A method and device for detecting semiconductor wafer defects

Abstract

The present application provides a method and device for detecting defects in a semiconductor wafer. In the present application, after irradiating the semiconductor wafer with an infrared heating tube, the semiconductor wafer will be heated. When there are defects such as scratches, pits, and cracks on the surface of the semiconductor wafer, these defects will hinder the propagation of heat energy, causing local heat accumulation or dissipation, resulting in a temperature difference between the defective part and the defect-free part. Based on this principle, when there are defects on the surface of the semiconductor wafer, after heating the semiconductor wafer, infrared imaging is performed. Since different temperatures correspond to different pixel values in the infrared image, after obtaining the infrared image of the heated semiconductor wafer, it is possible to determine whether there are defects in the semiconductor wafer by analyzing the pixel values of the pixel points. By the above method, the accuracy of detecting surface defects of the semiconductor wafer can be improved, which is beneficial to improving the yield of the semiconductor wafer.

Description

Technical Field

[0001] This application relates to the field of semiconductor detection technologies, and more particularly, to a method and apparatus for detecting defects in semiconductor wafers. Background Art

[0002] Before a semiconductor wafer undergoes an etching process, it is necessary to detect whether there are defects (such as scratches, pits, cracks, etc.) on the semiconductor wafer. If the defect detection of the semiconductor wafer is not carried out, the yield of the semiconductor wafer will be reduced. Currently, a camera device is usually used to scan the semiconductor wafer, that is, to check by imaging. However, since the surface of the semiconductor wafer has a metallic luster and has good light reflection characteristics, it will have a certain impact on imaging, thereby affecting the detection result and causing the detection result to be inaccurate. Summary of the Invention

[0003] In view of this, embodiments of this application provide a method and apparatus for detecting defects in semiconductor wafers to improve the accuracy of semiconductor wafer defect detection.

[0004] In a first aspect, embodiments of this application provide a method for detecting defects in semiconductor wafers. The detection method is applied to an Equipment Front End Module (EFEM) device. An optical box is provided on the EFEM device, and an infrared heating tube and an infrared camera for collecting infrared images are provided inside the optical box. After the wafer cassette is placed in the stock area of the EFEM device by the overhead crane system, before the EFEM device transfers the semiconductor wafer in the wafer cassette to an etching process device through a wafer manipulator for an etching process, the detection method includes:

[0005] Controlling the wafer manipulator to transfer the semiconductor wafer to a specified position in the optical box, and controlling the infrared camera to take a picture of the semiconductor wafer to obtain a first infrared image;

[0006] Controlling the infrared heating tube to irradiate the semiconductor wafer, and after a preset time period, controlling the infrared camera to take a picture of the semiconductor wafer to obtain a second infrared image;

[0007] After aligning the first infrared image and the second infrared image, comparing the pixel points at the same positions of the first infrared image and the second infrared image, and determining a target area composed of pixel points in the second infrared image whose pixel value change amount is greater than a preset threshold;

[0008] Removing duplicates from the pixel values of the pixel points in the target area, and sorting the de-duplicated pixel values in ascending order to obtain a pixel value sequence;

[0009] Using the following formula to determine the sorting position in the pixel value sequence:

[0010] ;

[0011] Among them, N is the total number of pixel values included in the pixel value sequence, and the successive values of K are 1 and 3;

[0012] Calculate the pixel value threshold range using the following formula:

[0013] R1 = Q1 - 1.5M;

[0014] R2 = Q3 + 1.5M;

[0015] Among them, Q1 is the first pixel value corresponding to the sorted position I obtained by rounding when K1 takes the value of 1, Q3 is the second pixel value corresponding to the sorted position I obtained by rounding when K1 takes the value of 3, and M is the difference between the second pixel value and the first pixel value;

[0016] Determine whether there is a target pixel value in the pixel value sequence that does not fall within the pixel value threshold range;

[0017] If there is the target pixel value, it is determined that the semiconductor wafer has a defect.

