Flatness evaluation method, defect point identification method, and device

Abstract

This application provides a flatness evaluation method, a defect point identification method, and an apparatus. The method includes: acquiring the height of each measurement point on a wafer and calculating an average height in units of exposed areas; for each exposed area of ​​the wafer, determining a first flatness of each measurement point in the exposed area based on the difference between the height of each measurement point in the exposed area and the average height of the corresponding exposed area; determining a second flatness of each measurement point in the exposed area based on the first flatness and the planar coordinates of each measurement point in the exposed area, thereby evaluating the flatness of the wafer based on the first flatness and the second flatness of each measurement point; wherein the planar coordinates are the coordinates of the measurement point in a plane, and the direction corresponding to the height is perpendicular to the plane. This method enables the evaluation of wafer surface flatness from multiple dimensions, improving the evaluation accuracy.

Description

Technical Field

[0001] This application relates to the field of semiconductor manufacturing technology, and in particular to a flatness evaluation method, a defect identification method and apparatus. Background Technology

[0002] Semiconductor devices, such as memory, are formed through various manufacturing steps performed on a wafer. During the manufacturing process, the wafer surface may have uneven areas due to the influence of manufacturing equipment or operations, resulting in a lower flatness (or smoothness) of the wafer surface that fails to meet manufacturing requirements.

[0003] As semiconductor dimensions become increasingly smaller, flatness has a greater impact on semiconductor performance. In order to promptly identify areas with abnormal wafer surface flatness, it is necessary to evaluate the wafer surface flatness to prevent wafers with insufficient flatness from entering subsequent manufacturing processes or being put into use. Summary of the Invention

[0004] This application provides a flatness evaluation method, a defect point identification method, and an apparatus, which realizes the expression of wafer surface flatness based on multiple dimensions and improves the accuracy of flatness evaluation.

[0005] In a first aspect, embodiments of this application provide a flatness evaluation method, the method comprising:

[0006] The height of each measurement point on the wafer is obtained, and the average height is calculated on a per-exposure-area basis. For each exposure area of ​​the wafer, a first flatness of each measurement point within the exposure area is determined based on the difference between the height of each measurement point within the exposure area and the average height of the corresponding exposure area. A second flatness of each measurement point within the exposure area is determined based on the first flatness and the planar coordinates of each measurement point within the exposure area. The flatness of the wafer is then evaluated based on the first flatness and the second flatness of each measurement point. Wherein, the planar coordinates are the coordinates of the measurement point in a plane, and the direction corresponding to the height is perpendicular to the plane.

[0007] In some embodiments, determining the second flatness of each measurement point within the exposure area based on the first flatness of each measurement point within the exposure area and the planar coordinates of each measurement point within the exposure area includes:

[0008] Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, a plane fitting is performed on the first flatness to obtain a flatness plane; for each measurement point within the exposure area, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane.

[0009] In some embodiments, the method further includes:

[0010] Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, a surface fitting is performed on the first flatness to obtain a flatness surface; for each measurement point within the exposure area, the third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0011] In some embodiments, the method further includes:

[0012] Flatness heatmaps are plotted and stored based on the first flatness, the second flatness, and the third flatness at each measurement point of the wafer.

[0013] In some embodiments, determining the second flatness of each measurement point within the exposure area based on the first flatness of each measurement point within the exposure area and the planar coordinates of each measurement point within the exposure area includes:

[0014] Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, a surface fitting is performed on the first flatness to obtain a flatness surface; for each measurement point on the wafer, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0015] Secondly, embodiments of this application provide a defect identification method, including:

[0016] Obtain the flatness of various measurement points on multiple wafers;

[0017] Based on the flatness of the measurement points, anomalies are identified from the measurement points of the wafer;

[0018] Based on the anomalies of multiple wafers corresponding to the same chuck, the defect points of the chuck are identified.

[0019] In some embodiments, the flatness of the measurement point is obtained based on the method provided in the first aspect of this application. The flatness of the measurement point may include a first flatness and a second flatness, and may also include a third flatness.

[0020] In some implementations, the flatness of the measurement point includes a first flatness, a second flatness, and a third flatness; obtaining the flatness of each measurement point on multiple wafers includes:

[0021] For each exposure area of ​​each wafer in the plurality of wafers, the first flatness of each measurement point in the exposure area is determined based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area.

[0022] Using the horizontal and vertical coordinates in the plane coordinate system as independent variables, the first flatness is subjected to plane fitting and surface fitting respectively to obtain the flatness plane and the flatness surface. The plane coordinates are the coordinates of the measurement point in the plane, and the direction corresponding to the height is perpendicular to the plane.

[0023] For each measurement point within the exposure area, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane, and the third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0024] Accordingly, based on the flatness of the measurement points, anomalies are identified from the measurement points of the wafer, including:

[0025] For each measurement point on the wafer, if any one of the first flatness, second flatness, and third flatness corresponding to the measurement point exceeds the corresponding flatness range, then the measurement point is determined to be an abnormal point.

[0026] In some embodiments, the plurality of wafers are a consecutive plurality of wafers corresponding to the same chuck; based on the anomalies of the plurality of wafers corresponding to the same chuck, identifying the defect points of the chuck includes:

[0027] Based on the location of the anomaly in the corresponding wafer, an anomaly distribution map corresponding to the wafer is drawn; based on the anomaly distribution maps of multiple consecutive wafers corresponding to the same chuck, the overlapping anomaly points of the multiple consecutive wafers are determined; based on the overlapping anomaly points, the defect points of the chuck are determined.

[0028] In some embodiments, the method further includes:

[0029] Based on the defect points of the chuck, generate a defect point distribution map corresponding to the chuck; and / or,

[0030] A wafer inspection record table is generated based on the location of abnormal points in the wafer, the location of chuck defects, and the wafers corresponding to the chuck defects.

[0031] Thirdly, embodiments of this application provide a flatness evaluation apparatus, comprising:

[0032] The height acquisition module is used to acquire the height of each measurement point on the wafer and calculate the average height in units of the exposure area;

[0033] The first indicator determination module is used to determine the first flatness of each measurement point in the exposure area based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area for each exposure area of ​​the wafer.

[0034] The second indicator determination module is used to determine the second flatness of each measurement point in the exposure area based on the first flatness of each measurement point in the exposure area and the planar coordinates of each measurement point in the exposure area, so as to evaluate the flatness of the wafer based on the first flatness and the second flatness of each measurement point; wherein, the planar coordinates are the coordinates of the measurement point in the plane, and the direction corresponding to the height is perpendicular to the plane.

[0035] Fourthly, embodiments of this application also provide a defect identification device, comprising:

[0036] The flatness acquisition module is used to acquire the flatness of each measurement point on multiple wafers;

[0037] An anomaly detection module is used to determine anomalies from the measurement points of the wafer based on the flatness of the measurement points.

