Wafer stage life determination method, electronic device, and storage medium

Abstract

The present disclosure relates to a method for determining the life of a wafer table, an electronic device, and a computer-readable storage medium, and relates to the field of semiconductor production and manufacturing technology, and can be applied to scenarios for predicting the service life of a wafer table. The method includes: obtaining the usage time data of the wafer table, and the wafer surface height data of the wafers processed by the wafer table; dividing the obtained wafers into multiple wafer areas, and constructing a surface height statistical model corresponding to the wafer based on the usage time data, multiple wafer areas, and wafer surface height data; based on the surface height statistical model, determining a first correlation curve between the wafer surface height of each wafer area and the usage time of the wafer table; based on the first correlation curve, determining the service life threshold of the wafer table. The present disclosure can predict the service life of a wafer table by observing the correlation between various wafer indicators and the usage time of the wafer table.

Description

Technical Field

[0001] The present disclosure relates to the field of semiconductor production and manufacturing technology, and in particular to a method for determining the life of a wafer stage, an electronic device, and a computer-readable storage medium. Background Art

[0002] Exposure is a critical step in the photolithography process of integrated circuit manufacturing, where the pattern on the mask is projected onto the photoresist through an optical system using light to achieve pattern transfer. During the exposure process, the wafer table on which the exposure machine places the wafer is made of metal. Prolonged contact with the wafer can cause wear, leading to surface flatness issues, ultimately affecting overlay, causing defects, and resulting in yield loss. Furthermore, when the wafer is placed on the table, its edges naturally sag due to its own weight, causing the edge pins to wear more severely than other parts.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0004] The purpose of the present disclosure is to provide a method for determining the life of a wafer table, an electronic device, and a computer-readable storage medium, thereby overcoming, at least to a certain extent, the problem in related solutions that the service life of the wafer table cannot be predicted and whether to replace the wafer table can only be determined based on yield loss data.

[0005] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by practice of the present disclosure.

[0006] According to a first aspect of the present disclosure, a method for determining the life of a wafer table is provided, comprising: obtaining usage time data of a wafer table and wafer surface height data of wafers processed by the wafer table; dividing the obtained wafers into multiple wafer areas, and constructing a surface height statistical model corresponding to the wafer based on the usage time data, the multiple wafer areas and the wafer surface height data; determining a first correlation curve between the wafer surface height of each of the wafer areas and the usage time of the wafer table based on the surface height statistical model; and determining a service life threshold of the wafer table based on the first correlation curve.

[0007] In an exemplary embodiment of the present disclosure, the obtaining of the usage time data of the wafer table and the wafer surface height data of the wafer processed by the wafer table includes: obtaining the equipment usage data of the wafer table and a pre-configured data acquisition attribute column of the wafer table; obtaining the wafer table identification, wafer table replacement time, and wafer table usage time of the wafer table from the equipment usage data according to the data acquisition attribute column; generating the usage time data based on the wafer table identification, the wafer table replacement time, and the wafer table usage time; obtaining the work log of the wafer table, and determining the wafer data from the work log, wherein the wafer data includes the number of processed wafers, the wafer size, and the wafer surface height data.

[0008] In an exemplary embodiment of the present disclosure, determining wafer data from the work log includes: determining the number of wafers that have been processed by each wafer table based on the work log; obtaining the wafer size and original height data of each wafer, the original height data including the height position coordinates contained in each wafer and the surface height value corresponding to each height position coordinate; generating the wafer surface height data based on the height position coordinates and the surface height values.

[0009] In an exemplary embodiment of the present disclosure, the obtained wafers are divided into multiple wafer areas, and a surface height statistical model corresponding to the wafer is constructed based on the usage time data, the multiple wafer areas and the wafer surface height data, including: obtaining the wafer size of the wafer and a pre-configured size division interval; based on the size division interval and the wafer size, each of the wafers is divided into multiple wafer areas; based on the wafer surface height data, the surface height value of each of the wafer areas is determined; based on the surface height value, the height mean value, height mean square error, height standard deviation and specified ratio height value of each of the wafer areas are calculated as area height statistical values; based on the usage time data and the area height statistical values, the surface height statistical model is created.

[0010] In an exemplary embodiment of the present disclosure, the method further includes: constructing an edge roll-off model corresponding to the wafer based on the usage time data, the multiple wafer areas and the wafer surface height data; determining a second correlation curve between the wafer edge roll-off and the wafer table usage time based on the edge roll-off model; and determining the service life threshold of the wafer table by combining the first correlation curve and the second correlation curve; wherein the first correlation curve is a correlation curve between the wafer surface height of each of the wafer areas and the wafer table usage time, and the second correlation curve is a correlation curve between the wafer edge roll-off and the wafer table usage time.

[0011] In an exemplary embodiment of the present disclosure, the edge roll-off model corresponding to the wafer is constructed based on the usage time data, the multiple wafer areas and the wafer surface height data, including: taking the wafer that has completed area division as the area-divided wafer; determining the wafer center point, and performing area cutting processing on the area-divided wafer at preset angles based on the wafer center point to obtain multiple cut fan-shaped areas; based on the cut fan-shaped areas, determining the edge area and non-edge area corresponding to the wafer, the edge area being the wafer area that is greater than a specified distance from the wafer center point; obtaining the area surface height corresponding to each edge area from the wafer surface height data as the edge area height; and constructing the edge roll-off model based on the usage time data and the edge area height.

[0012] In an exemplary embodiment of the present disclosure, constructing the edge roll-off model based on the usage time data and the edge area height in the edge area includes: dividing the edge area into a first edge area and a second edge area, the first edge area and the second edge area having different distances from the center point of the wafer; determining a first edge area height corresponding to the first edge area based on the edge area height, and constructing a height linear plane for each of the first edge areas based on the first edge area height; determining a projection position height of the second edge area height corresponding to the second edge area in each of the height linear planes; constructing the edge roll-off model based on the usage time data, a plurality of the height linear planes, and the corresponding projection position heights; wherein, constructing the edge roll-off model based on the usage time data, the plurality of the height linear planes, and the corresponding projection position heights includes: using a height difference between each of the height linear planes and the corresponding projection position height as an edge roll-off amount; determining a wafer stage usage time corresponding to each edge roll-off amount based on the usage time data; and constructing the edge roll-off model based on the determined plurality of edge roll-off amounts and the corresponding wafer stage usage time.

[0013] In an exemplary embodiment of the present disclosure, the combination of the first correlation curve and the second correlation curve to determine the service life threshold of the wafer table includes: determining the maximum height and the minimum height of the regional height statistics based on the first correlation curve, and determining the wafer height range according to the maximum height and the minimum height; determining the maximum roll-off amount and the minimum roll-off amount of the wafer edge roll-off amount based on the second correlation curve, and determining the roll-off amount range according to the maximum roll-off amount and the minimum roll-off amount; determining a first service life threshold according to the wafer height range, and determining a second service life threshold according to the roll-off amount range; and using the smaller value of the first service life threshold and the second service life threshold as the service life threshold of the wafer table.

