CN113013048A - Wafer defect detection method - Google Patents
Wafer defect detection method Download PDFInfo
- Publication number
- CN113013048A CN113013048A CN202110205022.1A CN202110205022A CN113013048A CN 113013048 A CN113013048 A CN 113013048A CN 202110205022 A CN202110205022 A CN 202110205022A CN 113013048 A CN113013048 A CN 113013048A
- Authority
- CN
- China
- Prior art keywords
- defect
- detection method
- wafer
- defects
- defect detection
- 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.)
- Pending
Links
- 230000007547 defect Effects 0.000 title claims abstract description 92
- 238000001514 detection method Methods 0.000 title claims abstract description 20
- 238000005070 sampling Methods 0.000 claims abstract description 24
- 230000003252 repetitive effect Effects 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims description 10
- 239000002184 metal Substances 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000007689 inspection Methods 0.000 claims description 6
- 230000035945 sensitivity Effects 0.000 abstract description 5
- 239000002699 waste material Substances 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/10—Measuring as part of the manufacturing process
- H01L22/12—Measuring as part of the manufacturing process for structural parameters, e.g. thickness, line width, refractive index, temperature, warp, bond strength, defects, optical inspection, electrical measurement of structural dimensions, metallurgic measurement of diffusions
Landscapes
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Computer Hardware Design (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Power Engineering (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 invention discloses a wafer defect detection method, which comprises the following steps: step one, importing a wafer scanning result; step two, importing the machine program information and reading the scanning area; step three, judging the scanning mode, if the scanning mode is judged to be a non-repetitive unit, entering the step four; if the scanning mode is judged to be the repeated unit, entering a step six; step four, adopting normal rule defect sampling; step five, normally calculating the defect number, and then finishing; step six, judging the number of the repeated unit areas; seventhly, sampling the defects in different areas; and step eight, calculating the defect quantity in different areas, and then finishing. The wafer defect detection method provided by the invention does not waste the machine productivity, and can improve the sensitivity of defect detection.
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 prior art, the wafer defect detection is generally performed randomly according to the total number of defects, and particularly for some tiny defects, the accurate defect number cannot be obtained. Or in order to obtain the accurate defect number, the program is disassembled into a plurality of programs so as to obtain the defect numbers distributed in different areas, but the scanning time is greatly increased, and the productivity of the machine is reduced.
Disclosure of Invention
The invention aims to solve the technical problem of providing a wafer defect detection method, which does not waste the productivity of a machine and can improve the sensitivity of defect detection.
The wafer defect detection method comprises the following steps:
step one, importing the wafer scanning result
Step two, importing the machine program information and reading the scanning area
Step three, judging the scanning mode, if the scanning mode is judged to be a non-repetitive unit, entering the step four; if the scanning mode is judged to be the repeated unit, entering a step six;
step four, adopting normal rule defect sampling;
step five, normally calculating the defect number, and then finishing;
step six, judging the number of the repeated unit areas;
seventhly, sampling the defects in different areas;
and step eight, calculating the defect quantity in different areas, and then finishing.
Further, the normal rule defect sampling described in the fourth step is a random sampling rule.
Further, the regional defect sampling in the seventh step is an array sampling rule.
Further, the normal method for calculating the number of defects is to divide the number of defects by the total number of moving clusters and multiply the number of inspections.
Further, the defect is a metal disconnection defect.
Further, the number of the repeating unit regions is i, and i is not less than 2.
Further, the sum of the number of the regional calculation defects is counted as the total number of the defects.
Further, the method for calculating the number of defects of each area comprises the steps of dividing the number of defects of each area by the total number of the moving clusters of each area and multiplying the number of the checks of each area.
The invention changes the sampling rule without changing the scanning mode, judges one scanning mode on the original basis, separately samples different scanning modes, and can be realized by reading the scanning program through the Klaity defect detector, thereby saving the productivity of the machine and simultaneously not reducing the sensitivity of the defects. The sensitivity of defect inspection using this calculation method is similar to the method of splitting the program into multiple parts, but will not reduce the throughput of the machine.
Drawings
FIG. 1 is a schematic diagram of the steps of the method of the present invention.
FIG. 2 is a diagram of a scan area and a main defect distribution.
FIG. 3 is a diagram illustrating a defect inspection sampling and calculating method in the prior art, which is a program divided into multiple parts.