[0038] The defect identification module is used to identify defects in the chuck based on the location of abnormal points in multiple consecutive wafers manufactured from the same chuck.

[0039] Fifthly, embodiments of this application also provide an electronic device, including: a memory and at least one processor;

[0040] The memory stores computer-executed instructions;

[0041] The at least one processor executes computer execution instructions stored in the memory, causing the electronic device to implement the method provided in the first or second aspect.

[0042] Sixthly, embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method provided in the first or second aspect.

[0043] In a seventh aspect, embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the method provided in the first or second aspect.

[0044] The flatness evaluation method, defect point identification method, and apparatus provided in this application take the exposure area as a unit. Based on the difference between the height of the measurement point and the average height, the first flatness of each measurement point is calculated. Combining the first flatness with the planar coordinates, the distribution of the first flatness is obtained. Based on the distribution of the first flatness, the second flatness of each measurement point is calculated. This realizes the expression of flatness from two different dimensions. The wafer surface flatness is evaluated by combining the first and second flatness, which improves the accuracy of flatness evaluation. Through flatness evaluation, abnormal exposure areas can be detected in time, preventing wafers with insufficient flatness from entering subsequent processes and improving product yield. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with those of this application and, together with the description, serve to explain the principles of the embodiments of this application.

[0046] Figure 1 This is a schematic diagram of a wafer surface flatness evaluation process provided in an embodiment of this application;

[0047] Figure 2 This is a schematic flowchart of a flatness evaluation method provided in an embodiment of this application;

[0048] Figure 3 A flowchart illustrating another flatness evaluation method provided in this application embodiment;

[0049] Figure 4 A schematic diagram of a manufacturing log processing framework provided in an embodiment of this application;

[0050] Figure 5 A flowchart illustrating another flatness evaluation method provided in this application embodiment;

[0051] Figure 6 A flowchart illustrating yet another flatness evaluation method provided in this application embodiment;

[0052] Figure 7 This is a schematic diagram of the structure of a flatness evaluation device provided in an embodiment of this application;

[0053] Figure 8 This is a flowchart illustrating a defect assessment method provided in an embodiment of this application;

[0054] Figure 9A A schematic diagram of the anomaly point distribution provided in an embodiment of this application;

[0055] Figure 9B A schematic diagram of the defect point distribution provided in an embodiment of this application;

[0056] Figure 10 This is a structural block diagram of an electronic device provided in an embodiment of this application.

[0057] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the embodiments of this application in any way, but rather to illustrate the concepts of the embodiments of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0058] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0059] Figure 1 This is a schematic diagram of a wafer surface flatness evaluation process provided in an embodiment of this application, referring to... Figure 1 As shown, an exposure machine is a semiconductor processing device responsible for exposing and transferring images onto wafers, recording the original exposure data, and compiling it into a manufacturing log for the wafer. The flatness evaluation device retrieves the wafer's manufacturing log from the website corresponding to the exposure machine, parsing the height and basic information of each measurement point on the wafer surface, obtaining a height set and a basic information set. Measurement points can be divided according to exposure areas (Shots) to obtain measurement points within each exposure area. Basic information may include batch, wafer ID, exposure area ID, time, etc. Based on a pre-established flatness calculation model, flatness is determined on a per-exposure-area basis. Specifically, based on the pre-established flatness calculation model and the height set corresponding to the exposure area, the flatness of each measurement point within that exposure area is calculated. This process is repeated across all exposure areas to obtain the flatness of each measurement on the wafer. A heatmap is generated based on the flatness, and this heatmap and the basic information set are stored together. This allows for subsequent queries of the heatmap, where the basic information set can be used to identify the specific wafer or measurement point being viewed, providing more comprehensive information.

[0060] In some embodiments, heatmaps can be stored in network attached storage (NAS), manufacturing logs can be stored in a distributed file system, such as the Hadoop Distributed File System (HDFS), and the basic information set can be stored in a database, such as SQL Server DB.

[0061] The flatness calculation model can specifically calculate the first flatness Z0 based on the average height of the height set and the difference between each height. Then, using the first flatness Z0 as the dependent variable and the plane coordinates (x, y) of the measurement point as the independent variable, plane fitting and surface fitting are performed to obtain the fitted plane Z′0 and the fitted surface Z′0′, respectively. The difference between the first flatness Z0 and the fitted plane Z′0 is calculated to obtain the second flatness Z1. The difference between the first flatness Z0 and the fitted surface Z′0′ is calculated to obtain the third flatness Z2. Based on the flatness of these three dimensions—the first flatness Z0, the second flatness Z1, and the third flatness Z2—the wafer surface flatness is evaluated.

[0062] In this heatmap, a gradient from blue to red can be used to represent the change in wafer surface height (or flatness) from low to high. The lowest point is represented by the darkest blue, the highest point by the darkest red, and other colors are drawn uniformly based on color bands.

[0063] The closer the flatness is to 0, the flatter or smoother it is.

[0064] By expressing flatness in multiple dimensions, the accuracy of wafer surface flatness assessment is improved, thereby timely detection of wafers with uneven surfaces, preventing them from entering subsequent processes and improving the yield of semiconductor products.

[0065] Figure 2 This is a flowchart illustrating a flatness evaluation method provided in an embodiment of this application. The flatness evaluation method provided in this embodiment can be executed by an electronic device with corresponding data processing capabilities, such as a flatness evaluation device. Figure 2 As shown, the flatness evaluation method includes the following steps S201 to S203.

[0066] S201, obtain the height of each measurement point on the wafer, and calculate the average height in units of the exposed area.

[0067] An exposure area (Shot) is a unit of measurement used by an exposure machine during exposure. An exposure area includes multiple measurement points (or sampling points).

[0068] The average height is the average height of all measurement points within the same exposure area of ​​the wafer.

[0069] Height can also be referred to as thickness. The height of each measurement point can be determined based on the height coordinates in the three-dimensional coordinate system of each measurement point on the wafer. The average height of the height is then calculated in units of the exposure area to obtain the average height Mean(H) corresponding to the exposure area.

[0070] In some embodiments, the height of each measurement point on the wafer can be determined based on the detection light signal reflected from the wafer surface.

[0071] In other embodiments, the height of each measurement point on the wafer, as well as subsequent planar coordinates and basic wafer information, can be obtained by parsing the manufacturing logs corresponding to the wafer.

[0072] Optionally, obtaining the height of each measurement point on the wafer includes:

[0073] Obtain the manufacturing log of the wafer; parse the manufacturing log to obtain the height of each measurement point on the wafer.

[0074] The wafer manufacturing log can be generated by the exposure machine. After processing the wafer, the exposure machine obtains raw exposure data and organizes this raw exposure data into a manufacturing log.