[0014] According to a second aspect of the present disclosure, a wafer table life determination device is provided, comprising: a data acquisition module configured to acquire usage time data of the wafer table and wafer surface height data of the wafer processed by the wafer table; a height model construction module configured to divide the obtained wafers into multiple wafer areas, and construct a surface height statistical model corresponding to the wafer according to the usage time data, the multiple wafer areas and the wafer surface height data; a first curve determination module configured to determine a first correlation curve between the wafer surface height of each of the wafer areas and the usage time of the wafer table based on the surface height statistical model; and a service life determination module configured to determine a service life threshold of the wafer table based on the first correlation curve.

[0015] In an exemplary embodiment of the present disclosure, the data acquisition module includes a data acquisition unit, which is configured to perform the following operations: acquiring equipment usage data of the wafer table, and a pre-configured data acquisition attribute column of the wafer table; acquiring the wafer table identification, wafer table replacement time, and wafer table usage time of the wafer table from the equipment usage data according to the data acquisition attribute column; generating the usage time data based on the wafer table identification, the wafer table replacement time, and the wafer table usage time; acquiring a work log of the wafer table, and determining wafer data from the work log, wherein the wafer data includes the number of processed wafers, the wafer size, and the wafer surface height data.

[0016] In an exemplary embodiment of the present disclosure, the data acquisition unit also includes a height value acquisition sub-unit, which is configured to perform: determining the number of wafers that have been processed by each wafer table based on the work log; obtaining the wafer size and original height data of each wafer, the original height data including the height position coordinates contained in each wafer and the surface height value corresponding to each height position coordinate; generating the wafer surface height data based on the height position coordinates and the surface height values.

[0017] In an exemplary embodiment of the present disclosure, the height model building module includes a height model building unit, which is configured to perform: obtaining the wafer size of the wafer, and a pre-configured size division interval; dividing each of the wafers into multiple wafer areas based on the size division interval and the wafer size; determining the surface height value of each of the wafer areas based on the wafer surface height data; calculating the height average, height mean square error, height standard deviation and specified proportion height value of each of the wafer areas according to the surface height values ​​as area height statistical values; and creating the surface height statistical model according to the usage time data and the area height statistical values.

[0018] In an exemplary embodiment of the present disclosure, the service life determination module includes a service life determination unit, which is configured to perform: constructing an edge roll-off model corresponding to the wafer based on the usage time data, the multiple wafer areas and the wafer surface height data; determining a second correlation curve between the wafer edge roll-off amount and the wafer table usage time based on the edge roll-off amount model; combining the first correlation curve and the second correlation curve to determine the service life threshold of the wafer table; wherein the first correlation curve is a correlation curve between the wafer surface height of each of the wafer areas and the wafer table usage time, and the second correlation curve is a correlation curve between the wafer edge roll-off amount and the wafer table usage time.

[0019] In an exemplary embodiment of the present disclosure, the service life determination unit includes a roll-off model determination unit, which is configured to execute: treating a wafer that has completed area division as a area-divided wafer; determining the center point of the wafer, and performing area cutting processing on the area-divided wafer at preset angles based on the center point of the wafer to obtain multiple cut fan-shaped areas; based on the cut fan-shaped areas, determining the edge area and non-edge area corresponding to the wafer, the edge area being the wafer area that is greater than a specified distance from the center point of the wafer; obtaining the area surface height corresponding to each edge area from the wafer surface height data as the edge area height; and constructing the edge roll-off model based on the usage time data and the edge area height.

[0020] In an exemplary embodiment of the present disclosure, the roll-off amount model determination unit includes a roll-off amount model determination subunit, which is configured to perform: dividing the edge area into a first edge area and a second edge area, the first edge area and the second edge area having different sizes from the center point of the wafer; determining the first edge area height corresponding to the first edge area based on the edge area height, and constructing a height linear plane for each first edge area according to the first edge area height; determining the projection position height of the second edge area height corresponding to the second edge area in each height linear plane; constructing the edge roll-off amount model according to the usage time data, multiple height linear planes and the corresponding projection position heights; wherein the height difference between each height linear plane and the corresponding projection position height is used as the edge roll-off amount; determining the wafer stage usage time corresponding to each edge roll-off amount based on the usage time data; and constructing the edge roll-off amount model according to the determined multiple edge roll-off amounts and the corresponding wafer stage usage time.

[0021] In an exemplary embodiment of the present disclosure, the service life determination unit includes a service life determination sub-unit, which is configured to perform: determining the maximum height and the minimum height of the regional height statistics based on the first correlation curve, and determining the wafer height interval according to the maximum height and the minimum height; determining the maximum roll-off amount and the minimum roll-off amount of the wafer edge roll-off amount based on the second correlation curve, and determining the roll-off amount interval according to the maximum roll-off amount and the minimum roll-off amount; determining a first service life threshold according to the wafer height interval, and determining a second service life threshold according to the roll-off amount interval; and using the smaller value of the first service life threshold and the second service life threshold as the service life threshold of the wafer table.

[0022] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for determining the wafer table life according to any one of the above items is implemented.

[0023] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for determining the wafer table life according to any one of the above items is implemented.

[0024] The technical solution provided by the present disclosure may have the following beneficial effects:

[0025] The wafer table lifespan determination method in the exemplary embodiment of this disclosure, on the one hand, constructs a surface height statistical model based on the surface heights of different wafer regions. This model can determine the correlation between surface height and wafer table usage time. Furthermore, based on this correlation between the surface heights of different wafer regions and wafer table usage time, the wafer table's service life can be predicted.

[0026] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0028] Figure 1 A flowchart of a method for determining wafer stage life in an exemplary embodiment of the present disclosure is schematically shown.

[0029] Figure 2 The diagram schematically shows a variation trend of the surface height of the middle area of ​​the wafer in an exemplary embodiment of the present disclosure.

[0030] Figure 3 The diagram schematically shows a variation trend of the edge roll-off amount of a wafer in an exemplary embodiment of the present disclosure.

[0031] Figure 4 A schematic diagram of determining a wafer table service life threshold based on two dimensions, namely, the edge roll-off amount and the surface height value of the wafer, in an exemplary embodiment of the present disclosure is schematically shown.

[0032] Figure 5 A block diagram of a wafer stage life determination apparatus according to an exemplary embodiment of the present disclosure is schematically shown.

[0033] Figure 6 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is schematically shown.

[0034] Figure 7 A schematic diagram schematically illustrates a computer-readable storage medium according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the drawings represent like or similar parts, and thus repetitive description thereof will be omitted.

[0036] In addition, the described features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, well-known structures, methods, devices, implementations, materials or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0037] The blocks shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. Specifically, these functional entities may be implemented in software, or in one or more software-hardened modules, or in different networks and / or processor devices and / or microcontroller devices.

[0038] During the exposure process, the wafer table on which the exposure machine places the wafer has metal pins supporting the wafer. Long-term contact with the wafer can cause wear, leading to abnormal wafer surface flatness, ultimately affecting semiconductor pattern overlay errors, defects, and yield loss. Due to its own weight, the edges of the wafer placed on the wafer table naturally sag, causing the edge pins to wear more severely than other parts. The disclosed embodiments predict the lifespan of the wafer table by developing a wafer edge roll-off indicator and statistical indicators of wafer surface flatness for each wafer segment, and observing the correlation between these indicators and the wafer table's usage time.