Detailed Description
When a scan program is established for wafer defect detection, it is first necessary to determine which defects are repetitive units and non-repetitive units to determine the scanning mode, and an array mode is used for repetitive units such as SRAM structures, and a random mode is used for non-repetitive units. During the development of 14nm M109, the SRAM194 is found to have a large number of metal line-break defects, as shown in FIG. 2, but only a few metal line-break defects can be detected by the conventional sampling observation method, and the defects are extremely small and can be swept only in the array mode.
In the specific example, 12589 defects are scanned totally, 200 defects are sampled and observed, and 2 metal disconnection defects are observed, according to the traditional calculation method: normal bridge defect count/remove cluster total count 2/200 re view count 3500 ea;
in the prior art, the defect is improved by splitting the scanning program into three pieces of SRAM194+
SRAM691&907+ Periphery area, but what promote is the time of scanning, what reduce is the productivity of the board, delay is the progress of developing;
SRAM194 hip is sampled and observed for 200ea in a separation mode, metal disconnection defects 89ea are observed, and according to a defect number calculation method: normal bridge defect count/remove cluster total count 89/200 × 1425 634 ea; much larger than the previous 35 ea; but the productivity is reduced by 40%;
FIG. 1 is a schematic diagram illustrating a wafer defect inspection method according to the present invention.
The wafer defect detection method comprises the following steps:
step one, importing the wafer scanning result
Step two, importing the machine program information and reading the scanning area
Step three, judging the scanning mode, if the scanning mode is judged to be a non-repetitive unit, entering the step four; if the scanning mode is judged to be the repeated unit, entering a step six;
step four, adopting normal rule defect sampling;
step five, normally calculating the defect number, and then finishing;
step six, judging the number of the repeated unit areas;
seventhly, sampling the defects in different areas;
and step eight, calculating the defect quantity in different areas, and then finishing.
The normal rule defect sampling described in step four is a random sampling rule.
And seventhly, sampling the defect in the areas by areas according to an array sampling rule.
The normal method for calculating the defect number is to divide the defect number by the total number of the moving clusters and multiply the number of the checks. The defect is a metal disconnection defect. The number of the repeating unit regions in this embodiment is 2.
And adding the number of defects of each repeating unit area, wherein the number of defects of each repeating unit area is the number of defects of the area divided by the total number of the moving clusters of the area and multiplied by the number of checks of the area. In this embodiment, the normalized bridge defect count is 42/100 1490+0/100 2010 625ea
The invention changes the sampling rule without changing the scanning mode, namely, judges one scanning mode on the original basis, and separately samples the array mode and the random mode, which can be realized by reading the scanning program by the Klary defect detector, thereby saving the productivity of the machine and simultaneously not reducing the sensitivity of the defect. Simulating a calculable normalized bridge defectcount (42/100) 1490+0/100 (2010) 625ea in the calculation mode; the former 634ea is approached, and the productivity of the machine is also saved.
The present invention has been described in detail with reference to the specific embodiments and examples, but these are not intended to limit the present invention. Many variations and modifications may be made by one of ordinary skill in the art without departing from the principles of the present invention, which should also be considered as within the scope of the present invention.
Claims (8)
1. A wafer defect detection method is characterized by comprising the following steps:
step one, importing a wafer scanning result;
step two, importing the machine program information and reading the scanning area;
step three, judging the scanning mode, if the scanning mode is judged to be a non-repetitive unit, entering the step four; if the scanning mode is judged to be the repeated unit, entering a step six;
step four, adopting normal rule defect sampling;
step five, normally calculating the defect number, and then finishing;
step six, judging the number of the repeated unit areas;
seventhly, sampling the defects in different areas;
and step eight, calculating the defect quantity in different areas, and then finishing.
2. The wafer defect detection method of claim 1, wherein:
the normal rule defect sampling described in step four is a random sampling rule.
3. The wafer defect detection method of claim 1, wherein:
and seventhly, sampling the defect in the areas by areas according to an array sampling rule.
4. The wafer defect detection method of claim 1, wherein:
the normal method of calculating the number of defects is to divide the number of defects by the total number of moving clusters and multiply the number of inspections.
5. The wafer defect detection method of claim 1, wherein:
the defect is a metal disconnection defect.
6. The wafer defect detection method of claim 1, wherein:
the number of the repeating unit areas is i, and i is greater than or equal to 2.
