Defect detection device, defect detection method, and program

Abstract

To detect a defect in an edge area of a wafer with high sensitivity.SOLUTION: A defect detection device 50 comprises: a data input I / F 51 that acquires parameters used for detection of a defect; an image input I / F 52 that acquires a photographed image of a wafer; and a control unit 53 that analyzes the photographed image on the basis of the parameters to detect a defect in the wafer. The parameters include a threshold for detecting a projecting defect and a defect determination level. The control unit 53 cuts out a rectangular area including an edge ring image indicating an edge of the wafer as a ROI image, on the basis of the threshold for detecting a projecting defect, binarizes an area of the ROI image having a higher luminance value to be a first value and an area having a lower luminance value to be a second value, thereby creating a binarized image, acquires the image coordinates on an inner periphery of the area displayed with the first value in the binarized image as the inner periphery coordinates, calculates the level of change in irregularities in a circumferential direction of the inner periphery coordinates as a coordinate differential value, and compares the coordinate differential value with the defect determination level to detect a defect.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a defect detection device, a defect detection method, and a program. [Background technology]

[0002] Wafers made of semiconductors such as silicon wafers are widely used as substrates in the manufacturing process of semiconductor devices. Known examples of such wafers include polished wafers (PW wafers) that are obtained by slicing a single crystal ingot and polishing it to a mirror finish, and epitaxial wafers in which an epitaxial layer is formed on the surface of a PW wafer. For example, epitaxial wafers are used as device substrates for various semiconductor devices such as MOSFETs (Metal-Oxide-Semiconductor Field-Effect Transistors), DRAMs (Dynamic Random Access Memory), power transistors, and back-illuminated solid-state imaging devices.

[0003] In order to improve the yield and reliability in the manufacturing process of semiconductor devices, defect inspection technology for the front and back surfaces of wafers, which are the substrates for semiconductor devices, is becoming increasingly important. Defects that exist on the front and back surfaces of wafers are diverse, including crystal defects such as pits and COPs (Crystal Originated Particles), polishing irregularities caused by processing, scratches, and the adhesion of foreign particles.

[0004] Conventionally, wafer inspection is performed by scanning the front and back surfaces of a wafer after a final mirror polishing with a laser beam using an LPD (Light Point Defect) inspection device (laser surface inspection machine) to detect scattered light caused by particles and scratches on the surface. In addition, to determine the presence or absence of defects that are difficult to detect with an LPD inspection device, a visual inspection is also used to determine the presence or absence of defects on the front and back surfaces of a wafer. Since visual inspection is a sensory inspection, variations in judgments by inspectors are unavoidable, and it takes time for inspectors to become accustomed to the inspection, so there is a demand for the establishment of objective and automatic inspection methods.

[0005] Therefore, the present applicants have proposed an automatic wafer inspection method for appropriately evaluating wafers without relying on visual inspection in Patent Document 1 for defects on the back side of PW wafers, in Patent Document 2 for defects on the front side of epitaxial wafers, and in Patent Document 3 for defects on the back side of epitaxial wafers. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2010-103275 A [Patent Document 2] JP 2017-062157 A [Patent Document 3] JP 2017-072403 A Summary of the Invention [Problem to be solved by the invention]

[0007] In conventional appearance inspection and automatic inspection, it is difficult to detect defects in the boundary (edge ​​region) between the chamfer and the front and back surfaces of the wafer due to halation of the chamfer. Therefore, especially in automatic inspection, a peripheral region of about 1 mm from the edge of the wafer is set as a defect detection exclusion region. However, in recent years, problems have arisen such as dust generation due to resist residue caused by the angularity of the edge region and focus shift (defocus) of the interface of the front surface during exposure caused by deterioration of the flatness of the edge region. Since it is required that there are no defects even in the defect detection exclusion region, inspection of the edge region is necessary. In addition, depending on the product, polishing may be performed further inside the chamfer, and in such products, it is desired to detect defects in the polished region.

[0008] The present invention has been made in consideration of the above problems, and has an object to detect defects in the edge region of a wafer with high sensitivity. [Means for solving the problem]

[0009] The gist of the present invention for solving the above problems is as follows.

