JP3635072B2 - Crystal defect automatic inspection device and automatic inspection method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a semiconductor crystal evaluation technique, and more particularly to a crystal defect automatic inspection method for automatically inspecting a crystal defect appearing in a parabolic shape of a semiconductor crystal and an automatic inspection apparatus for performing the same.
[0002]
[Prior art]
Generally, semiconductor wafers are manufactured by growing a cylindrical semiconductor single crystal ingot by a Czochralski (CZ) method, a floating zone (FZ) method, or the like, and thinning the grown semiconductor single crystal ingot. After slicing the wafer into slicing wafers, a lapping process is performed to adjust the thickness and flatness of the wafer, and an etching process is performed to etch the wafer to remove wafer processing distortion. Then, a polishing process or the like for further improving the surface roughness and flatness of the etched wafer to provide a mirror surface is performed, and a semiconductor wafer as a final product is manufactured. Memory, LSI, and the like are manufactured by subsequently forming elements on the semiconductor wafer that is the product manufactured in this way.
[0003]
In recent years, with the miniaturization of elements accompanying the high integration of semiconductor circuits such as DRAMs, a high-quality semiconductor wafer with high purity and low defects is required as its substrate. In particular, a crystal defect called a Grown-in defect is a defect caused by single crystal growth, and a void type defect in which vacancy-type point defects are aggregated is known to deteriorate oxide breakdown voltage characteristics and device characteristics. ing. Therefore, it is important to reduce the density and size of defects, and it is necessary to inspect the crystal defects in the semiconductor crystal to accurately evaluate the substance and to take appropriate measures against the crystal defects.
[0004]
Evaluation of crystal defects may be performed by inspecting the quality of a wafer that is a product after the polishing step is performed. In this case, many processes have been performed until a wafer that is a product is manufactured. Since the wafer is evaluated later, if the product wafer is out of the standard, there is a problem that the time loss and the manufacturing cost loss are large.
[0005]
Further, the defects due to the single crystal growth as described above are influenced by the growth conditions during the growth of the single crystal ingot and are not changed in principle in the wafer processing step. Therefore, crystal defects in a single crystal are generally measured by cutting a wafer for inspection immediately after growing a single crystal ingot, or sampling and evaluating the sample at an early stage of the wafer processing process. ing.
[0006]
As a method for evaluating crystal defects in a semiconductor crystal, for example, as disclosed in JP-A-4-285100, the surface of an inspection wafer cut out from a single crystal ingot is mixed with a mixed solution of hydrofluoric acid and nitric acid. After removing the cutting distortion at the time of wafer cutting by etching, K₂Cr₂O₇There is a method in which the surface of the wafer is selectively etched with a mixed solution of hydrofluoric acid and water, and the number of parabolic patterns (sometimes called ripple patterns or radial patterns) appearing on the surface is counted.
[0007]
K₂Cr₂O₇A mixture of HF, hydrofluoric acid and water is well known as a SECCO solution, and its composition is, for example, 0.15 mol / l K₂Cr₂O₇Water and 49% hydrofluoric acid in a volume ratio of 1: 2. This SECCO solution is also used for observing a linear defect image by selectively etching the oxidation-induced stacking fault (OSF) after the heat treatment, or for viewing slip dislocations that have entered during ingot growth. .
[0008]
When the surface of the semiconductor wafer is selectively etched with this SECCO solution, the surface of the wafer after selective etching in a non-stirred state with the semiconductor wafer placed perpendicular to the liquid surface of the SECCO solution is observed with a microscope. A parabolic ripple pattern as shown in a) appears. This is because, when there are very small pits (defects) in the wafer, this pit part is selectively etched and a gas such as hydrogen is generated due to a chemical reaction, and etching unevenness occurs when the gas escapes upward. It is something that can be done. Therefore, it is considered that such a parabolic pattern appearing on the wafer surface is caused by a certain type of crystal defect inherent in the crystal. In general, such a parabolic pattern defect is represented by FPD (Flow Pattern Defect). It is said. Therefore, by evaluating the number of parabolic patterns on the wafer surface, defects in the crystal can be evaluated.
[0009]
On the other hand, when the semiconductor wafer is placed horizontally with respect to the liquid surface of the SECCO solution and processed without stirring, a circular pattern as shown in FIG. 16B appears on the wafer surface after selective etching. Such a pattern on the wafer surface is formed by selectively etching a defect present in the semiconductor wafer and generating gas from that portion, as described above. However, for example, as shown in FIG. 16B, when concentric patterns or large circular patterns appear on the wafer surface, the patterns overlap each other, so that each concentric pattern and other circular patterns are identified. In the case of a wafer having a relatively high defect density, it is extremely difficult to accurately count overlapping circular patterns. Therefore, normally, when a crystal defect is inspected, a semiconductor wafer is introduced perpendicularly to the liquid surface of the SECCO liquid, and a parabolic pattern defect (FPD) as shown in FIG. Counting.
[0010]
Conventionally, the FPD appearing on the surface of the wafer is photographed under a halogen lamp condensing lamp, and its overall distribution, or representative points (for example, the wafer peripheral part, the central part, and the intermediate part thereof). Part (R / 2 position)) and the inspection specifications were determined and inspected. At this time, the FPD in the measurement area is counted visually using an optical microscope, or the surface of the wafer is imaged with a CCD camera, and the obtained image data is displayed on a monitor and is operated using an electronic pen. Counted visually.
[0011]
For example, the parabolic pattern defect (FPD) image data obtained by this CCD camera is detected as a parabolic pattern as shown in FIG. 16A, and the parabolic pattern exists independently (for example, parabolic pattern A). ) And parabola patterns (Parabolic patterns B, C, D, E), etc., and as seen in the parabolic pattern C, parabolic patterns C1, C2, etc. in which the parabolic patterns completely overlap are observed. There are also cases where the parabolic pattern is partially off from the measurement area, such as the parabolic pattern E.
[0012]
The operator inspects a parabolic pattern defect (FPD) by visual observation using the image data obtained by the CCD camera in this way. At this time, for example, if it is in an independent state such as a parabolic pattern A, it is easy to count and inspect, but if there are many overlapping parts of parabolic patterns such as parabolic patterns B to E, It becomes difficult to perform the inspection. Furthermore, the parabolic pattern includes a pattern that should be inspected as a defect and a pattern that is not inspected. For example, the parabolic patterns C1 and C2 are patterns that are not evaluated as defects and are difficult to determine. Therefore, in order to accurately inspect such parabolic pattern defects, the skill level of the operator is required.