7. The wafer defect detection method of claim 6, wherein:
and calculating the sum of the number of the regional calculation defects as the total number of the defects.
8. The wafer defect detection method of claim 7, wherein:
the method for calculating the defect number of each area comprises the step of dividing the defect number of each area by the total number of the movable clusters of each area and multiplying the defect number of each area by the inspection number of each area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110205022.1A CN113013048A (en) | 2021-02-24 | 2021-02-24 | Wafer defect detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110205022.1A CN113013048A (en) | 2021-02-24 | 2021-02-24 | Wafer defect detection method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113013048A true CN113013048A (en) | 2021-06-22 |
Family
ID=76409055
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110205022.1A Pending CN113013048A (en) | 2021-02-24 | 2021-02-24 | Wafer defect detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113013048A (en) |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS6147635A (en) * | 1984-08-14 | 1986-03-08 | Nippon Jido Seigyo Kk | Pattern inspection method using pattern defect inspection apparatus |
| KR960026515A (en) * | 1994-12-28 | 1996-07-22 | 김주용 | Semiconductor wafer inspection apparatus and method |
| KR20010018786A (en) * | 1999-08-23 | 2001-03-15 | 윤종용 | Inspection Method of weak Point of Semiconductor Wafer |
| JP2001281164A (en) * | 1989-12-20 | 2001-10-10 | Hitachi Ltd | Method and device for inspecting pattern |
| KR20040008417A (en) * | 2002-07-18 | 2004-01-31 | 주식회사 하이닉스반도체 | Detecting method for defect of wafer |
| CN101238346A (en) * | 2005-06-06 | 2008-08-06 | 恪纳腾技术公司 | Computer-implemented methods for performing defect-related functions |
| US20080205745A1 (en) * | 2007-02-28 | 2008-08-28 | Chen Chien-Huei Adam | Methods for accurate identification of an edge of a care area for an array area formed on a wafer and methods for binning defects detected in an array area formed on a wafer |
| JP2009218570A (en) * | 2008-02-15 | 2009-09-24 | Fujitsu Microelectronics Ltd | Defect control system and defect control method |
| CN101681862A (en) * | 2008-03-28 | 2010-03-24 | 外知铺乐内特有限公司 | Fpd substrate and semiconductor wafer inspection system using duplicate images |
| CN103887198A (en) * | 2014-03-20 | 2014-06-25 | 上海华力微电子有限公司 | Method for scanning storage regions without repeated boundaries |
| CN103928365A (en) * | 2014-04-28 | 2014-07-16 | 上海华力微电子有限公司 | Method for defect scanning of unit chips with different picture conditions in photomask |
| US20150042978A1 (en) * | 2013-08-06 | 2015-02-12 | Kla-Tencor Corporation | Setting Up a Wafer Inspection Process Using Programmed Defects |
| CN104465441A (en) * | 2014-11-26 | 2015-03-25 | 上海华力微电子有限公司 | Defect detection method |
| CN104698741A (en) * | 2003-07-03 | 2015-06-10 | 恪纳腾技术公司 | Methods and systems for inspection of wafers and reticles using designer intent data |
| CN106662538A (en) * | 2014-08-27 | 2017-05-10 | 科磊股份有限公司 | Pereater detection |
| CN109977808A (en) * | 2019-03-11 | 2019-07-05 | 北京工业大学 | A kind of wafer surface defects mode detection and analysis method |
| US20190277776A1 (en) * | 2018-03-09 | 2019-09-12 | Kla-Tencor Corporation | Detecting die repeating programmed defects located in backgrounds with non-repeating features |
-
2021
- 2021-02-24 CN CN202110205022.1A patent/CN113013048A/en active Pending
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS6147635A (en) * | 1984-08-14 | 1986-03-08 | Nippon Jido Seigyo Kk | Pattern inspection method using pattern defect inspection apparatus |
| JP2001281164A (en) * | 1989-12-20 | 2001-10-10 | Hitachi Ltd | Method and device for inspecting pattern |
| KR960026515A (en) * | 1994-12-28 | 1996-07-22 | 김주용 | Semiconductor wafer inspection apparatus and method |
| KR20010018786A (en) * | 1999-08-23 | 2001-03-15 | 윤종용 | Inspection Method of weak Point of Semiconductor Wafer |
| KR20040008417A (en) * | 2002-07-18 | 2004-01-31 | 주식회사 하이닉스반도체 | Detecting method for defect of wafer |
| CN104698741A (en) * | 2003-07-03 | 2015-06-10 | 恪纳腾技术公司 | Methods and systems for inspection of wafers and reticles using designer intent data |