[0039] Based on this, in this example embodiment, a method for determining the life of a wafer table is first provided. The method for determining the life of a wafer table disclosed in the present invention can be implemented using a server, or the method described in the present invention can be implemented using a terminal device. The terminals described in the present invention may include mobile terminals such as mobile phones, tablet computers, laptop computers, PDAs, and personal digital assistants (PDAs), as well as fixed terminals such as desktop computers. Figure 1The following schematically illustrates a process flow of a method for determining the life of a wafer stage according to some embodiments of the present disclosure. Figure 1 The wafer stage life determination method may include the following steps:

[0040] In step S110 , the usage time data of the wafer stage and the wafer surface height data of the wafers processed by the wafer stage are obtained.

[0041] According to some exemplary embodiments of the present disclosure, a wafer stage, also known as a wafer tray, may be a device used to support wafers in an exposure machine. Usage time data may include all data related to the usage time of the wafer stage during the exposure process. Wafer surface height data may include specific data on the surface height of wafers processed by the exposure machine.

[0042] Since the wafer table is in contact with the wafer for a long time, wear may occur, resulting in abnormal flatness of the wafer surface height. In order to determine whether the wafer table needs to be replaced, the trend of changes in the wafer surface height can be analyzed, and then based on the statistical results, it can be determined whether the wafer table needs to be replaced. Therefore, the usage time data of the wafer table can be obtained. The usage time data of the wafer table may include data such as the wafer table identification, replacement time point, and working time after replacement. In addition, the wafer surface height data of the wafer processed by the wafer table can also be obtained. The wafer surface height data may include surface height values ​​corresponding to different position coordinates in the wafer.

[0043] In step S120 , the obtained wafers are divided into a plurality of wafer regions, and a surface height statistical model corresponding to the wafer is constructed based on the usage time data, the plurality of wafer regions and the wafer surface height data.

[0044] According to some exemplary embodiments of the present disclosure, the wafer area may be obtained by dividing the wafer into regions. The surface height statistical model may be a statistical model for representing the correlation between the surface height of the wafer and the usage time of the wafer stage.

[0045] After obtaining the wafer surface height data, in order to perform statistical analysis on the surface height values ​​of different areas of the wafer, the wafer processed by the wafer stage can be divided into regions to obtain multiple wafer regions. For each of the multiple wafer regions obtained, the surface height values ​​in each wafer region can be statistically analyzed based on the wafer surface height data. Then, combined with the usage time data, the changing trend of the surface height statistics of the multiple wafer regions over the wafer stage usage time can be analyzed to construct a surface height statistical model corresponding to the wafer.

[0046] Step S130 : determining a first correlation curve between the wafer surface height of each wafer region and the wafer stage usage time based on the surface height statistical model.

[0047] According to some exemplary embodiments of the present disclosure, the wafer surface height may be all surface height values ​​on the wafer. The first correlation curve may be a trend change curve obtained by numerical fitting based on the wafer surface height and the usage time of the wafer stage.

[0048] After constructing a statistical model of the wafer's surface height, the correlation between the wafer surface height of each wafer area and the wafer table's usage time can be determined based on the surface height statistical model. The numerical changes between the two can be curve-fitted to obtain a first correlation curve. The first correlation curve can reflect the trend of the wafer surface height change based on the wafer table's usage time. For example, when the wafer table is initially working, the change trend of the wafer surface height is relatively stable; as the wafer table's working time increases, the wafer table's ejector pins wear out, which may cause abnormal changes in the wafer's surface height value. The above changes can all be reflected in the first correlation curve.

[0049] Step S140 : determining a service life threshold of the wafer stage based on the first correlation curve.

[0050] According to some exemplary embodiments of the present disclosure, the service life threshold may be a maximum value of the service life of the wafer table, and is used to determine whether the wafer table should be replaced currently.

[0051] Based on the fitted first correlation curve, we can analyze the wafer table usage time corresponding to abnormal changes in wafer surface height. This indicates that a new wafer table needs to be replaced to ensure wafer yield. Therefore, when abnormal changes in wafer surface height occur, the wafer table usage time at that time is used as the wafer table lifespan threshold, allowing for timely replacement of the wafer table.

[0052] According to the wafer table lifespan determination method of this exemplary embodiment, a surface height statistical model is constructed based on the surface heights of different wafer regions. This model can be used to determine the correlation between surface height and wafer table usage. Furthermore, based on this correlation between the surface heights of different wafer regions and wafer table usage, the wafer table's service life can be predicted.

[0053] Next, the wafer stage life determination method in this example embodiment will be further described.

[0054] In an exemplary embodiment of the present disclosure, for step S110, the usage time data of the wafer table and the wafer surface height data of the wafer processed by the wafer table are obtained, including: obtaining the equipment usage data of the wafer table and a pre-configured data acquisition attribute column; according to the data acquisition attribute column, obtaining the wafer table identification, wafer table replacement time, and wafer table usage time of the wafer table from the equipment usage data; generating usage time data based on the wafer table identification, wafer table replacement time, and wafer table usage time; obtaining the work log of the wafer table, and determining the wafer data from the work log, the wafer data including the number of processed wafers, wafer size, and wafer surface height data.

[0055] The equipment usage data may be usage data of all components of the wafer table during the exposure process. The data acquisition attribute column may be an attribute column used to obtain specified data from the equipment usage data. The wafer table identifier may be a unique identifier corresponding to each wafer table. The wafer table replacement time may be the time point corresponding to the replacement of the wafer table (Table) by the process tool. The wafer table usage duration may be the duration that the wafer table carries wafers for wafer processing. The work log may be a log file recorded when the wafer table processes wafers during the exposure process. Wafer data may be data generated by the wafer table during wafer processing. The number of wafers may be the number of wafers processed by the wafer table. The wafer size may be a specific dimension value of the wafer, for example, the wafer size may include the wafer radius.

[0056] During the semiconductor exposure process, the wafer stage generates corresponding equipment usage data during wafer processing. This equipment usage data includes usage data for all components of the wafer stage. To obtain the data used by the wafer stage during wafer height analysis, a data acquisition attribute column can be pre-configured to obtain usage time data. For example, the attribute column names of the data acquisition attribute column may include exposure machine ID, wafer stage ID, wafer stage replacement time, wafer stage usage data creation time, and wafer stage usage data update time. Based on the pre-configured data acquisition attribute column, usage time data is obtained from the equipment usage data.

[0057] Additionally, the wafer stage will record a corresponding work log during wafer processing. Once generated, the work log will be uploaded and stored in the exposure machine. The work log being uploaded can be distinguished from the work log that has already been uploaded by the file name. When obtaining the work log, the log report file (lot report) from the exposure machine is downloaded and parsed via the File Transfer Protocol (FTP). This is used as the wafer stage work log. Based on the work log, the total number of wafers exposed by each wafer stage per day can be counted. Wafer data is then determined from the work log. This wafer data includes the number of wafers processed by the wafer stage, wafer dimensions, and wafer surface height data. The acquired equipment usage data and wafer surface height data can be used as a data source for analyzing wafer surface height values ​​and wafer stage usage time.

[0058] To obtain equipment usage data, you can configure the data acquisition attribute column through the settings interface. For example, an engineer can configure the exposure machine to provide the time, table information, and corresponding machine information for each wafer table change. This generates a data acquisition attribute column, which is used to determine the replacement time and usage duration of each table. Based on the configured data acquisition attribute column, wafer table usage data can be obtained from the equipment usage data, providing a data foundation for analyzing wafer table usage duration.