[0075] The exposure machine can upload the manufacturing logs of each wafer to the machine's website, allowing the flatness evaluation equipment to download the manufacturing logs of each wafer to be evaluated from the website. The downloaded manufacturing logs are parsed to extract the height of each measurement point on the wafer. Organized by exposure area, a height set H is obtained for each exposure area. The height set H includes the height of each measurement point within the corresponding exposure area.

[0076] The i-th element in the height set H corresponding to the j-th exposure region can be represented as: {Shot j :h i , i∈[1,m]}, where m is the total number of measurement points within the exposure area.

[0077] Flatness assessment equipment can obtain newly added manufacturing logs from the machine site by periodically refreshing the machine site.

[0078] The height of the measurement point is obtained by parsing the logs, which is fast and efficient.

[0079] Manufacturing logs generated by the exposure machine can be stored in network storage, databases, or distributed file systems.

[0080] A distributed file system could be HDFS. HDFS is highly fault-tolerant, automatically recovering data after loss by storing multiple copies, thus improving data storage security. HDFS also supports streaming data access and has low performance requirements on the running hardware.

[0081] Optionally, the method further includes:

[0082] Based on the wafer identifier, the manufacturing log of the wafer is obtained from the distributed file system.

[0083] Wafer identification is used to distinguish different wafers. It can be a numerical code or a combination of letters and numbers, such as a combination of 2 letters and 9 numbers.

[0084] Optionally, obtaining the manufacturing log of the wafer includes:

[0085] According to a preset cycle, check the log download website to see if there are any new logs; if so, retrieve the new logs.

[0086] The preset period can be in seconds, such as 10s, 20s, 30s or other times.

[0087] After the exposure machine performs the exposure process on the wafer, it uploads the corresponding manufacturing log to a log download website. By periodically refreshing this log download website, newly added manufacturing logs can be obtained in a timely manner.

[0088] S202, for each exposure area of ​​the wafer, based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area, determine the first flatness of each measurement point in the exposure area.

[0089] First flatness is one of the metrics used to measure the flatness of a wafer surface.

[0090] The first flatness Z0 of each measurement point is obtained by subtracting the height difference of each measurement point within the exposure area from the average height Mean(H) corresponding to the exposure area.

[0091] The formula for calculating the first flatness is: Z0 = Mean(H) – H.

[0092] In some embodiments, the first flatness may also be expressed as a ratio of height to average height.

[0093] S203, based on the first flatness of each measurement point in the exposure area and the planar coordinates of each measurement point in the exposure area, determine the second flatness of each measurement point in the exposure area, so as to evaluate the flatness of the wafer based on the first flatness and the second flatness of each measurement point.

[0094] Wherein, the planar coordinates are the coordinates of the plane corresponding to the measurement point, and the direction corresponding to the height is perpendicular to the plane.

[0095] The three-dimensional coordinates of the measurement point are (x, y, h), where h represents the coordinate corresponding to the height. The above planar coordinates are the remaining coordinates excluding the coordinate h corresponding to the height, i.e., (x, y).

[0096] The planar coordinates and height, or three-dimensional coordinates, of the measurement point can be stored in the manufacturing log. The planar coordinates and height, or three-dimensional coordinates, of the measurement point can be obtained by parsing the manufacturing log.

[0097] Specifically, the distribution function of the first flatness Z0 can be determined based on the first flatness Z0 and the plane coordinates (x,y) of each measurement point, and the second flatness of each measurement point can be determined based on the distribution function of the first flatness Z0.

[0098] The distribution function describes the correspondence between the first flatness Z0 and the planar coordinates (x, y). The distribution function can be obtained through plane fitting or surface fitting.

[0099] For example, the second flatness can be the difference or ratio of the first flatness Z0 to the distribution function of the first flatness Z0.

[0100] Furthermore, after obtaining the first flatness and the second flatness, it is also possible to determine whether there are any abnormal measurement points among the measurement points of the wafer based on the first flatness and the second flatness, and record them as abnormal points. If they exist, a prompt message is generated based on the abnormal points to indicate the uneven parts on the wafer surface.

[0101] The value of at least one of the first and second flatness values ​​corresponding to the outlier point is outside the corresponding value range.

[0102] The flatness evaluation method provided in this embodiment takes the exposure area as a unit. Based on the difference between the height of the measurement point and the average height, the first flatness of each measurement point is calculated. Combining the first flatness with the planar coordinates, the distribution of the first flatness is obtained. Based on the distribution of the first flatness, the second flatness of each measurement point is calculated. This realizes the expression of flatness from two different dimensions. The wafer surface flatness is evaluated by combining the first and second flatness, which improves the accuracy of flatness evaluation. Through flatness evaluation, abnormal exposure areas can be detected in time, preventing wafers with insufficient flatness from entering subsequent processes and improving product yield.

[0103] Figure 3 This is a schematic flowchart of another flatness evaluation method provided in an embodiment of this application. Figure 2 Based on the illustrated embodiment, step S203 is further refined, and steps related to third flatness and flatness heatmap drawing are added after step S203, such as... Figure 3 As shown, the flatness evaluation method provided in this embodiment may include the following steps:

[0104] S301, obtain the height of each measurement point on the wafer.

[0105] S302, for each exposure area of ​​the wafer, calculate the average height of each measurement point within the exposure area to obtain the average height of the exposure area.

[0106] S303, based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area, determine the first flatness of each measurement point in the exposure area.

[0107] S304, using the horizontal and vertical coordinates in the plane coordinate system as independent variables, perform plane fitting on the first flatness to obtain a flatness plane.

[0108] S305, for each measurement point within the exposure area, determine the second flatness of the measurement point based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane.

[0109] The planar coordinate system includes the horizontal coordinate (x) and the vertical coordinate (y). With x and y as independent variables and the first flatness Z0 as the dependent variable, a fitted plane is obtained through plane fitting, which is the flatness plane Z′0, where Z′0 = h. w (x,y)=W1x+W2y+b1, where W1 and W2 are parameters obtained during the plane fitting process, and b1 is a constant coefficient.

[0110] Any plane fitting algorithm can be used to obtain the flatness plane Z′0, and this application does not limit it.

[0111] When fitting a plane, the parameters of the fitted plane can be solved using gradient descent. Set a maximum number of iterations (e.g., 300, 500, 1000, or other values) and a stopping condition, establish a loss function, and update the parameters of the fitted plane using the negative gradient direction until the stopping condition is met, thus obtaining the fitted plane Z′0.

[0112] The stopping condition can be reaching the maximum number of iterations, or the value of the loss function being less than a set value, such as 0.01. Other stopping conditions can also be set, but this application does not limit them.

[0113] For example, the loss function J(w) can be:

[0114]

[0115] Where, x i and y i and are the x and y coordinates of the i-th measurement point, respectively, and m is the total number of measurement points in the exposure area.

[0116] For h w The parameter w to be solved i The parameter update relationship is:

[0117]

[0118] Where α is the learning rate, set to 0.1. Parameter wi It can be any element between W1 and W2.