[0018] Optionally, the method further includes:

[0019] Determine the target pixel points in the target area that are equal to the target pixel value;

[0020] Calculate the distance between any two target pixel points using the following formula:

[0021] ;

[0022] Among them, and are the horizontal and vertical coordinates of one target pixel point, and are the horizontal and vertical coordinates of another target pixel point;

[0023] After obtaining the distance between any two target pixel points, calculate the standard deviation of all distances;

[0024] When the standard deviation is greater than or equal to a preset standard deviation, control the wafer manipulator to transfer the semiconductor wafer to an etching process equipment for an etching process.

[0025] Optionally, the method further includes:

[0026] When the standard deviation is less than the preset standard deviation, control the wafer manipulator to place the semiconductor wafer into a wafer cassette to be processed.

[0027] Optionally, the method further includes:

[0028] When the number of semiconductor wafers continuously placed into the wafer cassette to be processed exceeds a preset number, an alarm signal is issued.

[0029] Optionally, before de-duplicating the pixel values of the pixel points in the target area, the method further includes:

[0030] For each column of pixels in the target area, calculate the average value of the pixel values of this column of pixels;

[0031] After obtaining the average values of the pixel values of each column of pixels, perform an average calculation on the average values of the pixel values of each column of pixels to obtain a global average value;

[0032] For each of the average values of the pixel values, calculate the difference between the average value of the pixel value and the global average value, and use the difference as a correction value;

[0033] For each pixel point in the target area, calculate the difference between the pixel value of this pixel point and the correction value to obtain a corrected image, so as to use the pixel values of the pixel points in the corrected image for de-duplication.

[0034] In a second aspect, an embodiment of the present application provides a detection device for semiconductor wafer defects. The detection device is set in an equipment front end module (EFEM) device. An optical box is provided on the EFEM device, and an infrared heating tube and an infrared camera for collecting infrared images are provided in the optical box. The detection device includes:

[0035] A first control unit, configured to, after the overhead crane system places the wafer cassette in the loading area of the EFEM device, before the EFEM device transfers the semiconductor wafers in the wafer cassette to the etching process equipment through a wafer manipulator for an etching process, control the wafer manipulator to transfer the semiconductor wafers to a specified position in the optical box, and control the infrared camera to take a picture of the semiconductor wafers to obtain a first infrared image;

[0036] A second control unit, configured to control the infrared heating tube to irradiate the semiconductor wafers, and control the infrared camera to take a picture of the semiconductor wafers after a preset time period to obtain a second infrared image;

[0037] A comparison unit, configured to, after aligning the first infrared image and the second infrared image, compare the pixel points at the same positions of the first infrared image and the second infrared image, and determine a target area composed of pixel points with a pixel value change amount greater than a preset threshold from the second infrared image;

[0038] A sorting unit, configured to remove duplicates from the pixel values of the pixel points in the target area, and sort the de-duplicated pixel values in ascending order to obtain a pixel value sequence;

[0039] A first calculation unit, configured to determine the sorting position in the pixel value sequence by using the following formula:

[0040] ;

[0041] where N is the total number of pixel values included in the pixel value sequence, and K takes values of 1 and 3 in sequence;

[0042] A second calculation unit, configured to calculate the pixel value threshold range by using the following formula:

[0043] R1 = Q1 - 1.5M;

[0044] R2 = Q3 + 1.5M;

[0045] where Q1 is the first pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 1, Q3 is the second pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 3, and M is the difference between the second pixel value and the first pixel value;

[0046] A judgment unit, configured to judge whether there is a target pixel value in the pixel value sequence that does not fall within the pixel value threshold range; if there is the target pixel value, it is determined that the semiconductor wafer has a defect.

