CN116297524B - Multi-mode detection method for wafer with image - Google Patents
Multi-mode detection method for wafer with image Download PDFInfo
- Publication number
- CN116297524B CN116297524B CN202310363772.0A CN202310363772A CN116297524B CN 116297524 B CN116297524 B CN 116297524B CN 202310363772 A CN202310363772 A CN 202310363772A CN 116297524 B CN116297524 B CN 116297524B
- Authority
- CN
- China
- Prior art keywords
- mode
- wafer
- defect
- detection
- modes
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 47
- 230000007547 defect Effects 0.000 claims abstract description 45
- 230000004927 fusion Effects 0.000 claims abstract description 9
- 235000012431 wafers Nutrition 0.000 claims description 29
- 230000003287 optical effect Effects 0.000 claims description 25
- 239000013598 vector Substances 0.000 claims description 19
- 238000006073 displacement reaction Methods 0.000 claims description 9
- 230000003068 static effect Effects 0.000 claims description 7
- 238000003384 imaging method Methods 0.000 claims description 6
- 238000010586 diagram Methods 0.000 claims description 5
- 210000001747 pupil Anatomy 0.000 claims description 5
- 238000013041 optical simulation Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 2
- 239000004065 semiconductor Substances 0.000 abstract description 4
- 230000035945 sensitivity Effects 0.000 abstract description 2
- 238000007689 inspection Methods 0.000 description 9
- 238000000034 method Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/9501—Semiconductor wafers
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Testing Or Measuring Of Semiconductors Or The Like (AREA)
Abstract
The application discloses a multi-mode detection method of an image wafer, which belongs to the field of semiconductor detection and comprises multi-mode wafer scanning, optimal mode selection, registration of images of different modes and multi-mode fusion detection defect judgment; the application can select the most suitable scanning mode according to different types of defects, improves the sensitivity and the robustness of detection, has high detection efficiency, and can be popularized and applied in the field of wafer broad spectrum detection.
Description
Technical Field
The application belongs to the field of semiconductor detection, and particularly relates to a multi-mode detection method for a wafer with an image.
Background
Wafer inspection is a quality guarantee of the subsequent process of the semiconductor, and in the existing optical inspection, different divisions such as bright field inspection and dark field inspection are commonly used, however, these are all single imaging, which results in reduced inspection throughput and single inspection defect types.
With the development of image processing technology, the application expects to make up the problem of low detection efficiency by multi-mode fusion detection by fusing detection images under different modes.
Disclosure of Invention
In order to overcome the defects in the prior art, the present application is directed to a multi-mode inspection method for an image wafer, which can solve the above-mentioned problems.
Design principle: and scanning the wafer for multiple times by utilizing a plurality of detection devices with different angles or wavelengths, and carrying out fusion processing on images obtained in different scanning modes, thereby realizing the multi-angle, multi-scale and multi-feature comprehensive analysis of the wafer defects.
A multi-mode detection method for an image wafer comprises the following steps: scanning the wafer in multiple modes, and scanning the wafer in each mode in sequence through detection equipment to obtain a wafer image in multiple modes; selecting an optimal mode, namely selecting a main mode and a second optical mode based on the interested defect and the signal distribution thereof; registering images of different modes, acquiring a static TDI image and a scanning TDI image based on a positioning pattern, and registering to obtain a relative displacement error; and judging the true defects based on the distances between the feature vector group of the defect difference diagram and the core signals by multi-mode fusion detection defect judgment.
Further, the multiple modes of the detection device include different optical combinations of different wavelengths, different angles, pupil shapes, polarized light, imaging focal lengths.
Compared with the prior art, the application has the beneficial effects that: the multi-mode detection method can select the most suitable scanning mode (combination of different wavelengths, pupil shapes, polarized light and imaging focal length) according to different types of defects, and improves the sensitivity and the robustness of detection; the multi-mode information can be used for complementation and correction, so that the possibility of false detection and omission is reduced; the switching and adjustment of multiple scanning modes can be realized in a single system, and the flexibility and efficiency of detection are improved; the system can be compatible and integrated with the existing bright field detection system, and hardware equipment or a software platform does not need to be replaced. The scheme can be popularized and applied in the field of wafer broad spectrum detection.