[0119] The second flatness Z1 can be defined as the difference between the first flatness Z0 and the flatness plane Z′0, i.e., Z1 = Z0 - Z′0. For each measurement point, the second flatness of that measurement point is the difference between the first flatness of that measurement point and the value of that measurement point on the flatness plane Z′0.

[0120] By using plane fitting, another flatness index, namely the second flatness Z1, is obtained to better characterize the specific parts of flatness and improve the accuracy of flatness assessment.

[0121] S306, using the horizontal and vertical coordinates in the plane coordinate system as independent variables, perform surface fitting on the first flatness to obtain a flatness surface.

[0122] S307, for each measurement point within the exposure area, determine the third flatness of the measurement point based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0123] The fitting process for the flatness surface Z′0′ is similar to that for the flatness plane Z′0, and will not be described in detail here.

[0124] The expression for the flatness surface Z′0′ is:

[0125] Z′0′=h w (x,y)=W3x+W4y+W5x 2 +W6y 2 +b2

[0126] Among them, W3 to W6 are all parameters obtained during the surface fitting process, and b2 is a constant coefficient.

[0127] The third flatness Z2 can be defined as the difference between the first flatness Z0 and the flatness surface Z′0′, i.e., Z2 = Z0 - Z′0′. For each measurement point, the third flatness of that measurement point is the difference between the first flatness of that measurement point and the value of that measurement point on the flatness surface Z′0′.

[0128] By fitting surfaces, a new dimension of flatness index, namely the third flatness Z2, is obtained to better characterize the specific parts of flatness and improve the accuracy of flatness assessment.

[0129] The steps for determining the second and third flatness can be performed sequentially or in parallel. Figure 3Taking parallel execution as an example, in some embodiments, steps S306 and S307 can be executed first, followed by steps S304 and S305. This application does not limit this.

[0130] S308, based on the first flatness, the second flatness and the third flatness of each measurement point of the wafer, respectively, draw and store flatness heat maps.

[0131] A flatness heatmap is drawn with the first flatness Z0, the second flatness Z1, and the third flatness Z2 as dimensions, respectively, to visually evaluate the flatness of each exposure area of ​​the wafer based on the flatness heatmap.

[0132] For example, a flatness heatmap can use a gradient from blue to red to represent changes in flatness (first flatness Z0, second flatness Z1, or third flatness Z2).

[0133] For each of the first flatness Z0, the second flatness Z1, and the third flatness Z2, in the flatness heatmap corresponding to that flatness, the darkest red represents the maximum flatness of each measurement point on the wafer, and the darkest blue represents the minimum flatness of each measurement point on the wafer. Through the mapping relationship between color and flatness, the flatness is mapped to a color between blue and red.

[0134] In some embodiments, flatness heatmaps can be generated separately for each flatness level, with each exposure area as a unit. Then, the flatness heatmaps corresponding to each exposure area are stitched together. Based on the maximum and minimum flatness values ​​of each measurement point on the wafer, the mapping relationship between flatness and color is updated. That is, the color of each measurement point in the flatness heatmap is corrected to obtain the flatness heatmap corresponding to the wafer.

[0135] Optionally, for each of the first, second, and third flatnesses, a flatness heatmap is plotted and stored based on the flatness at each measurement point on the wafer, including:

[0136] For each exposure area of ​​the wafer, based on the minimum and maximum flatness of the measurement points within the exposure area, the color corresponding to each measurement point within the light area is determined, and a flatness heatmap of the exposure area under the given flatness is plotted. The flatness heatmaps of each exposure area of ​​the wafer under the given flatness are stitched together, and based on the minimum and maximum flatness of the measurement points on the wafer, the color corresponding to each measurement point is updated, and a flatness heatmap of the wafer under the given flatness is plotted and stored.

[0137] The flatness (including first flatness, second flatness, and third flatness) of measurement points within each exposure area is determined on a unit basis. The process of drawing flatness heatmaps for each of the first, second, and third flatness levels is illustrated below using one of the flatness levels as an example.

[0138] Based on the maximum and minimum values ​​of the flatness of the measurement points within the exposure area, the mapping relationship between flatness and color is determined. Based on this mapping relationship and the flatness of each measurement point within the exposure area, the color of each measurement point within the exposure area in the flatness heatmap is determined, and a flatness heatmap of the exposure area under the given flatness is drawn.

[0139] After obtaining the flatness heatmaps of each exposed area of ​​the wafer, the flatness heatmaps corresponding to the wafer are drawn. The specific process is as follows: stitch together the flatness heatmaps corresponding to all exposed areas of the wafer to form a circle corresponding to the wafer. Update the mapping relationship between flatness and color using the maximum and minimum flatness values ​​of all exposed areas. Based on the new mapping relationship, update the color corresponding to each measurement point to obtain the flatness heatmap of the wafer under that flatness.

[0140] The mapping relationship between flatness and color can be a linear mapping, with the minimum flatness value corresponding to the darkest blue, the maximum flatness value corresponding to the darkest red, and the color corresponding to the intermediate value determined based on the color band between the darkest blue and the darkest red.

[0141] For example, taking the minimum flatness of the exposure area A1 as -0.02mm and the maximum as 0.015mm, each color in the color band can be mapped to a value within the range of [-0.020, 0.015], establishing a mapping relationship between flatness and color. Here, -0.020 corresponds to the darkest blue, and 0.015 corresponds to the darkest red. This mapping relationship is updated when the maximum and minimum values ​​are updated. For example, if the minimum flatness of each measurement point in the wafer is -0.080 and the maximum is 0.170, the value range is updated to [-0.080, 0.170], and the color band is remapped to a value within the range of [-0.080, 0.170]. Based on the new mapping relationship, the color corresponding to each measurement point is updated. In exposure area A1, a flatness value of -0.020 corresponds to a color that can change from the darkest blue to a lighter blue, and a flatness value of 0.015 corresponds to a color that can change from the darkest red to a very light blue.

[0142] After obtaining the flatness of each measurement point within an exposure area, a flatness heatmap corresponding to that exposure area can be plotted. The determination of the flatness of measurement points within each exposure area can be performed in parallel, and the flatness heatmaps corresponding to each exposure area can also be plotted in parallel.

[0143] In some embodiments, flatness heatmaps corresponding to each exposure area may also be stored, such as in a network memory.

[0144] By drawing heatmaps on an exposure-area-by-exposure basis, the parallelism of heatmap drawing is improved, thus increasing drawing efficiency. After stitching together the heatmaps of each exposure area of ​​the wafer to form the shape corresponding to the wafer, the heatmap corresponding to the entire wafer can be obtained by updating the mapping relationship, resulting in high drawing efficiency.