[0010] (1) A defect detection device comprising: a data input I / F for acquiring parameters used for defect detection; an image input I / F for acquiring a photographed image of a wafer; and a control unit for analyzing the photographed image based on the parameters and detecting defects in the wafer, wherein the parameters include a threshold for detecting protrusion defects and a defect judgment level, wherein the control unit cuts out a rectangular region including an edge ring image showing an edge of the wafer as an ROI image from the photographed image, binarizes a higher brightness value of the ROI image into a first value and a lower brightness value into a second value based on the threshold for detecting protrusion defects to generate a binary image, acquires image coordinates of an inner circumference of the region displayed by the first value in the binary image as inner circumference coordinates, calculates a change level of unevenness in the circumferential direction of the inner circumference coordinates as a coordinate differential value, and detects defects by comparing the coordinate differential value with the defect judgment level.

[0011] (2) The defect detection device according to (1), wherein the parameters include a grouping size, and the control unit detects the defects that exist within a range defined by the grouping size as a single defect.

[0012] (3) A defect detection device comprising: a data input I / F for acquiring parameters used for defect detection; an image input I / F for acquiring a photographed image of a wafer; and a control unit for analyzing the photographed image based on the parameters and detecting defects in the wafer, wherein the parameters include a double ring determination threshold and a threshold for detecting isolated defects; the control unit cuts out a rectangular area including an edge ring image showing an edge of the wafer from the photographed image as an ROI image, detects as a double ring image an image that appears inside the edge ring image and is composed of pixels whose brightness values ​​are equal to or greater than the double ring determination threshold, and detects as defects blobs of pixels whose brightness values ​​are equal to or greater than the threshold for detecting isolated defects within the area sandwiched between the edge ring image and the double ring image.

[0013] (4) The defect detection device described in (3), wherein the parameters include a mask enlargement size, and the control unit enlarges the width between the outer and inner circumferences of the edge ring image based on the mask enlargement size, and detects as the defect a blob of pixels whose brightness value is greater than or equal to the isolated defect detection threshold within the area sandwiched between the enlarged edge ring image and the double ring image.

[0014] (5) A defect detection device described in (3) or (4), wherein the parameters include a double ring removal size, and the control unit does not detect the defect if the number of pixels in the longitudinal direction of the blob is greater than or equal to the double ring removal size.

[0015] (6) A defect detection device described in any of (1) to (5), wherein the parameters include an invalid range start position and an invalid range end position, and the control unit does not detect the defect in an area of ​​the edge area of ​​the wafer that is defined by the invalid range start position and the invalid range end position.

[0016] (7) A defect detection method comprising the steps of: acquiring parameters used for defect detection; acquiring a photographed image of the wafer; and analyzing the photographed image based on the parameters to detect defects in the wafer, wherein the parameters include a protrusion defect detection threshold and a defect judgment level, and the control step comprises the steps of: extracting a rectangular region including an edge ring image showing an edge of the wafer from the photographed image as an ROI image; binarizing a higher brightness value of the ROI image into a first value and a lower brightness value into a second value based on the protrusion defect detection threshold to generate a binary image; acquiring image coordinates of an inner circumference of the region displayed by the first value in the binary image as inner circumference coordinates; calculating a change level of unevenness in the circumferential direction of the inner circumference coordinates as a coordinate differential value; and detecting a protrusion defect by comparing the coordinate differential value with the defect judgment level.

[0017] (8) A defect detection method comprising the steps of: acquiring parameters used for defect detection; acquiring a photographed image of a wafer; and analyzing the photographed image based on the parameters to detect defects in the wafer, wherein the parameters include a double ring determination threshold and an isolated defect detection threshold; and the control step comprises the steps of: extracting a rectangular region including an edge ring image indicating an edge of the wafer from the photographed image as an ROI image; detecting an image that appears inside the edge ring image and is composed of pixels whose brightness values ​​are equal to or greater than the double ring determination threshold as a double ring image; and detecting, within the region sandwiched between the edge ring image and the double ring image, a blob of pixels whose brightness values ​​are equal to or greater than the isolated defect detection threshold as a defect.

