CN117197617A - Defect classification method and system for repeated defects - Google Patents
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Abstract
The invention relates to the field of wafer detection, in particular to a defect classification method and system for repeated defects. The method comprises the following steps: acquiring a position information set of at least one group of repeated defects of a wafer; acquiring a total sampling number and a sampling proportion relation corresponding to sampling positions of a wafer so as to determine the area sampling number in different sampling areas of the wafer according to the total sampling number and the sampling proportion relation from a plurality of sampling areas divided in advance on the wafer; respectively selecting corresponding sampling positions from a plurality of sampling areas according to the sampling quantity of the areas; photographing at the selected sampling positions respectively, so as to obtain a defect photo set corresponding to at least one group of repeated defects; and classifying the repeated defects through the defect photo set. The invention actually provides a standardized sampling flow capable of improving sampling automation, and the automatic sampling method can perform low-correlation sampling in a correlation area, thereby ensuring the reliability of limited sample data.
Description
Technical Field
The invention relates to the field of wafer defect detection, in particular to a defect classification method and system for repeated defects.
Background
In the manufacture of semiconductor wafers, in a series of processes such as single crystal pulling, slicing, lapping, polishing, layering, photolithography, doping, heat treatment, needle testing, dicing, etc., chemical vapor deposition, optical development, and chemical mechanical polishing may cause defects on the wafer surface during the processes, and the defects on the wafer may directly affect the service life and reliability.
At present, the common classification flow of wafer defects is as follows:
firstly, utilizing defect scanning equipment to initially find defects to be classified. See, for example, CN115172199a for a method and system for identifying wafer defects. The method utilizes the density distribution characteristics of the aggregation type defects to widely identify the aggregation type defects (namely cluster point defects) so as to guide the subsequent accurate defect classification.
And step two, selecting a photographing scheme according to the scanning condition of the defects to be classified in the step one.
Specifically, when the number of identified defects is relatively small, then the defect photographs are taken one by one for the occurrence positions of the defects. For example, the invention patent application of publication number CN103344660a discloses an electron microscopic analysis method for defect detection in accordance with a circuit pattern. The analysis method converts a defect position file obtained by preliminary scanning into a defect file with a characteristic circuit pattern, and then an electron microscope determines the defect position by comparing the characteristic circuit patterns in the defect file, so that all the defect positions are photographed and sampled one by one. For another example, the invention of publication number CN113013048A discloses a wafer defect detection method that employs an array sampling rule for repeating units to more fully sample wafer defects.
However, when the number of recognized cluster point defects is too large, the acquisition pressure of the defective image is also significantly increased. At this time, it is generally only possible to take a random point-taking picture on the wafer according to the current defect recognition situation. Before production, the staff sets sampling detection rules according to the production process indexes (such as wafer design netlist) proposed by upstream clients and combined with defect distribution, quantity, production management system and other factors.
In addition, in the prior art, an attempt is made to improve the detection accuracy by means of multi-photo stitching. Wherein,
the invention patent application with publication number of CN115132599A discloses a defect detection method, wherein a plurality of initial detection pictures are obtained by photographing defects to be detected at multiple angles, and a final detection picture is obtained by adopting a picture splicing mode so as to improve detection precision. However, this method of detecting multi-picture stitching certainly requires a lot of machine resources.
And thirdly, inputting all wafer scanning results (such as photographing scanning results) into an automatic defect classification model (for example, an ADC defect classification model) for automatic defect classification, or manually classifying by a worker.
In the current wafer defect detection process, the photographing scheme in the second step is usually manually selected by an engineer. However, the production line of wafers is usually operated continuously for 24 hours, and once one of the devices or one of the links fails, the delay of the whole production line is greatly affected. The real-time detection efficiency of defects in the factory is very high. The manual selection of the photographing scheme has relatively serious problems of time occupation and machine resource occupation. Especially, aiming at the conditions that the process graph of the wafer is relatively complex and the defect type and distribution are relatively wide, the time-consuming problem of the second step seriously affects the operation and maintenance work of the whole production line.
For example, the invention patent application publication number CN115015289a discloses an integrated circuit defect detection method, in which a designer can divide the functional importance of a chip for different areas in an integrated circuit according to actual situations in the design stage of a chip design netlist (GDS), and manually mark each detection area for subsequent photographing and sampling. Then, the inspector uses the automatic optical inspection device to program inspection programs with different conditions for different inspection areas according to different marks. In other words, the above application proposes a way to manually mark functional detection zones and differentially sample for different detection zones. The manual partitioning and differential sampling condition setting method still has a plurality of problems when applied to actual wafer defect detection:
For example, on the one hand, a field technology engineer and an upstream designer are required to cooperatively participate in the processes of detection area selection, marking, sampling result analysis and the like, which obviously puts extremely high demands on labor cost and material cost in the wafer processing process. On the other hand, although the partition setting mode based on the differential sampling conditions reduces the detection time to a certain extent, the reliability and accuracy of the sampling result are also easily affected by the professional ability of the staff in a mode of setting different detection conditions for different wafer manufacturing processes and different wafer detection areas.