[0013]
In addition, as described above, since such crystal defect inspection methods are all performed manually, individual differences are likely to occur in the inspection results, and further, depending on the position of the wafer in the thickness direction where defects exist. Since the size of the parabolic pattern defect changes, when the multi-point measurement is performed on the wafer surface, the operator has a variation in the count, making it difficult to perform a stable evaluation.
[0014]
In addition, when evaluating crystal defects, the defect inspection involves measuring multiple points on the wafer surface, which places a heavy burden on the operator, such as a long-time microscope operation. Problem arises.
[0015]
On the other hand, in the manufacture of semiconductor wafers, it is required to feed back inspection results quickly and perform efficient manufacturing, and shortening of inspection time and use at night are strongly desired.
[0016]
[Problems to be solved by the invention]
Therefore, the present invention has been made in view of the above problems, and enables automatic operation so that inspection can be performed even at night, reducing the burden on the operator, and does not cause variations in inspection results, and with high accuracy. It is an object of the present invention to provide an automatic crystal defect inspection method and automatic inspection apparatus capable of stably inspecting a crystal defect of a semiconductor crystal.
[0017]
[Means for Solving the Problems]
In order to achieve the above object, according to the present invention, there is provided a method for automatically inspecting a crystal defect of a semiconductor crystal, comprising slicing a grown semiconductor single crystal to produce a semiconductor wafer, and obtaining the obtained semiconductor wafer. The semiconductor wafer is subjected to selective etching to cause a parabolic pattern defect (FPD) to appear on the surface of the semiconductor wafer, the surface of the semiconductor wafer is imaged to obtain image data, and the image data is subjected to image processing to obtain image data. There is provided an automatic inspection method for crystal defects characterized by converting the above parabolic defect (FPD) into an independent parabola, and automatically quantifying the crystal defect by automatically discriminating the independent parabola..
[0018]
Thus, a semiconductor crystal was grown and sliced to produce a semiconductor wafer, and the resulting semiconductor wafer was subjected to selective etching to cause a parabolic pattern defect (FPD) to appear on the surface of the semiconductor wafer. Thereafter, the surface of the semiconductor wafer is imaged to obtain image data, and image processing is performed on the image data to convert a parabolic pattern defect (FPD) on the image data into an independent parabola. By automatically discriminating and quantifying crystal defects, crystal defects in semiconductor crystals can be automatically inspected, reducing the burden on the operator and further inspecting defects according to certain standards. It is possible to inspect the crystal defects of the semiconductor crystal with high accuracy and stability without variation in the results.
[0019]
At this time, the parabolic pattern defect (FPD) on the image data is converted into an independent parabola by the image processing. First, the imaged image data is binarized to convert the parabolic pattern defect (FPD) into a parabolic shape. And detecting the end points, vertices, and intersection points of the skeleton lines of the parabolic skeleton line, and then, among the detected parabolic skeleton lines, the intersection points of the skeleton lines are on the skeleton line. If there is not, the parabolic skeleton line is converted into an independent parabola as it is, and if there is an intersection of the skeleton lines on the skeleton line, the parabolic skeleton line is separated and connected to an independent parabola. Preferably done by converting.
[0020]
In this way, first, the imaged image data is binarized, and the parabolic pattern defect (FPD) is detected for the parabolic skeleton line, the end point of the parabolic skeleton line, the vertex, and the intersection of the skeleton lines. Later, among the detected parabolic skeleton lines, those that do not have an intersection of skeleton lines on the skeleton line are converted into independent parabolas as they are, and there are intersections of the skeleton lines on the skeleton line. By separating and connecting the skeleton lines to independent parabolas, parabolic pattern defects (FPD) on the image data exist independently or between parabolic pattern defects (FPDs). Even if they are overlapped, all the parabolic pattern defects (FPD) to be measured can be easily and reliably converted into independent parabolas using a certain algorithm.
[0021]
In this case, the separation and connection processing of the parabolic skeleton lines is performed by increasing the end points of the parabolic skeleton lines and the intersections of the skeleton lines by a set pixel, and erasing the skeleton lines in the region increased by the set pixel. After separating the skeleton line (as an erase circle), the XY axis is set with the intersection (the center of the erase circle) between the skeleton lines as the origin, and the range from 0 ° to 90 ° is the first area, 90 ° to 180 ° An area where each of the separated skeleton lines exists (separated state), with the range of ° being the second area, the range of 180 ° to 270 ° being the third area, and the range of 270 ° to 360 ° being the fourth area The skeleton lines where the areas where the separated skeleton lines exist are point-symmetrical with each other are connected by the shortest straight line, and the angle formed by each separated skeleton line is less than half of the set value. Preferably by connecting the lines together.
[0022]
In this way, the end point of the parabolic skeleton line and the intersection of the skeleton lines are enlarged by the set pixel, and after removing the skeleton line of the region enlarged by the set pixel (as an erase circle), the skeleton line is separated. Area where each skeleton line is separated by setting the XY axes with the intersection point of the skeleton lines (the center of the erased circle) as the origin, and the four divided ranges of 0 ° to 360 ° as the first to fourth areas, respectively. Check the (separated state), connect the skeleton lines where the areas where the separated skeleton lines exist are point-symmetrical with the shortest straight line, and the angle formed by each separated skeleton line is half of the set value By connecting the following skeleton lines, even if the skeleton lines are difficult to separate due to overlapping parabolic patterns on the image data, they can be reliably converted into independent parabolas.
[0023]
Furthermore, at this time, after binarizing the image data and detecting the vertex of the parabolic skeleton line, if there is one skeleton line branching from the vertex of the skeleton line, the skeleton line is not converted into an independent parabola. Can be excluded from measurement.
[0024]
In this way, after binarizing image data and detecting the vertex of the skeleton line, if there is one skeleton line that branches off from the vertex of the skeleton line, the measurement on the semiconductor wafer is performed by excluding the skeleton line from the measurement target. To remove parabolic defect (FPD) outside the area and efficiently convert only the parabolic defect (FPD) to be measured on the image data (within the measurement area) into an independent parabola. Can do. Therefore, measurement accuracy can be further improved.
[0025]
Then, quantification of crystal defects performed by automatically discriminating the independent parabola is performed when the vertical line is dropped from a position separated by a set number of pixels from a vertex on a horizontal line passing through the vertex of the independent parabola. An independent parabola whose angle formed by a straight line intersecting the independent parabola and connecting the intersection of the perpendicular and the parabola and the apex of the parabola and a horizontal line passing through the apex of the parabola is 20 ° to 65 °. It can be done by automatically identifying the crystal defect and quantifying the crystal defect.