[0018] (9) A program for causing a computer to function as the defect detection device according to any one of (1) to (6). Effect of the Invention

[0019] According to the present invention, defects in edge regions can be detected with high sensitivity. [Brief description of the drawings]

[0020] [Figure 1] 1 is a diagram showing a configuration of a wafer inspection apparatus according to an embodiment; [Diagram 2] 1 is a block diagram showing a configuration of a defect detection device according to an embodiment; [Diagram 3] FIG. 4 is a diagram illustrating defect detection parameters according to an embodiment. [Figure 4] 3 is a diagram showing an area in which a defect detection device according to an embodiment detects defects; [Diagram 5] 5 is a flowchart showing a detection process for protrusion defects by the defect detection device according to the embodiment. [Figure 6] 1A to 1C are diagrams illustrating an ROI image extraction process in the defect detection device according to an embodiment. [Figure 7] FIG. 1 is a diagram showing an example of a protrusion defect and an isolated defect; [Figure 8] 5A to 5C are diagrams illustrating a binarization process and an inner circumference coordinate acquisition process in the defect detection device according to the embodiment. [Figure 9] 5 is a flowchart showing a detection process for an isolated defect in the defect detection device according to the embodiment. [Figure 10] 5A to 5C are diagrams illustrating a detection process of a first mask region in the defect detection device according to the embodiment. [Figure 11] FIG. 13 is a diagram showing an example of a double ring image. [Figure 12] 5A to 5C are diagrams illustrating a detection process of a second mask region in the defect detection device according to the embodiment. [Figure 13] FIG. 4 is a diagram showing an invalid range of defect detection in the defect detection device according to the embodiment;

[0021] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0022] <Wafer inspection equipment> A wafer inspection apparatus according to an embodiment of the present invention is shown in Fig. 1. The wafer inspection apparatus 100 shown in Fig. 1 includes an optical system 30, a scanning unit 40, and a defect detection apparatus 50. The wafer inspection apparatus 100 is an apparatus that inspects the appearance of a wafer surface, including the front surface or back surface of the wafer.

[0023] The wafer W is a silicon wafer or the like, and may be a polished wafer, an epitaxial wafer in which an epitaxial layer is formed on the front surface of a polished wafer, or a wafer in which a thin film such as a CVD (Chemical Vapor Deposition) film is formed on the back surface of an epitaxial wafer. The type of thin film may be, for example, an oxide film such as a silicon oxide film, or a nitride film such as a silicon nitride film.

[0024] The scanning unit 40 scans the optical system 30 parallel to the surface of the wafer W. The scanning unit 40 may scan the optical system 30 in the circumferential direction, or vertically and horizontally. The wafer inspection apparatus 100 may have a plurality of optical systems 30 (e.g., three), and the scanning unit 40 may scan each optical system 30 in the circumferential direction. The scanning unit 40 may be composed of an arm connected to the optical system 30, and a drive stepping motor, servo motor, etc. for driving the arm.

[0025] The optical system 30 has a ring fiber illumination 10 and an imaging unit 20. The optical system 30 is installed perpendicular to the front or back surface of the wafer W, and irradiates the front or back surface of the wafer W with the ring fiber illumination 10, and the scattered light is received by the imaging unit 20. Fig. 1 shows how the back surface of the wafer W is irradiated with the optical system 30.

[0026] The ring fiber illuminator 10 illuminates the wafer W. A typical ring fiber illuminator can be used as the ring fiber illuminator 10, and the illuminance of the illumination light L is, for example, about 100,000 to 1,000,000 lux. The angle that the illumination light L makes with respect to the wafer W is a typical one, for example, about 10 to 30 degrees.

[0027] The configuration of the photographing unit 20 is not particularly limited as long as it can receive and photograph the scattered light from the wafer W. For example, as shown in Fig. 1, the photographing unit 20 includes a lens barrel 22, a lens 23, and a light receiving unit 24. Each of the lens barrel 22, the lens 23, and the light receiving unit 24 can be a commonly used lens. For example, a telecentric lens can be used as the lens 23, and for example, a CCD camera can be used as the light receiving unit 24.

[0028] The photographing unit 20 photographs the wafer surface divided into a plurality of regions along the circumferential direction of the wafer W. The image photographed of each region is also called a shot image (part image). The photographing unit 20 may obtain the shot images by rotating a stage on which the wafer W is placed and photographing the rotating wafer W. The photographing unit 20 associates information specifying the relationship between the shot image and the position on the wafer surface where the shot image was photographed with the shot image, and outputs the information to the defect detection device 50.