Therefore, there is a need for a sampling method that can improve the defect sampling efficiency during the defect sampling stage, while ensuring the reliability and accuracy of the defect sampling.
Disclosure of Invention
The invention aims to provide a defect classification method for repeated defects, which partially solves or alleviates the defects in the prior art and can improve the efficiency of classifying the defects of wafers.
In order to solve the technical problems, the invention adopts the following technical scheme:
a defect classification method of repeating defects, comprising the steps of:
S101, acquiring a position information set of at least one group of repeated defects of a wafer, wherein the position information set comprises: location information of at least one defect to be classified having the same or similar location;
s102, acquiring total sampling quantity and sampling proportion relation corresponding to sampling positions of the wafer, so as to determine regional sampling quantity in different sampling regions of the wafer according to the total sampling quantity and sampling proportion relation from a plurality of sampling regions divided in advance on the wafer; the sampling position is used for photographing and sampling, and the wafer is divided into a first sampling area, a second sampling area and a third sampling area in sequence from the center to the edge;
s103, respectively selecting corresponding sampling positions from a plurality of sampling areas according to the sampling quantity of the areas; wherein when the repeating defect comprises: when the first repeating defect and the second repeating defect, respectively, S103 includes the steps of:
selecting a first sampling location from at least one sampling region corresponding to the first repeat defect;
judging whether the first sampling position comprises the second repeated defect or not; if yes, selecting at least one third sampling position containing the second repeating defect from the sampling area where the first sampling position is located;
When the distance between the third sampling position and the first sampling position is larger than a preset distance, selecting the third sampling position as a second sampling position;
s104, photographing at the selected sampling positions respectively, so as to obtain a defect photo set corresponding to at least one group of repeated defects;
s105, classifying the repeated defects through the defect photo set.
In some embodiments, prior to S102, further comprising the steps of:
s106, acquiring the current processing technology of the wafer, and acquiring historical data of the wafer defect from a historical defect database through the current processing technology; wherein the historical defect database comprises the following steps:
defects formed after the wafer is processed by at least one processing technology, and forming positions and forming reasons corresponding to the defects; wherein the reason for formation includes one or more of: illumination factors, mechanical damage, edge effects, surface residues;
s107, selecting at least one ring area on the wafer; when the duty ratio of the illumination factors in the forming reasons of the defects contained in the circular ring area belongs to a first preset threshold range; and/or determining the annular region as a second sampling region when the number of defects which do not belong to the illumination factors in the forming reasons of the defects contained in the annular region belongs to a second preset threshold range;
S108, dividing two sides of the second sampling area into a first sampling area and a third sampling area along the direction from the center to the edge of the wafer in sequence.
In some embodiments, prior to S106, further comprising the step of:
s109, judging whether a processing technology matched with the current processing technology exists in the regional division database; wherein the region division database includes: at least one processing technology and a dividing rule of a sampling area corresponding to the processing technology;
if yes, selecting a dividing rule corresponding to the current processing technology, and dividing a sampling area of the wafer by adopting the corresponding dividing rule;
if not, S106 is executed, or a prompt signal is sent to the user.
In some embodiments, the defect picture includes at least one complete functional unit or at least one group of related functional units.
In some embodiments, the width of the first sampling region, the radius of the second sampling region, and the width of the third sampling region are about 1:1:1.
In some embodiments, the sampling scale relationship is: sampling positions are selected from the first sampling region, the second sampling region and the third sampling region according to the ratio of about 1:2:1.
In some embodiments, S105 includes the steps of:
inputting the defect photo set into an ADC classification model, and outputting a defect category corresponding to at least one defect photo through the ADC classification model;
when the defect type with the largest defect number is only one, the defect type is used as the defect type of the repeated defect;
when the defect type with the largest defect number is two or more, selecting the defect type with the highest priority as the defect type of the corresponding repeated defect, and/or selecting the defect type of the defect in the second sampling area as the defect type of the corresponding repeated defect.
The invention also provides a defect classification system of repeated defects, which comprises:
a defect position obtaining module to be classified, configured to obtain a position information set of at least one group of repeated defects of a wafer, wherein the position information set includes: location information of at least one defect to be classified having the same or similar location;
a sampling data acquisition module configured to acquire a total sampling number and a sampling proportion relation corresponding to sampling positions of the wafer to determine a region sampling number in different sampling regions of the wafer from a plurality of sampling regions divided in advance on the wafer according to the total sampling number and the sampling proportion relation; the sampling position is used for photographing and sampling, and the wafer is divided into a first sampling area, a second sampling area and a third sampling area in sequence from the center to the edge;
A sampling position acquisition module configured to select corresponding sampling positions from a plurality of sampling areas according to the area sampling number; wherein when the repeating defect comprises: when the first repeating defect and the second repeating defect are generated, the sampling position acquisition module correspondingly comprises:
a first sampling unit configured to select a first sampling location corresponding to the first repeat defect from at least one sampling area;
a second sampling unit configured to determine whether the first sampling location includes the second repeat defect; if yes, selecting at least one third sampling position containing the second repeating defect from the sampling area where the first sampling position is located; when the distance between the third sampling position and the first sampling position is larger than a preset distance, selecting the third sampling position as a second sampling position;
a photographing module configured to photograph at the selected sampling locations, respectively, thereby obtaining a defect photograph set corresponding to at least one repeated defect;
a classification module configured for classifying the duplicate defects by the defect photo set.