[0026]
In this way, when a perpendicular line is dropped from a position that is a set number of pixels away from the vertex on the horizontal line passing through the vertex of the transformed independent parabola, the perpendicular line and the independent parabola intersect, and the perpendicular line and the parabola line By automatically discriminating an independent parabola whose angle formed by a straight line connecting the intersection and the apex of the parabola and a horizontal line passing through the apex of the parabola is 20 ° to 65 ° as a crystal defect, and quantifying the crystal defect, Only crystal defects (FPD) that are problematic in semiconductor devices can be quantified with high accuracy.
[0027]
In this case, the semiconductor single crystal is grown by the Czochralski method (CZ method) or the floating zone method (FZ method), and the selective etching applied to the semiconductor wafer manufactured from the semiconductor single crystal is K.₂Cr₂O₇It is preferable to use a mixed solution of hydrofluoric acid and water..
[0028]
In this way, a semiconductor single crystal is grown by the CZ method or the FZ method, and sliced from the semiconductor single crystal.₂Cr₂O₇By performing selective etching with a mixed solution of hydrofluoric acid and water, a parabolic pattern defect (FPD) occurs on the wafer surface. Since this FPD is known as a cause of a decrease in device yield, the necessity of the inspection is great, and it is very useful in manufacturing a semiconductor wafer to automatically inspect such an FPD as described above.
[0029]
Furthermore, according to the present invention, there is provided an automatic inspection device for a crystal defect for inspecting a parabolic pattern defect (FPD) appearing after selectively etching a surface of a semiconductor crystal, and holding at least the semiconductor crystal to be inspected. An imaging means for obtaining image data by imaging the surface of the held semiconductor crystal and performing image processing on the captured image data to convert a parabolic defect (FPD) on the image data into an independent parabola There is provided an automatic crystal defect inspection apparatus comprising: an image processing means for measuring, and a measuring means for automatically determining an independent parabola converted by the image processing means to quantify the crystal defect..
[0030]
In this way, at least a holding stage for holding a semiconductor crystal, an imaging means for imaging the surface of the semiconductor crystal to obtain image data, and image processing for performing parabolic pattern defects (FPD) to independent parabolas by performing image processing If an automatic inspection device for crystal defects having a measuring means for automatically determining independent parabola and quantifying crystal defects, a parabolic pattern defect (FPD) appearing on the surface of a selectively etched semiconductor crystal is automatically detected. Since inspection can reduce the burden on the operator and defects can be inspected according to a certain standard, there is no variation in inspection results, and crystal defects in semiconductor crystals can be inspected with high accuracy and stability. Automatic inspection device.
[0031]
At this time, it is preferable that the imaging means for obtaining image data by imaging the surface of the semiconductor crystal is a means for obtaining image data by imaging the surface of the semiconductor crystal with a CCD camera.
[0032]
Thus, if the imaging means is a means for obtaining the image data by imaging the surface of the semiconductor crystal with a CCD camera, the surface of the semiconductor crystal can be easily read and stored as two-dimensional image data.
[0033]
Further, image processing means for performing image processing on the captured image data to convert a parabolic pattern defect (FPD) on the image data into an independent parabola, binarizes the captured image data, and forms a parabola. After detecting a pattern defect (FPD) as a parabolic skeleton line, detecting an end point, a vertex, and an intersection of the skeleton lines of the parabolic skeleton line, a skeleton of the detected parabolic skeleton lines is detected. If there is no intersection between the skeleton lines on the line, the parabolic skeleton line is converted into an independent parabola as it is, and if there is an intersection between the skeleton lines on the skeleton line, the separation connection processing means is used. It is preferably a means for converting a parabolic skeleton line into an independent parabola by separating and connecting..
[0034]
In this way, the image processing means binarizes the image data, detects a parabolic defect (FPD), a parabolic skeleton line, and the end points, vertices, and intersections of the skeleton lines of the parabolic skeleton line. After that, if the detected parabolic skeleton line is converted into an independent parabola as described above, even if a parabolic defect (FPD) in the image data exists alone, Even if the defects (FPD) overlap each other, all the parabolic pattern defects (FPD) to be measured can be easily and surely converted into independent parabolas using a certain algorithm.
[0035]
At this time, the separation and connection processing means enlarges the end point of the parabolic skeleton line and the intersection of the skeleton lines by a set pixel, and erases the skeleton line of the area increased by the set pixel (as an erase circle) After separating the skeleton lines, the XY axes are set with the intersection (the center of the erased circle) between the skeleton lines as the origin, and the range from 0 ° to 90 ° is the first area, and the range from 90 ° to 180 ° is the first. 2 areas, 180 ° to 270 ° range as the third area, 270 ° to 360 ° range as the fourth area, the area where each of the separated skeleton lines exists (separation state) is confirmed and separated Connect the skeleton lines where the areas where the skeleton lines exist are point-symmetric to each other with the shortest straight line and the angle between each separated skeleton line is less than half of the set value. Can be a means.
[0036]
In this way, the separation and connection processing means enlarges the end points of the parabolic skeleton lines and the intersections of the skeleton lines by the set pixels, and erases the skeleton lines in the area increased by the set pixels (as an erase circle). After separating the lines, check the area (separated state) where each separated skeleton line exists as described above, and the straight line that minimizes the skeleton lines where the area where the separated skeleton line exists is point-symmetric If the skeleton lines are connected to each other and the angle between each separated skeleton line is less than half of the set value, the parabolic patterns overlap on the image data and are difficult to separate. Even if it exists, it can be reliably converted into an independent parabola.
[0037]
Further, the measuring means for automatically determining the independent parabola converted by the image processing means and quantifying the crystal defect is a perpendicular line from a position separated from a vertex on a horizontal line passing through the vertex of the independent parabola by a set number of pixels. When the vertical line is lowered, the angle between the straight line intersecting the independent parabola and connecting the intersection of the vertical line and the parabola and the apex of the parabola and the horizontal line passing through the apex of the parabola is from 20 °. It can be a means for automatically discriminating an independent parabola at 65 ° as a crystal defect and quantifying the crystal defect..
[0038]
In this way, when the measuring means drops a perpendicular from a position separated by a set number of pixels from the vertex on the horizontal line passing through the vertex of the converted independent parabola, the perpendicular and the independent parabola intersect, and the perpendicular The crystal defect is quantified by automatically discriminating an independent parabola whose angle formed by the straight line connecting the intersection of the parabola and the apex of the parabola and the horizontal line passing through the apex of the parabola is 20 ° to 65 ° as a crystal defect. If it is a means, only the crystal defect (FPD) which becomes a problem with a semiconductor device can be quantified with high precision.