[0145] In this embodiment, the first flatness is obtained by measuring the height of the point and the average height within the exposure area. The first flatness is then fitted with a plane and a surface, and the difference between the first flatness and the fitted plane and surface is used as the second flatness and the third flatness, respectively, resulting in flatness described by three different dimensions. The wafer surface flatness is evaluated based on the combination of these three flatnesses, which improves the accuracy of flatness evaluation. At the same time, a flatness heatmap of the wafer is plotted for each flatness, which improves the visualization of flatness and allows relevant personnel to quickly determine whether there are any flatness abnormalities in the wafer based on the heatmap, thus improving the efficiency and convenience of wafer flatness determination.

[0146] Optionally, store flatness heatmaps, including:

[0147] The flatness heatmap is stored in a network memory.

[0148] Storing heatmaps using network storage offers advantages such as low storage cost and ease of management.

[0149] In some embodiments, the flatness heatmap can also be stored in a database.

[0150] Optionally, the method further includes:

[0151] Based on the first flatness, the second flatness, and the third flatness, abnormal points are determined from the measurement points of the wafer; based on the abnormal points, a prompt message is generated.

[0152] At least one of the flatness values ​​of the first flatness, second flatness, and third flatness corresponding to the outlier point is outside the corresponding value range.

[0153] By generating prompts, relevant personnel are promptly alerted to areas with flatness anomalies in the wafers being manufactured. This improves the timeliness of alerts and prevents losses in subsequent processes due to wafers with flatness anomalies.

[0154] Figure 4 This is a schematic diagram of a data processing framework provided in an embodiment of this application, as shown below. Figure 4As shown, this data processing framework is a real-time production-consumption processing framework. Manufacturing logs are generated in real time by producers, such as exposure machines or equipment, and uploaded to a downloader, such as a log download website. A monitor periodically refreshes the log download website to detect the existence of new manufacturing logs. If a new manufacturing log is found, it is immediately downloaded and the corresponding message is written to Kafka. Consumers, such as the manufacturing log parsing device of a flatness evaluation device, parse the manufacturing logs obtained from Kafka to obtain the three-dimensional coordinates and basic information of each measurement point on the wafer corresponding to the manufacturing log. The three-dimensional coordinates include two-dimensional planar coordinates and height. The data output module outputs the set of three-dimensional coordinates and wafer basic information to the flatness analysis device of the flatness evaluation device. The flatness analysis device determines the flatness of each part and draws a flatness heatmap.

[0155] Flatness assessment equipment may include multiple consumers and flatness analysis devices.

[0156] The monitor is also used to report errors or issue alarms.

[0157] The processing framework also includes a storage layer, which comprises a database (DB), a network storage device (NAS), and HDFS.

[0158] The database is used to store wafer identifiers or wafer IDs, the network storage is used to store flatness heatmaps, and HDFS is used to store manufacturing logs.

[0159] In some embodiments, HDFS can be used to store cold data in manufacturing logs, such as older manufacturing logs, while hot data in manufacturing logs, such as recently generated manufacturing logs, can be stored in NAS.

[0160] Figure 5 This is a schematic flowchart of another flatness evaluation method provided in an embodiment of this application. Figure 2 Based on the illustrated embodiment, steps S202 and S203 are further refined. In this embodiment, the failure mode is used to indicate the region where the failure address and its associated address are located. This embodiment addresses the case where there is only one failure mode, such as... Figure 5 As shown, the flatness evaluation method may include the following steps:

[0161] S501 checks the log download website according to a preset cycle to see if there are any new manufacturing logs.

[0162] If a new manufacturing log exists, obtain that new manufacturing log and proceed with the subsequent flatness determination steps.

[0163] In some embodiments, manufacturing logs are divided into hot data and cold data, stored in different regions: hot data is stored in network storage, while cold data is stored in a distributed file system. Therefore, when a log download website adds a new manufacturing log, it can first determine whether the log is hot or cold data.

[0164] Since network storage is more efficient than distributed file systems in terms of storage and retrieval, storing hot data in network storage can improve the efficiency of hot data processing.

[0165] S502, if so, then retrieve the basic information of the wafer from the database, and determine whether the manufacturing log is hot data or cold data based on the time corresponding to the manufacturing log.

[0166] The basic information includes wafer identifiers, and may also include wafer batch, wafer manufacturing log corresponding time, etc.

[0167] Manufacturing logs are considered hot data when the time corresponding to the manufacturing log is within the most recent preset time period; otherwise, they are considered cold data.

[0168] The recent preset time period can be the most recent week, the most recent three days, the most recent day, or other time periods.

[0169] S503, if the manufacturing log is hot data, then the manufacturing log is retrieved from the network memory based on the wafer identifier of the wafer.

[0170] S504, if the manufacturing data is cold log data, then the manufacturing log is obtained from the distributed file system based on the wafer identifier of the wafer.

[0171] In other embodiments, manufacturing logs can also be categorized into cold data, warm data, and hot data based on their corresponding time periods, with different storage areas for each type of manufacturing log. Therefore, the type of manufacturing log can be determined based on its corresponding time period, and the manufacturing log can be retrieved from the storage area corresponding to that type.

[0172] S505, parse the manufacturing log to obtain the height and planar coordinates of each measurement point on the wafer.

[0173] S506 calculates the average height in units of the exposed area.

[0174] S507, for each exposure area of ​​the wafer, based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area, determine the first flatness of each measurement point in the exposure area.

[0175] S508, based on the first flatness of each measurement point in the exposure area and the planar coordinates of each measurement point in the exposure area, determine the second flatness of each measurement point in the exposure area.

[0176] Optionally, step S508 may specifically include:

[0177] Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, a surface fitting is performed on the first flatness to obtain a flatness surface; for each measurement point on the wafer, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0178] The second flatness calculated in this embodiment is equivalent to the third flatness in the aforementioned embodiment. That is, the flatness may include the first flatness, and at least one of the second flatness and the third flatness.

[0179] S509, based on the first flatness and the second flatness of each measurement point of the wafer, respectively, draw and store a flatness heat map.

[0180] In some embodiments, wafer chuckspots can be determined based on a plurality of determined flatnesses, and the locations of the chuckspots can be recorded.

[0181] The front-end page can display relevant information about each wafer, such as its lot, wafer identifier, status, time, and defects. A lot is a crystal pillar formed by the growth of single-crystal silicon. After the crystal pillar is cut, multiple wafers are obtained, such as 12. Users can also view the wafer flatness heatmap through relevant controls on the front-end page, and can also view the flatness of each exposed area of ​​the wafer and its corresponding flatness heatmap, such as defects, for manual verification of wafer flatness.

[0182] In this embodiment, partitioning and storing data according to hot and cold data reduces the storage cost of manufacturing logs and improves the access efficiency of hot data. By periodically refreshing the website corresponding to the manufacturing logs, wafer flatness is analyzed in a timely manner based on newly uploaded manufacturing logs, improving the timeliness of flatness analysis. By expressing the wafer surface with high specificity from multiple dimensions, flatness in multiple dimensions is obtained, enriching the dimensions of flatness. By comprehensively evaluating wafer surface flatness using flatness in multiple dimensions, the accuracy of flatness evaluation is improved.