In some embodiments, comprising:
the historical data acquisition module is configured to acquire the current processing technology of the wafer and acquire the historical data of the wafer defect from the historical defect database through the current processing technology; wherein,
the historical defect database comprises the following steps: after the wafer is processed by at least one processing technology, forming defects, and forming positions and forming reasons corresponding to the defects; wherein the reason for formation includes one or more of: illumination factors, mechanical damage, edge effects, surface residues;
a first automatic partitioning module configured to select at least one ring area on the wafer;
when the duty ratio of the illumination factors in the forming reasons of the defects contained in the circular ring area belongs to a first preset threshold range; and/or determining the annular region as a second sampling region when the number of defects which do not belong to the illumination factors in the forming reasons of the defects contained in the annular region belongs to a second preset threshold range;
the second automatic partitioning module is configured to divide two sides of the second sampling area into a first sampling area and a third sampling area in sequence along the direction from the center to the edge of the wafer.
In some embodiments, further comprising: a third automatic partitioning module configured to determine whether a machining process matching the current machining process exists in a region division database; wherein the region division database includes: at least one processing technology and a dividing rule of a sampling area corresponding to the processing technology; if yes, selecting a dividing rule corresponding to the current processing technology, and dividing a sampling area of the wafer by adopting the corresponding dividing rule; if not, outputting the division result to a sampling position acquisition module, or sending a prompt signal to a user.
In some embodiments, the defect picture includes at least one complete functional unit or at least one group of related functional units.
The beneficial technical effects are as follows:
the invention provides a method for rapidly sampling and rapidly classifying defects of wafers with a plurality of defect types. Specifically, the method takes the pre-grouped repeated defects as sampling objects, and respectively selects the sample points with high independence for different repeated defects on a plurality of associated areas (such as a first sampling area, a second sampling area and a third sampling area), so that the effectiveness of a sample point set is improved as much as possible under the condition that the sample points are limited. In other words, the invention can perform regional centralized sampling on the wafer scale and distributed sampling on the regional scale, thereby effectively reducing the necessary sampling quantity and improving the efficiency of the defect classification process.
Furthermore, the invention can select limited defect formation reason combination to automatically set the rapid sampling partition of the wafer, so as to reduce the manual intervention in the sampling process to a certain extent and reduce the necessary time consumption of defect classification. In addition, the wafer under the typical wafer processing technology can be rapidly partitioned by selecting key defect causes such as illumination factors, mechanical damage, edge effect, surface residues and the like, so that the wafer processing technology has accuracy and universality.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Like elements or portions are generally identified by like reference numerals throughout the several figures. In the drawings, elements or portions thereof are not necessarily drawn to scale. It will be apparent to those of ordinary skill in the art that the drawings in the following description are of some embodiments of the invention and that other drawings may be derived from these drawings without inventive faculty.
FIG. 1 is a flowchart illustrating a wafer defect classification method according to an exemplary embodiment of the present invention;
FIG. 2 is a schematic diagram of defect distribution of a wafer in an exemplary embodiment;
FIG. 3 is a schematic diagram of a sample partition of a wafer in an exemplary embodiment;
FIG. 4a is a schematic diagram illustrating the selection of sampling locations according to an exemplary embodiment;
FIG. 4b is a schematic diagram illustrating the selection of sampling locations according to an exemplary embodiment;
FIG. 5 is a schematic diagram of the results of defect classification categories in an exemplary embodiment;
fig. 6 is a schematic block diagram illustrating a defect classification method according to an exemplary embodiment of the present invention.
Reference numeral identification summary:
01 is a wafer, 02 is a chip, 03 is a defect (or repeat defect), 03a is a first repeat defect,
03b is a second repeat defect, 04 is a third sampling region, 05 is a second sampling region, 06 is a first sampling region, 07 is a sampling position, 07a is a first sampling position, 07b is a second sampling position, 07c is a third sampling position, and 07d is a fourth sampling position.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In this document, suffixes such as "module", "component", or "unit" used to represent elements are used only for facilitating the description of the present invention, and have no particular meaning in themselves. Thus, "module"
"component" or "unit" may be used in combination.