Drawings
FIG. 1 is a flow chart of a multi-mode inspection method for an imaged wafer;
fig. 2 is a schematic diagram corresponding to fig. 1.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1 and 2, a multi-mode inspection method of an image wafer includes the following steps.
And scanning the wafer in multiple modes, and scanning the wafer in each mode in sequence through detection equipment to obtain wafer images in multiple modes. Wherein the multiple modes of the detection device comprise different optical combinations of different wavelengths, different angles, pupil shapes, polarized light, imaging focal lengths.
And selecting an optimal mode, namely selecting a main mode and a second optical mode based on the interested defect and the signal distribution thereof.
Specifically, the optimal mode selection includes the following steps.
S11, selecting a main mode, and determining a main optical mode as the main mode through optical simulation aiming at given wafers and defects of interest (DOI) of clients. Specifically, optical simulation is to determine in which optical mode (wavelength, polarization, defocus, and pupil shape) the optical signal of the defect is strongest by solving maxwell's equations for diffraction imaging.
In the main optical mode, all DOIs can be detected, but the false detection rate has not yet reached the requirement.
S12, randomly sampling, and randomly extracting 10-20 defects of interest and defects of false detection.
S13, traversing other optical modes and generating signal distribution of the interested defects.
Specifically, an existing bright field detection system is used for traversing optical modes set into other various optional combinations, and then spot scanning is carried out on the DOI and the false detection defect which are randomly extracted, so that a local image is obtained. And performing defect detection on the image to obtain a defect signal, and drawing the signal and the optical mode into a signal distribution diagram in a one-to-one correspondence manner.
S14, selecting a second mode, and selecting the optical mode with strong sampled defect signals of interest as the second optical mode.
And registering images of different modes, acquiring a static TDI image and a scanning TDI image based on the positioning pattern, and registering to obtain a relative displacement error. TDI is an image acquisition sensor based on time delay integration.
In particular, the registration of the different modality images comprises the following steps.
S21, positioning a special pattern on the wafer as a positioning pattern (alignment mark).
S22, the main mode and the second mode are used for respectively acquiring the static TDI image and the scanning TDI image of the positioning pattern.
S23, registering the scanning TDI images and the static TDI images under different modes to obtain relative displacement errors, wherein the relative displacement errors represent the displacement between the scanning images under different optical modes and are used for registering the two different optical modes.
And judging the true defects based on the distances between the feature vector group of the defect difference diagram and the core signals by multi-mode fusion detection defect judgment. After the two optical modes are determined, signals of two different modes are utilized to enhance the signals of the true defects, and the false detection defect signals are restrained.
Specifically, the multi-mode fusion detection defect determination includes the following steps.
S31, extracting local feature vectors, and extracting the local feature vectors from wafer defect difference graphs of different modes.
S32, calculating a core signal, taking the local feature vector of each mode as a group, and taking the feature vector group under different modes as an average value in a feature space to serve as the core signal.
S33, calculating the distance between each feature vector and the corresponding core signal (Correlation Distance). The operation formula is as follows: correlation Distance = Σ i Dot (FVi, centroid). Where Dot is a vector Dot product, FVi is the i-th vector feature, centroid is a core signal of the feature vector space, and i is a positive integer greater than or equal to 2.
S34, judging the true defect and the false defect according to the distance obtained in the S33, wherein the larger the distance is, the more likely the true defect is.
Since the multi-mode fusion detection needs to scan the wafer sequentially for each mode on the existing single-channel bright field detection system, the performance improvement of the multi-mode fusion detection needs to be able to compensate the loss of wafer throughput caused by the detection mode. The scheme can be popularized and applied to the detection of the wide-spectrum bright field defects of the semiconductor wafer.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims (4)
1. The multi-mode detection method for the wafer with the image is characterized by comprising the following steps of:
scanning the wafer in multiple modes, and scanning the wafer in each mode in sequence through detection equipment to obtain a wafer image in multiple modes;
selecting an optimal mode, namely selecting a main mode and a second optical mode based on the interested defect and the signal distribution thereof;
registering images of different modes, acquiring a static TDI image and a scanning TDI image based on a positioning pattern, and registering to obtain a relative displacement error;
detecting defect judgment by multi-mode fusion, and judging true defects based on the distance between a feature vector group of a defect difference diagram and a core signal;
wherein, the multi-mode fusion detection defect determination includes:
s31, extracting local feature vectors, and extracting the local feature vectors from wafer defect difference graphs of different modes;
s32, calculating a core signal, taking the local feature vector of each mode as a group, and taking the feature vector group under different modes as an average value in a feature space to serve as the core signal;
s33, calculating the distance Correlation Distance, correlation Distance delta sigma of the core signal corresponding to each feature vector i Dot (FVi, centroid); wherein Dot is a vector Dot product, FVi is an ith vector feature, centroid is a core signal of a feature vector space, and i is a positive integer greater than or equal to 2;
s34, judging the true defect and the false defect according to the distance obtained in the S33, wherein the larger the distance is, the more likely the true defect is.