[0029] <Defect detection equipment> Next, a configuration example of a defect detection device 50 will be described with reference to Fig. 2. The defect detection device 50 shown in Fig. 2 includes a data input I / F (interface) 51, an image input I / F 52, a control unit 53, a storage unit 54, and a data output I / F 55. The defect detection device 50 may further include a communication I / F such as a LAN (Local Area Network) I / F to enable communication with an external device.

[0030] The data input I / F 51 is an interface between the defect detection device 50 and an input device, and the defect detection device 50 is connected to the input device via the data input I / F 51. The input device is a keyboard, a mouse, a pointing device, or the like. The data input I / F 51 acquires parameters (defect detection parameters) used for defect detection from the input device, and outputs them to the storage unit 54. The defect detection parameters may be set by a user using the input device.

[0031] An example of the defect detection parameters is shown in Fig. 3. The defect detection parameters are used in the processing of the control unit 53. Therefore, the defect detection parameters shown in Fig. 3 will also be mentioned in the explanation of the control unit 53 described later. Furthermore, in this specification, the names of the defect detection parameters will be enclosed in "".

[0032] The image input I / F 52 is an interface between the defect detection device 50 and the photographing unit 20, and the defect detection device 50 is connected to the photographing unit 20 via the image input I / F 52. The image input I / F 52 acquires a photographed image of the wafer W photographed by the photographing unit 20. The image input I / F 52 outputs the photographed image to the storage unit 54. If the photographed image is analog data, the image input I / F 52 converts it into digital data. In this embodiment, the photographed image output by the image input I / F 52 is an 8-bit digital image.

[0033] The storage unit 54 includes one or more memories, and may include, for example, a semiconductor memory, a magnetic memory, an optical memory, etc. Each memory included in the storage unit 54 may function, for example, as a main memory device, an auxiliary memory device, or a cache memory. The storage unit 54 stores any information used in the operation of the defect detection apparatus 50. A part of the storage unit 54 may be provided outside the defect detection apparatus 50.

[0034] The data output I / F 55 outputs the analysis results by the control unit 53 to a display device such as a display.

[0035] The control unit 53 analyzes the captured image based on the defect detection parameters and detects defects. The control unit 53 may be configured with dedicated hardware such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array), or may be configured with a processor, or may be configured to include both.

[0036] FIG. 4 is a cross-sectional view of a wafer W, showing an edge region for detecting defects. The wafer W has a chamfered portion (bevel portion) BV on the front and back sides by chamfering. In the example shown in FIG. 4, the back side of the wafer W has a polished surface (polished surface) P by polishing a predetermined region (e.g., 500 to 600 μm) further inward from the chamfered portion BV. In the present invention, the control unit 53 performs defect detection for a predetermined region (e.g., 1 mm) inward from the edge end face EF and the polished surface (polished surface) P. The inner side refers to the side facing the center of the wafer W (the direction of the arrow in the figure).

[0037] <Processing of control unit> Next, the processing of the control unit 53 in the present invention will be described.

[0038] 5 is a flowchart showing an example of a detection process of a protrusion defect by the control unit 53. In step S101, the control unit 53 inputs a shot image of the wafer W from the storage unit 54. Then, the control unit 53 cuts out a rectangular area including an edge ring image generated at a position where the polishing surface P contacts the boundary part B from each shot image as an ROI (Region of Interest) image based on the defect detection parameters "ROI cut-out start position" and "ROI cut-out width". The "ROI cut-out start position" is a parameter indicating the cut-out start position of the ROI image in the shot image. The "ROI cut-out width" is a parameter indicating the width to be cut out as an ROI image.

[0039] FIG. 6 is a diagram for explaining the ROI image cutout process in step S101. In the example shown in FIG. 6, an edge ring image E is displayed on the right side of a shot image of 640×480 pixels. The edge ring image E is displayed in white in the shot image because its brightness is high due to halation. For example, the "ROI cutout start position" indicates the image coordinates in the X direction (horizontal direction) of the cutout start position of the ROI image with the upper left corner pixel of the shot image as the origin, the "ROI cutout width" indicates the number of pixels in the X direction of the ROI image, the "ROI cutout start position" is 566, and the "ROI cutout width" is 44. In this case, the control unit 53 cuts out the ROI image with a width of 44 pixels from the 566th pixel in the X direction of the shot image as shown in FIG. 6. In the following description, the image obtained by rotating the ROI image shown in FIG. 6 counterclockwise by 90 degrees is again referred to as the ROI image.