[0039]
At this time, the apparatus of the present invention preferably includes stock means capable of stocking a plurality of semiconductor crystals to be inspected and transport means for automatically supplying and collecting the semiconductor crystals from the stock means to the holding stage..
[0040]
As described above, the automatic inspection apparatus for crystal defects according to the present invention includes stock means capable of stocking a plurality of semiconductor crystals and transport means for automatically supplying and recovering semiconductor crystals from the stock means to the holding stage. Even when there is no operator, crystal defects can be automatically and continuously inspected. Therefore, the inspection process for crystal defects can be completely automated, the burden on the operator can be further reduced, and the inspection efficiency and throughput can be significantly improved.
[0041]
Further, at this time, a reading means for reading the ID given to the semiconductor crystal to be inspected, a checking means for checking the measurement condition based on the ID of the read semiconductor crystal, and the checking of the measurement condition of the semiconductor crystal It is preferable to have switching means for automatically switching to the measured conditions.
[0042]
As described above, the automatic inspection device for crystal defects according to the present invention includes a reading unit for reading an ID of a semiconductor crystal, a checking unit for checking a measurement condition based on the read ID, and a switching unit for automatically switching the measurement condition. By having it, it is possible to automatically inspect crystal defects by switching the measurement conditions for each semiconductor crystal, so that it is possible to accurately inspect crystal defects even if there are no workers on various semiconductor wafers Can do.
[0043]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, although an embodiment is described about the present invention, the present invention is not limited to these.
Conventionally, inspection of parabolic pattern defects (FPD) appearing on the surface of a wafer has been counted visually by an operator, so that it is difficult to perform a stable inspection due to variations in inspection results, and an accurate inspection is performed. In order to do so, the skill level of the operator was also required. Further, in such inspection of FPD, reduction of inspection time, use at night, etc. are strongly desired in order to reduce the burden on the operator and to manufacture an efficient semiconductor wafer.
[0044]
Therefore, the present inventors have reduced the burden on the operator by enabling automatic operation so that crystal defects can be inspected even at night, and the accuracy of the semiconductor crystal is stable with high accuracy without variation in inspection results. In order to inspect crystal defects, the surface of a semiconductor wafer subjected to selective etching is imaged to obtain image data, and image processing is performed on the image data to separate parabolic pattern defects (FPD) on the image data. We have developed an automatic inspection method for crystal defects and an automatic inspection device for quantifying crystal defects by converting the parabola into a parabola and automatically distinguishing the converted independent parabola, and have completed the present invention through repeated studies. .
[0045]
First, an example of an automatic crystal defect inspection apparatus according to the present invention will be described with reference to the drawings. FIG. 2 is a schematic explanatory view of an automatic inspection apparatus for crystal defects according to the present invention, FIG. 2 (a) is a schematic sectional view of the automatic inspection apparatus, and FIG. 2 (b) is a schematic plan view. Is shown.
[0046]
The automatic inspection apparatus 1 for crystal defects according to the present invention is an automatic inspection apparatus that inspects a parabolic pattern defect (FPD) that appears after selective etching of the surface of a semiconductor crystal. The main configuration of the automatic inspection apparatus 1 will be described. A holding stage 2 holding a semiconductor crystal 6 for inspection (a disk-shaped semiconductor wafer divided into four), an imaging means 3 for imaging the surface of the held semiconductor crystal 6 and obtaining image data, and imaging Image processing means 4 that performs image processing on the converted image data and converts the FPD on the image data into an independent parabola, and a measurement that automatically discriminates the independent parabola converted by the image processing means and quantifies crystal defects Means 5 are provided.
[0047]
Here, it is preferable that the image pickup means 3 for picking up the image of the surface of the semiconductor crystal 6 to obtain image data is means for picking up the image of the surface of the semiconductor crystal with a CCD camera and obtaining image data. The CCD camera is preferably capable of observing the surface of the semiconductor crystal for inspection at a magnification of about 30 to 100 times. Depending on the inspection specification, the surface of the semiconductor crystal is usually imaged at about 50 times. The image data can be stored in the computer 7, for example. The image data stored in the computer 7 is analyzed by the image processing means 4 for performing image processing programmed in the computer 7 and the measuring means 5 for quantifying crystal defects, and the crystal defects are automatically quantified. be able to.
[0048]
The automatic inspection apparatus 1 for crystal defects includes a stock unit 8 that can stock a plurality of semiconductor crystals 6 and a transport unit 9 that automatically supplies and recovers the semiconductor crystal 6 from the stock unit 8 to the holding stage 2. It is preferable. If the stock means 8 and the transport means 9 are provided in this way, the inspection process for crystal defects can be completely automated, and even when there is no operator at night, the inspection for crystal defects is automatically continued. Thus, the inspection efficiency and throughput can be further improved, and the burden on the operator can be further reduced. A plurality of stock means for this semiconductor wafer can be provided, and the transport means can be freely moved according to the position and number of stock means.
[0049]
Further, the crystal defect automatic inspection apparatus 1 is based on reading means (not shown) for reading an ID and an inspection code given to the semiconductor crystal 6 to be inspected, and the read ID and inspection code of the semiconductor crystal. It is preferable to have collation means (not shown) for collating the measurement conditions and switching means (not shown) for automatically switching to the measurement conditions for collating the measurement conditions of the semiconductor crystal. At this time, the reading means can be combined with the imaging means 3 in FIG. 2, and the collating means and the switching means can be programmed on the computer 7 or may be provided separately.
[0050]
Next, a method of automatically inspecting a semiconductor crystal for crystal defects using such an automatic crystal defect inspection apparatus will be described.
The crystal defect automatic inspection method of the present invention is obtained by, for example, growing a semiconductor crystal by the Czochralski (CZ) method or the floating zone method (FZ method) and slicing the semiconductor single crystal to produce a semiconductor wafer. After the selective etching is performed on the semiconductor wafer to cause a parabolic pattern defect (FPD) to appear on the surface of the semiconductor wafer, the surface of the semiconductor wafer is imaged using, for example, the automatic inspection device for crystal defects described above. Image data is obtained, image processing is performed on the image data to convert a parabolic pattern defect (FPD) on the image data into an independent parabola, and the independent parabola is automatically determined to quantify crystal defects. To.