The terms "upper," "lower," "inner," "outer," "front," "rear," "one end," "the other end," and the like herein refer to an orientation or positional relationship based on that shown in the drawings, merely for convenience of description and to simplify the description, and do not denote or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted," "configured to," "connected," and the like, herein, are to be construed broadly as, for example, "connected," whether fixedly, detachably, or integrally connected, unless otherwise specifically defined and limited; the two components can be mechanically connected, can be directly connected or can be indirectly connected through an intermediate medium, and can be communicated with each other. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Herein, "and/or" includes any and all combinations of one or more of the associated listed items.
Herein, "plurality" means two or more, i.e., it includes two, three, four, five, etc.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As used in this specification, the term "about", typically expressed as +/-5% of the value,
more typically +/-4% of the value, more typically +/-3% of the value, more typically +/-2% of the value, even more typically +/-1% of the value, even more typically +/-0.5% of the value.
In this specification, certain embodiments may be disclosed in a format that is within a certain range. It should be appreciated that such a description of "within a certain range" is merely for convenience and brevity and should not be construed as a inflexible limitation on the disclosed ranges. Accordingly, the description of a range should be considered to have specifically disclosed all possible sub-ranges and individual numerical values within that range. For example, a rangeThe description of (c) should be taken as having specifically disclosed sub-ranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6, etc., as well as individual numbers within such ranges, e.g., 1,2,3,
4,5 and 6. The above rule applies regardless of the breadth of the range.
Herein, a "Wafer" may also be referred to as Wafer. The wafer generally refers to a silicon wafer used for manufacturing a silicon semiconductor circuit, and the original material is silicon.
Herein, a "chip" may also be referred to as a Die or Die, i.e., die. Wherein Die is the body of a small integrated circuit fabricated from semiconductor material without packaging. In other words, die may refer to the Die before the chip is unpackaged, which is a single wafer area cut from wafer with a laser.
In general, a Die may include a complete functional unit or a group of related functional units,
so as to facilitate the subsequent production and assembly of the integrated circuit. The functional unit may be a circuit replica, for example, one or more tiny components of a transistor, a capacitor, a resistor, etc. As shown in fig. 2, one wafer 01 may be cut into a plurality of Die (chips 02) according to actual production requirements.
As used herein, a "defect point" generally refers to an abnormal point on a wafer caused by a processing problem, human error, or some other accidental factor (such as contamination of a machine or a wafer with dust), which may directly affect the service life and reliability of the wafer. And a plurality of closely spaced and consecutive defect points in the wafer are generally referred to as clustered defect points. For example, a plurality of defect points connected without interruption at a point pitch of 150 μm may be regarded as a Cluster point defect (Cluster), also called a Cluster (or wafer defect).
When these clusters are caused by process problems or human errors, they tend to have a certain repeatability, and they can appear continuously on the wafers processed next, with a large impact on the wafer yield. Information about the size, geometry and spatial location of clusters is therefore of great value to process engineers seeking to identify potential production problems. Clustered point defects, such as mechanical damage, are common, and form a regularly distributed wafer pattern.
Herein, "repeat defect" is also referred to as: repeater Defect or Repeater. Wherein,
when a cluster point defect (cluster) repeatedly appears at the same or similar positions of a plurality of dies (die) of one wafer, or when a cluster point defect repeatedly appears at the same or similar positions of a plurality of wafers, such a cluster point defect may be determined as a repeated defect. For example, the repeated defects may be defects generated by corresponding process defects (such as dust, etc.) on the wafer at the same position on the reticle. In addition, when the defect classification is performed, a plurality of cluster point defects with the same or similar positions can be used as the repeated defects to be classified in the same group.
Herein, a Reticle is also referred to as a photomask, reticle, or Reticle, etc., i.e., reticles or masks, which are used as a pattern transfer tool or master in a microelectronic fabrication process, bearing pattern design and process technology information, is considered a "negative" of a lithographic process.
Example 1
As shown in fig. 1-5, a first aspect of the present invention provides a defect classification method of repeated defects,
the method comprises the following steps:
s101, acquiring a position information set of at least one group of repeated defects of a wafer, wherein the position information set comprises: location information of at least one defect to be classified having the same or similar location.
In some embodiments, the position information of the plurality of cluster point defects may be preliminarily detected by the defect scanning apparatus/defect detecting apparatus in advance.
In some embodiments, the location information may be the coordinates of the cluster point defect on the wafer, or may also be the coordinates of the cluster point defect on the chip (Die).
In some embodiments, cluster point defects having the same or similar coordinates are divided into the same set of repeating defects.
For example, in some embodiments, the defect detection device may generate a klarf file during the process of detecting a wafer defect, and when resolving the klarf file, the device may perform Repeater calculation according to the position of the defect, and assign a corresponding Repeater ID value. Wherein the ID values are identical (except 0), i.e. they indicate that the defects belong to the same Repeater group. Thus, in this embodiment, repeater information can be obtained from the defect database.