2. The multi-modality detection method of claim 1, wherein the optimal modality selection includes:
s11, selecting a main mode, and determining a main optical mode as a main mode by optical simulation aiming at given wafers and interested defects of clients;
s12, randomly sampling, and randomly extracting 10-20 defects of interest and defects of false detection;
s13, traversing other optical modes and generating signal distribution of the interested defects;
s14, selecting a second mode, and selecting the optical mode with strong sampled defect signals of interest as the second optical mode.
3. The multi-modality detection method of claim 1, wherein the registration of the different modality images includes:
s21, positioning a special pattern on the wafer to serve as a positioning pattern;
s22, respectively acquiring a static TDI image and a scanning TDI image of the positioning pattern by using a main mode and a second mode;
s23, registering the scanning TDI images and the static TDI images under different modes to obtain relative displacement errors, wherein the relative displacement errors represent the displacement between the scanning images under different optical modes and are used for registering the two different optical modes.
4. The multi-modality detection method of claim 1, wherein: the multiple modes of the detection device comprise different optical combinations of different wavelengths, different angles, pupil shapes, polarized light, imaging focal lengths.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310363772.0A CN116297524B (en) | 2023-04-07 | 2023-04-07 | Multi-mode detection method for wafer with image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310363772.0A CN116297524B (en) | 2023-04-07 | 2023-04-07 | Multi-mode detection method for wafer with image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116297524A CN116297524A (en) | 2023-06-23 |
| CN116297524B true CN116297524B (en) | 2023-11-14 |
Family
ID=86799634
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310363772.0A Active CN116297524B (en) | 2023-04-07 | 2023-04-07 | Multi-mode detection method for wafer with image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116297524B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPWO2002040980A1 (en) * | 2000-11-17 | 2004-03-25 | 株式会社荏原製作所 | Substrate inspection method, substrate inspection device, and electron beam device |
| KR20110020437A (en) * | 2009-08-24 | 2011-03-03 | 주식회사 동부하이텍 | Inspection method of patterned wafer for detecting defects |
| JP2012021919A (en) * | 2010-07-16 | 2012-02-02 | Keyence Corp | Image processing system, image processing method and computer program |
| JP2015041164A (en) * | 2013-08-20 | 2015-03-02 | キヤノン株式会社 | Image processor, image processing method and program |
| CN106872487A (en) * | 2017-04-21 | 2017-06-20 | 佛山市南海区广工大数控装备协同创新研究院 | The surface flaw detecting method and device of a kind of view-based access control model |
| CN110911298A (en) * | 2018-09-18 | 2020-03-24 | 台湾积体电路制造股份有限公司 | Method for determining wafer inspection parameters |
| CN111754553A (en) * | 2020-06-24 | 2020-10-09 | 上海联影医疗科技有限公司 | Multi-modal scanning image registration method and device, computer equipment and storage medium |
| CN113196173A (en) * | 2018-12-14 | 2021-07-30 | Asml荷兰有限公司 | Apparatus and method for grouping image patterns to determine wafer behavior during patterning |
| CN113670935A (en) * | 2021-08-25 | 2021-11-19 | 武汉中导光电设备有限公司 | Semiconductor wafer defect detection equipment and detection method |
| CN115513082A (en) * | 2022-09-27 | 2022-12-23 | 中电科风华信息装备股份有限公司 | Method and system for realizing multi-mode and multi-position detection of wafer |
| CN115719326A (en) * | 2021-08-24 | 2023-02-28 | 中国电子技术标准化研究院 | PCB defect detection method and device |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3550347B2 (en) * | 2000-07-21 | 2004-08-04 | 松下電器産業株式会社 | Display method |
| US8045788B2 (en) * | 2003-07-14 | 2011-10-25 | August Technology Corp. | Product setup sharing for multiple inspection systems |