[0051]
Hereinafter, the automatic inspection method for crystal defects according to the present invention will be described in more detail with reference to the drawings. FIG. 3 is a flowchart showing an example of the automatic inspection method for crystal defects according to the present invention.
[0052]
(Preparation of semiconductor wafer)
First, a semiconductor wafer for inspection is prepared.
A semiconductor single crystal ingot such as silicon is grown by the Czochralski method (CZ method) or the floating zone method (FZ method), and the grown semiconductor single crystal ingot is formed to a predetermined thickness by a slicer such as a wire saw, for example, 1 to 2 mm. A semiconductor wafer having a thickness of about 1 is cut out. Thereafter, the obtained semiconductor wafer is etched with a mixed solution of hydrofluoric acid and nitric acid to remove surface distortions, thereby producing a semiconductor wafer for inspection. At this time, it is preferable to print the wafer ID and the inspection code on the surface thereof by laser marking or the like so that the semiconductor wafer for inspection can be identified when the crystal defect is inspected.
[0053]
Thus, by previously printing the ID and inspection code on the surface of the semiconductor crystal with laser marking or the like, the measurement position, measurement magnification, measurement range, etc. are automatically determined for each semiconductor crystal at the time of crystal defect inspection. Since the inspection can be performed by switching the measurement conditions, it is possible to accurately inspect the crystal defect without an operator.
[0054]
At this time, the inspection code printed on the surface of the semiconductor crystal for inspection is based on the inspection specification. For example, the necessary recipe relating to the above measurement conditions is expressed by simple four-digit alphanumeric characters. It can be registered in the laser marker and the inspection device.
[0055]
Further, the shape of the semiconductor wafer is not particularly limited. For example, when a grown semiconductor wafer having a large diameter of 200 mm or more is manufactured, the wafer is made easy to perform an etching process or a crystal defect inspection. It is good also as a fan-shaped wafer by dividing into four.
[0056]
(Pretreatment of semiconductor wafers)
After thoroughly cleaning the semiconductor wafer prepared above with pure water, slowly inject a semiconductor wafer for inspection (hereinafter simply abbreviated as a wafer) perpendicularly to the liquid surface of the SECCO liquid in a container containing the SECCO liquid. And the surface of the semiconductor wafer is selectively etched by holding it for 1 to 60 minutes, preferably 30 minutes in a stationary state (without stirring or the like). By performing selective etching on the wafer surface in this way, a parabolic pattern defect (FPD) that extends upward in the vertical direction with respect to the direction in which the wafer is immersed as shown in FIG. 16A appears on the wafer surface.
[0057]
At this time, the immersion time of the semiconductor wafer is not particularly limited, but if the etching is performed for more than 60 minutes, the parabolic patterns become too large, and the parabolic patterns overlap with each other, which is inconvenient for counting FPDs. On the other hand, when the immersion time is less than 1 minute, the parabola pattern does not sufficiently appear and it is difficult to count the FPD.
[0058]
(Imaging)
Thereafter, the pre-processed semiconductor wafer is held on a holding stage, the wafer surface is imaged, and image data is stored.
First, the pre-processed semiconductor wafer is stocked in stock means, moved from the stock means to a holding stage using a transfer robot as a transfer means, aligned, and then held on the holding stage.
[0059]
At this time, the semiconductor wafer is aligned so that the apex of the parabolic pattern is at the top when imaged by the imaging means, but the alignment of the semiconductor wafer is not particularly limited, and the imaging means and the wafer The position can be selected as appropriate depending on the positional relationship of the image, the direction of image processing, and the like. By performing the alignment mechanically in this manner, the alignment accuracy is good, and even when the same semiconductor wafer is repeatedly inspected, it is possible to perform a stable inspection with little variation.
[0060]
After the semiconductor wafer for inspection is held on the holding stage, the wafer ID and inspection code printed on the wafer surface are read using a reading means such as a CCD camera, and the read wafer ID and inspection code are sent to the computer. Based on the ID and the inspection code, the semiconductor wafer measurement conditions are verified by the verification means programmed on the computer, and the semiconductor wafer measurement conditions are automatically switched by the switching means. Can be automatically selected and set. If the measurement conditions can be automatically switched in this way, an accurate crystal defect inspection can be performed without an operator.
[0061]
Thereafter, the surface of the semiconductor wafer held on the holding stage is picked up using an imaging means such as a CCD camera and read as two-dimensional image data, and the obtained image data is stored in a computer or the like.
[0062]
(Image processing)
Subsequently, image processing is performed on the image data obtained above using an image processing unit, and a parabolic pattern defect on the image data is converted into an independent parabola. FIG. 4 is a flowchart showing an example of image processing.
In the image processing by the image processing means, first, the captured image data is binarized, and a parabolic pattern defect (FPD) is detected as a parabolic skeleton line. By binarizing the image data in this way, for example, a parabolic skeleton line as shown in FIG. 5 is detected from a parabolic pattern defect (FPD) appearing on the wafer as shown in FIG. can do. Note that FIG. 16A and FIG. 5 are upside down because the semiconductor wafer is held so that the apex of the parabolic pattern is positioned above the image data when the semiconductor wafer is aligned. It is.
[0063]
Next, by searching the measurement area of the obtained image data (FIG. 5), the end points and vertices of parabolic skeleton lines as shown in FIG. 6 and the intersections of the skeleton lines are detected.
After that, among the detected parabolic skeleton lines, those that do not have an intersection of the skeleton lines on the skeleton lines convert the parabolic skeleton lines into independent parabolas as they are. For example, since the skeleton line A in FIG. 6 has no intersection between the skeleton lines on the skeleton line, the skeleton line A is converted into an independent parabola A as shown in FIG. On the other hand, as for skeleton lines B to E in FIG. 6 where the intersections of skeleton lines exist on the skeleton line, each parabolic skeleton line is separated and connected using the separation and connection processing means to form independent parabolas. Convert.
[0064]
With regard to the separation and connection processing by this separation and connection processing means, the following describes the algorithm of the separation and connection processing by giving some examples regarding the crossing state of the skeleton lines.
The parabolic skeleton line separation and connection process is performed for the purpose of clarifying the end points of the detected skeleton lines and the intersection points of the skeleton lines, and for the set pixels, for example, 2-5 pixels, centering on these intersection points and end points. (Two pixels are usually sufficient.) Increase to form a circle. Next, smoothing is performed by reducing the circle enlarged by 2 to 5 pixels by 1 pixel, and then the skeleton line in the circle is erased to make an erased circle. By performing such processing, noise is removed, and parabolic skeleton lines are separated at the intersections of the skeleton lines. By this separation processing, the skeleton lines B to E shown in FIG. 6 are separated at the intersections of the skeleton lines as shown in FIG. In addition, if the set pixels when forming the circle are too small or too large, the accuracy when connecting the separated skeleton lines is lowered, so the set pixels are set to 2 to 5 pixels as described above. It is preferable to do.
[0065]
・ Consolidation process (1)
First, the case where a connection process is performed with respect to the intersection BC of the skeleton line B and the skeleton line C shown in FIG. FIG. 10 shows an enlarged view of the intersection BC after the separation process.
As shown in FIG. 10, the skeleton line separated at the intersection point BC is the intersection point from the vertex (b1) of the skeleton line B to the separation point (b3) of the intersection point BC, and from the vertex (c1) of the skeleton line C. The line c1c4 from the separation point (c4) of BC, the line b4b5 from the separation point (b4) of the intersection BC to the end point (b5) of the skeleton line B, and the end point of the skeleton line C from the separation point (c5) of the intersection BC The four separated skeleton lines of the line c5c6 up to c6) are obtained. In these separated skeleton lines, candidates for separated skeleton lines that can be linked to any one skeleton line are the other three separated skeleton lines.
[0066]
In order to select and connect an appropriate skeleton line from these three separated skeleton lines, the separation state of the separated skeleton lines is confirmed, and a connection process is performed on the separated skeleton lines having a certain relationship. Do.
That is, the separation state of the separated skeleton lines is set by virtually setting the XY axes with the intersection (the center of the erased circle) between the skeleton lines as the origin, and the range of 0 ° to 90 ° is the first area, 90 ° to A range of 180 ° is a second area, a range of 180 ° to 270 ° is a third area, a range of 270 ° to 360 ° is a fourth area, and is confirmed in an area where each separated skeleton line exists, Connect the skeleton lines where the areas where the separated skeleton lines exist are point-symmetric to each other with the shortest straight line, and the skeleton lines where the angle formed by each separated skeleton line is less than half of the set value. Link.
[0067]
Specifically, with reference to FIG. 11, the separated state of the separated skeleton line is that the c1c4 line is 0 ° to 90 ° when the X-axis and Y-axis are virtually set with the center of the intersection BC (cross circle) as the origin. The b1b3 line is in the range of 90 ° to 180 ° (second area), the c5c6 line is in the range of 180 ° to 270 ° (third area), and the b4b5 line is 270. It turns out that it exists in the range (4th area) of (degree)-360 degrees. After confirming the separation state of the skeleton line thus separated, for example, when the c1c4 line in the range of 0 ° to 90 ° (first area) including the vertex c1 is combined, And a line in the third area (180 ° to 270 °) at a point-symmetrical position is selected as a candidate for a combined line. That is, in FIG. 11, the c5c6 line is a connection target of the c1c4 line.
[0068]
Subsequently, the c1c4 line and the c5c6 line are connected by the shortest straight line, and the lines are connected when the angle formed by the straight line and the c1c4 line or the c5c6 line is equal to or less than half the set value. For example, when etching is performed under the etching conditions performed this time, since the angle of the set value is empirically 30 °, the separated skeleton lines are connected if they are 15 ° or less. That is, in the case of the c1c4 line and the c5c6 line, the angle formed by each skeleton line and the straight line connecting the skeleton lines at the shortest is 15 ° or less (because it is almost a straight line, the angle is 0 °). The line and the c5c6 line can be connected to form a c1c6 line.
Similarly, the b1b3 line (the line existing in the second area) having the vertex b1 of the skeletal line B can be connected to the b4b5 line in the fourth area having a point-symmetrical relationship to obtain a new b1b5 line. be able to.
[0069]
However, in the actual defect inspection, not only one skeleton line separation state as described above exists in each area, but also a plurality of skeleton lines in the same area as shown in FIGS. 12 and 14, for example. In some cases, there are lines. Then, the case where the intersection CC1 shown in FIG. 12 is connected, and the case where the skeleton line as shown in FIG. 14 is connected as another example will be described.
[0070]
・ Consolidation process (2)
FIG. 12 shows an enlarged view of the intersection CC1 between the skeleton line C and the skeleton line C1 subjected to the separation processing shown in FIG.
As shown in FIG. 12, the skeleton line separated at the intersection CC1 is the skeleton from the line c1c2 from the vertex (c1) of the skeleton line C to the separation point (c2) of the intersection CC1, and from the separation point (c3) of the intersection CC1. The line c3c4 extends to the end point (c4) of the line C, and the line c16c17 is separated from the vertex (c16) of the skeleton line C1 to the separation point (c17) of the intersection CC1. In these separated skeleton lines, the candidate for the separated skeleton line that can be connected to any one skeleton line is the other two separated skeleton lines.
[0071]
For example, as shown in FIG. 13, when the X-axis and Y-axis are virtually set with the center of the intersection CC1 (cross circle) as the origin, the c1c2 line is 0 ° to 90 °. In the range (first area), the c3c4 line exists in the range of 180 ° to 270 ° (third area), and the c16c17 line exists in the range of 0 ° to 90 ° (first area). That is, there are a plurality of lines in the same area. When the skeleton lines where the areas where these separated skeleton lines exist are point-symmetrical with each other are connected by the shortest straight line, the two straight lines connecting c2 and c3 and the straight line connecting c17 and c3 are separated from the c3c4 line. Be drawn.
[0072]
However, as described above, the present invention connects the skeleton lines having the angle between the skeleton lines that are less than half of the set value and the skeleton lines that are less than half the set value, as described above. Of these, a combination of the c1c2 line and the c3c4 line satisfies the connection condition, and a new c1c4 line can be obtained by connecting these lines. At this time, the line c16c17 that is not to be connected is deleted (or connected to another line).
[0073]
・ Consolidation process (3)
Next, a case where separated skeleton lines as shown in FIG. 14 are connected will be described. The separated skeleton line shown in FIG. 14 includes a line f1f2 from the vertex (f1) of the skeleton line to the separation point (f2), a line f3f4 from the separation point (f3) to the end point (f4) of the skeleton line, and the separation. There are three lines f5f6 from the point (f5) to the end point (f6) of the other skeleton line. In these separated skeleton lines, the candidate for the separated skeleton line that can be connected to any one skeleton line is the other two separated skeleton lines.
[0074]
The separation state of these separated skeleton lines is set in the range of 0 ° to 90 ° (first area) when the X axis and the Y axis are set virtually with the center of the erased circle as the origin, as described above. In addition, the f5f6 line and the f3f4 line exist in the range of 180 ° to 270 ° (third area). That is, if two lines exist in the same third area and the areas where the separated skeleton lines exist are connected in a point-symmetric relationship with each other by the shortest straight line, f2 and f3 are connected. Two straight lines connecting the straight line and f2 and f5 are drawn from the f1f2 line.
[0075]
However, in the same manner as described above, the angle formed by each skeleton line separated from the straight line in which the skeleton lines are the shortest among these two straight lines is a combination of the f1f2 line and the f3f4 line. By connecting these separated skeleton lines, a new f1f4 line can be obtained. At this time, the line f5f6 that is not to be connected is deleted (or connected to another line).
[0076]
As described above, among the parabolic skeleton lines, those having no skeletal line intersection on the skeleton line convert the parabolic skeleton line into an independent parabola as it is, and the skeletal line intersection points on the skeleton line. The existing ones can be converted into independent parabolas by separating and connecting each parabolic skeleton line using the separation and connection processing means.
[0077]
In addition, when converting a parabolic skeleton line into an independent parabola, after binarizing the image data and detecting the vertex of the parabolic skeleton line, there is one skeleton line that branches from the vertex of the skeleton line It is preferable to exclude the skeleton line from being measured without converting it into an independent parabola. That is, for example, when there are two lines extending from the vertex a1 to the lower left (end point a2) and the lower right (end point a3) in the measurement area, as in the skeleton line A shown in FIG. On the other hand, when the skeleton line from the vertex e1 has only one line at the lower left (end point e2) as in the skeleton line E shown in FIG.
[0078]
That is, the skeleton line E is a parabolic pattern defect (FPD) similar to the skeleton line A, but there is only one skeleton line that branches from the vertex of the skeleton line in the measurement area, and the other branches to the other. Since the skeletal line is outside the measurement area, by excluding such a skeleton line from the measurement object, only the parabolic pattern defect (FPD) within the measurement area range on the image data can be efficiently converted into an independent parabola. The measurement accuracy can be further improved. In the flowchart of FIG. 4, the confirmation of the vertex branching condition is performed before the confirmation of the intersection of the skeleton lines, but is not limited to this, for example, after the confirmation of the intersection of the skeleton lines. Vertex branching conditions may be checked.
By performing the processing as described above, a parabolic pattern defect (FPD) on the image data, for example, a parabolic pattern defect (FPD) on the image data shown in FIG. Parabola can be obtained.
[0079]
(Quantification of crystal defects)
Thereafter, the crystal defects are quantified by automatically discriminating the independent parabola converted by the above processing. As shown in FIG. 1, the quantification of the crystal defect is performed when a perpendicular line is dropped from a position separated by a set number of pixels from a vertex on a horizontal line passing through the vertex of an independent parabola. In addition, an independent parabola whose angle formed by a straight line connecting the intersection of the perpendicular and the parabola and the apex of the parabola and a horizontal line passing through the apex of the parabola is 20 ° to 65 ° is automatically determined as a crystal defect, This is done by quantifying what is identified as a crystal defect.
[0080]
Here, as to the angle formed by the straight line connecting the intersection of the perpendicular and the parabola and the apex of the parabola and the horizontal line passing through the apex of the parabola, as a result of actually investigating the FPD by microscopic observation, this angle is almost 20 It was found to be in the range of ° to 65 °. Therefore, it was determined that, by using this as a measurement object, only crystal defects that are problematic in semiconductor devices can be quantified with high accuracy.
[0081]
At this time, since extremely small parabolic pattern defects (FPD) are excluded from the measurement target, the set number of pixels from the vertex on the horizontal line passing through the vertex of the parabola to the position where the perpendicular is lowered is empirically about 10 pixels. It is preferable to set.
[0082]
In the above, the angle formed by the straight line connecting the intersection of the perpendicular and the parabola and the apex of the parabola and the horizontal line passing through the apex of the parabola is set, and crystal defects are automatically determined. A method is adopted in which the area of the parabola formed from the vertex of the converted independent parabola and the two end points is obtained, and a parabola whose area is larger than a preset minimum set area is automatically determined as a crystal defect. You can also. Thus, by automatically determining based on the area of the parabola, crystal defects can be automatically determined with higher accuracy.
[0083]
(End of inspection)
After the inspection is completed, the inspection result is automatically recorded in the computer, and the semiconductor wafer after the inspection is transferred from the holding stage to the stock means by the transfer robot. Thereafter, the next semiconductor wafer is continuously carried from the stock means to the holding stage, and the same crystal defect inspection as described above can be automatically repeated.
[0084]
By performing the automatic inspection method for crystal defects as described above, it is possible to automatically inspect a parabolic pattern defect (FPD) without an operator, so that the inspection time can be shortened by night use and the like. The burden on the operator can be reduced, and further, inspection results can be inspected for crystal defects in a semiconductor crystal with high accuracy and no variation.
[0085]
【Example】
EXAMPLES Hereinafter, although an Example is shown and this invention is demonstrated more concretely, this invention is not limited to these.
A crystal defect was inspected in the same measurement area using the same wafer by a skilled worker and the automatic inspection apparatus for crystal defects of the present invention.
[0086]
As a semiconductor wafer for inspection, a semiconductor silicon single crystal was grown by the CZ method, and a fan-shaped wafer in which a wafer having a diameter of 200 mm obtained by slicing the semiconductor single crystal was divided into four parts was used. The obtained fan-shaped semiconductor wafer is selectively etched with a SECCO solution to cause a parabolic pattern defect (FPD) to appear on the surface of the semiconductor wafer, and then the crystal defects of the present invention as shown in FIG. Using the inspection apparatus, an area of 10 mm in measurement area × 1 mm in height from the position excluding 10 mm from the center was taken as 1 point, and 8 points in the plane were inspected. Microscope observation with a CCD camera was inspected under the condition of a measurement magnification of 50 times. Moreover, the same measurement area was imaged with a CCD camera, and the obtained image data was displayed on a monitor, and a skilled worker visually counted using an electronic pen.
[0087]
Comparing the results of inspecting crystal defects of a semiconductor wafer with an automatic inspection device of the present invention and a skilled worker, the result of confirming the detection capability of the automatic inspection device of the present invention as a correct numerical value of the skilled worker, With respect to the total of 195 defects counted by the operator, the automatic inspection apparatus of the present invention misses 5 (missing rate 2.6%), and mistakenly identifies 2 (false detection rate 1.0%). The coincidence rate was 96.4%, and the detection capability was excellent. Comparing the miss rate and the false detection rate with the case where a plurality of workers inspect the same semiconductor crystal, it was found that the automatic inspection apparatus of the present invention has small inspection variations and can perform a stable inspection. In addition, the repeated measurement accuracy when the same point of the same sample was repeatedly measured was much higher than that performed by the operator, and a stable inspection could be performed.
