CN112086373A - Wafer defect detection method - Google Patents
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Abstract
The invention provides a wafer defect detection method, which comprises the following steps: providing a wafer to be detected, wherein the wafer to be detected comprises a plurality of units to be detected; selecting the unit to be detected from different positions of the wafer to be detected as a sampling unit; extracting characteristic values from the sampling unit, and obtaining standard characteristic values according to a plurality of characteristic values; and extracting a characteristic value to be detected from the unit to be detected, comparing the characteristic value to be detected with the standard characteristic value, and judging whether the unit to be detected has defects or not. According to the invention, the standard characteristic values are extracted from the sampling units selected from different positions of the wafer to be detected, and the characteristic values of the units to be detected are compared with the standard characteristic values, so that the gradual deviation defect can be accurately detected, the uniformity in the wafer surface can be effectively monitored, and the product yield can be improved.
Description
Technical Field
The invention relates to the field of semiconductor integrated circuit manufacturing, in particular to a wafer defect detection method.
Background
In the manufacturing process of the integrated circuit, the defect detection of the wafer is an important means for improving the yield of the product (YE), and the work of tracking the cause of the defect, collecting and analyzing the defect data, improving and evaluating the defect and the like is combined, so that the yield of the product can be effectively improved, the production cost is reduced, and the product competitiveness is improved. With the increasing development speed of products, the requirement for detecting the defects of the wafer is also increased.
At present, wafer defect detection generally performs in-plane scanning on a wafer through a defect scanning device to obtain the number and distribution of defects on the surface of the wafer. The method comprises the steps of scanning a large number of identical repeating units arranged in a matrix mode on the surface of a wafer line by line, comparing whether abnormal differences exist among all corresponding pixel points in images of adjacent repeating units in each line or not, and further identifying abnormal points in a single repeating unit, namely positions with defects. And after all adjacent repeating units are compared by line-by-line scanning, the distribution and the number of the defects in the wafer surface can be obtained. However, in the defect detection process, the alignment of defect detection is only performed between adjacent repeating units, which means that the defect detection process cannot detect some defects with gradual deviations from the standard specification. Since the difference reflected between adjacent repeating units is very slight for defects that are graded off the standard specification, such defects cannot be detected accurately. The gradual defects are often caused by the non-uniformity of the photolithography, film forming or etching processes in the wafer surface, are important defect types affecting yield indexes such as product uniformity, and need to be effectively monitored and improved.
Therefore, it is necessary to provide a new wafer defect detection method to solve the above problems.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, an object of the present invention is to provide a wafer defect detecting method for solving the problem that the defect detecting method of the prior art cannot detect a gradual defect.
To achieve the above and other related objects, the present invention provides a wafer defect detecting method, comprising the steps of:
providing a wafer to be detected, wherein the wafer to be detected comprises a plurality of units to be detected;
selecting the unit to be detected from different positions of the wafer to be detected as a sampling unit;
extracting characteristic values from the sampling unit, and obtaining standard characteristic values according to a plurality of characteristic values;
and extracting a characteristic value to be detected from the unit to be detected, comparing the characteristic value to be detected with the standard characteristic value, and judging whether the unit to be detected has defects or not.
As a preferred embodiment of the present invention, the method for selecting the units to be detected from different positions of the wafer to be detected includes performing pseudo-random sampling on a plurality of units to be detected.
As a preferred embodiment of the present invention, the process of selecting the unit to be detected from different positions of the wafer to be detected includes selecting the unit to be detected from different quadrants of the wafer to be detected.
As a preferred embodiment of the present invention, the step of selecting the to-be-detected cells from different positions of the to-be-detected wafer includes selecting the to-be-detected cells from different positions in each exposure area.
As a preferred embodiment of the present invention, the process of selecting the units to be detected from different positions of the wafer to be detected includes selecting the units to be detected from areas having different distances from the center position of the wafer to be detected.
As a preferable aspect of the present invention, the method of deriving the standard feature value from a plurality of the feature values includes using a median value of the plurality of the feature values as the standard feature value.
As a preferred embodiment of the present invention, after obtaining the standard feature value, the method further includes a step of comparing the feature value extracted in the plurality of sampling units with the standard feature value, and removing the abnormal sampling unit, and then obtaining the standard feature value again.
As a preferable aspect of the present invention, the characteristic value includes a gray value of each pixel in an image captured by the unit to be detected.
As a preferable aspect of the present invention, the method further includes the step of combining the standard gradation values of the respective pixels into a standard reference unit after obtaining the standard gradation value of each of the pixels as the standard feature value; after the image of the unit to be detected is obtained through shooting, comparing the gray value of each pixel in the image with the standard gray value of the corresponding pixel in the standard reference unit one by one, and judging whether each pixel has a defect.
As a preferable aspect of the present invention, the defect includes a gradual deviation of a shape or a size of a specific structure in the unit to be detected along a specific direction in the wafer plane to be detected.
As described above, the present invention provides a method for detecting a wafer defect, in which a standard characteristic value is extracted from sampling units selected from different positions of a wafer to be detected, and a characteristic value of the unit to be detected is compared with the standard characteristic value, so that a gradual deviation defect can be accurately detected, uniformity in the wafer surface can be effectively monitored, and the yield of products can be improved.
Drawings
Fig. 1 is a flowchart illustrating a method for fabricating a semiconductor structure according to an embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating a wafer to be tested according to an embodiment of the invention.
Fig. 3 is a schematic diagram illustrating a regular distribution of defects in a wafer surface according to an exposure area according to an embodiment of the invention.
FIG. 4 is a schematic diagram illustrating a defect distribution in an exposure area according to a first embodiment of the present invention.
FIG. 5 is a schematic diagram of selecting sampling units at different positions of an exposure area according to an embodiment of the present invention.
Fig. 6 is a schematic diagram illustrating a distribution of defects in a wafer plane according to a quadrant region according to an embodiment of the present invention.
Fig. 7 is a schematic diagram illustrating quadrant-wise division of sampling areas in a wafer plane according to an embodiment of the present invention.
Fig. 8 is a schematic diagram illustrating distribution of defects in a wafer plane in an edge region according to an embodiment of the invention.
Fig. 9 is a schematic diagram illustrating a sampling area divided according to different distances from a center of a wafer to be detected in a wafer plane according to an embodiment of the present invention.
Fig. 10 is a schematic diagram illustrating a pixel distribution of a single cell to be detected according to an embodiment of the invention.
Fig. 11 is a schematic diagram illustrating a wafer to be inspected having a graded defect according to a second embodiment of the present invention.
Fig. 12 is a schematic diagram of a left reference cell, a cell to be detected, and a right reference cell in a single area according to a second embodiment of the present invention.
Description of the element reference numerals
100 wafer
101 unit to be detected
101a edge cell
101b sampling unit
101c pixel
101d sampling pixel
102 exposure region
102a first type of defects
103 second type of defects
103a first quadrant region
103b second quadrant region
103c third quadrant region
103d fourth quadrant region
104 type III defects
104a edge sampling area
104b transition sampling area
104c central sampling area
200 wafer
201 unit to be detected
205 area of dashed line
205a first area
205b second region
205c third region
205d left reference cell
205e units to be detected
205f right reference cell
S1-S4 Steps 1) -4)
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.
Please refer to fig. 1 to 12. It should be noted that the drawings provided in the present embodiment are only schematic and illustrate the basic idea of the present invention, and although the drawings only show the components related to the present invention and are not drawn according to the number, shape and size of the components in actual implementation, the form, quantity and proportion of the components in actual implementation may be changed arbitrarily, and the layout of the components may be more complicated.
Example one
Referring to fig. 1 to 10, the present invention provides a wafer defect detection method, which includes the following steps:
1) providing a wafer 100 to be detected, wherein the wafer 100 to be detected comprises a plurality of units 101 to be detected;
2) selecting the unit to be detected 101 from different positions of the wafer to be detected 100 as a sampling unit;
3) extracting characteristic values from the sampling unit, and obtaining standard characteristic values according to a plurality of characteristic values;
4) extracting a characteristic value to be detected from the unit to be detected 101, comparing the characteristic value to be detected with the standard characteristic value, and judging whether the unit to be detected has defects.