[0059] In an exemplary embodiment of the present disclosure, wafer data is determined from a work log, including: determining the number of wafers that have been processed on each wafer table based on the work log; obtaining the wafer size and original height data of each wafer, the original height data including the height position coordinates contained in each wafer and the surface height value corresponding to each height position coordinate; generating wafer surface height data based on the height position coordinates and the surface height values.

[0060] The raw height data may be raw data of the wafer surface height obtained from the wafer stage. The height position coordinates may be position coordinates corresponding to different surface heights on the wafer. The surface height values ​​may be all surface height values ​​on the wafer.

[0061] After downloading and parsing the wafer stage work log, you can retrieve raw data about wafer flatness from the work log. For example, you can determine the number of wafers processed by each wafer stage based on the work log. In addition, you can retrieve raw wafer data from the work log, including, for example, the wafer dimensions and raw height data for each wafer. Wafer dimensions can include data such as the radius of the wafer processed by each wafer stage. Raw height data can include the height position coordinates contained in each wafer and the surface height value corresponding to each height position coordinate.

[0062] For example, wafer raw data can be stored as follows: ;in, It can be a certain exposure area of ​​the wafer during the manufacturing process; They are the horizontal and vertical coordinates of a point in the wafer, which are used to determine the position coordinates of a point in the wafer; Can be wafer The surface height value corresponding to the point. Based on the height position coordinates and surface height values ​​of all points in the wafer, the wafer surface height data can be generated so that the change trend of the wafer surface height can be analyzed based on the wafer surface height data.

[0063] In an exemplary embodiment of the present disclosure, for step S120, the obtained wafers are divided into multiple wafer areas, and a surface height statistical model corresponding to the wafer is constructed based on the usage time data, multiple wafer areas and wafer surface height data, including: obtaining the wafer size of the wafer, and a pre-configured size division interval; based on the size division interval and the wafer size, each wafer is divided into multiple wafer areas; based on the wafer surface height data, the surface height value of each wafer area is determined; based on the surface height value, the height mean, height mean square error, height standard deviation and specified ratio height value of each wafer area are calculated as the area height statistical value; based on the usage time data and the area height statistical value, a surface height statistical model is created.

[0064] The size division interval may be the interval size used to divide the wafer into regions. The height average may be the corresponding average value of the wafer height in each wafer region. The height mean square deviation may be the mean square deviation of the wafer surface height. The height standard deviation may be the standard deviation of the wafer surface height. The specified ratio height value may be the surface height of a specified location on the wafer. The regional height statistics may be a related statistical value determined based on the wafer surface height value.

[0065] Since the wafer size of the wafer can be determined from the work log of the wafer table. In order to perform statistical analysis on the surface height value of the wafer, the wafer can be divided into regions according to the pre-configured size division interval. For example, the wafer radius can be 150mm, and the size division interval of the wafer can be determined as the initial size division interval of 30mm and the subsequent size division interval of 20mm. Through the above size division intervals, the wafer is divided into 8 sections according to the radius, namely 0~30mm, 30mm~50mm, 50mm~70mm, 70mm~90mm, 90mm~110mm, 110mm~130mm, 130mm~150mm and full map, that is, 8 different wafer areas.

[0066] Once the wafer surface height data is obtained, the surface height values ​​corresponding to each wafer region can be determined. Based on the surface height values ​​of all points on the wafer, the height mean (Mean), height root mean square (RMS), height standard deviation (STD), and specified ratio height values ​​(such as the height value at the 99.7% ratio of the surface height values) of each wafer region (z-axis) in the set 𝐻 can be calculated. The height values ​​obtained by the above calculations are used as regional height statistics.

[0067] After obtaining regional height statistics, the Wafer Table can be monitored by observing long-term changes in height statistics. A surface height statistical model can be created based on usage data and regional height statistics. A correlation is established between the wafer table's usage time and height statistics such as the wafer surface mean, RMS, STD, and 99.7% indicator. For example, by combining the actual usage time of the Wafer Table with the number of wafers exposed, the time-varying changes in various indicators in the center area (excluding 130mm-150mm) of the wafer and those at the edge (130mm-150mm) are observed to determine whether there are significant differences. This surface height statistical model can then be constructed to predict whether the Wafer Table is damaged and needs replacement to avoid wafer yield loss.

[0068] After obtaining the surface height statistical model, a first correlation curve can be determined based on the surface height statistical model. Figure 2 , Figure 2 A schematic diagram illustrates the changing trend of the surface height of the central region of a wafer in an exemplary embodiment of the present disclosure. The height statistics of different sections of the wafer change over the wafer stage's lifetime. Because the portion of the wafer near the center point may also experience wear, surface height values ​​are segmented for management and monitoring. Figure 2 The left figure shows the curve of the STD of the surface height of the wafer edge area changing with the working time of the wafer stage. Figure 2 The left figure shows the STD curves of the surface height of the wafer edge area corresponding to three different wafer stages (wafer stage 1, wafer stage 2, and wafer stage 3) as the wafer stage operates for a certain period of time. Figure 2 The right figure shows the curve of the STD of the surface height of the center area of ​​the wafer as the working time of the wafer stage changes. Figure 2 The right figure contains the curves of the STD of the surface height of the center area of ​​the wafer corresponding to three different wafer stages (wafer stage 1, wafer stage 2 and wafer stage 3) as the wafer stage works. Figure 2From the correlation curve in Figure 2, we can observe the wear of the table in different areas of the wafer (edge ​​area and central area) as the wafer table usage time (or number of exposures) increases.

[0069] In an exemplary embodiment of the present disclosure, the method for determining the life of a wafer table in an embodiment of the present disclosure further includes: constructing an edge roll-off model corresponding to the wafer based on usage time data, multiple wafer regions and wafer surface height data; determining a second correlation curve between the wafer edge roll-off amount and the wafer table usage time based on the edge roll-off amount model; and determining the service life threshold of the wafer table by combining the first correlation curve and the second correlation curve; wherein the first correlation curve is a correlation curve between the wafer surface height of each wafer region and the wafer table usage time, and the second correlation curve is a correlation curve between the wafer edge roll-off amount and the wafer table usage time.

[0070] The edge roll-off model can be a statistical model of the relationship between wafer table usage and wafer roll-off, monitoring the wafer table through long-term observation of wafer edge conditions. The wafer edge roll-off can be the difference between the surface height of the edge region and the surface height of the non-edge region of each wafer. The second correlation curve can be a trend curve derived from numerical fitting of the wafer edge roll-off and wafer table usage.

[0071] By analyzing the first correlation curve, a wafer table lifespan threshold is determined. Furthermore, by analyzing the second correlation curve, another wafer table lifespan threshold is determined. Ultimately, the smaller of the two lifespan thresholds can be used as the wafer table lifespan threshold. In subsequent processes, the wafer table can be replaced based on the determined lifespan threshold to improve wafer production yield.

[0072] In an exemplary embodiment of the present disclosure, an edge roll-off model corresponding to the wafer is constructed based on usage time data, multiple wafer areas and wafer surface height data, including: using a wafer that has completed area division as a area-divided wafer; determining the center point of the wafer, and performing area cutting processing on the area-divided wafer at preset angles based on the wafer center point to obtain multiple cut fan-shaped areas; based on the cut fan-shaped areas, determining the edge area and non-edge area corresponding to the wafer, the edge area being the wafer area that is greater than a specified distance from the wafer center point; obtaining the area surface height corresponding to each edge area from the wafer surface height data as the edge area height; and constructing an edge roll-off model based on the usage time data and the edge area height.

[0073] Among them, the area-divided wafer can be a wafer obtained by dividing the wafer into areas according to the size division interval. The center point of the wafer can be the position coordinate point of the center of the wafer. The preset angle can be the interval angle used for dividing the wafer into fan-shaped areas based on the center point of the wafer. The cutting fan-shaped area can be the area obtained by dividing the wafer into fan-shaped areas based on the center point of the wafer and the preset angle. The edge area can be a wafer area that is greater than a specified distance from the center point of the wafer (far away from the center point of the wafer). The non-edge area can be a wafer area that is less than or equal to a specified distance from the center point of the wafer (close to the center point of the wafer). Both the edge area and the non-edge area can be areas obtained after the fan-shaped division process. The edge area height can be the surface height value corresponding to the edge area of ​​the wafer.

[0074] For the processed wafer, the wafer that has been divided into regions according to the size division interval in the above steps will be used as the region-divided wafer. After obtaining the region-divided wafer, the region-divided wafer can be region-cut at preset angles based on the center point of the wafer. The preset angle can be configured as 1°, 2°, ..., 5°, and so on. For example, when the preset angle is 1°, a straight line is drawn from the center point of the wafer to the edge of the wafer, and a straight line is drawn every 1°. The area between the two straight lines is a cutting sector area, which is recorded as , the total number of regions after cutting is 360, .

[0075] After obtaining the cutting sector area, the edge area and non-edge area corresponding to the wafer can be determined based on the cutting sector area. When determining the edge area and non-edge area, it can be based on the size of the wafer. For example, when the radius of the wafer is 150mm, the area less than or equal to 130mm from the center of the wafer can be regarded as the non-edge area, and the area at the edge of the wafer (130mm~150mm from the center of the wafer) can be regarded as the edge area. .

[0076] After determining the edge regions through the above steps, the surface height corresponding to each edge region can be obtained from the wafer surface height data as the edge region height. An edge roll-off model is then constructed based on the usage time data and edge region height. This edge roll-off model can be used to predict the wafer stage's service life by analyzing the correlation between the wafer edge roll-off indicator, actual usage time, and number of exposures.

[0077] In an exemplary embodiment of the present disclosure, an edge roll-off model is constructed based on usage time data and the edge area height in the edge area, including: dividing the edge area into a first edge area and a second edge area, the first edge area and the second edge area having different sizes from the center point of the wafer; determining the first edge area height corresponding to the first edge area based on the edge area height, and constructing a height linear plane for each first edge area according to the first edge area height; determining the projection position height of the second edge area height corresponding to the second edge area in each height linear plane; and constructing an edge roll-off model based on usage time data, multiple height linear planes and their corresponding projection position heights.

[0078] The first edge region and the second edge region may be different edge regions, and the distance between the first edge region and the second edge region and the wafer center point may be different. The height of the first edge region may be the height value of the wafer surface in the first edge region of the wafer. The height of the second edge region may be the height value of the wafer surface in the second edge region of the wafer. The height linear plane may be a linear plane obtained by fitting the surface height values ​​in the first edge region. The projection position height may be the height of the projection position of the position point in the second edge region on the height linear plane.

[0079] After determining the edge region, in order to obtain the wafer edge roll-off index, the edge region can be further subdivided into a first edge region and a second edge region. The first and second edge regions have different distances from the wafer center point. For example, if the wafer radius is 150mm, the region containing all points greater than 130mm and less than 140mm from the center point can be used as the first edge region. Alternatively, the region containing all points greater than 140mm and less than 150mm from the center point can be used as the second edge region.

[0080] For the first edge region, the surface heights of all points in the first edge region (130 mm to 140 mm) can be obtained as the height of the first edge region, and a linear plane can be fitted based on the height set of the first edge region height as the height linear plane. The height linear plane can be recorded as ; Further, all points in the second edge area (140mm~150mm) can be calculated on the linear plane The height of the projection position on the .

[0081] After obtaining the height linear plane and the projection position height, an edge roll-off model can be constructed based on the usage time data, multiple height linear planes and their corresponding projection position heights. The edge roll-off model can reflect the changing trend of the edge roll-off index of the wafer as the wafer table is used for a certain period of time, thereby determining the service life threshold of the wafer table based on the changing trend of the edge roll-off index.

[0082] In an exemplary embodiment of the present disclosure, an edge roll-off amount model is constructed based on usage time data, multiple height linear planes and their corresponding projection position heights, including: taking the height difference between each height linear plane and the corresponding projection position height as the edge roll-off amount; determining the wafer stage usage time corresponding to each edge roll-off amount based on the usage time data; and constructing an edge roll-off amount model based on the determined multiple edge roll-off amounts and their corresponding wafer stage usage time.

[0083] The edge roll-off amount may be an evaluation indicator reflecting whether a roll-off phenomenon occurs at the edge of the wafer.

[0084] After obtaining the height linear plane corresponding to the first edge region , and the projection position height of all points in the second edge area corresponding to the first edge area in the height linear plane After that, the height difference between the two can be used as the edge roll-off of the wafer, that is, , theoretically, if there is no roll-off at the edge of the wafer, then and The heights should be exactly the same. Should be equal to 0; otherwise, if the wafer rolls off, Greater than 0. So we can use Characterize whether a single measurement point has a roll-off phenomenon, and the collection It can represent the edge roll phenomenon of the entire wafer.

[0085] After determining the wafer edge roll-off, the wafer table usage duration corresponding to each wafer edge roll-off value can be derived from the usage data. Furthermore, an edge roll-off model is constructed based on the multiple edge roll-off values ​​determined and their corresponding wafer table usage durations. For the constructed edge roll-off model, a spline curve can be used to extract key information from the set. By observing the spline curve's trend over time, the need for wafer table replacement can be predicted.

[0086] Since the edge of the wafer is more susceptible to wear, edge roll-off is used as a monitoring indicator. If the roll-off of the edge (130mm~150mm) of the wafer decreases with the increase of usage time (or number of exposures), it means that the table is worn, that is, the support force of the edge pin on the wafer is reduced. Figure 3 , Figure 3 The diagram schematically shows a variation trend of the edge roll-off amount of a wafer in an exemplary embodiment of the present disclosure. Figure 3 The figure contains the average height of the wafer edge roll-off corresponding to the two wafer stages (wafer stage 1 and wafer stage 2) as the wafer stage works for a certain period of time. Each curve represents the change in the wafer edge roll-off on different dates. Figure 3 It can be seen from the figure that when the average height of the edge roll-off corresponding to the wafer stage shows a downward trend, it means that the wafer stage may be worn. Therefore, the wafer stage can be replaced, and the trend of the change of the wafer edge roll-off after the wafer stage is replaced can be counted. Figure 3 It can be seen that after the wafer stage is replaced, the downward trend of the wafer edge roll-off disappears, and the edge roll-off changes back to a relatively gentle trend.

[0087] In an exemplary embodiment of the present disclosure, a first correlation curve and a second correlation curve are combined to determine a service life threshold of a wafer table, including: determining a maximum height and a minimum height of the regional height statistics based on the first correlation curve, and determining a wafer height range according to the maximum height and the minimum height; determining a maximum roll-off amount and a minimum roll-off amount of the wafer edge roll-off amount based on the second correlation curve, and determining a roll-off amount range according to the maximum roll-off amount and the minimum roll-off amount; determining a first service life threshold according to the wafer height range, and determining a second service life threshold according to the roll-off amount range; and using the smaller value of the first service life threshold and the second service life threshold as the service life threshold of the wafer table.

[0088] Among them, the maximum roll-off amount may be the maximum value obtained by the edge roll-off amount of the wafer. The minimum roll-off amount may be the minimum value obtained by the edge roll-off amount of the wafer. The roll-off amount interval may be a numerical interval determined based on the minimum roll-off amount and the maximum roll-off amount, and the roll-off amount interval includes all values ​​of the wafer edge roll-off amount. The maximum height value may be the maximum value obtained by the surface height value of the wafer. The minimum height value may be the minimum value obtained by the surface height value of the wafer. The wafer height interval may be a numerical interval determined based on the minimum height value and the maximum height value, and the roll-off amount interval includes all values ​​of the wafer edge roll-off amount. The first service life threshold may be a service life threshold of the wafer table determined based on the first correlation curve. The second service life threshold may be a service life threshold of the wafer table determined based on the second correlation curve.

[0089] After determining a first correlation curve based on the surface height statistical model, the maximum and minimum roll-off values ​​of the wafer edge roll-off can be determined based on the first correlation curve, and the corresponding roll-off range of the wafer can be determined based on the obtained maximum and minimum roll-off values. Similarly, after determining a second correlation curve based on the edge roll-off model, the maximum and minimum height values ​​of the regional height statistics can be determined based on the second correlation curve, and the wafer height range can be determined based on the maximum and minimum height values.

[0090] The roll-off interval defines the normal range of wafer edge roll-off values. If the wafer edge roll-off exceeds the specified range, the wafer edge roll-off indicator is considered abnormal. Therefore, the second service life threshold corresponding to the wafer stage can be determined based on the roll-off interval. Similarly, the wafer height interval defines the normal range of wafer surface height values. If the wafer surface height value exceeds the specified range, the wafer surface height indicator is considered abnormal. Therefore, the first service life threshold corresponding to the wafer stage can be determined based on the wafer height interval.

[0091] refer to Figure 4 , Figure 4 A schematic diagram of determining a wafer table service life threshold based on two dimensions, namely, the edge roll-off amount and the surface height value of the wafer, in an exemplary embodiment of the present disclosure is schematically shown. Figure 4 The left figure provides a trend curve of the edge standard deviation values ​​corresponding to wafer stage 1 and wafer stage 2 as the wafer stage operates. Based on these curves, the edge roll-off value changes before and after wafer stage wear can be observed over a long period of time to determine the edge roll-off range. Figure 4The right figure shows a trend curve of the surface flatness of wafers processed on wafer stage 1 and wafer stage 2, respectively, over time. By observing the changes in surface height values ​​before and after wafer stage wear, the corresponding wafer height range can be determined. By configuring roll-off ranges and wafer height ranges, the accuracy of the wafer stage lifespan can be improved, primarily for processes where wafer edge roll-off or mid-range height values ​​are significantly affected by wafer stage wear.

[0092] After determining the wafer table's service life threshold based on the two evaluation indicators, to ensure the product yield of wafers produced and processed by the wafer table, the smaller value of the first service life threshold and the second service life threshold can be used as the wafer table's service life threshold. Defining the wafer table's service life threshold can automatically trigger an email (or other prompt method) to remind the relevant engineer to replace the wafer table. By analyzing the long-term changing trends of the random table usage time (or number of exposures) of various statistical indicators, the actual wafer table service life threshold can be predicted. If the wafer table's operating time exceeds the defined service life threshold, a notification can be sent to the relevant engineer to replace the wafer table in a timely manner to ensure the product yield of the wafer.

[0093] It should be noted that the terms “first”, “second”, etc. used in the present disclosure are only used to distinguish the correlation curves between different data and should not impose any limitations on the present disclosure.

[0094] In summary, the usage time data of the wafer table and the wafer surface height data of the wafers processed by the wafer table are obtained; the obtained wafers are divided into multiple wafer areas, and a surface height statistical model corresponding to the wafer is constructed based on the usage time data, multiple wafer areas and wafer surface height data; based on the surface height statistical model, a first correlation curve between the wafer surface height of each wafer area and the usage time of the wafer table is determined; based on the first correlation curve, the service life threshold of the wafer table is determined. On the one hand, a surface height statistical model is constructed based on the surface heights of different wafer areas, and the correlation between the surface height and the usage time of the wafer table can be determined through the model. On the other hand, based on the correlation between the surface heights of different wafer areas and the usage time of the wafer table, the purpose of predicting the service life of the wafer table can be achieved.

[0095] It should be noted that although the steps of the method of the present invention are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in this specific order, or that all steps must be performed to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0096] In addition, in this exemplary embodiment, a wafer stage life determination device is also provided. Figure 5 The wafer stage life determination device 500 may include: a data acquisition module 510 , a height model construction module 520 , a first curve determination module 530 and a service life determination module 540 .

[0097] Specifically, the data acquisition module 510 is configured to execute the acquisition of the usage time data of the wafer table and the wafer surface height data of the wafer processed by the wafer table; the height model construction module 520 is configured to execute the division of the obtained wafers into multiple wafer areas, and construct a surface height statistical model corresponding to the wafer based on the usage time data, multiple wafer areas and wafer surface height data; the first curve determination module 530 is configured to execute a first correlation curve between the wafer surface height of each wafer area and the usage time of the wafer table based on the surface height statistical model; the service life determination module 540 is configured to execute the determination of the service life threshold of the wafer table based on the first correlation curve.

[0098] In an exemplary embodiment of the present disclosure, the data acquisition module 510 includes a data acquisition unit, which is configured to perform the following operations: acquiring equipment usage data of the wafer table, and a pre-configured data acquisition attribute column of the wafer table; acquiring the wafer table identification, wafer table replacement time, and wafer table usage time of the wafer table from the equipment usage data according to the data acquisition attribute column; generating usage time data based on the wafer table identification, wafer table replacement time, and wafer table usage time; acquiring a work log of the wafer table, and determining wafer data from the work log, wherein the wafer data includes the number of processed wafers, wafer size, and wafer surface height data.

[0099] In an exemplary embodiment of the present disclosure, the data acquisition unit also includes a height value acquisition sub-unit, which is configured to perform: determining the number of wafers that have been processed on each wafer table based on the work log; obtaining the wafer size and original height data of each wafer, the original height data including the height position coordinates contained in each wafer and the surface height value corresponding to each height position coordinate; generating wafer surface height data based on the height position coordinates and the surface height values.

[0100] In an exemplary embodiment of the present disclosure, the height model construction module 520 includes a height model construction unit, which is configured to perform: obtaining the wafer size of the wafer, and a pre-configured size division interval; dividing each wafer into multiple wafer areas based on the size division interval and the wafer size; determining the surface height value of each wafer area based on the wafer surface height data; calculating the height average, height mean square error, height standard deviation and specified proportion height value of each wafer area according to the surface height value as the area height statistical value; creating a surface height statistical model based on the usage time data and the area height statistical value.