[0047] Optionally, the detection device further includes:

[0048] A determination unit, configured to determine the target pixel points in the target area that are equal to the target pixel value;

[0049] A third calculation unit, configured to calculate the distance between any two target pixel points by using the following formula:

[0050] ;

[0051] where, and are the horizontal and vertical coordinates of one target pixel point, and are the horizontal and vertical coordinates of another target pixel point;

[0052] A fourth calculation unit, configured to calculate the standard deviation of all distances after obtaining the distance between any two target pixel points;

[0053] A third control unit, configured to control the wafer manipulator to transfer the semiconductor wafer to an etching process device for an etching process when the standard deviation is greater than or equal to a preset standard deviation.

[0054] Optionally, the third control unit is further configured to:

[0055] When the standard deviation is less than the preset standard deviation, control the wafer manipulator to place the semiconductor wafer into a wafer cassette to be processed.

[0056] Optionally, the detection device further includes:

[0057] An alarm unit, configured to send an alarm signal when the number of semiconductor wafers continuously placed into the wafer cassette to be processed exceeds a preset number.

[0058] Optionally, the sorting unit is further configured to:

[0059] Before removing duplicates from the pixel values of the pixel points in the target area, calculate the mean pixel value of each column of pixels in the target area for each column of pixels in the target area;

[0060] After obtaining the mean pixel values of each column of pixels, perform an average calculation on the mean pixel values of each column of pixels to obtain a global mean value;

[0061] For each of the mean pixel values, calculate the difference between the mean pixel value and the global mean value, and use the difference as a correction value;

[0062] For each pixel point in the target area, calculate the difference between the pixel value of the pixel point and the correction value to obtain a corrected image, so as to use the pixel values of the pixel points in the corrected image to remove duplicates.

[0063] The technical solutions provided by the embodiments of the present application may include the following beneficial effects:

[0064] In the present application, after irradiating a semiconductor wafer with an infrared heating tube, the semiconductor wafer will be heated. When there are defects such as scratches, pits, and cracks on the surface of the semiconductor wafer, these defects will hinder the propagation of heat energy, resulting in local heat accumulation or dissipation, thereby causing a temperature difference between the defective part and the defect-free part. Based on this principle, when there are defects on the surface of the semiconductor wafer, after heating the semiconductor wafer, infrared imaging is performed. Since different temperatures correspond to different pixel values in the infrared image, after obtaining the infrared image of the heated semiconductor wafer, it is possible to analyze whether there are defects in the semiconductor wafer by analyzing the pixel values of the pixel points. By the above method, the accuracy of detecting surface defects of the semiconductor wafer can be improved, which is beneficial to improving the yield of the semiconductor wafer.

[0065] To make the above objects, features, and advantages of the present application more obvious and understandable, the following provides preferred embodiments in conjunction with the accompanying drawings and describes them in detail as follows. Description of the Drawings

[0066] To more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0067] Figure 1 Flow diagram of a method for detecting semiconductor wafer defects provided by an embodiment of the present application;

[0068] Figure 2 Flow diagram of another method for detecting semiconductor wafer defects provided by an embodiment of the present application;

[0069] Figure 3 Flow diagram of another method for detecting semiconductor wafer defects provided by an embodiment of the present application;

[0070] Figure 4 Structural diagram of a device for detecting semiconductor wafer defects provided by an embodiment of the present application. Detailed Embodiments

[0071] To make the objects, technical solutions, and advantages of the embodiments of the present application clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of them. Usually, the components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0072] Figure 1The figure is a schematic flow chart of a method for detecting semiconductor wafer defects provided by an embodiment of the present application. The detection method is applied to an EFEM (Equipment Front-End Module) device. An opaque chamber is provided on the EFEM device, and an infrared heating tube and an infrared camera for collecting infrared images are provided inside the opaque chamber. After the overhead crane system places the wafer cassette on the stocker area of the EFEM device, before the EFEM device transfers the semiconductor wafer in the wafer cassette to the etching process equipment through a wafer manipulator, as Figure 1 shown, the detection method includes the following steps:

[0073] Step 101: Control the wafer manipulator to transfer the semiconductor wafer to a specified position in the opaque chamber, and control the infrared camera to take a picture of the semiconductor wafer to obtain a first infrared image.