[0183] Figure 6 A flowchart illustrating another flatness evaluation method provided in this application embodiment is shown below. Figure 6 As shown, the flatness evaluation method specifically includes:

[0184] In response to wafer evaluation requests from the front-end API, a hot / cold data determination is performed. Specifically, based on the time corresponding to the wafer, the manufacturing log for that wafer is determined to be either hot or cold data. If it is hot data, such as manufacturing logs generated within the last 3 days, the manufacturing logs for that wafer are retrieved from the NAS; if it is cold data, the manufacturing logs for that wafer are retrieved from HDFS. Based on the manufacturing logs, flatness heatmaps for each exposure area are asynchronously drawn, and the flatness heatmaps of each exposure area are stitched together to obtain the wafer's flatness heatmap. The storage path of the wafer's flatness heatmap is then returned.

[0185] Corresponding to the above method embodiments, Figure 7 This is a schematic diagram of a flatness evaluation device provided in an embodiment of this application. Figure 7 As shown, the flatness assessment device includes: a height acquisition module 710, a first index determination module 720, and a second index determination module 730.

[0186] The height acquisition module 710 is used to acquire the height of each measurement point on the wafer and calculate the average height in units of the exposure area; the first index determination module 720 is used to determine the first flatness of each measurement point in the exposure area based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area for each exposure area of ​​the wafer; the second index determination module 730 is used to determine the second flatness of each measurement point in the exposure area based on the first flatness and the planar coordinates of each measurement point in the exposure area, so as to evaluate the flatness of the wafer based on the first flatness and the second flatness of each measurement point; wherein, the planar coordinates are the coordinates of the measurement point in the plane, and the direction corresponding to the height is perpendicular to the plane.

[0187] In some implementations, the second indicator determination module 730 is specifically used for:

[0188] Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, a plane fitting is performed on the first flatness to obtain a flatness plane; for each measurement point within the exposure area, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane.

[0189] In some embodiments, the apparatus further includes:

[0190] The third indicator determination module is used to perform surface fitting on the first flatness using the horizontal and vertical coordinates in the plane coordinate system as independent variables to obtain a flatness surface; and for each measurement point in the exposure area, the third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0191] In some embodiments, the apparatus further includes:

[0192] The heatmap drawing module is used to draw and store flatness heatmaps based on the first flatness, the second flatness, and the third flatness at each measurement point of the wafer.

[0193] In some implementations, the heatmap drawing module is specifically used for:

[0194] For each exposure area of ​​the wafer, based on the minimum and maximum flatness of the measurement points within the exposure area, the color corresponding to each measurement point within the light area is determined, and a flatness heatmap of the exposure area under the given flatness is plotted. The flatness heatmaps of each exposure area of ​​the wafer under the given flatness are stitched together, and based on the minimum and maximum flatness of the measurement points on the wafer, the color corresponding to each measurement point is updated, and a flatness heatmap of the wafer under the given flatness is plotted and stored.

[0195] In some embodiments, the apparatus further includes:

[0196] An anomaly alert module is used to determine anomaly points from the measurement points of the wafer based on the first flatness, the second flatness, and the third flatness; and to generate alert information based on the anomaly points.

[0197] In some implementations, the second indicator determination module 730 is specifically used for:

[0198] Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, a surface fitting is performed on the first flatness to obtain a flatness surface; for each measurement point on the wafer, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0199] In some implementations, the height acquisition module 710 includes:

[0200] The log acquisition unit is used to acquire the manufacturing log of the wafer; the log parsing unit is used to parse the manufacturing log to obtain the height of each measurement point of the wafer.

[0201] In some implementations, the log acquisition unit is specifically used for:

[0202] According to a preset cycle, check the log download website to see if there are any new manufacturing logs; if so, obtain the new logs.

[0203] In some implementations, the log acquisition unit is specifically used for:

[0204] Based on the wafer identifier, the manufacturing log of the wafer is obtained from the distributed file system.

[0205] In some implementations, the log acquisition unit is specifically used for:

[0206] Based on the time corresponding to the manufacturing log, it is determined whether the manufacturing log is hot data or cold data; if the manufacturing log is hot data, the manufacturing log is retrieved from the network storage based on the wafer identifier of the wafer; if the manufacturing log is cold data, the manufacturing log is retrieved from the distributed file system based on the wafer identifier of the wafer.

[0207] In some embodiments, the apparatus further includes:

[0208] The basic information acquisition module is used to obtain the basic information of the wafer from the database, including the wafer identifier.

[0209] The above-described apparatus embodiment is an embodiment corresponding to the foregoing method embodiment, and has the same technical effects as the method embodiment. A detailed description of this apparatus embodiment can be found in the detailed description of the foregoing method embodiment, and will not be repeated here.

[0210] This application also provides an electronic device, including at least one processor and a memory.

[0211] The memory stores computer-executable instructions. The at least one processor executes the computer-executable instructions stored in the memory, causing the electronic device to implement the aforementioned flatness evaluation method.

[0212] After evaluating the flatness of each measurement point on the wafer based on the flatness evaluation method provided in the above embodiments, measurement points with abnormal flatness on the wafer can also be identified based on the flatness of each measurement point on the wafer and recorded as abnormal points.

[0213] In some embodiments, the defective point of the chuck can also be determined based on the distribution of abnormal points on multiple consecutive wafers corresponding to the same chuck.

[0214] Specifically, the defect points of the chuck can be determined based on the overlap of multiple consecutive wafer abnormalities processed on the same chuck.

[0215] If four consecutive wafers have overlapping abnormal points, the overlapping area is recorded as the defect point of the chuck.

[0216] Figure 8 This is a flowchart illustrating a defect assessment method provided in an embodiment of this application. This defect assessment method can be executed by an electronic device with corresponding data processing capabilities, such as a defect assessment device. Figure 8 As shown, the defect assessment method includes the following steps S801 to S803.

[0217] S801, obtain the flatness of each measurement point on the wafer.

[0218] In some embodiments, the flatness of the measurement point is obtained based on the flatness evaluation method provided in any of the above embodiments of this application. The flatness of the measurement point includes a first flatness and a second flatness, and may also include a third flatness.

[0219] S802, based on the flatness of the measurement points, determine the abnormal points from the measurement points of the wafer.

[0220] An outlier (focus spot) can be any measurement point in the flatness measurement that exceeds the corresponding flatness range.