| CN101238346A (en) * | 2005-06-06 | 2008-08-06 | 恪纳腾技术公司 | Computer-implemented methods for performing defect-related functions |
| US20080205745A1 (en) * | 2007-02-28 | 2008-08-28 | Chen Chien-Huei Adam | Methods for accurate identification of an edge of a care area for an array area formed on a wafer and methods for binning defects detected in an array area formed on a wafer |
| JP2009218570A (en) * | 2008-02-15 | 2009-09-24 | Fujitsu Microelectronics Ltd | Defect control system and defect control method |
| CN101681862A (en) * | 2008-03-28 | 2010-03-24 | 外知铺乐内特有限公司 | Fpd substrate and semiconductor wafer inspection system using duplicate images |
| US20150042978A1 (en) * | 2013-08-06 | 2015-02-12 | Kla-Tencor Corporation | Setting Up a Wafer Inspection Process Using Programmed Defects |
| TW201511156A (en) * | 2013-08-06 | 2015-03-16 | Kla Tencor Corp | Setting up a wafer inspection process using programmed defects |
| CN103887198A (en) * | 2014-03-20 | 2014-06-25 | 上海华力微电子有限公司 | Method for scanning storage regions without repeated boundaries |
| CN103928365A (en) * | 2014-04-28 | 2014-07-16 | 上海华力微电子有限公司 | Method for defect scanning of unit chips with different picture conditions in photomask |
| CN106662538A (en) * | 2014-08-27 | 2017-05-10 | 科磊股份有限公司 | Pereater detection |
| CN104465441A (en) * | 2014-11-26 | 2015-03-25 | 上海华力微电子有限公司 | Defect detection method |
| US20190277776A1 (en) * | 2018-03-09 | 2019-09-12 | Kla-Tencor Corporation | Detecting die repeating programmed defects located in backgrounds with non-repeating features |
| CN109977808A (en) * | 2019-03-11 | 2019-07-05 | 北京工业大学 | A kind of wafer surface defects mode detection and analysis method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP4014379B2 (en) | Defect review apparatus and method | |
| US5844850A (en) | Apparatus for analyzing a failure in a semiconductor wafer and method thereof | |
| US7975245B2 (en) | Computer-implemented methods for determining if actual defects are potentially systematic defects or potentially random defects | |
| JP3566470B2 (en) | Pattern inspection method and apparatus | |
| US10146036B2 (en) | Semiconductor wafer inspection using care area group-specific threshold settings for detecting defects | |
| JP4799574B2 (en) | Method and apparatus for detecting linear pattern | |
| US20020052053A1 (en) | Inspection system and semiconductor device manufacturing method | |
| CN1672038A (en) | System and method for process variation monitor | |
| JP2003086645A (en) | Inspection device, inspection system and method for manufacturing semiconductor device | |
| CN1975741A (en) | System and method for product yield prediction | |
| KR20010093674A (en) | Apparatus for testing semiconductor, for analizing defects in semiconductor, for correcting semiconductor design data, and method trherefor, and computer readable recording media | |
| JP2004177397A (en) | Method and apparatus for inspecting image defect, and device for inspecting appearance | |
| CN102129164A (en) | Method and system for judging mask defects | |
| JPH03232250A (en) | Method and device for inspecting pattern | |
| US20120185818A1 (en) | Method for smart defect screen and sample | |
| JP4711570B2 (en) | Pattern inspection method and inspection apparatus | |
| US10719655B2 (en) | Method and system for quickly diagnosing, classifying, and sampling in-line defects based on CAA pre-diagnosis database | |
| US6009545A (en) | System for analyzing a failure in a semiconductor wafer by calculating correlation coefficient between collated data of defects per prescribed unit and failures per prescribed unit | |
| JPH08162510A (en) | Device and method for estimating yield | |
| CN112086373A (en) | Wafer defect detection method | |
| CN114140425A (en) | Detection method for wafer back defect | |
| CN111653500A (en) | Method for judging wafer yield loss | |
| US6539272B1 (en) | Electric device inspection method and electric device inspection system | |
| CN113013048A (en) | Wafer defect detection method | |
| JP2004079593A (en) | Contamination inspection method and device thereof |
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 |