, when a cell is selected, a trend chart and a histogram may be displayed.

  Next, the transient characteristics will be described. The average value of the rise time (and / or fall time, hereinafter the same) of the EES data when the target substrate processing apparatus processes each substrate in the EEQA operation is used for the determination of the transient characteristics. That is, the EEQA control unit 50 issues an abnormal alarm when the average value of the rise time of the EES data exceeds a predetermined reference value. The reference value can be determined based on the reference data acquired in step S1, for example, based on the rise time of the EES data acquired by the golden tool 100a.

  FIG. 8 is a diagram illustrating an example of a screen showing the determination result of the transient characteristic. This screen is displayed when the transient characteristic is selected on tab X. The contents of the screen are such that the average value of the EES data in each cell in FIG. 5 is replaced with the average value of the rise time. Again, when a cell is selected, a trend chart and a histogram may be displayed. Further, when one point in the trend chart is selected (for example, double-clicked), a screen shown in FIG. 9 may be displayed. FIG. 9 shows a time change of the EES data in one substrate.

  Next, the change with time will be described. The maximum value (or minimum value, hereinafter the same) of the EES data when the target substrate processing apparatus processes each substrate in the EEQA operation is used to determine the change with time. That is, the EEQA control unit 50 issues an abnormal alarm when the maximum value of the EES data exceeds a predetermined reference value. The reference value can be determined based on the reference data acquired in step S1, for example, based on the maximum value of the EES data acquired by the golden tool 100a.

  FIG. 10 is a diagram showing an example of a screen showing the determination result of the change with time. This screen is displayed when the change with time is selected on the tab X. The contents of the screen are such that the average value of the EES data is displayed in each cell in FIG. 5 and replaced with the maximum value of the EES data. Again, when a cell is selected, a trend chart and a histogram may be displayed.

  Above, an abnormal alarm is issued when there is an abnormality in the reproducibility, stability, transient characteristics, and change with time as compared with the reference value. Further, in addition to the abnormal alarm, the EEQA control unit 50 may issue a prediction alarm.

  That is, the EEQA control unit 50 determines, for the EES data having the highest correlation every time an abnormal alarm occurs, a: abnormal alarm name, b: EES data name, c: EES data value when the abnormal alarm occurs, d: normal ( The EES data value at the time when the abnormal alarm does not occur) is stored in an internal database in association with the EES data value. When the EES data value (c ′) obtained during the EEQA process is greatly deviated from the normal EES data value (d), for example, when the ratio c ′ / d is not within a predetermined range. Then, the EEQA control unit 50 issues a prediction alarm. The predetermined range can be set arbitrarily.

  The determination as to whether or not the above-described abnormality alarm or the predictive alarm is issued is performed as the abnormality determination by the EEQA control unit 50 (Step S3 in FIG. 3).

  As described above, in the first embodiment, the abnormality determination is performed while performing the EEQA operation. Therefore, it is not necessary to take the EES data out of the target substrate processing apparatus 100b, and a complete system can be constructed in the target substrate processing apparatus 100b, and the abnormality determination can be completed at the end of the EEQA operation. Further, the operator does not need to make a determination, and the EEQA control unit 50 in the target substrate processing apparatus 100b can automatically perform the abnormality determination. Therefore, EEQA can be realized efficiently.

  The EEQA operation described above is performed separately from the main operation. The EEQA operation is performed by selecting a specific job, but during the main operation, the same EES data as in the EEQA operation may be acquired for each recipe and used for quality assurance such as failure prediction.

(Second embodiment)
In the first embodiment described above, the abnormality is determined while performing the EEQA operation. On the other hand, the second embodiment described below performs automatic adjustment while performing the EEQA operation.

  FIG. 11 is a flowchart illustrating a procedure of EEQA according to the second embodiment. The difference from FIG. 3 is that the EEQA control unit 50 controls the substrate processing unit 10, specifically, adjusts the device parameters and the substrate processing recipe instead of / in addition to the abnormality determination (step S <b> 3 ′). In this adjustment, the EEQA control unit 50 first determines whether adjustment is necessary based on the acquired EES data and the reference data. This determination may be made from the viewpoints of reproducibility, stability, transient characteristics, and aging as in the case of the abnormality determination in the first embodiment. If it is determined that the adjustment is necessary, the EEQA control unit 50 adjusts the parameters and the recipe so that the EES data approaches the reference data. For this adjustment, an advanced process control (APC) function may be applied.

  For example, as shown in FIG. 2, the polishing module 1 has a dresser 21 and dresses (sharpens) the turntable 31 by swinging on a turntable 31 on which a polishing pad 32 is installed. If the EES data is the torque of the dresser 21 and this change over time has worsened, the swing speed in the substrate processing recipe may be reduced. Thereby, the dressing function can be kept constant and the turntable 31 can be dressed uniformly.

  The polishing module 1 has an airbag that presses the substrate against the polishing pad 32 on the turntable 31 when polishing the substrate. If the EES data is the airbag pressure and there is a polishing module with poor reproducibility, the polishing module may not be used in substrate processing. Conversely, if there is a polishing module 1 having good airbag pressure stability, the polishing module 1 may be used. Thereby, the substrate can be processed using the polishing module 1 having good performance, and excellent polishing characteristics can be maintained.

  As described above, in the second embodiment, the substrate processing recipe and the device parameters are automatically adjusted while performing the EEQA operation. Therefore, EEQA can be efficiently realized as in the first embodiment.

  The above embodiments have been described for the purpose of enabling a person having ordinary knowledge in the technical field to which the present invention pertains to implement the present invention. Various modifications of the above embodiment can be naturally made by those skilled in the art, and the technical idea of the present invention can be applied to other embodiments. Accordingly, the invention is not limited to the embodiments described, but is to be accorded the widest scope consistent with the spirit as defined by the appended claims.

DESCRIPTION OF SYMBOLS 1 Polishing module 2 Cleaning module 3 Transport module 10 Substrate processing part 50 EEQA control part 51 Host PC
100 Substrate processing apparatus 100a Golden tool 100b Target substrate processing apparatus

Claims (2)

A polishing pad for polishing a substrate, and an airbag for pressing the substrate against the polishing pad, a substrate polishing apparatus provided with a plurality of polishing modules,
While performing the apparatus quality assurance operation by applying a predetermined recipe whose start and end are predetermined, the pressure of the airbag in the substrate polishing apparatus is obtained, and the plurality of polishing modules are obtained based on the pressure of the airbag. And a device quality assurance control unit for adjusting which of the two is used. A polishing pad for polishing a substrate, and an airbag for pressing the substrate against the polishing pad, a quality assurance method for a substrate polishing apparatus provided with a plurality of polishing modules having:
While performing the apparatus quality assurance operation by applying a predetermined recipe whose start and end are predetermined, the pressure of the airbag in the substrate polishing apparatus is obtained, and the plurality of polishing modules are obtained based on the pressure of the airbag. A quality assurance method for a substrate polishing apparatus, which adjusts which of the above is used.