[0074] Step 102: Control the infrared heating tube to irradiate the semiconductor wafer, and after a preset time period, control the infrared camera to take a picture of the semiconductor wafer to obtain a second infrared image.

[0075] Step 103: After aligning the first infrared image and the second infrared image, compare the pixel points at the same positions of the first infrared image and the second infrared image, and determine a target area composed of pixel points with a pixel value change amount greater than a preset threshold from the second infrared image.

[0076] Step 104: Remove duplicates from the pixel values of the pixel points in the target area, and sort the de-duplicated pixel values in ascending order to obtain a pixel value sequence.

[0077] Step 105: Use the following formula (1) to determine the sorting position in the pixel value sequence:

[0078] ; (Formula 1)

[0079] where N is the total number of pixel values included in the pixel value sequence, and K takes values of 1 and 3 in sequence.

[0080] Step 106: Use the following formula (2) to calculate the pixel value threshold range:

[0081] R1 = Q1 - 1.5M;

[0082] R2 = Q3 + 1.5M; (Formula 2)

[0083] Among them, when K1 takes the value of 1, Q1 is the first pixel value corresponding to the sorting position I obtained by rounding; when K1 takes the value of 3, Q3 is the second pixel value corresponding to the sorting position I obtained by rounding, and M is the difference between the second pixel value and the first pixel value.

[0084] Step 107: Determine whether there is a target pixel value in the pixel value sequence that does not fall within the pixel value threshold range; if there is such a target pixel value, it is determined that the semiconductor wafer has a defect.

[0085] Specifically, in order to avoid the adverse impact of the non-semiconductor wafer area in the infrared image on the detection result, when detecting the defect of the semiconductor wafer using the infrared image, it is necessary to remove as much as possible the part of the non-semiconductor wafer area in the infrared image. To achieve the above purpose, first, take the first infrared image before heating the semiconductor wafer, then control the infrared heating tube to work and irradiate the semiconductor wafer to heat it. After heating for a preset duration, stop irradiating the semiconductor wafer. Since the infrared heating tube also heats the surrounding environment during the heating process of the semiconductor wafer, and because the heat dissipation speed of the surrounding environment is higher than that of the semiconductor wafer, it is possible to wait for a preset duration and then take a picture of the semiconductor wafer to obtain the second infrared image. Since there is a large temperature difference between the surrounding environment and the semiconductor wafer after the preset duration, the second infrared image can show which area is the area where the semiconductor wafer is located and which areas are non-semiconductor wafer areas. In order to be able to distinguish the area where the semiconductor wafer is located through the infrared image, the first infrared image and the second infrared image can be aligned, and the pixel points at the same position of the first infrared image and the second infrared image can be compared. The pixel values of the pixel points in the area where the semiconductor wafer is located in the second infrared image change more relative to the pixel points in the non-semiconductor wafer area. Therefore, the target area, that is, the area where the semiconductor wafer is located, can be determined by setting a threshold.

[0086] After determining the target area (i.e., the area where the semiconductor wafer is located in the second infrared image), the pixel values of the pixel points in the target area are de-duplicated. For example, if there are 5 pixel points in the target area and the pixel values are 10, 20, 30, 30, 40 respectively, then the de-duplicated data set is 10, 20, 30, 40. Then, the de-duplicated pixel values are sorted in ascending order to obtain a pixel value sequence. Then, using Formula 1, the sorting positions are determined and the pixel values corresponding to these positions are obtained. Suppose the pixel value sequence is: 1, 2, 3, 4, 5, 6, 7, 8, 9, 100, and the sorting positions obtained using Formula 1 include: 2.75 and 8.25. Then, the sorting positions obtained by rounding are 3 and 8, and the pixel values corresponding to these sorting positions are 3 and 8 respectively. At this time, Q1 can be determined as 3, Q2 as 8, and M as 5. Therefore, R1 can be obtained as -4.5 and R2 as 15.5. Therefore, the pixel value threshold range calculated using Formula 2 is (-4.5, 15.5). Then, this pixel value threshold range is used to screen the pixel value sequence to determine which pixel values in the pixel value sequence are not within this range. Only 100 in the above pixel value sequence is not within this range. If there are such pixel values, then it is determined that the semiconductor wafer has defects.