[0040] FIG. 7 is a diagram showing an example of a pixel (protrusion defect) PD indicating a protrusion defect and a pixel (isolated defect) ID indicating an isolated defect in an image obtained by enlarging a part of an ROI image. The protrusion defect PD is a pixel that is in contact with the inner circumference of the edge ring image E and has a high brightness value. The protrusion defect PD is displayed in white in the ROI image, protruding from the inner circumference of the edge ring image E. The isolated defect ID is a pixel inside the edge ring image E, separated from the inner circumference of the edge ring image E toward the inside, and has a high brightness value. The isolated defect ID is displayed in white as an isolated blob in the ROI image. First, the detection process of the protrusion defect will be described, and then the detection process of the isolated defect will be described.

[0041] 5, in step S102, the control unit 53 binarizes the ROI image into a first value for higher brightness values ​​and a second value for lower brightness values ​​based on the defect detection parameter "protrusion defect detection threshold" to generate a binarized image. The "protrusion defect detection threshold" is a parameter indicating a threshold for performing binarization processing for detecting protrusion defects.

[0042] In step S103, the control unit 53 acquires, as inner circumference coordinates, image coordinates of the inner circumference of the area displayed by the first value in the binarized image.

[0043] 8 is a diagram for explaining the binarization process in step S102 and the inner circumference coordinate acquisition process in step S103. For example, assume that the "protrusion defect detection threshold" is 110. In this case, the control unit 53 converts pixels in the ROI image having a brightness value of 110 or more to a first value, and converts pixels in the ROI image having a brightness value of less than 110 to a second value. As shown in FIG. 8, the first value is generally displayed in white, and the second value is generally displayed in black.

[0044] Next, the control unit 53 scans the binarized image in the Y direction as shown in Fig. 8, and obtains the image coordinates in the Y direction of the inner circumference I (indicated by the dashed line in the figure) where the color changes from white to black as the inner circumference coordinates. The unit of the image coordinates is the pixel.

[0045] 5, in step S104, the control unit 53 performs differentiation processing on the inner circumference coordinates to calculate the change level of the unevenness in the circumferential direction (X direction) as a coordinate differential value. For example, the control unit 53 calculates the difference value between the inner circumference coordinates adjacent in the circumferential direction as the coordinate differential value.

[0046] In step S105, the control unit 53 detects a protrusion defect by comparing the coordinate differential value with a "protrusion defect judgment level" of the defect detection parameters. The "protrusion defect judgment level" is a parameter indicating the minimum coordinate differential value for judging a defect as a protrusion defect. For example, assume that the "protrusion defect judgment level" is 3. In this case, the control unit 53 detects a location where the change level is 3 or greater as a protrusion defect.

[0047] In step S105, the control unit 53 may merge defects existing within a range defined by the "grouping size" of the defect detection parameters as one protrusion defect. The "grouping size" is a parameter indicating the range to be merged. For example, assume that the "grouping size" indicates a central angle in units of 0.1 degrees and has a value of 15. In this case, the control unit 53 detects protrusion defects existing within a sector-shaped range with a central angle of 1.5 degrees, with the center of the wafer W as the center of a circle, as one protrusion defect.

[0048] Next, the process of detecting an isolated defect will be described with reference to a flowchart of FIG.

[0049] In step S201, the control unit 53 cuts out an ROI image, similar to step S101. In step S202, the control unit 53 binarizes the ROI image to generate a binarized image, similar to step S102.

[0050] In step S203, the control unit 53 detects an area in the binarized image that is outside the inner circumference of the edge ring image (the side toward the circumferential direction from the center of the wafer W) as a first mask area. The control unit 53 may enlarge the width between the outer and inner circumferences of the edge ring image based on a "mask enlargement size" of the defect detection parameters, and detect an area outside the inner circumference of the enlarged edge ring image as the first mask area. The "mask enlargement size" is a parameter that indicates the amount of enlargement of the width of the edge ring image.