S102, acquiring total sampling quantity and sampling proportion relation corresponding to sampling positions of the wafer, so as to determine regional sampling quantity in different sampling regions of the wafer according to the total sampling quantity and sampling proportion relation from a plurality of sampling regions divided in advance on the wafer; the sampling position 07 is used for photographing and sampling, and the wafer is divided into a first sampling area 06, a second sampling area 05 and a third sampling area 04 in sequence from the center to the edge, as shown in fig. 3.
Wherein, regional sample quantity is:and n=1 represents the first sampling area,
n=2 represents the second sampling region, and n=3 represents the third sampling region.
In some embodiments, the total sampling number X, and the sampling ratio relationship (Y1:Y2:Y3) may be a predetermined value.
In some embodiments, the total sample amount, sample ratio relationship may also be manually set or adjusted by a user (e.g., a process engineer) in conjunction with actual production requirements.
Preferably, in some embodiments, for defect detection of a typical machining process, the ratio of the area sampling numbers of the first, second and third sampling areas is about: y1: y2:
y3=1:2:1. In other words, the preferred sampling number of the first, second and third sampling regions is about 0.25X,
0.5X、0.25X。
S103, respectively selecting corresponding sampling positions from a plurality of sampling areas according to the sampling quantity of the areas.
And as shown in fig. 4 a-4 b, when the repeating defect includes: when the first and second repeat defects 03a and 03b, S103 includes the steps of:
selecting a first sampling location 07a from at least one sampling area corresponding to the first repeat defect 03 a;
judging whether the first sampling position 07a includes the second repeat defect 03b; if so, the first and second data are not identical,
Then, in the sampling region where the first sampling position 07a is located, a selection is made to include the second repeat
At least one third sampling location of notch 03 b;
when the distance between the third sampling position and the first sampling position is larger than a preset distance,
the third sampling location is selected as the second sampling location 07b.
As shown in fig. 4b, in some embodiments, after the position of the first sampling position 07a in the first sampling area is determined, the second sampling position 07b may be selected at any position in the first sampling area (such as inside the first sampling area, or at an edge of the first sampling area), so long as a space between the first and second sampling positions is greater than a preset distance L.
For example, in some embodiments, in order to quickly obtain the second sampling position, a diagonal sampling method, a symmetrical sampling method, or the like may be used to obtain the point when two or more sets of repeated defects exist on the chip where the sampling position is located.
Specifically, in some embodiments, as shown in fig. 4B, the diagonal sampling method is to take the current first sampling position 07a (for example, the center point coordinate of the sampling position) as the point a, take the center point of the wafer as the point B, and obtain the circle L1 with the center point being the point B and the circumference passing through the point a. Taking the point A as the vertex, setting an inscribed polygon L2 (such as a rectangle, a square, a regular pentagon and the like) in the circle L1, checking the positions of other vertices of the inscribed polygon, and selecting the vertex position or the adjacent region thereof with the second repeating defect 03b as a second sampling position 07b.
Specifically, in some embodiments, the symmetrical sampling method is to take the current first sampling position 07a as the point a, take the center point of the wafer as the point B, make a straight line passing through the point a and the point B, and select the point C on the straight line, where the distance between the point C and the point B is the same as or similar to the distance between the point a and the point B. And when there is a second repeat defect 03b at point C, then point C or its vicinity is selected as the second sampling location 07b.
It can be appreciated that, in this embodiment, the second sampling position selection rule may be flexibly customized by the user according to the actual requirement, which is not limited in this disclosure.
S104, photographing at the selected sampling positions respectively, so as to obtain defect photo sets corresponding to at least one repeated defect.
For example, in some embodiments, the sampling locations acquired in S103 may be transmitted to a photographing apparatus such as a Scanning Electron Microscope (SEM), an optical microscope, or the like, and then the photographing apparatus may take photographing samples for the respective sampling locations, respectively.
S105, classifying the repeated defects through the defect photo set.
For example, in some embodiments, the defect photo set may be directly input to the ADC classification model for automatic defect classification, or alternatively, may be manually classified by a worker.
For the wafer defect detection scenario with numerous defect types, in this embodiment, a method for performing low-association point extraction on an association region (or the same region) is actually provided, so as to improve accuracy and reliability of automated sample data acquisition. Specifically, the method takes a plurality of repeated defects obtained by pre-grouping as selection objects, and respectively performs sample point selection with high independence on different repeated defects on a plurality of associated areas (such as a first sampling area, a second sampling area and a third sampling area), so that the effectiveness of a sample point set is improved as much as possible under the condition that the sample points are limited.
In some embodiments, prior to S102, further comprising the steps of:
s106 obtains a current processing process (e.g., process type, process name, etc.) of the wafer,
acquiring historical data of wafer defects from a historical defect database through the current processing technology; wherein the historical defect database comprises the following steps: defects formed after the wafer is processed by at least one processing technology, and forming positions and forming reasons corresponding to the defects; wherein the reason for formation includes one or more of: illumination factors, mechanical damage, edge effects, surface residues;
S107, selecting at least one ring area on the wafer; when the duty ratio of the illumination factors in the formation reasons contained in the circular ring area belongs to a first preset threshold range; and/or determining the annular region as a second sampling region when the number of defects which do not belong to illumination factors in the formation reasons contained in the annular region belongs to a second preset threshold range;
s108, dividing two sides of the second sampling area into a first sampling area and a third sampling area along the direction from the center to the edge of the wafer in sequence.
In the embodiment of the invention, finite typical factors such as illumination factors, mechanical damage, edge effects, surface residues and the like are comprehensively selected as reference conditions for accelerating partition setting, so that rapid sampling partition setting is conveniently carried out on wafers obtained by a conventional wafer processing technology. In other words, the partitioning method in this embodiment can further improve defect classification automation, and reduce the necessity of manual intervention.
Preferably, in some embodiments, the edge effect comprises one or more of: substrate edge effect, desorption edge effect, thinning edge effect.
For example, in some embodiments, the edge portion of the substrate of the wafer may have lattice distortion, impurity accumulation, and the like, which may cause a difference in electrical properties of the wafer.
For example, in some embodiments, the material near the edge of the wafer may undergo desorption phenomena due to temperature, pressure, etc., thereby causing contamination of the wafer surface and affecting the electrical performance of the wafer.
As another example, in some embodiments, a large error (or non-uniformity) in the thickness of the wafer material may be caused during the thinning process of the wafer, thereby affecting the final product quality of the wafer.
Preferably, when the number of the repeated defects detected in the initial step is too large, or when the requirement on the identification accuracy of the defect type is too high, the substrate edge effect, the desorption edge effect and the thinning edge effect are selected as key edge effect types in the embodiment so as to complete the automatic sampling partition setting.
It can be appreciated that, unlike the existing manual area selection detection method, the invention provides a standardized sampling position selection method capable of reducing the manual participation and improving the sampling automation.
In some embodiments, prior to S106, further comprising the step of:
S109, judging whether a processing technology matched with the current processing technology exists in the regional division database; wherein the region division database includes: at least one processing technology and a dividing rule of a sampling area corresponding to the processing technology;
if yes, selecting a dividing rule corresponding to the current processing technology, and dividing a sampling area of the wafer by adopting the corresponding dividing rule;
if not, S106 is executed, or a prompt signal is sent to the user.
In some embodiments, the defect picture includes at least one complete functional unit or at least one group of related functional units.
In some embodiments, the width of the first sampling region, the radius of the second sampling region, and the width of the third sampling region are about 1:1:1.
In some embodiments, the width refers to the difference between the outer radius and the inner radius of the sampling area.
In some embodiments, the sampling scale relationship is: sampling positions are selected from the first sampling region, the second sampling region and the third sampling region according to the ratio of about 1:2:1.
In some embodiments, S105 includes the steps of:
inputting the defect photo set into an ADC classification model, and outputting a defect category corresponding to at least one defect photo through the ADC classification model;
When the defect type with the largest defect number is only one, the defect type is used as the defect type of the repeated defect;
when the defect type with the largest defect number is two or more, selecting the defect type with the highest priority as the defect type of the corresponding repeated defect, and/or selecting the defect type of the defect in the second sampling area as the defect type of the corresponding repeated defect.
As shown in fig. 5, when the defect categories of the classified repeated defects are 1, 2, and 3, respectively, the defect categories that remain unidentified are also marked as 1.
When the defect categories of the classified repeated defects are 1, 2 and 2, respectively. And at this time, the classification priority of the defect class 2 is higher than that of the defect class 1 (for example, the historical occurrence frequency of the defect class 2 is higher), and the defect class which is not identified is marked as 1.
In the embodiment of the invention, the defect photo set with higher reliability is acquired by sampling the association region with low association degree, and the rapid classification method can be further adopted for the acquired defect photo set so as to improve the defect classification efficiency, thereby timely managing and maintaining the wafer processing production line.
In some embodiments, bin represents a classification of a defect (or defect class).
In some embodiments, the sampling location selected for the first sampling region may be located in the first sampling region, or may be located at an edge of the first sampling region, such as a junction between the first and second sampling regions. Likewise, in sampling for the second sampling region or the third sampling region, the sampling may also be performed at the edge or boundary thereof.
Example two
As shown in fig. 6, the present invention also provides a defect classification system for repeating defects corresponding to the classification method in the first embodiment, which includes:
a defect location obtaining module to be classified 10 configured to obtain a set of location information of at least one set of repeated defects of a wafer, wherein the set of location information includes: location information of at least one defect to be classified having the same or similar location;
a sampling data acquisition module 20 configured to acquire a total sampling number and a sampling proportion relation corresponding to sampling positions of the wafer to determine a region sampling number in different sampling regions of the wafer from among a plurality of sampling regions divided in advance on the wafer in accordance with the total sampling number and sampling proportion relation; the sampling position is used for photographing and sampling, and the wafer is divided into a first sampling area, a second sampling area and a third sampling area in sequence from the center to the edge;
A sampling position acquisition module 30 configured to select corresponding sampling positions from a plurality of sampling regions according to the region sampling number, respectively; wherein when the repeating defect comprises: when the first repeating defect and the second repeating defect are generated, the sampling position acquisition module correspondingly comprises: a first sampling unit 31 configured for selecting a first sampling location corresponding to the first repeat defect from at least one sampling area; a second sampling unit 32 configured to determine whether the first sampling location includes the second repeat defect; if yes, selecting at least one third sampling position containing the second repeating defect from the sampling area where the first sampling position is located; when the distance between the third sampling position and the first sampling position is larger than a preset distance, selecting the third sampling position as a second sampling position;
a photographing module 40 configured to take photographs at the selected sampling locations respectively,
obtaining a defect photo set corresponding to at least one group of repeating defects;
a classification module 50 is configured for classifying the duplicate defects by the defect photo set.
In some embodiments, the system further comprises:
a historical data acquisition module 60 configured to acquire a current processing process of the wafer, and acquire historical data of wafer defects from a historical defect database through the current processing process; wherein the historical defect database comprises the following steps: after the wafer is processed by at least one processing technology, forming defects, and forming positions and forming reasons corresponding to the defects; wherein the reason for formation includes one or more of: illumination factors, mechanical damage, edge effects, surface residues;
a first automatic partitioning module 70 configured to select at least one ring area on the wafer; when the duty ratio of illumination factors in the defect factors contained in the circular ring area belongs to a first preset threshold range; and/or determining the circular ring area as a second sampling area when the number of defect causes which do not belong to illumination factors in the defect causes contained in the circular ring area belongs to a second preset threshold range;
a second auto-partition module 80 configured for use in a center-to-edge direction of the wafer,
And dividing two sides of the second sampling area into a first sampling area and a third sampling area respectively.
In some embodiments, the system further comprises:
a third automatic partitioning module configured to determine whether a machining process matching the current machining process exists in a region division database; wherein the region division database includes: at least one processing technology and a dividing rule of a sampling area corresponding to the processing technology; if yes, selecting a dividing rule corresponding to the current processing technology, and dividing a sampling area of the wafer by adopting the corresponding dividing rule; if not, outputting the division result to a sampling position acquisition module, or sending a prompt signal to a user.
In some embodiments, the defect picture includes at least one complete functional unit or at least one group of related functional units.
In some embodiments, classification module 50 includes:
the first classification unit is configured to input the defect photo set into an ADC classification model, and output a defect category corresponding to at least one defect photo through the ADC classification model;
when the defect type with the largest defect number is only one, the defect type is used as the defect type of the repeated defect;
A second classification unit configured to select, when the defect type with the largest number of defects is two or more, the defect type with the highest priority as the defect type of the corresponding repeated defect;
and/or a third classification unit configured to select a defect type of a defect located in the second sampling area as a defect type of the corresponding repeat defect.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising several instructions for causing a computer terminal (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the claims, which are to be protected by the present invention.
Claims (10)
1. A defect classification method of repeating defects, comprising the steps of:
s101, acquiring a position information set of at least one group of repeated defects of a wafer, wherein the position information set comprises: location information of at least one defect to be classified having the same or similar location;
s102, acquiring total sampling quantity and sampling proportion relation corresponding to sampling positions of the wafer, so as to determine regional sampling quantity in different sampling regions of the wafer according to the total sampling quantity and sampling proportion relation from a plurality of sampling regions divided in advance on the wafer; the sampling position is used for photographing and sampling, and the wafer is divided into a first sampling area, a second sampling area and a third sampling area in sequence from the center to the edge;
S103, respectively selecting corresponding sampling positions from a plurality of sampling areas according to the sampling quantity of the areas; wherein when the repeating defect comprises: when the first repeating defect and the second repeating defect, respectively, S103 includes the steps of:
selecting a first sampling location from at least one sampling region corresponding to the first repeat defect;
judging whether the first sampling position comprises the second repeated defect or not; if yes, then
Selecting at least one third sampling position containing the second repeating defect in the sampling area where the first sampling position is located;
when the distance between the third sampling position and the first sampling position is larger than a preset distance, selecting the third sampling position as a second sampling position;
s104, photographing at the selected sampling positions respectively, so as to obtain a defect photo set corresponding to at least one group of repeated defects;
s105, classifying the repeated defects through the defect photo set.
2. The defect classification method of claim 1, further comprising the step of, prior to S102:
s106, acquiring the current processing technology of the wafer, and acquiring historical data of the wafer defect from a historical defect database through the current processing technology; wherein the historical defect database comprises the following steps: defects formed after the wafer is processed by at least one processing technology, and forming positions and forming reasons corresponding to the defects; wherein the reason for formation includes one or more of: illumination factors, mechanical damage, edge effects, surface residues;
S107, selecting at least one ring area on the wafer; when the duty ratio of the illumination factors in the forming reasons of the defects contained in the circular ring area belongs to a first preset threshold range; and/or determining the annular region as a second sampling region when the number of defects which do not belong to the illumination factors in the forming reasons of the defects contained in the annular region belongs to a second preset threshold range;
s108, dividing two sides of the second sampling area into a first sampling area and a third sampling area along the direction from the center to the edge of the wafer in sequence.
3. The defect classification method of claim 2, further comprising the step of, prior to S106:
s109, judging whether a processing technology matched with the current processing technology exists in the regional division database; wherein the region division database includes: at least one processing technology and a dividing rule of a sampling area corresponding to the processing technology;
if yes, selecting a dividing rule corresponding to the current processing technology, and dividing a sampling area of the wafer by adopting the corresponding dividing rule;
If not, S106 is executed, or a prompt signal is sent to the user.
4. A method of classifying repetitive defects according to claim 1 wherein the defect picture includes at least one complete functional unit or at least one group of related functional units.
5. The method of claim 1, wherein the width of the first sampling region, the radius of the second sampling region, and the width of the third sampling region are about 1:1:1; and/or, the sampling proportion relation is as follows: sampling positions are selected from the first sampling region, the second sampling region and the third sampling region according to the ratio of about 1:2:1.
6. The defect classification method of a repeated defect according to claim 1, wherein S105 comprises the steps of:
inputting the defect photo set into an ADC classification model, and outputting a defect category corresponding to at least one defect photo through the ADC classification model;
when the defect type with the largest defect number is only one, the defect type is used as the defect type of the repeated defect;
when the defect type with the largest defect number is two or more, selecting the defect type with the highest priority as the defect type of the corresponding repeated defect, and/or selecting the defect type of the defect in the second sampling area as the defect type of the corresponding repeated defect.
7. A defect classification system for repeating defects, comprising:
a defect position obtaining module to be classified, configured to obtain a position information set of at least one group of repeated defects of a wafer, wherein the position information set includes: location information of at least one defect to be classified having the same or similar location;
a sampling data acquisition module configured to acquire a total sampling number and a sampling proportion relation corresponding to sampling positions of the wafer to determine a region sampling number in different sampling regions of the wafer from a plurality of sampling regions divided in advance on the wafer according to the total sampling number and the sampling proportion relation; the sampling position is used for photographing and sampling, and the wafer is divided into a first sampling area, a second sampling area and a third sampling area in sequence from the center to the edge;
a sampling position acquisition module configured to select corresponding sampling positions from a plurality of sampling areas according to the area sampling number; wherein when the repeating defect comprises: when the first repeating defect and the second repeating defect are generated, the sampling position acquisition module correspondingly comprises:
A first sampling unit configured to select a first sampling location corresponding to the first repeat defect from at least one sampling area;
a second sampling unit configured to determine whether the first sampling location includes the second repeat defect; if yes, selecting at least one third sampling position containing the second repeating defect from the sampling area where the first sampling position is located; when the distance between the third sampling position and the first sampling position is larger than a preset distance, selecting the third sampling position as a second sampling position;
a photographing module configured to photograph at the selected sampling locations, respectively, thereby obtaining a defect photograph set corresponding to at least one repeated defect;
a classification module configured for classifying the duplicate defects by the defect photo set.
8. The defect classification system of claim 7, comprising:
the historical data acquisition module is configured to acquire the current processing technology of the wafer and acquire the historical data of the wafer defect from the historical defect database through the current processing technology; wherein the historical defect database comprises the following steps: after the wafer is processed by at least one processing technology, forming defects, and forming positions and forming reasons corresponding to the defects; wherein the reason for formation includes one or more of: illumination factors, mechanical damage, edge effects, surface residues;
A first automatic partitioning module configured to select at least one ring area on the wafer; when the duty ratio of the illumination factors in the forming reasons of the defects contained in the circular ring area belongs to a first preset threshold range; and/or determining the annular region as a second sampling region when the number of defects which do not belong to the illumination factors in the forming reasons of the defects contained in the annular region belongs to a second preset threshold range;
the second automatic partitioning module is configured to divide two sides of the second sampling area into a first sampling area and a third sampling area in sequence along the direction from the center to the edge of the wafer.
9. The defect classification system of claim 7, further comprising:
a third automatic partitioning module configured to determine whether a machining process matching the current machining process exists in a region division database; wherein the region division database includes: at least one processing technology and a dividing rule of a sampling area corresponding to the processing technology; if yes, selecting a dividing rule corresponding to the current processing technology, and dividing a sampling area of the wafer by adopting the corresponding dividing rule; if not, outputting the division result to a sampling position acquisition module, or sending a prompt signal to a user.
10. The defect classification system of claim 7, wherein the defect picture comprises at least one complete functional unit or at least one group of related functional units.
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