| US11922613B2 (en) * | 2019-12-30 | 2024-03-05 | Micron Technology, Inc. | Apparatuses and methods for determining wafer defects |
-
2023
- 2023-04-07 CN CN202310363772.0A patent/CN116297524B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPWO2002040980A1 (en) * | 2000-11-17 | 2004-03-25 | 株式会社荏原製作所 | Substrate inspection method, substrate inspection device, and electron beam device |
| KR20110020437A (en) * | 2009-08-24 | 2011-03-03 | 주식회사 동부하이텍 | Inspection method of patterned wafer for detecting defects |
| JP2012021919A (en) * | 2010-07-16 | 2012-02-02 | Keyence Corp | Image processing system, image processing method and computer program |
| JP2015041164A (en) * | 2013-08-20 | 2015-03-02 | キヤノン株式会社 | Image processor, image processing method and program |
| CN106872487A (en) * | 2017-04-21 | 2017-06-20 | 佛山市南海区广工大数控装备协同创新研究院 | The surface flaw detecting method and device of a kind of view-based access control model |
| CN110911298A (en) * | 2018-09-18 | 2020-03-24 | 台湾积体电路制造股份有限公司 | Method for determining wafer inspection parameters |
| CN113196173A (en) * | 2018-12-14 | 2021-07-30 | Asml荷兰有限公司 | Apparatus and method for grouping image patterns to determine wafer behavior during patterning |
| CN111754553A (en) * | 2020-06-24 | 2020-10-09 | 上海联影医疗科技有限公司 | Multi-modal scanning image registration method and device, computer equipment and storage medium |
| CN115719326A (en) * | 2021-08-24 | 2023-02-28 | 中国电子技术标准化研究院 | PCB defect detection method and device |
| CN113670935A (en) * | 2021-08-25 | 2021-11-19 | 武汉中导光电设备有限公司 | Semiconductor wafer defect detection equipment and detection method |
| CN115513082A (en) * | 2022-09-27 | 2022-12-23 | 中电科风华信息装备股份有限公司 | Method and system for realizing multi-mode and multi-position detection of wafer |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116297524A (en) | 2023-06-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109559348B (en) | Bridge non-contact deformation measurement method based on feature point tracking | |
| US9846930B2 (en) | Detecting defects on a wafer using defect-specific and multi-channel information | |
| CN111106055B (en) | Wafer position determining method | |
| KR102379872B1 (en) | Detecting defects on a wafer using defect-specific information | |
| US7330581B2 (en) | Image defect inspection method, image defect inspection apparatus and appearance inspection apparatus | |
| US20130294677A1 (en) | Defect inspection method and defect inspection device | |
| CN101424645B (en) | Soldered ball surface defect detection device and method based on machine vision | |
| JP4275345B2 (en) | Pattern inspection method and pattern inspection apparatus | |
| KR100598381B1 (en) | in-line typed apparatus for auto wafer-defect classification and control method thereof | |
| JP2005156475A (en) | Pattern defect inspection device and method | |
| TW201636602A (en) | Systems and methods for enhancing inspection sensitivity of an inspection tool | |
| JP2010164487A (en) | Defect inspecting apparatus and defect inspecting method | |
| CN116297524B (en) | Multi-mode detection method for wafer with image | |
| CN117007940A (en) | Self-adaptive method for detecting performance of circuit board | |
| US8606017B1 (en) | Method for inspecting localized image and system thereof | |
| CN116563298A (en) | Cross line center sub-pixel detection method based on Gaussian fitting | |
| JP2009097959A (en) | Defect detecting device and defect detection method | |
| JP2009222625A (en) | Device and method for inspecting pattern | |
| JP2000321038A (en) | Method for detecting fault of pattern | |
| CN113916904B (en) | Method and system for detecting surface defects of wafer | |
| JP4483039B2 (en) | Inspection device | |
| JPH05133729A (en) | Method and device for measuring surface of object | |
| CN117392158A (en) | Image processing method, system, device and storage medium | |
| CN118261870A (en) | Image-based inductance defect detection method and device and electronic equipment | |
| JP2003281538A (en) | Image processor, image inspecting method and printing failure detecting method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |