CN111539955A - Defect detection method - Google Patents
Defect detection method Download PDFInfo
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- CN111539955A CN111539955A CN202010466327.3A CN202010466327A CN111539955A CN 111539955 A CN111539955 A CN 111539955A CN 202010466327 A CN202010466327 A CN 202010466327A CN 111539955 A CN111539955 A CN 111539955A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/001—Industrial image inspection using an image reference approach
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30148—Semiconductor; IC; Wafer
Abstract
The invention provides a defect detection method, which comprises the steps of providing an information file of a graph to be detected and a reference graph of the graph to be detected; searching the image of the graph to be detected according to the information file of the graph to be detected; generating a characteristic contour map from the reference graph; the characteristic profile graph of the reference graph and the image of the graph to be detected are matched, compared and displayed in an overlapping mode, and graph difference is captured.
Description
Technical Field
The invention relates to the technical field of semiconductors, in particular to a defect detection method.
Background
In the semiconductor chip manufacturing process, the defect detection scanning electron microscope plays an important role in the processes of analyzing defects, reducing defects and improving yield.
With the development of integrated circuit technology, the critical dimension becomes smaller and smaller, and the feature size of the defect affecting the yield of the chip also becomes smaller and smaller. In the actual production process, when a defect detection scanning electron microscope detects the situations of small change of a pattern or alignment deviation of the pattern and the like, the defect condition is difficult to be accurately distinguished from a defect image by manpower. Referring to FIGS. 1a to 1c, FIG. 1a shows a defect pattern image; FIG. 1b is a reference pattern image of the defect pattern of FIG. 1 a; FIG. 1c shows an image of a defect location outlined by a dashed line after comparison of FIGS. 1a and 1 b; therefore, the difference between the defect pattern and the reference pattern is extremely small, and the defect pattern and the reference pattern are difficult to be identified by naked eyes; for another example, fig. 2a to 2b, wherein fig. 2a is a schematic view of another defect pattern; fig. 2b is a schematic diagram of a reference pattern of the defect pattern in fig. 2a, and thus it can be seen that the overall pattern of the defect pattern is slightly smaller than the reference pattern, and these slight differences are difficult to be recognized by naked eyes.
Therefore, the defect scanning electron microscope is used for accurately detecting the defects, the analysis and the troubleshooting of the defect cause are further promoted, and the quality of the wafer is improved, so that the method becomes very important.
Therefore, a new defect detection method needs to be proposed to solve the above problems.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides a defect detection method, which is used to solve the problem in the prior art that it is difficult to accurately distinguish the defect condition when the defect detection scanning electron microscope detects a small change of the pattern or a pattern alignment shift.
To achieve the above and other related objects, the present invention provides a defect detecting method, which at least includes the steps of: providing an information file of a graph to be detected and a reference graph of the graph to be detected; searching the image of the graph to be detected according to the information file of the graph to be detected; thirdly, generating a characteristic contour map from the reference graph; and fourthly, matching and comparing the characteristic profile graph of the reference graph with the image of the graph to be detected, overlapping and displaying the characteristic profile graph and the image of the graph to be detected, and capturing graph differences.
Preferably, the information file of the pattern to be detected in the first step includes position information and image information of the pattern to be detected.
Preferably, the reference pattern of the pattern to be detected in the first step is a pattern with the same relative coordinates of the pattern to be detected in other unit chips in the same wafer, or a pattern with the same coordinates of unit chips in other wafers in the same process.
Preferably, the reference pattern in the first step is a sample pattern generated by using pattern analysis software to map the pattern to be detected in the same wafer with the same relative coordinates in other unit chips or map of the unit chips of other wafers with the same process with the same coordinates.
Preferably, the reference graph in the first step is a graph in an original GDS file of the graph to be detected or other files containing a structure and coordinate information of the graph to be detected.
Preferably, in the second step, the image of the graph to be detected is searched according to the position information of the graph to be detected.
Preferably, in the third step, the feature profile generated by the reference graph is a two-dimensional feature profile.
Preferably, in the third step, the feature profile generated by the reference image is a three-dimensional feature profile.
Preferably, the method for capturing the graphic difference in the fourth step is as follows: the system sets a difference interval value, and if the difference value between the characteristic profile graph and the graph to be detected after comparison by the graph analysis software is within the interval value, the system does not report an error; if the difference value is not within the interval value, the system will report an error and identify the difference after comparison.
As described above, the defect detection method of the present invention has the following advantageous effects: according to the invention, the reference graph is used for generating the characteristic outline graph, the graph to be detected and the characteristic outline graph are displayed in an overlapping mode, the defect micro-difference characteristic parameters can be accurately captured based on the defect scanning electron microscope machine, the readability and the efficiency of defect image detection are improved, and the guarantee is provided for the efficiency and the accuracy of defect detection.
Drawings
FIG. 1a shows a defect pattern image in the prior art;
FIG. 1b is a reference pattern image of the defect pattern of FIG. 1 a;
FIG. 1c shows an image of the defect location after comparison of FIGS. 1a and 1 b;
FIG. 2a is a schematic diagram of another defect pattern in the prior art;
FIG. 2b is a schematic diagram of a reference pattern of the defect pattern in FIG. 2 a;
FIG. 3a is an image of a reference pattern according to the present invention;
FIG. 3b shows a feature profile of the reference pattern of FIG. 3 a;
FIG. 3c is a diagram showing the positions of the defects captured after the feature profile and the to-be-detected defect pattern are displayed in an overlapping manner;
FIG. 4a is a schematic diagram of a GDS file according to a reference diagram of the present invention;
FIG. 4b is a two-dimensional feature profile of a graph in a GDS file according to the present invention;
FIG. 4c is a schematic diagram showing the feature profile and the defect map to be detected after being displayed in an overlapping manner;
FIG. 4d shows the difference between the feature profile and the defect map to be detected;
FIG. 5 is a flowchart illustrating a defect detection method according to the present invention.
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. 3a to 5. It should be noted that the drawings provided in the present embodiment are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
Example one
The present invention provides a defect detection method, as shown in fig. 5, fig. 5 is a flowchart of the defect detection method of the present invention, and the method includes the following steps in this embodiment: the defect detection method is suitable for capturing the defect image according to the coordinates given by the defect scanning position information file in the daily defect monitoring process.
Providing an information file of a graph to be detected and a reference graph of the graph to be detected; the invention further comprises that the information file of the graph to be detected in the first step comprises the position information and the image information of the graph to be detected. Still further, in this embodiment, the reference pattern of the pattern to be detected in the first step is a pattern with the same relative coordinates of the pattern to be detected in other unit chips in the same wafer, or a pattern with the same coordinates of unit chips in other wafers in the same process. Furthermore, the reference pattern in the first step is a pattern with the same relative coordinates of the pattern to be detected in other unit chips in the same wafer, or a sample pattern generated by the pattern analysis software of the patterns with the same coordinates of other unit chips in other wafers in the same process, as shown in fig. 3a, where fig. 3a is an image of the reference pattern of the present invention.
Searching the image of the graph to be detected according to the information file of the graph to be detected; further, in the second step, the image of the graph to be detected is searched according to the position information of the graph to be detected. And further, searching the image of the graph to be detected according to the coordinate information of the graph to be detected in the step two.
Thirdly, generating a characteristic contour map from the reference graph; and in the third step, the feature profile generated by the reference graph is a two-dimensional feature profile. In this embodiment, the image of the reference pattern in the peripheral unit chip is searched through the position information file of the defect pattern, pattern analysis software is introduced into the defect scanning machine, the plurality of reference pattern images are subjected to calculation processing and fitting to generate a two-dimensional feature profile, and further, in the third step, the feature profile generated by the reference pattern is a feature profile generated by the pattern analysis software on the four patterns of the upper, lower, left and right sides around the pattern to be detected. In other words, in this embodiment, the four graphs, i.e., the upper, lower, left, and right, around the graph to be detected are subjected to computation processing and fitting to generate a two-dimensional feature profile graph. In other embodiments, the feature profile generated by the reference graph in step three may also be a three-dimensional feature profile. Namely, the four graphs of the upper, lower, left and right sides around the graph to be detected are calculated, processed and fitted to generate a three-dimensional characteristic profile graph. As shown in fig. 3b, fig. 3b is a feature profile of the reference pattern of fig. 3 a.
And fourthly, matching and comparing the characteristic profile graph of the reference graph with the image of the graph to be detected, overlapping and displaying the characteristic profile graph and the image of the graph to be detected, and capturing graph differences. Further, the method for capturing the graph difference in the fourth step is as follows: the system sets a difference interval value, and if the difference value between the characteristic profile graph and the graph to be detected after comparison by the graph analysis software is within the interval value, the system does not report an error; if the difference value is not within the interval value, the system will report an error and identify the difference after comparison. The machine station compares the generated two-dimensional characteristic profile graph with the defect position graph image, and displays the two-dimensional characteristic profile graph and the defect position graph image in an overlapping mode, and meanwhile, the difference position is marked automatically. As shown in fig. 3c, fig. 3c is a defect position diagram captured after the feature profile diagram and the defect pattern to be detected are displayed in an overlapping manner.
Example two
The difference between this embodiment and the first embodiment is that, for a pattern with a special monitoring requirement, the embodiment can capture an image of a scanning electron microscope according to graphic structure information and coordinate file information provided by a GDS file, and further, the reference graphic in the first step in this embodiment is a graphic in an original GDS file of the graphic to be detected or in another file containing a graphic structure to be detected and coordinate information. Therefore, the reference graph in the first step of this embodiment includes the graph in the original GDS file of the graph to be detected. As shown in FIG. 4a, FIG. 4a is a schematic diagram of a GDS file as a reference diagram according to the present invention. And searching a specific graphic image according to the graphic structure information and the coordinate file information given by the GDS file.
Step three, generating a feature profile map for the graph in the original GDS file, further generating the feature profile map as a two-dimensional feature profile map, as shown in fig. 4b, where fig. 4b is a two-dimensional feature profile map for the graph in the GDS file in the present invention; and fourthly, matching and comparing the characteristic profile graph of the reference graph with the image of the graph to be detected, overlapping and displaying the characteristic profile graph and the image of the graph to be detected, and capturing graph differences. As shown in fig. 4c, fig. 4c is a schematic diagram of a feature profile and a defect map to be detected after being displayed in an overlapping manner, and the step is to match and compare the two-dimensional feature profile with a specific graphic image under a scanning electron microscope and automatically identify differences in graphics or size, as shown in fig. 4d, fig. 4d is a schematic diagram of a feature profile and a defect map to be detected after being displayed in an overlapping manner. If the difference value between the characteristic contour map and the graph to be detected after comparison by the graph analysis software is within the interval value, the system does not report an error; if the difference value is not within the interval value, the system will report an error and identify the difference after comparison.
In summary, the reference graph is used to generate the characteristic profile graph, the graph to be detected and the characteristic profile graph are displayed in an overlapping mode, the defect micro-difference characteristic parameters can be accurately captured based on the defect scanning electron microscope machine, the readability and the efficiency of defect image detection are improved, and the defect detection efficiency and the defect detection accuracy are guaranteed. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
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 method for defect detection, the method comprising at least the steps of:
providing an information file of a graph to be detected and a reference graph of the graph to be detected;
searching the image of the graph to be detected according to the information file of the graph to be detected;
thirdly, generating a characteristic contour map from the reference graph;
and fourthly, matching and comparing the characteristic profile graph of the reference graph with the image of the graph to be detected, overlapping and displaying the characteristic profile graph and the image of the graph to be detected, and capturing graph differences.
2. The defect detection method of claim 1, wherein: and the information file of the graph to be detected in the first step comprises the position information and the image information of the graph to be detected.
3. The defect detection method of claim 1, wherein: the reference pattern of the pattern to be detected in the first step is a pattern with the same relative coordinates of the pattern to be detected in other unit chips in the same wafer, or a pattern with the same coordinates of other unit chips of other wafers in the same process.
4. The defect detection method of claim 3, wherein: the reference pattern in the first step is a sample pattern generated by pattern analysis software from the same coordinate patterns of the pattern to be detected in other unit chips in the same wafer or the same coordinate patterns of other unit chips in the same wafer in a plurality of same processes.
5. The defect detection method of claim 1, wherein: and the reference graph in the step one is the graph in the original GDS file of the graph to be detected or other files containing the structure and the coordinate information of the graph to be detected.
6. The defect detection method of claim 2, wherein: and in the second step, searching the image of the graph to be detected according to the position information of the graph to be detected.
7. The defect detection method of claim 6, wherein: and in the second step, searching the image of the graph to be detected according to the coordinate information of the graph to be detected.
8. The defect detection method according to claim 1 or 4, characterized in that: and in the third step, the feature profile generated by the reference graph is a two-dimensional feature profile.
9. The defect detection method according to claim 1 or 4, characterized in that: and in the third step, the feature profile generated by the reference graph is a three-dimensional feature profile.
10. The defect detection method of claim 1, wherein: the method for capturing the graph difference in the fourth step comprises the following steps: the system sets a difference interval value, and if the difference value between the characteristic profile graph and the graph to be detected after comparison by the graph analysis software is within the interval value, the system does not report an error; if the difference value is not within the interval value, the system will report an error and identify the difference after comparison.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2022134305A1 (en) * | 2020-12-21 | 2022-06-30 | 东方晶源微电子科技（北京）有限公司 | Wafer defect detection method and apparatus, device and storage medium |
| CN116758073A (en) * | 2023-08-17 | 2023-09-15 | 粤芯半导体技术股份有限公司 | Mask plate data detection method and system |
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| CN1869667A (en) * | 2006-06-08 | 2006-11-29 | 李贤伟 | Profile analysing method for investigating defect of printed circuit board |
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