In step 1), please refer to step S1 of fig. 1 and fig. 2, a wafer 100 to be inspected is provided, where the wafer 100 to be inspected includes a plurality of units 101 to be inspected. As an example, as shown in fig. 2, a plurality of units 101 to be detected are included on the wafer 100 to be detected, and the units 101 to be detected are repeating units with the same design specification and are arranged in rows and columns. The wafer 100 to be detected may be a wafer that has undergone any semiconductor process, such as photolithography, film formation, or etching, and may need to detect defects that may appear on the surface of the wafer, and obtain the number and distribution state of the defects. In addition, the edge unit 101a in the edge area of the wafer 100 to be detected is generally an incomplete unit or a unit with poor process uniformity, and will not be a product, and therefore is not an object of interest for defect detection.
In step 2), please refer to step S2 of fig. 1 and fig. 3 to 9, select the to-be-detected cells 101 from different positions of the to-be-detected wafer 100 as sampling cells. As an example, the method for selecting the units 101 to be detected from different positions of the wafer 100 to be detected includes performing pseudo-random sampling on a plurality of units 101 to be detected. Specifically, thousands of units 101 to be detected on the wafer 100 to be detected are numbered, a plurality of numbers are selected by a pseudo-random sampling method, and the plurality of units 101 to be detected corresponding to the numbers are used as sampling units. The plurality of units 101 to be tested are selected from different positions of the wafer 100 to be tested by pseudo-random sampling.
Further, since the defect distribution in the wafer surface may exhibit a specific distribution rule according to a specific cause of the defect, when selecting the sampling units by the pseudo-random sampling method, it is necessary to consider to eliminate the influence of the defect distribution in the wafer surface and avoid selecting too many sampling units with defects, so as to ensure that the sampling units can represent the normal specification of the units in the wafer surface as much as possible.
As an example, as shown in fig. 3 to 5, the process of selecting the to-be-detected cells 101 from different positions of the to-be-detected wafer 100 includes selecting the to-be-detected cells 101 from different positions in each exposure area 102. As shown in fig. 3 and 4, the defects in the wafer surface are regularly distributed in the exposure region 102(by shot). In fig. 3, the units 101 to be detected on the wafer 100 to be detected form one exposure area 102 through a 4 × 5 array to perform a single photolithography exposure process, and the photolithography process of the wafer is completed by sequentially exposing a plurality of exposure areas 102. As can be seen from fig. 3, the first type of defects 102a are regularly distributed in the plurality of exposure regions 102. Fig. 4 shows the distribution of the first type of defects 102a in a single exposure area 102, and it can be seen from fig. 3 that the first type of defects 102a are distributed at almost the same position in the exposure area 102. It can be concluded that the generation of the first type of defect 102a is strongly related to the photolithography process, for example, the generation may be caused by abnormal feature patterns due to too high or too low exposure energy (dose) in the photolithography process. As shown in fig. 5, in order to prevent the first type of defect 102a from affecting the selection of the sampling units, in this embodiment, the cells 101 to be detected are selected from different positions in each exposure area 102 on the basis of the pseudo-random sampling when the sampling units are selected. As an example, when the number of sampling units to be selected is 5, the units to be detected 101 are selected as sampling units from different positions in a plurality of different exposure areas 102. As shown in fig. 5, in the exposure area 102 formed by a plurality of units 101 to be detected through a 4 × 5 array, the sampling units 101b are selected from different positions of the exposure area 102. It should be noted that, in order to eliminate the influence of the first type of defect 102a on the selection of the sampling units as much as possible, when the total number of the sampling units to be selected is greater than the total number of the units 101 to be detected in one of the exposure areas 102, the selection positions of the sampling units in a plurality of different exposure areas 102 may be repeated, but the selection of the sampling units needs to be distributed at different positions in the exposure area 102 as much as possible.