[0101] In an exemplary embodiment of the present disclosure, the service life determination module 540 includes a service life determination unit, which is configured to perform: constructing an edge roll-off model corresponding to the wafer based on usage time data, multiple wafer areas and wafer surface height data; determining a second correlation curve between the wafer edge roll-off amount and the wafer table usage time based on the edge roll-off amount model; combining the first correlation curve and the second correlation curve to determine the service life threshold of the wafer table; wherein the first correlation curve is a correlation curve between the wafer surface height of each wafer area and the wafer table usage time, and the second correlation curve is a correlation curve between the wafer edge roll-off amount and the wafer table usage time.

[0102] In an exemplary embodiment of the present disclosure, the service life determination unit includes a roll-off model determination unit, which is configured to execute: treating a wafer that has completed area division as a area-divided wafer; determining the center point of the wafer, and performing area cutting processing on the area-divided wafer at preset angles based on the center point of the wafer to obtain multiple cut fan-shaped areas; determining the edge area and non-edge area corresponding to the wafer based on the cut fan-shaped area, where the edge area is the wafer area that is greater than a specified distance from the center point of the wafer; obtaining the area surface height corresponding to each edge area from the wafer surface height data as the edge area height; and constructing an edge roll-off model based on the usage time data and the edge area height.

[0103] In an exemplary embodiment of the present disclosure, a roll-off amount model determination unit includes a roll-off amount model determination sub-unit, which is configured to execute: dividing the edge area into a first edge area and a second edge area, the first edge area and the second edge area having different sizes from the center point of the wafer; determining the first edge area height corresponding to the first edge area based on the edge area height, and constructing a height linear plane for each first edge area according to the first edge area height; determining the projection position height of the second edge area height corresponding to the second edge area in each height linear plane; constructing an edge roll-off amount model according to usage time data, multiple height linear planes and their respective corresponding projection position heights; wherein the roll-off amount model determination sub-unit is further configured to execute: taking the height difference between each height linear plane and the corresponding projection position height as the edge roll-off amount; determining the wafer stage usage time corresponding to each edge roll-off amount based on the usage time data; and constructing an edge roll-off amount model according to the determined multiple edge roll-off amounts and their respective corresponding wafer stage usage times.

[0104] In an exemplary embodiment of the present disclosure, the service life determination unit includes a service life determination sub-unit, which is configured to perform: determining the maximum height and the minimum height of the regional height statistics based on the first correlation curve, and determining the wafer height range according to the maximum height and the minimum height; determining the maximum roll-off amount and the minimum roll-off amount of the wafer edge roll-off amount based on the second correlation curve, and determining the roll-off amount range according to the maximum roll-off amount and the minimum roll-off amount; determining a first service life threshold according to the wafer height range, and determining a second service life threshold according to the roll-off amount range; and using the smaller value of the first service life threshold and the second service life threshold as the service life threshold of the wafer table.

[0105] The specific details of the virtual modules of each wafer stage life determination device mentioned above have been described in detail in the corresponding wafer stage life determination method, so they will not be repeated here.

[0106] It should be noted that while the above detailed description mentions several modules or units of the wafer table life determination apparatus, this division is not mandatory. In fact, depending on the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in a single module or unit. Conversely, the features and functions of a single module or unit described above can be further divided and embodied by multiple modules or units.

[0107] In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0108] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods, or program products. Therefore, various aspects of the present invention may be implemented as a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which may be collectively referred to herein as a "circuit," "module," or "system."

[0109] Reference below Figure 6 6 to describe the electronic device 600 according to such an embodiment of the present disclosure. Figure 6 The electronic device 600 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0110] like Figure 6 As shown, electronic device 600 is implemented as a general-purpose computing device. Components of electronic device 600 may include, but are not limited to, the aforementioned at least one processing unit 610, the aforementioned at least one storage unit 620, a bus 630 connecting various system components (including storage unit 620 and processing unit 610), and a display unit 640.

[0111] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present disclosure described in the above “Exemplary Method” section of this specification.

[0112] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 621 and / or a cache memory unit 622 , and may further include a read-only memory unit (ROM) 623 .

[0113] The storage unit 620 may include a program / utility 624 having a set (at least one) of program modules 625, such program modules 625 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0114] Bus 630 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0115] The electronic device 600 can also communicate with one or more external devices 670 (e.g., a keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 600, and / or any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., a router, modem, etc.). This communication can occur via an input / output (I / O) interface 650. Furthermore, the electronic device 600 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 660. As shown, the network adapter 660 communicates with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 600, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0116] Through the description of the above embodiments, it will be readily understood by those skilled in the art that the example embodiments described herein can be implemented via software or via a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or mobile hard drive) or on a network and includes several instructions for causing a computing device (such as a personal computer, server, terminal device, or network device) to execute the methods according to the embodiments of the present disclosure.

[0117] In exemplary embodiments of the present disclosure, a computer-readable storage medium is also provided, storing a program product capable of implementing the aforementioned methods of this specification. In some possible embodiments, various aspects of the present invention may also be implemented in the form of a program product comprising program code. When the program product is executed on a terminal device, the program code is configured to cause the terminal device to perform the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section of this specification.

[0118] refer to Figure 7 As shown, a program product 700 for implementing the above method according to an embodiment of the present invention is described. The program product 700 may be a portable compact disk read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0119] The program product may utilize any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0120] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0121] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0122] Program code for performing the operations of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0123] Furthermore, the above-described figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above-described figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0124] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow from the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the claims.

[0125] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for determining wafer stage life, characterized in that: include: Acquiring usage time data of a wafer stage and wafer surface height data of wafers processed by the wafer stage; Dividing the obtained wafers into a plurality of wafer regions, and constructing a surface height statistical model corresponding to the wafer according to the usage time data, the plurality of wafer regions and the wafer surface height data; Determining a first correlation curve between the wafer surface height of each of the wafer regions and the wafer stage usage time based on the surface height statistical model; Constructing an edge roll-off model corresponding to the wafer based on the usage time data, the multiple wafer regions, and the wafer surface height data, specifically comprising: using a wafer that has completed region division as a region-divided wafer; determining a wafer center point, and performing region cutting processing on the region-divided wafer at preset angles based on the wafer center point to obtain multiple cut sector-shaped regions; determining an edge region and a non-edge region corresponding to the wafer based on the cut sector-shaped regions, wherein the edge region is a wafer region that is greater than a specified distance from the wafer center point; obtaining a regional surface height corresponding to each edge region from the wafer surface height data as an edge region height; constructing the edge roll-off model based on the usage time data and the edge region height; Determining a second correlation curve between wafer edge roll-off and wafer stage usage time based on the edge roll-off model; The first correlation curve and the second correlation curve are combined to determine a service life threshold of the wafer table.

2. The method according to claim 1, characterized in that The obtaining of the usage time data of the wafer stage and the wafer surface height data of the wafers processed by the wafer stage includes: Acquire equipment usage data of the wafer stage and a pre-configured data acquisition attribute column of the wafer stage; According to the data acquisition attribute column, the wafer table identification, wafer table replacement time, and wafer table usage time of the wafer table are acquired from the equipment usage data; generating the usage time data based on the wafer stage identifier, the wafer stage replacement time, and the wafer stage usage time; Obtain a work log of the wafer table, and determine wafer data from the work log, wherein the wafer data includes the number of wafers that have been processed, the wafer size, and the wafer surface height data.