[0051] 10 is a diagram for explaining the detection process of the first mask region in step S203. For example, the "mask enlargement size" is set to 2. In this case, the control unit 53 enlarges the width of the edge ring image E by two pixels toward the inner circumference (toward the bottom in this figure), and detects the region outside the inner circumference of the enlarged edge ring image (toward the top in this figure) as the first mask region M1. In the figure, the first mask region M1 is shown in black.

[0052] Returning to FIG. 9, in step S204, when the defect detection parameter "double ring removal" is enabled, the control unit 53 detects a double ring image from the ROI image based on the defect detection parameter "double ring determination threshold." "Double ring removal" is a parameter indicating whether or not to perform double ring removal processing. "Double ring determination threshold" is a parameter indicating a threshold when performing double ring removal processing. Here, double ring refers to a state in which the edge ring image E appears in the shape of double rings.

[0053] 11 is a diagram showing an example of a double ring image. The double ring image D is an image that appears inside the edge ring image E in the ROI image, and is an image made up of pixels whose brightness value is equal to or greater than the "double ring determination threshold." For example, assume that "double ring removal" is enabled and the "double ring determination threshold" is 5. In this case, the control unit 53 detects pixels whose brightness value is equal to or greater than 5 in the region inside the edge ring image E in the ROI image as the double ring image D.

[0054] Returning to FIG. 9, in step S205, the control unit 53 detects, in the ROI image, an area inside the outer periphery of the double ring image as a second mask area.

[0055] Fig. 12 is a diagram for explaining the detection process of the second mask region in step S205. As shown in Fig. 12, the control unit 53 detects the region inside (below in this figure) the outer periphery of the double ring image D in the ROI image as the second mask region M2. In the figure, the second mask region M2 is shown in black.

[0056] Returning to FIG. 9, in step S206, the control unit 53 detects an isolated defect in a judgment region obtained by excluding the first mask region and the second mask region from the ROI image, based on the defect detection parameter "threshold for detecting isolated defects." Since each pixel of the ROI image and the binary image corresponds one-to-one, the first mask region detected in the binary image can be removed from the ROI image. The "threshold for detecting isolated defects" is a parameter indicating a threshold when performing a binary process for detecting isolated defects. In other words, the judgment region is a region sandwiched between the edge ring image (the enlarged edge ring image when the width is enlarged) and the double ring image.

[0057] For example, assume that the "threshold for detecting isolated defects" is 50. In this case, the control unit 53 converts pixels in the judgment region having a brightness value of 50 or more to a first value, and converts pixels in the judgment region having a brightness value of less than 50 to a second value. Then, a blob of pixels converted to the first value is detected as an isolated defect.

[0058] In step S206, when the blob is in contact with the double ring image, the control unit 53 may determine that the blob is a double ring image and not detect the blob as an isolated defect.

[0059] In step S206, the control unit 53 may determine whether or not the blob is an isolated defect based on the defect detection parameter "double ring removal size." The "double ring removal size" is a parameter indicating the size of the blob when the blob is considered to be a double ring image. For example, assume that the "double ring removal size" is 100. In this case, if the number of pixels in the longitudinal direction of the blob is 100 or more, the control unit 53 determines that the blob is a double ring image and does not detect it as an isolated defect.

[0060] Although the detection process for protrusion defects and isolated defects has been described above, the process of the control unit 53 is not limited to this. Other process examples will be described below.

[0061] The control unit 53 may determine the size (area) of the protrusion defect and the isolated defect based on the defect detection parameters "first defect size threshold" and "second defect size threshold". The "first defect size threshold" and "second defect size threshold" are parameters indicating the classification of defect sizes. For example, the "first defect size threshold" is 5 and the "second defect size threshold" is 10. In this case, the control unit 53 determines a defect having a pixel count of 5 or more and less than 10 as a defect of the first size. The control unit 53 also determines a defect having a pixel count of 10 or more as a defect of the second size. The control unit 53 may obtain the number of defects of the first size, the number of defects of the second size, and the number of defects of other sizes or the total number of defects, and display them on a display device via the data output I / F 55.