As an example, as shown in fig. 6 to 7, the process of selecting the to-be-detected unit 101 from different positions of the to-be-detected wafer 100 includes selecting the to-be-detected unit 101 from different quadrants of the to-be-detected wafer 100. As shown in fig. 6, defects are distributed in quadrant areas in the wafer plane. Specifically, in fig. 6, most of the defects 103 of the second type are distributed in the lower half, i.e., the third quadrant and the fourth quadrant, of the wafer 100 to be detected. Such defect distributions may generally be due to abnormal processing. For example, in the wet etching process, etching or drying non-uniformity occurs on the lower half of the wafer 100 to be detected due to abnormality; or in a process chamber for etching, film formation, or the like, the region is contaminated by the falling of chamber particles. As shown in fig. 7, in order to prevent the second type of defect 103 from affecting the selection of the sampling units, in this embodiment, the selection of the unit to be detected 101 from different quadrants of the wafer to be detected 100 is also satisfied on the basis of the pseudo-random sampling when selecting the sampling units. In fig. 7, the sampling area of the wafer 100 to be detected is divided into a first quadrant area 103a, a second quadrant area 103b, a third quadrant area 103c and a fourth quadrant area 103d according to different quadrants. When selecting the sampling units, on the basis of pseudo-random sampling, the selection of the sampling units is also evenly distributed in the first quadrant area 103a, the second quadrant area 103b, the third quadrant area 103c and the fourth quadrant area 103d, so as to avoid the influence of the second type of defect 103 on the selection of the sampling units. It should be noted that in the present embodiment, the four different areas are divided into four different areas according to quadrants, but in other described cases of the present invention, the divided areas may be further increased or decreased according to specific requirements. For example, a quadrant region is further divided into two sector regions, so as to obtain eight sampling regions; or two adjacent quadrant areas are combined into one sampling area, and then two sampling areas are obtained.
As an example, as shown in fig. 8 to 9, the process of selecting the to-be-detected units 101 from different positions of the to-be-detected wafer 100 includes selecting the to-be-detected units 101 from areas having different distances from the center position of the to-be-detected wafer 100. As shown in fig. 8, the defects are distributed in the wafer plane in the center/edge region. Specifically, in fig. 8, the third type of defect 104 is locally concentrated on the edge region of the wafer 100 to be detected. Such defect distributions may generally be due to process non-uniformities. For example, in the process of etching or film formation, the process results are unevenly distributed according to the center/edge region, and further structural defects intensively distributed in the center or edge region occur. As shown in fig. 9, in order to prevent the third type of defect 104 from affecting the selection of the sampling units, in this embodiment, when selecting the sampling units, on the basis of the pseudo-random sampling, it is further satisfied that the units to be detected 101 are selected from the regions with different distances from the center position of the wafer to be detected 100. In fig. 9, the sampling area of the wafer 100 to be detected is divided into an edge sampling area 104a, a transition sampling area 104b and a center sampling area 104c according to different distances from the center of the wafer 100 to be detected. When selecting a sampling unit, on the basis of pseudo-random sampling, the selection of the sampling unit is also evenly distributed in the edge sampling area 104a, the transition sampling area 104b and the center sampling area 104c, so as to avoid the influence of the third type of defect 104 on the selection of the sampling unit. It should be noted that in the present embodiment, three sampling regions are divided according to the difference of the center/edge distances, but in other cases of the present invention, the divided regions may be further increased or decreased according to specific requirements. For example, only two sampling areas, namely a central sampling area and an edge sampling area, are divided; alternatively, the number of transition sampling areas is further increased to obtain four or more sampling areas.
In this embodiment, when the unit to be detected 101 is selected based on the pseudo-random sampling, the position distribution of the plurality of units to be detected 101 is required to comply with the three sampling area division methods. Of course, the distribution of the three sampling regions need not be satisfied at the same time in the present invention, and in other cases, when the unit 101 to be detected is selected, only one or two of the three sampling region distributions may be satisfied. In addition, other feasible methods for dividing the sampling region may be correspondingly introduced for the defect distribution patterns other than the first type of defect 102a, the second type of defect 103, and the third type of defect 104.