[0087] It should be noted that having defects does not mean that the semiconductor wafer is completely unusable.

[0088] In a feasible implementation Figure 2 is a schematic flowchart of another method for detecting semiconductor wafer defects provided by an embodiment of the present application. After determining that the semiconductor wafer has defects, in order to determine whether the defects affect the yield, as Figure 2 shown, the method further includes the following steps:

[0089] Step 201, determine the target pixel points in the target area that are equal to the target pixel value.

[0090] Step 202, calculate the distance between any two target pixel points using the following Formula 3:

[0091] ;

[0092] where and are the horizontal and vertical coordinates of one target pixel point, and are the horizontal and vertical coordinates of another target pixel point.

[0093] Step 203, after obtaining the distance between any two target pixel points, calculate the standard deviation of all distances.

[0094] Step 204: When the standard deviation is greater than or equal to the preset standard deviation, control the wafer manipulator to transfer the semiconductor wafer to the etching process equipment for the etching process.

[0095] Specifically, after determining the target pixel values that do not fall within the pixel value threshold range, it can be determined that the target pixel points are the pixel points corresponding to the defective areas. Therefore, the target pixel points where the target pixel values are located can be found in the target area, and the distance between any two target pixel points can be calculated using Formula 3. Using all the obtained distances, the standard deviation can be calculated. Since the standard deviation can reflect the dispersion of these target pixel points, the larger the standard deviation, the more dispersed these target pixel points are, that is, the smaller the defect problem of the semiconductor wafer. The smaller the standard deviation, the more concentrated these target pixel points are, which will lead to a larger defect problem of the semiconductor wafer. Therefore, when the standard deviation is greater than or equal to the preset standard deviation, it indicates that the defect problem of the semiconductor wafer is smaller. Therefore, the wafer manipulator can be controlled to transfer the semiconductor wafer to the etching process equipment for the etching process.

[0096] In a feasible implementation, when the standard deviation is less than the preset standard deviation, control the wafer manipulator to place the semiconductor wafer into the wafer cassette to be processed.

[0097] In a feasible implementation, when the number of semiconductor wafers continuously placed into the wafer cassette to be processed exceeds the preset number, an alarm signal is issued.

[0098] Specifically, when multiple semiconductor wafers are continuously placed into the wafer cassette to be processed, it indicates that there may be a batch problem at this time. Therefore, an alarm message can be issued to remind the staff to check and avoid batch events.

[0099] In a feasible implementation, Figure 3 is a schematic flowchart of another method for detecting semiconductor wafer defects provided by the embodiment of the present application. Before de-duplicating the pixel values of the pixel points in the target area, as Figure 3 shown, the following steps are further included:

[0100] Step 301: For each column of pixels in the target area, calculate the mean pixel value of this column of pixels.

[0101] Step 302: After obtaining the mean pixel values of each column of pixels, perform an average calculation on the mean pixel values of each column of pixels to obtain the global mean.

[0102] Step 303: For each of the mean pixel values, calculate the difference between the mean pixel value and the global mean, and use the difference as the correction value.

[0103] Step 304: For each pixel point in the target area, calculate the difference between the pixel value of this pixel point and the correction value to obtain a corrected image, so as to use the pixel values of the pixel points in the corrected image for duplicate removal.

[0104] Specifically, the output responses of the detector units on the infrared focal plane array in the infrared camera are not completely consistent, which will cause fixed stripe pattern noise in the obtained infrared image. This stripe pattern usually shows light and dark alternation in the column direction. Therefore, through Figure 3 the method shown can eliminate this column-direction brightness deviation, thereby removing stripe noise, and providing accurate data for subsequent duplicate removal.

[0105] Figure 4 The figure is a schematic structural diagram of a detection device for semiconductor wafer defects provided by an embodiment of the present application. The detection device is set in an equipment front-end module EFEM device. An opaque box is provided on the EFEM device, and an infrared heating tube and an infrared camera for collecting infrared images are provided in the opaque box. As Figure 4 shown, the detection device includes:

[0106] A first control unit 41, configured to, after the overhead crane system places the wafer cassette in the stock area of the EFEM device, before the EFEM device transfers the semiconductor wafer in the wafer cassette to the etching process equipment for etching through the wafer manipulator, control the wafer manipulator to transfer the semiconductor wafer to a specified position in the opaque box, and control the infrared camera to take a picture of the semiconductor wafer to obtain a first infrared image;

[0107] A second control unit 42, configured to control the infrared heating tube to irradiate the semiconductor wafer, and control the infrared camera to take a picture of the semiconductor wafer after a preset time period to obtain a second infrared image;

[0108] A comparison unit 43, configured to, after aligning the first infrared image and the second infrared image, compare the pixel points at the same positions of the first infrared image and the second infrared image, and determine a target area composed of pixel points with a pixel value change amount greater than a preset threshold from the second infrared image;

[0109] A sorting unit 44, configured to remove duplicates from the pixel values of the pixel points in the target area, and sort the de-duplicated pixel values in ascending order to obtain a pixel value sequence;

[0110] A first calculation unit 45, configured to use the following formula to determine the sorting position in the pixel value sequence:

[0111] ;

[0112] Wherein, N is the total number of pixel values included in the pixel value sequence, and the successive values of K are 1 and 3;

[0113] A second calculation unit 46 is configured to calculate a pixel value threshold range by using the following formula:

[0114] R1 = Q1 - 1.5M;

[0115] R2 = Q3 + 1.5M;

[0116] Wherein, Q1 is the first pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 1, Q3 is the second pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 3, and M is the difference between the second pixel value and the first pixel value;

[0117] A judgment unit 47 is configured to judge whether there is a target pixel value in the pixel value sequence that does not fall within the pixel value threshold range; if there is the target pixel value, it is determined that the semiconductor wafer has a defect.

[0118] In a feasible implementation, the detection device further includes:

[0119] A determination unit is configured to determine a target pixel point in the target area that is equal to the target pixel value;

[0120] A third calculation unit is configured to calculate the distance between any two target pixel points by using the following formula:

[0121] ;

[0122] Wherein, and are the horizontal and vertical coordinates of a target pixel point, and are the horizontal and vertical coordinates of another target pixel point;

[0123] A fourth calculation unit is configured to calculate the standard deviation of all distances after obtaining the distance between any two target pixel points;

[0124] A third control unit is configured to, when the standard deviation is greater than or equal to a preset standard deviation, control the wafer manipulator to transfer the semiconductor wafer to an etching process device for an etching process.

[0125] In a feasible implementation, the third control unit is further configured to:

[0126] When the standard deviation is less than the preset standard deviation, control the wafer manipulator to place the semiconductor wafer into a wafer cassette to be processed.

[0127] In a feasible implementation, the detection device further includes:

[0128] An alarm unit configured to issue an alarm signal when the number of semiconductor wafers continuously placed into the wafer cassette to be processed exceeds a preset number.

[0129] In a feasible implementation, the sorting unit is further configured to:

[0130] Before de-duplicating the pixel values of the pixel points in the target area, calculate the average pixel value of each column of pixels in the target area for each column of pixels in the target area;

[0131] After obtaining the average pixel values of each column of pixels, perform an average calculation on the average pixel values of each column of pixels to obtain a global average value;

[0132] For each of the average pixel values, calculate the difference between the average pixel value and the global average value, and use the difference as a correction value;

[0133] For each pixel point in the target area, calculate the difference between the pixel value of the pixel point and the correction value to obtain a corrected image, so as to use the pixel values of the pixel points in the corrected image for de-duplication.

[0134] Regarding Figure 4 The principle of the relevant content can be referred to Figures 1 - 3 The relevant explanations of the shown content will not be elaborated in detail here.

[0135] In the embodiments provided in the present application, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

[0136] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0137] In addition, each functional unit in the embodiments provided in this application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

[0138] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0139] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0140] Finally, it should be noted that the above-mentioned embodiments are only specific implementation manners of this application, used to illustrate the technical solutions of this application, rather than limiting it. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed in this application can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes, or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for detecting semiconductor wafer defects, characterized in that, The detection method is applied to the equipment front-end module EFEM device. An opaque box is provided on the EFEM device. An infrared heating tube and an infrared camera for collecting infrared images are provided inside the opaque box. After the overhead crane system places the wafer cassette in the stock area of the EFEM device, before the EFEM device transfers the semiconductor wafer in the wafer cassette to the etching process equipment through the wafer manipulator for the etching process, the detection method includes: Controlling the wafer manipulator to transfer the semiconductor wafer to a specified position in the opaque box, and controlling the infrared camera to take a picture of the semiconductor wafer to obtain a first infrared image; Controlling the infrared heating tube to irradiate the semiconductor wafer so as to heat the semiconductor wafer, stopping the heating, and after a preset time period, controlling the infrared camera to take a picture of the semiconductor wafer to obtain a second infrared image; After aligning the first infrared image and the second infrared image, comparing the pixel points at the same positions of the first infrared image and the second infrared image, and determining a target area composed of pixel points in the second infrared image whose pixel value change amount is greater than a preset threshold; Removing duplicates from the pixel values of the pixel points in the target area, and sorting the de-duplicated pixel values in ascending order to obtain a pixel value sequence; Using the following formula to determine the sorting position in the pixel value sequence: ； where N is the total number of pixel values included in the pixel value sequence, and the successive values of K are 1 and 3; Using the following formula to calculate the pixel value threshold range: R1 = Q1 - 1.5M; R2 = Q3 + 1.5M; where Q1 is the first pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 1, Q3 is the second pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 3, and M is the difference between the second pixel value and the first pixel value; Judging whether there is a target pixel value in the pixel value sequence that does not fall within the pixel value threshold range; If there is the target pixel value, it is determined that the semiconductor wafer has a defect.

2. The detection method according to claim 1, wherein The method further includes: Determining the target pixel points in the target area that are equal to the target pixel value; Using the following formula to calculate the distance between any two target pixel points: ； Among them, and are the horizontal and vertical coordinates of a target pixel point, and are the horizontal and vertical coordinates of another target pixel point; After obtaining the distance between any two target pixel points, calculating the standard deviation of all distances; When the standard deviation is greater than or equal to a preset standard deviation, controlling the wafer manipulator to transfer the semiconductor wafer to the etching process equipment for the etching process.

3. The detection method according to claim 2, wherein The method further includes: When the standard deviation is less than the preset standard deviation, controlling the wafer manipulator to place the semiconductor wafer into the wafer cassette to be processed.

4. The detection method according to claim 3, wherein The method further includes: When the number of semiconductor wafers continuously placed in the wafer cassette to be processed exceeds a preset number, an alarm signal is issued.

5. The detection method according to claim 1, characterized in that, Before removing duplicates from the pixel values of the pixel points in the target area, the method further includes: For each column of pixels in the target area, calculating the average pixel value of the column of pixels; After obtaining the average pixel values of each column of pixels, calculate the average of the average pixel values of each column of pixels to obtain the global average value; For each of the average pixel values, calculate the difference between the average pixel value and the global average value, and use the difference as the correction value; For each pixel point in the target area, calculate the difference between the pixel value of the pixel point and the correction value to obtain a corrected image, so as to use the pixel values of the pixel points in the corrected image for duplicate removal.

6. A detection device for semiconductor wafer defects, characterized in that, The detection device is set in the equipment front end module EFEM equipment. There is a dark box on the EFEM equipment. An infrared heating tube and an infrared camera for collecting infrared images are arranged in the dark box. The detection device includes: A first control unit, configured to, after the overhead crane system places the wafer cassette in the stock area of the EFEM equipment, before the EFEM equipment transfers the semiconductor wafer in the wafer cassette to the etching process equipment for etching by the wafer manipulator, control the wafer manipulator to transfer the semiconductor wafer to a specified position in the dark box, and control the infrared camera to take a picture of the semiconductor wafer to obtain a first infrared image; A second control unit, configured to control the infrared heating tube to irradiate the semiconductor wafer to heat the semiconductor wafer, stop heating and control the infrared camera to take a picture of the semiconductor wafer after a preset time period to obtain a second infrared image; A comparison unit, configured to, after aligning the first infrared image and the second infrared image, compare the pixel points at the same positions of the first infrared image and the second infrared image, and determine a target area composed of pixel points with a pixel value change amount greater than a preset threshold from the second infrared image; A sorting unit, configured to remove duplicates from the pixel values of the pixel points in the target area, and sort the de-duplicated pixel values in ascending order to obtain a pixel value sequence; A first calculation unit, configured to determine the sorting position in the pixel value sequence by using the following formula: ； where N is the total number of pixel values included in the pixel value sequence, and K takes values of 1 and 3 in sequence; A second calculation unit, configured to calculate the pixel value threshold range by using the following formula: R1 = Q1 - 1.5M; R2 = Q3 + 1.5M; where Q1 is the first pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 1, Q3 is the second pixel value corresponding to the sorting position I obtained by rounding when K1 takes the value of 3, and M is the difference between the second pixel value and the first pixel value; A judgment unit, configured to judge whether there is a target pixel value in the pixel value sequence that does not fall within the pixel value threshold range; if there is the target pixel value, it is determined that the semiconductor wafer has a defect.

7. The detection device according to claim 6, characterized in that, The detection device further includes: A determination unit, configured to determine the target pixel points in the target area that are equal to the target pixel value; A third calculation unit, configured to calculate the distance between any two target pixel points by using the following formula: ； Among them, and are the horizontal and vertical coordinates of a target pixel point, and are the horizontal and vertical coordinates of another target pixel point; A fourth calculation unit, configured to calculate the standard deviation of all distances after obtaining the distance between any two target pixel points; A third control unit, configured to control the wafer manipulator to transfer the semiconductor wafer to an etching process device for an etching process when the standard deviation is greater than or equal to a preset standard deviation.

8. The detection device according to claim 7, wherein, The third control unit is further configured to: When the standard deviation is less than the preset standard deviation, control the wafer manipulator to place the semiconductor wafer into a wafer cassette to be processed.

9. The detection device according to claim 8, characterized in that The detection device further includes: An alarm unit, configured to send an alarm signal when the number of semiconductor wafers continuously placed into the wafer cassette to be processed exceeds a preset number.

10. The detection device according to claim 6, wherein The sorting unit is further configured to: Before removing duplicates from the pixel values of the pixel points in the target area, calculate the average pixel value of each column of pixels in the target area for each column of pixels in the target area; After obtaining the average pixel values of each column of pixels, perform an average calculation on the average pixel values of each column of pixels to obtain a global average value; For each of the average pixel values, calculate the difference between the average pixel value and the global average value, and use the difference as a correction value; For each pixel point in the target area, calculate the difference between the pixel value of the pixel point and the correction value to obtain a corrected image, so as to use the pixel values of the pixel points in the corrected image to remove duplicates.

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