[0062] Furthermore, the control unit 53 may be configured not to detect protrusion defects and isolated defects in an edge region of the wafer W that is defined by the defect detection parameters "invalid range start position" and "invalid range end position." The "invalid range start position" is a parameter indicating the start position of a range (invalid range) in which protrusion defects and isolated defects are not detected, and the "invalid range end position" is a parameter indicating the end position of the invalid range. A laser mark may be engraved on a part of the wafer W. In such a case, the laser mark can be excluded from the defect detection range by using the "invalid range start position" and "invalid range end position." The position of the laser mark is defined in SEMI standards T07 and M12.

[0063] FIG. 13 is a diagram showing an example of an invalid range for defect detection. For example, assume that the "invalid range start position" is 0 and the "invalid range end position" is 10. In this case, the control unit 53, as shown in FIG. 13(a), sets the position of the notch as a reference (0 degrees) and sets the range from 0 degrees to 10 degrees counterclockwise (central angle 10 degrees) as the invalid range. In the figure, the invalid range is indicated by narrow diagonal lines, and the range of the chamfered portion BV and the polished surface P is indicated by wide diagonal lines. Similarly, FIG. 13(b) shows an invalid range in the case where the "invalid range start position" is 350 and the "invalid range end position" is 10. In this case, the control unit 53 sets the position of the notch as 0 degrees and sets the range from 350 degrees to 10 degrees counterclockwise (central angle 20 degrees) as the invalid range. Similarly, FIG. 13(c) shows an invalid range in the case where the "invalid range start position" is 10 and the "invalid range end position" is 350. In this case, the control unit 53 sets the position of the notch at 0 degrees and sets the range from 10 degrees to 350 degrees counterclockwise (central angle of 340 degrees) as the invalid range.

[0064] As described above, the defect detection device 50 generates a binarized image by binarizing the ROI image with a higher brightness value as a first value and a lower brightness value as a second value based on the "protrusion defect detection threshold", obtains the image coordinates of the inner circumference of the area displayed by the first value in the binarized image as the inner circumference coordinate, calculates the change level of the unevenness in the circumferential direction of the inner circumference coordinate as a coordinate differential value, and compares the coordinate differential value with the "defect judgment level" to detect a protrusion defect. In addition, the defect detection device 50 detects an image that appears inside the edge ring image in the ROI image and is made up of pixels with a brightness value equal to or greater than the "double ring judgment threshold" as a double ring image, and detects a blob of pixels with a brightness value equal to or greater than the "isolated defect detection threshold" in the area sandwiched between the edge ring image and the double ring image as an isolated defect. This method makes it possible to expand the defect detection area to the limit of halation that can be detected from the raw image. That is, according to the present invention, it is possible to detect defects in the edge area. Furthermore, while the conventional limit for detecting defects in edge regions by visual inspection was approximately 50 μm in size, the present invention makes it possible to detect defects as small as 0.2 μm with high sensitivity.

[0065] <Program> A computer capable of executing program instructions can be used to function as the above-described defect detection apparatus 50. Here, the computer may be a general-purpose computer, a dedicated computer, a workstation, a PC (Personal Computer), etc. The program instructions may be program code, code segments, etc. for performing the necessary tasks.

[0066] The control unit 53 is a processor such as a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), or an SoC (System on a Chip), and may be configured with multiple processors of the same or different types. The processor performs the above-mentioned processes by reading and executing a program from the storage unit 15. At least a part of the process contents may be realized by hardware.

[0067] The program may be recorded on a computer-readable recording medium. By using such a recording medium, the program can be installed on the computer. Here, the recording medium on which the program is recorded may be a non-transitory recording medium. The non-transitory recording medium is not particularly limited, and may be, for example, a CD-ROM, a DVD-ROM, or a USB (Universal Serial Bus) memory. In addition, the program may be in a form that is downloaded from an external device via a network.