[0221] Optionally, the flatness of the measurement point includes a first flatness, a second flatness, and a third flatness; obtaining the flatness of each measurement point on multiple wafers includes:

[0222] For each exposure area of ​​each wafer in the plurality of wafers, a first flatness of each measurement point in the exposure area is determined based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area. Using the horizontal and vertical coordinates in a plane coordinate system as independent variables, the first flatness is subjected to plane fitting and surface fitting respectively to obtain a flatness plane and a flatness surface. The plane coordinates are the coordinates of the measurement point in the plane, and the direction corresponding to the height is perpendicular to the plane. For each measurement point in the exposure area, a second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane, and a third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0223] Accordingly, based on the flatness of the measurement points, anomalies are identified from the measurement points of the wafer, including:

[0224] For each measurement point on the wafer, if any one of the first flatness, second flatness, and third flatness corresponding to the measurement point exceeds the corresponding flatness range, then the measurement point is determined to be an abnormal point.

[0225] Taking flatness including first flatness, second flatness, and third flatness as an example, outliers can be measurement points where the absolute value of the difference between the first or second flatness and the corresponding flatness threshold is greater than or equal to a preset threshold, that is, the flatness of the measurement point satisfies |Z i -TH i|≥th, where i is 0, 1, or 2, and Z0, Z1, and Z2 represent the first, second, and third flatness of the measurement point, respectively; TH i For Z i The corresponding flatness threshold; th is the preset threshold.

[0226] The three flatness thresholds TH0, TH1, and TH2 can be the same or different.

[0227] S803, based on the abnormal points of multiple wafers corresponding to the same chuck, identifies the defect points of the chuck.

[0228] During the manufacturing process, wafers need to be fixed on a chuck. When there are contaminants on the chuck, such as particles, or when the support is worn, it can cause the wafer to deform, resulting in defects.

[0229] Specifically, the defect points of the chuck can be determined based on the abnormal points of multiple overlapping wafers corresponding to the same chuck.

[0230] To effectively identify defects in the chuck, analysis is performed on a unit consisting of multiple consecutive wafers fixed on the chuck, such as 4, 5, 6, or other numbers.

[0231] In some embodiments, defects in the chuck can be determined based on overlapping anomalies on multiple consecutive wafers.

[0232] Defects can be the overlapping regions of abnormal points from multiple consecutive wafers.

[0233] In this embodiment, the detection of anomalies and defects is performed by combining multi-dimensional flatness, which improves the accuracy and comprehensiveness of the detection.

[0234] Optionally, the plurality of wafers are a consecutive plurality of wafers corresponding to the same chuck; based on the anomalies of the plurality of wafers corresponding to the same chuck, the defect points of the chuck are identified, including:

[0235] Based on the location of the anomaly in the corresponding wafer, an anomaly distribution map corresponding to the wafer is drawn; based on the anomaly distribution maps of multiple consecutive wafers corresponding to the same chuck, the overlapping anomaly points of the multiple consecutive wafers are determined; based on the overlapping anomaly points, the defect points of the chuck are determined.

[0236] Specifically, the distribution maps of anomalies corresponding to multiple consecutive wafers can be aligned. If multiple consecutive wafers have overlapping anomalies, then the overlapping anomalies can be used to identify a defect point.

[0237] On the outlier distribution map, two different values ​​can be used to represent outliers and normal measurement points, i.e., measurement points that have not been identified as outliers, such as red for outliers and green for normal measurement points.

[0238] Optionally, the method further includes:

[0239] Based on the defects of the chuck, a defect point distribution map corresponding to the chuck is generated.

[0240] For example, Figure 9A This is a schematic diagram of the anomaly point distribution map provided in the embodiments of this application, such as... Figure 9A As shown, the anomaly distribution map is used to display the distribution of abnormal points and normal measurement points on the wafer. Figure 9A In the diagram, solid dots represent abnormal points, while hollow dots represent normal measurement points. Figure 9B This is a schematic diagram of the defect point distribution map provided in the embodiments of this application, as shown below. Figure 9B As shown, among the seven consecutive wafers (wafer 1 to wafer 7) fixed sequentially on chuck A, anomalies 91 to 98 are present. Anomalies 91 to 96 overlap. Since no anomalies were detected on wafer 2, wafers 3 to 7 are consecutive wafers, and anomalies 92 to 96 on them overlap. The center line of the overlapping area is shown in the figure. Figure 9B As shown by the dashed line in the defect point distribution map, a defect point is drawn at the location corresponding to that dashed line. Figure 9B Defect points are represented by ellipses filled with diagonal lines.

[0241] Optionally, the method further includes:

[0242] A wafer inspection record table is generated based on the location of abnormal points in the wafer, the location of chuck defects, and the wafers corresponding to the chuck defects.

[0243] The wafer inspection record includes the location of each detected anomaly, the location of each defect, and the wafer affected by each defect.

[0244] The wafer inspection record table can also record information such as the serial number of the abnormal point, the batch of the wafer corresponding to the abnormal point, the wafer identification, the chuck on which the wafer is fixed, the wafer status, the exposure status, and the time.

[0245] The flatness evaluation method and defect identification method provided in the embodiments of this application can be executed by the same device or different devices.

[0246] This application provides a defect identification method, including:

[0247] The height of each measurement point on the wafer is obtained, and the average height is calculated on a per-exposure-area basis. For each exposure area of ​​the wafer, a first flatness of each measurement point within the exposure area is determined based on the difference between the height of each measurement point within the exposure area and the average height of the corresponding exposure area. A second flatness of each measurement point within the exposure area is determined based on the first flatness and the planar coordinates of each measurement point within the exposure area. Wherein, the planar coordinates are the coordinates of the measurement point in a plane, and the direction corresponding to the height is perpendicular to the plane. Anomalies are identified from the measurement points of the wafer based on the first flatness and the second flatness. Defects in the chuck are identified based on the anomalies of multiple wafers corresponding to the same chuck.

[0248] Optionally, the method further includes:

[0249] Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, a surface fitting is performed on the first flatness to obtain a flatness surface; for each measurement point within the exposure area, the third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0250] Accordingly, based on the first flatness and the second flatness, outliers are determined from the measurement points of the wafer, including:

[0251] Anomalies are determined from the measurement points of the wafer based on the first flatness, the second flatness, and the third flatness.

[0252] This application embodiment also provides a defect point identification device, including: a flatness acquisition module for acquiring the flatness of each measurement point of multiple wafers; an anomaly point determination module for determining anomalies from the measurement points of the wafers based on the flatness of the measurement points; and a defect point identification module for identifying defects of the chuck based on the positions of anomalies of multiple consecutive wafers manufactured from the same chuck.

[0253] In some embodiments, the flatness of the measurement points is obtained based on the flatness evaluation method provided in any embodiment of this application.

[0254] In some implementations, the flatness of the measurement point includes a first flatness, a second flatness, and a third flatness; the flatness acquisition module is specifically used for:

[0255] For each exposure area of ​​each wafer in the plurality of wafers, a first flatness of each measurement point in the exposure area is determined based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area. Using the horizontal and vertical coordinates in the planar coordinate system as independent variables, the first flatness is subjected to planar fitting and surface fitting respectively to obtain a flatness plane and a flatness surface. For each measurement point in the exposure area, a second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane, and a third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface.