In step 3), please refer to step S3 of fig. 1 and fig. 10, a feature value is extracted from the sampling unit, and a standard feature value is obtained according to a plurality of feature values. Optionally, the method for deriving a standard feature value according to a plurality of feature values comprises using a median of the plurality of feature values as the standard feature value. The characteristic values comprise gray values of all pixels in the image shot by the unit to be detected.
As an example, as shown in fig. 10, one of the units to be detected 101 is selected as a sampling unit, and a plurality of pixels 101c form a 5 × 5 array. It should be noted that the array illustrated in this embodiment is 5 × 5, which is only for convenience of explaining the implementation method of the present invention, and in an actual single unit on a wafer, the number of pixels constituting a unit image is generally much higher than that of the array of 5 × 5, and the specific number of pixels needs to be determined by combining the resolution of the scanner and the precision required for defect scanning.
As an example, in the present embodiment, the number of the selected sampling units is 5, and the sampling units are respectively referred to as a first sampling unit, a second sampling unit, a third sampling unit, a fourth sampling unit, and a fifth sampling unit. The sampling pixels in each sampling unit have respective gray values. As shown in fig. 10, the sampling pixels 101d at the middle positions in the sampling unit also have respective gray-scale values. The gray-scale values of the sampling pixels 101d in the first sampling unit, the second sampling unit, the third sampling unit, the fourth sampling unit and the fifth sampling unit are 1, 2, 3, 4 and 5, respectively. The median of the above values can be selected as the standard characteristic value, i.e. the standard gray value is 3. For each pixel 101c in the unit 101 to be detected, the standard gray value of the pixel at the position can be obtained by taking the median of the gray values of the corresponding pixels in the plurality of sampling units according to the method. Further, by combining the standard gradation values of each pixel, a standard reference cell (gold reference die) can also be obtained. In the virtual standard reference cell, the gray scale value of each pixel is obtained by selecting the median of the corresponding pixels in the plurality of sampling cells. In addition, in addition to the median, other quantities may be selected that describe trends in a set of data sets, such as averages.
As an example, after obtaining the standard feature value, the method further includes a step of comparing the feature value extracted from the plurality of sampling units with the standard feature value, and obtaining the standard feature value again after removing the abnormal sampling units. For example, in a plurality of sampling units, the pixel values of the corresponding positions may constitute a set of data, and by analyzing the set of data, such as a box plot (box plot), a significant abnormal deviation value may be screened out. The positions corresponding to these abnormal deviation values may be the positions of defects, and need to be removed so as not to affect the establishment of the standard characteristic values and the standard reference units. Through the operation, the characteristic value of the defect position which is possibly contained is removed, and the standard reference unit is ensured to have a standard level (baseline) meeting the specification.
In step 4), please refer to step S4 of fig. 1 and fig. 2 and 10, a feature value to be detected is extracted from the unit to be detected 101, the feature value to be detected is compared with the standard feature value, and whether a defect exists in the unit to be detected 101 is determined. In step 3), after the standard characteristic value and the standard reference unit are obtained, in this step, all the units to be detected 101 that need to be detected on the wafer to be detected 100 in fig. 2 are compared one by one based on the standard characteristic value and the standard reference unit, so as to detect whether abnormal pixel points exist in the units to be detected 101, that is, whether defects exist.
As an example, as shown in fig. 10, after an image of the cell 101 to be detected is obtained through shooting, the gray scale value of each pixel in the image is compared with the standard gray scale value of the corresponding pixel in the standard reference cell one by one, and whether each pixel has a defect is determined. For example, in the detection process, the gray value of the scanned sampling pixel 101d in a certain to-be-detected cell 101 is 7, which is greater than the standard gray value 3, and exceeds the specification range of ± 2. At this time, it can be determined that the sampling pixel of the unit to be detected is abnormal, i.e. has a defect.