3. The method according to claim 2, characterized in that Determining wafer data from the work log includes: Based on the work log, determining the number of wafers processed by each wafer table; Obtaining wafer size and original height data of each wafer, wherein the original height data includes height position coordinates contained in each wafer and a surface height value corresponding to each height position coordinate; The wafer surface height data is generated based on the height position coordinates and the surface height value.

4. The method according to claim 1, wherein The obtained wafers are divided into a plurality of wafer regions, and a surface height statistical model corresponding to the wafer is constructed according to the usage time data, the plurality of wafer regions, and the wafer surface height data, including: Obtaining a wafer size of the wafer and a pre-configured size division interval; Dividing each of the wafers into a plurality of wafer areas based on the size division interval and the wafer size; Determining a surface height value of each of the wafer regions based on the wafer surface height data; Calculate the height average, height mean square deviation, height standard deviation and specified ratio height value of each wafer area according to the surface height value as the area height statistics; The surface height statistical model is created according to the usage time data and the regional height statistical values.

5. The method according to claim 1, characterized in that The step of constructing the edge roll-off model according to the usage time data and the edge area height includes: Dividing the edge region into a first edge region and a second edge region, wherein the first edge region and the second edge region have different distances from the center point of the wafer; determining a first edge region height corresponding to the first edge region based on the edge region height, and constructing a height linear plane for each first edge region according to the first edge region height; Determine a projection height of a second edge region height corresponding to the second edge region in each of the height linear planes; constructing the edge roll-off model according to the usage time data, the plurality of height linear planes and the corresponding projection position heights; The step of constructing the edge roll-off model based on the usage time data, the plurality of height linear planes, and the corresponding projection position heights includes: Taking the height difference between each of the height linear planes and the corresponding projection position height as the edge roll-off amount; Determining the wafer table usage time corresponding to each edge roll-off amount based on the usage time data; The edge roll-off amount model is constructed according to the determined plurality of edge roll-off amounts and the respective corresponding wafer stage usage times.

6. The method according to claim 4, characterized in that The determining the service life threshold of the wafer table by combining the first correlation curve and the second correlation curve includes: Determine a maximum height value and a minimum height value of the regional height statistics based on the first correlation curve, and determine a wafer height range according to the maximum height value and the minimum height value; Determining a maximum roll-off value and a minimum roll-off value of the wafer edge roll-off amount based on the second correlation curve, and determining a roll-off amount interval according to the maximum roll-off value and the minimum roll-off amount; Determine a first service life threshold value according to the wafer height range, and determine a second service life threshold value according to the roll-off amount range; The smaller value of the first service life threshold and the second service life threshold is used as the service life threshold of the wafer table.

7. An electronic device, characterized in that: include: processor; as well as A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by the processor, implement the wafer table life determination method according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for determining the wafer table life according to any one of claims 1 to 6 is implemented.

9. A wafer stage life determination device, comprising: a data acquisition module configured to acquire usage time data of the wafer stage and wafer surface height data of wafers processed by the wafer stage; a height model building module configured to divide the obtained wafer into a plurality of wafer regions, and build a surface height statistical model corresponding to the wafer based on the usage time data, the plurality of wafer regions, and the wafer surface height data; A first curve determination module is configured to determine a first correlation curve between the wafer surface height of each wafer area and the wafer stage usage time based on the surface height statistical model; The service life determination module includes a service life determination unit and a roll-off amount model determination unit, wherein the roll-off amount model determination unit is configured to perform: treating a wafer that has completed region division as a region division wafer; Determine a center point of the wafer, and perform a region cutting process on the region-divided wafer at preset angles based on the center point of the wafer to obtain a plurality of cutting sector-shaped regions; Based on the cutting sector area, determining the edge area and non-edge area corresponding to the wafer, wherein the edge area is a wafer area that is greater than a specified distance from the center point of the wafer; obtaining the regional surface height corresponding to each edge area from the wafer surface height data as the edge area height; and constructing the edge roll-off amount model based on the usage time data and the edge area height; The life determination unit is configured to perform: determining a second correlation curve between the wafer edge roll-off amount and the wafer table usage time based on the edge roll-off amount model; and determining a service life threshold of the wafer table by combining the first correlation curve and the second correlation curve.

10. The wafer stage life determination device according to claim 9, wherein: The data acquisition module includes a data acquisition unit, which is configured to perform the following operations: acquiring the equipment usage data of the wafer table and a pre-configured data acquisition attribute column of the wafer table; acquiring the wafer table identification, wafer table replacement time, and wafer table usage time of the wafer table from the equipment usage data according to the data acquisition attribute column; generating the usage time data based on the wafer table identification, the wafer table replacement time, and the wafer table usage time; acquiring the work log of the wafer table, and determining the wafer data from the work log, wherein the wafer data includes the number of wafers that have been processed, the wafer size, and the wafer surface height data.

11. The wafer stage life determination device according to claim 10, wherein: The data acquisition unit also includes a height value acquisition sub-unit, which is configured to perform: determining the number of wafers that have been processed by each wafer table based on the work log; obtaining the wafer size and original height data of each wafer, the original height data including the height position coordinates contained in each wafer and the surface height value corresponding to each height position coordinate; generating the wafer surface height data based on the height position coordinates and the surface height values.

12. The wafer stage life determination device according to claim 9, wherein: The height model construction module includes a height model construction unit, which is configured to perform: obtaining the wafer size of the wafer and a pre-configured size division interval; dividing each of the wafers into multiple wafer areas based on the size division interval and the wafer size; determining the surface height value of each of the wafer areas based on the wafer surface height data; calculating the height average, height mean square deviation, height standard deviation and specified proportion height value of each of the wafer areas according to the surface height values ​​as area height statistical values; and creating the surface height statistical model according to the usage time data and the area height statistical values.

13. The wafer stage life determination device according to claim 9, wherein: The roll-off amount model determination unit includes a roll-off amount model determination subunit, which is configured to perform: dividing the edge area into a first edge area and a second edge area, the first edge area and the second edge area having different sizes from the center point of the wafer; determining the first edge area height corresponding to the first edge area based on the edge area height, and constructing a height linear plane for each first edge area according to the first edge area height; determining the projection position height of the second edge area height corresponding to the second edge area in each height linear plane; constructing the edge roll-off amount model according to the usage time data, multiple height linear planes and the corresponding projection position heights; wherein the height difference between each height linear plane and the corresponding projection position height is used as the edge roll-off amount; determining the wafer stage usage time corresponding to each edge roll-off amount based on the usage time data; and constructing the edge roll-off amount model according to the determined multiple edge roll-off amounts and the corresponding wafer stage usage time.

14. The wafer stage life determination device according to claim 12, wherein: The service life determination unit includes a service life determination sub-unit, which is configured to perform: determining the maximum height and the minimum height of the regional height statistics based on the first correlation curve, and determining the wafer height range according to the maximum height and the minimum height; determining the maximum roll-off amount and the minimum roll-off amount of the wafer edge roll-off amount based on the second correlation curve, and determining the roll-off amount range according to the maximum roll-off amount and the minimum roll-off amount; determining a first service life threshold according to the wafer height range, and determining a second service life threshold according to the roll-off amount range; and using the smaller value of the first service life threshold and the second service life threshold as the service life threshold of the wafer table.

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