[0068] Although the embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art can make various modifications or alterations based on the present disclosure. Therefore, it should be noted that these modifications or alterations are included in the scope of the present disclosure. For example, the functions included in each component or step can be rearranged so as not to be logically inconsistent, and multiple components or steps can be combined or divided into one. [Industrial Applicability]

[0069] In this way, the present invention is capable of automatically detecting defects with high sensitivity, and is therefore useful for wafer inspection applications. [Explanation of symbols]

[0070] 10 Ring Fiber Illumination 20. Photography Department 22 Telescope tube 23 Lens 24 Light receiving part 30 Optical system 40 Scanning unit 50 Defect detection device 51 Data input interface 52 Image input I / F 53 Control section 54 Memory section 55 Data output I / F 100 Wafer Inspection Equipment

Claims

1. A data input I / F for acquiring parameters used for defect detection; An image input I / F for acquiring a photographed image of a wafer; a control unit that analyzes the captured image based on the parameters and detects defects on the wafer, The parameters include a protrusion defect detection threshold and a defect judgment level, The control unit is A rectangular region including an edge ring image showing an edge of the wafer is cut out as an ROI image from the captured image; generating a binarized image by binarizing the ROI image so that a higher brightness value is a first value and a lower brightness value is a second value based on the protrusion defect detection threshold value; acquiring, as inner perimeter coordinates, image coordinates of an inner perimeter of an area in the binarized image that is displayed by the first value; A change level of the unevenness in a circumferential direction of the inner circumference coordinate is calculated as a coordinate differential value; A defect detection apparatus that detects defects by comparing the coordinate differential value with the defect judgment level.

2. The parameters include a grouping size; The defect detection device according to claim 1 , wherein the control unit detects the defects that exist within a range defined by the grouping size as one defect.

3. A data input I / F for acquiring parameters used for defect detection; An image input I / F for acquiring a photographed image of a wafer; a control unit that analyzes the captured image based on the parameters and detects defects on the wafer, The parameters include a double ring determination threshold and an isolated defect detection threshold, The control unit is A rectangular region including an edge ring image showing an edge of the wafer is cut out as an ROI image from the captured image; an image that appears inside the edge ring image and is made up of pixels with a luminance value equal to or greater than the double ring determination threshold is detected as a double ring image; A defect detection device that detects, within an area between the edge ring image and the double ring image, blobs of pixels whose brightness values ​​are equal to or greater than the isolated defect detection threshold as defects.

4. The parameters include a mask enlargement size; The defect detection device described in claim 3, wherein the control unit expands the width between the outer and inner circumferences of the edge ring image based on the mask enlargement size, and detects as the defect a blob of pixels whose brightness value is greater than or equal to the isolated defect detection threshold within the area sandwiched between the enlarged edge ring image and the double ring image.

5. The parameters include a double ring removal size; The defect detection device according to claim 3 , wherein the control unit is configured to not detect the blob as a defect when the number of pixels in the longitudinal direction of the blob is equal to or larger than the double ring removal size.

6. The parameters include an invalid range start position and an invalid range end position, 4. The defect detection device according to claim 1, wherein the control unit does not detect the defect in an edge area of ​​the wafer that is defined by the invalid area start position and the invalid area end position.

7. obtaining parameters used to detect defects; acquiring a photographed image of the wafer; and a control step of analyzing the captured image based on the parameters to detect defects on the wafer, The parameters include a protrusion defect detection threshold and a defect judgment level, The control step includes: cutting out a rectangular region including an edge ring image showing an edge of the wafer from the captured image as an ROI image; a step of binarizing the ROI image into a first value having a higher brightness value and a second value having a lower brightness value based on the protrusion defect detection threshold value to generate a binarized image; acquiring, as inner perimeter coordinates, image coordinates of an inner perimeter of an area in the binarized image that is displayed by the first value; calculating a change level of unevenness in a circumferential direction of the inner circumference coordinate as a coordinate differential value; and detecting a protrusion-like defect by comparing the coordinate differential value with the defect judgment level.

8. obtaining parameters used to detect defects; acquiring a photographed image of the wafer; and a control step of analyzing the captured image based on the parameters to detect defects on the wafer, The parameters include a double ring determination threshold and an isolated defect detection threshold, The control step includes: cutting out a rectangular region including an edge ring image showing an edge of the wafer from the captured image as an ROI image; detecting, as a double ring image, an image that appears inside the edge ring image and is made up of pixels with a luminance value equal to or greater than the double ring determination threshold; detecting, as defects, blobs of pixels having brightness values ​​equal to or greater than the isolated defect detection threshold within an area between the edge ring image and the double ring image.

9. A program for causing a computer to function as the defect detection device according to claim 1 or 3.

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