In this embodiment, a plurality of units to be detected are selected as sampling units, feature values are extracted from the sampling units, standard feature values are obtained according to the feature values, and a standard reference unit is further obtained. When each unit to be detected in the wafer to be detected is detected, the gray values of each corresponding pixel of the unit to be detected and the standard reference unit are compared to obtain an abnormal pixel and the unit to be detected with the abnormal pixel. Because each unit to be detected is directly compared with the standard reference unit, the problem that the gradual-change defect cannot be detected only by comparing adjacent units to be detected in the prior art is solved.
Example two
Referring to fig. 11 to 12, the present invention provides a method for detecting a wafer defect, which will be described in detail in this embodiment in comparison with the first embodiment, and the method for detecting a graded defect is more accurate than the prior art.
As shown in fig. 11, a wafer 200 to be inspected having a gradual defect in a unit 201 to be inspected. As an example, the defect includes a gradual deviation of the appearance or size of a specific structure in the unit 201 to be detected along a specific direction in the wafer 200 to be detected. Specifically, in fig. 11, the gradual defect progresses from the edge region of the wafer to the center region of the wafer in the direction of the arrow in the figure, and the defect in the broken line region 205 in the figure has already progressed beyond the allowable specification, and it should be determined as an out-of-specification defect.
As an example, the gradual defect may be unevenness in the aperture size of the via hole after the via hole is etched. Due to the unevenness caused by the etching load effect of the etching machine, the aperture size of the through hole has the characteristics of small center and large edge in the wafer surface. For example, the standard specification of the aperture size of the through-hole is 1.0. + -. 0.2. mu.m. In the wafer edge area, as in the first area 205a and the third area 205c, the aperture size is 1.0 μm. The aperture size decreases gradually in a direction toward the center of the wafer. When within the dashed area 205, as in the second area 205b, the aperture size has been smaller than 0.8 μm, which is clearly outside the standard specification, it should be judged as an out-of-specification defect.
However, in the scanning inspection in the prior art, the above gradual defect cannot be accurately detected. For example, in fig. 11 and 12, in the second region 205b which is out of specification, there are three repeating units which are laterally continuous, namely a left reference unit 205d, a unit to be detected 205e and a right reference unit 205 f. In the prior art detection process, the gray values of corresponding pixels in two adjacent repeating units are compared, and when the difference is too large, for example, the difference of the gray values is greater than 10, the defect is considered to exist. The method has good effect on small area and even single defect, and is difficult to detect for gradual defect. For the second region 205b, in the left reference cell 205d, the cell to be detected 205e, and the right reference cell 205f thereof, the gray-scale values of pixels at a corresponding position are 17, 18, and 19, respectively, and the difference of the gray-scale values is only 1, which is much smaller than the set alarm specification 10. According to the prior art method, no defect is considered to be present in the second region 205b after scanning detection. For the first region 205a, in the left reference cell 205d, the cell to be detected 205e and the right reference cell 205f thereof, the gray values of the pixels at the corresponding positions are 30, 31 and 32 respectively; for the third region 205c, the gray-scale values of the pixels at the corresponding positions in the left reference cell 205d, the cell to be detected 205e and the right reference cell 205f are 33, 32 and 31, respectively, and compared with the standard gray-scale value 32 of the corresponding pixels in the standard reference cell, the first region 205a and the third region 205c are non-defective regions meeting the specification. That is, although the gray-scale values in the second region 205b are 17, 18 and 19, which are much smaller than the standard gray-scale value 32 in the prior art, the difference cannot be detected by the method of comparing adjacent repeating units, and thus the gradual-change defect cannot be detected.
In the present invention, a plurality of units 201 to be detected are selected as sampling units, feature values are extracted from the sampling units, standard feature values are obtained according to the plurality of feature values, and a standard reference unit is further obtained. The standard gray value of the corresponding pixel in the standard reference unit is 32, and the alarm specification is +/-10. When the detection method of the present invention is used to scan defects, the gray scale values of the cells 205e to be detected in the first region 205a and the third region 205c are both 32, which meet the specification range of standard gray scale values, and can be determined as being defect-free; for the second region 205b, the gray value of the cell 205e to be detected is only 18, which is much smaller than the standard gray value, and the difference is greater than 10, so that it is determined as defective. Therefore, the wafer defect detection method provided by the invention can accurately detect the gradual defect.