[0256] Correspondingly, the anomaly point identification module is specifically used for:

[0257] For each measurement point on the wafer, if any one of the first flatness, second flatness, and third flatness corresponding to the measurement point exceeds the corresponding flatness range, then the measurement point is determined to be an abnormal point.

[0258] In some embodiments, the plurality of wafers are consecutive wafers corresponding to the same chuck; the defect identification module is specifically used for:

[0259] Based on the location of the anomaly in the corresponding wafer, an anomaly distribution map corresponding to the wafer is drawn; based on the anomaly distribution maps of multiple consecutive wafers corresponding to the same chuck, the overlapping anomaly points of the multiple consecutive wafers are determined; based on the overlapping anomaly points, the defect points of the chuck are determined.

[0260] In some embodiments, the apparatus further includes:

[0261] The defect point distribution map generation module is used to generate a defect point distribution map corresponding to the chuck based on the defect points of the chuck.

[0262] In some embodiments, the apparatus further includes:

[0263] The record table generation module is used to generate a wafer inspection record table based on the location of abnormal points in the wafer, the location of chuck defects, and the wafer corresponding to the chuck defects.

[0264] The above-described apparatus embodiment is an embodiment corresponding to the foregoing method embodiment, and has the same technical effects as the method embodiment. A detailed description of this apparatus embodiment can be found in the detailed description of the foregoing method embodiment, and will not be repeated here.

[0265] Figure 10 This is a structural block diagram of an electronic device provided in an embodiment of this application. The electronic device includes a memory 810 and at least one processor 1020.

[0266] Among them, memory 1010 stores computer-executed instructions.

[0267] At least one processor 1020 executes computer execution instructions stored in memory 1010, causing the electronic device to implement the flatness evaluation method and / or defect identification method provided in the foregoing embodiments.

[0268] The memory 1010 and the processor 1020 are connected via a bus 1030.

[0269] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, cause the processor to implement the method provided in any embodiment of this application.

[0270] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the methods provided in any embodiment of this application.

[0271] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0272] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0273] The above are merely preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structural or procedural transformations made using the description and drawings of the present application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present application.

Claims

1. A method for evaluating flatness, characterized in that, include: Obtain the height of each measurement point on the wafer and calculate the average height in units of the exposed area; For each exposure area of ​​the wafer, the first flatness of each measurement point in the exposure area is determined based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area. Based on the first flatness of each measurement point within the exposure area and the planar coordinates of each measurement point within the exposure area, the second flatness of each measurement point within the exposure area is determined. Wherein, the planar coordinates are the coordinates of the measurement point in the plane, and the direction corresponding to the height is perpendicular to the plane; The determination of the second flatness of each measurement point within the exposure area based on the first flatness of each measurement point within the exposure area and the planar coordinates of each measurement point within the exposure area includes: Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, the first flatness is fitted to a plane to obtain a flatness plane. For each measurement point within the exposure area, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane. The method further includes: Using the horizontal and vertical coordinates of the plane coordinate system as independent variables, the first flatness is fitted with a surface to obtain a flatness surface. For each measurement point within the exposure area, the third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface. The flatness of the wafer is evaluated based on the first flatness, the second flatness, and the third flatness at each measurement point.

2. The method according to claim 1, characterized in that, The method further includes: Flatness heatmaps are plotted and stored based on the first flatness, the second flatness, and the third flatness at each measurement point of the wafer.

3. A defect point identification method, characterized in that, include: Obtain the flatness of various measurement points on multiple wafers; Based on the flatness of the measurement points, anomalies are identified from the measurement points of the wafer; Based on the abnormal points of multiple wafers corresponding to the same chuck, the defect points of the chuck are identified; The flatness of the measurement points includes first flatness, second flatness, and third flatness; obtaining the flatness of each measurement point on multiple wafers includes: For each exposure area of ​​each wafer in the plurality of wafers, the first flatness of each measurement point in the exposure area is determined based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area. Using the horizontal and vertical coordinates in the plane coordinate system as independent variables, the first flatness is subjected to plane fitting and surface fitting respectively to obtain the flatness plane and the flatness surface. The plane coordinates are the coordinates of the measurement point in the plane, and the direction corresponding to the height is perpendicular to the plane. For each measurement point within the exposure area, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane, and the third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface. Based on the flatness of the measurement points, anomalies are identified from the measurement points of the wafer, including: For each measurement point on the wafer, if any one of the first flatness, second flatness, and third flatness corresponding to the measurement point exceeds the corresponding flatness range, then the measurement point is determined to be an abnormal point.

4. The method according to claim 3, characterized in that, The multiple wafers are consecutive wafers corresponding to the same chuck; Based on anomalies of multiple wafers corresponding to the same chuck, defect points of the chuck are identified, including: Based on the location of the anomalies in the corresponding wafer, draw an anomaly distribution map corresponding to the wafer; Based on the distribution map of anomalies of multiple consecutive wafers corresponding to the same chuck, the overlapping anomalies of the multiple consecutive wafers are determined. Based on the overlapping anomalies, the defect points of the chuck are determined.

5. The method according to claim 3 or 4, characterized in that, The method further includes: Based on the defects of the chuck, generate a defect point distribution map corresponding to the chuck; and / or, A wafer inspection record table is generated based on the location of abnormal points in the wafer, the location of chuck defects, and the wafers corresponding to the chuck defects.

6. A defect point identification device, characterized in that, include: A flatness acquisition module is used to acquire the flatness of each measurement point on multiple wafers; the flatness of the measurement points includes first flatness, second flatness, and third flatness; acquiring the flatness of each measurement point on multiple wafers includes: For each exposure area of ​​each wafer in the plurality of wafers, the first flatness of each measurement point in the exposure area is determined based on the difference between the height of each measurement point in the exposure area and the average height of the corresponding exposure area. Using the horizontal and vertical coordinates in the plane coordinate system as independent variables, the first flatness is subjected to plane fitting and surface fitting respectively to obtain the flatness plane and the flatness surface. The plane coordinates are the coordinates of the measurement point in the plane, and the direction corresponding to the height is perpendicular to the plane. For each measurement point within the exposure area, the second flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness plane, and the third flatness of the measurement point is determined based on the difference between the first flatness of the measurement point and the value of the measurement point on the flatness surface. An anomaly detection module is used to determine anomalies from the measurement points of the wafer based on the flatness of the measurement points; including: For each measurement point on the wafer, if any one of the first flatness, second flatness, and third flatness corresponding to the measurement point exceeds the corresponding flatness range, then the measurement point is determined to be an abnormal point. The defect identification module is used to identify the defect points of the chuck based on the location of abnormal points on multiple wafers corresponding to the same chuck.

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