In addition, the standard reference unit is introduced, so that the gradual change type defects can be accurately detected, and the scanning type comparison of adjacent repeated units can be not relied on. This means that after obtaining the standard reference cells, the present invention can arbitrarily select the cells to be detected and the standard reference cells at different positions on the wafer for direct comparison, and detect the defects. The method has important significance for the random position sampling inspection of the wafer and the improvement of the sampling inspection efficiency.
In summary, the present invention provides a wafer defect detection method, which includes the following steps: providing a wafer to be detected, wherein the wafer to be detected comprises a plurality of units to be detected; selecting the unit to be detected from different positions of the wafer to be detected as a sampling unit; extracting characteristic values from the sampling unit, and obtaining standard characteristic values according to a plurality of characteristic values; and extracting a characteristic value to be detected from the unit to be detected, comparing the characteristic value to be detected with the standard characteristic value, and judging whether the unit to be detected has defects or not. According to the invention, the standard characteristic values are extracted from the sampling units selected from different positions of the wafer to be detected, and the characteristic values of the units to be detected are compared with the standard characteristic values, so that the gradual deviation defect can be accurately detected, the uniformity in the wafer surface can be effectively monitored, and the product yield can be improved.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A wafer defect detection method is characterized by comprising the following steps:
providing a wafer to be detected, wherein the wafer to be detected comprises a plurality of units to be detected;
selecting the unit to be detected from different positions of the wafer to be detected as a sampling unit;
extracting characteristic values from the sampling unit, and obtaining standard characteristic values according to a plurality of characteristic values;
and extracting a characteristic value to be detected from the unit to be detected, comparing the characteristic value to be detected with the standard characteristic value, and judging whether the unit to be detected has defects or not.
2. The wafer defect detection method of claim 1, wherein: the method for selecting the units to be detected from different positions of the wafer to be detected comprises the step of carrying out pseudo-random sampling on a plurality of units to be detected.
3. The wafer defect detection method of claim 2, wherein: the process of selecting the unit to be detected from different positions of the wafer to be detected comprises selecting the unit to be detected from different quadrants of the wafer to be detected.
4. The wafer defect detection method of claim 2, wherein: the process of selecting the to-be-detected units from different positions of the to-be-detected wafer comprises selecting the to-be-detected units from different positions in each exposure area.
5. The wafer defect detection method of claim 2, wherein: the process of selecting the units to be detected from different positions of the wafer to be detected comprises selecting the units to be detected from areas with different distances from the center position of the wafer to be detected.
6. The wafer defect detection method of claim 1, wherein: the method for deriving a standard feature value from a plurality of feature values comprises using a median value of the plurality of feature values as the standard feature value.
7. The wafer defect detection method of claim 1, wherein: after the standard characteristic value is obtained, the method further comprises the steps of comparing the characteristic value extracted from the plurality of sampling units with the standard characteristic value, removing the abnormal sampling units, and then obtaining the standard characteristic value again.
8. The wafer defect detection method of claim 1, wherein: the characteristic values comprise gray values of all pixels in the image shot by the unit to be detected.
9. The wafer defect detection method of claim 8, wherein: after obtaining the standard gray value of each pixel as the standard characteristic value, the method further comprises the step of combining the standard gray values of each pixel into a standard reference unit; after the image of the unit to be detected is obtained through shooting, comparing the gray value of each pixel in the image with the standard gray value of the corresponding pixel in the standard reference unit one by one, and judging whether each pixel has a defect.
10. The wafer defect detection method of claim 1, wherein: the defects comprise gradual deviation of the appearance or the size of a specific structure in the unit to be detected along a specific direction in the wafer surface to be detected.
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