[0088]
The present invention is not limited to the above embodiment. The above-described embodiment is an exemplification, and the present invention has substantially the same configuration as the technical idea described in the claims of the present invention, and any device that exhibits the same function and effect is the present invention. It is included in the technical scope of the invention.
[0089]
【The invention's effect】
As described above, using a crystal defect automatic inspection apparatus having at least a holding stage, an imaging means, an image processing means, and a measuring means, the surface of the semiconductor wafer is imaged to obtain image data, and the image data is obtained from the image data. After the process is converted into an independent parabola, the independent parabola is automatically discriminated and the crystal defects are quantified, whereby a crystal defect having a complicated shape such as FPD can be automatically inspected. By automatically inspecting the FPD in this way, there is no variation in inspection results between workers due to differences in skill level or individual differences, and high-accuracy and stable defect inspection can be performed. Furthermore, since automatic inspection at night is possible, the inspection time can be shortened to efficiently inspect crystal defects, and the burden on the operator can be remarkably reduced.
[Brief description of the drawings]
FIG. 1 is a schematic explanatory diagram showing a method for automatically discriminating independent parabolas in the present invention.
FIG. 2 is a schematic explanatory view showing an example of an automatic inspection apparatus for crystal defects according to the present invention. (A) Schematic sectional view, (b) Schematic plan view.
FIG. 3 is a flowchart showing an example of an automatic inspection method for crystal defects according to the present invention.
FIG. 4 is a flowchart showing an example of an image processing method of the present invention.
FIG. 5 is a diagram showing a result of detecting parabolic skeleton lines by binarizing image data obtained by imaging the surface of a semiconductor wafer.
6 is a diagram showing a result of detecting end points, vertices, and intersections of skeleton lines of parabolic skeleton lines from the image data in which the parabolic skeleton lines of FIG. 5 are detected.
FIG. 7 is a diagram illustrating branching of a skeleton line A and a skeleton line E.
FIG. 8 is a diagram showing skeleton lines B to E after separation processing.
FIG. 9 is a diagram showing an intersection point BC of a skeleton line B and a skeleton line C and an intersection point CC1 of the skeleton line C and the skeleton line C1.
FIG. 10 is an enlarged view in which an intersection BC of the skeleton line B and the skeleton line C is enlarged.
FIG. 11 is an explanatory diagram showing a connection process at an intersection BC.
FIG. 12 is an enlarged view of an intersection CC1 between the skeleton line C and the skeleton line C1.
FIG. 13 is an explanatory diagram showing a connection process at an intersection CC1.
FIG. 14 is an explanatory diagram showing a connection process for connecting the f1f2 line and the f3f4 line.
FIG. 15 is a diagram showing independent parabolas converted by the image processing of the present invention.
FIG. 16 is an observation view of the wafer surface after selective etching.
(A) When the wafer is thrown perpendicular to the liquid level of the SECCO liquid,
(B) When the wafer is placed horizontally with respect to the liquid level of the SECCO liquid.
[Explanation of symbols]
1 ... Automatic inspection device for crystal defects of the present invention,
2 ... holding stage, 3 ... imaging means,
4 ... image processing means, 5 ... measuring means,
6 ... semiconductor crystal, 7 ... computer,
8 ... Stock means, 9 ... Conveyance means.

Claims (11)

A method for automatically inspecting a crystal defect of a semiconductor crystal by slicing a grown semiconductor single crystal to produce a semiconductor wafer, and subjecting the obtained semiconductor wafer to selective etching to form a parabolic pattern on the surface of the semiconductor wafer. After the appearance of a defect (FPD), the surface of the semiconductor wafer is imaged to obtain image data,
Binarize the imaged image data, detect a parabolic defect (FPD) as a parabolic skeleton line, detect the end points, vertices, and intersections of the skeleton lines of the parabolic skeleton line; After that, among the detected parabolic skeleton lines, those that do not have an intersection of skeleton lines on the skeleton line, the parabolic skeleton line is converted into an independent parabola as it is, while the intersection of the skeleton lines on the skeleton line In which the parabolic skeleton is separated and connected to an independent parabola,
A method for automatically inspecting a crystal defect, wherein the crystal defect is quantified by automatically discriminating the independent parabola. In the parabolic skeleton line separation and connection process, the end point of the parabolic skeleton line and the intersection of the skeleton lines are enlarged by a set pixel, and the skeleton line of the region enlarged by the set pixel is erased (erased circle). After the skeleton lines are separated, the XY axes are set with the intersection (center of the erased circle) between the skeleton lines as the origin, the range from 0 ° to 90 ° is the first area, and the range from 90 ° to 180 ° The second area, the range from 180 ° to 270 ° as the third area, and the range from 270 ° to 360 ° as the fourth area, confirm the area (separation state) where each separated skeleton line exists The skeleton lines where the areas where the separated skeleton lines exist are point-symmetrical with each other are connected by the shortest straight line, and the skeleton lines where the angle formed by each separated skeleton line is less than half of the set value to claim 1, characterized in that by concatenating The automatic inspection method of the crystal defect of description. After binarizing the image data and detecting the vertex of a parabolic skeleton line, if there is one skeleton line that branches from the vertex of the skeleton line, the skeleton line is not measured without being converted into an independent parabola. The method for automatically inspecting crystal defects according to claim 1 or 2 , wherein: Quantification of crystal defects performed by automatically discriminating the independent parabola is performed when a perpendicular is drawn from a position separated by a set number of pixels from a vertex on a horizontal line passing through the vertex of the independent parabola. An independent parabola intersects and a straight line connecting the intersection of the perpendicular and the parabola and the apex of the parabola and a horizontal line passing through the apex of the parabola forms an independent parabola of 20 ° to 65 ° as a crystal defect. automatic test method of crystal defects according to any one of claims 1 to 3, characterized in that conducted by by automatically discriminating quantify crystal defects as. The semiconductor single crystal is grown by the Czochralski method (CZ method) or the floating zone method (FZ method), and K ₂ Cr ₂ O ₇ and hydrofluoric acid are selectively etched on the semiconductor wafer produced from the semiconductor single crystal. The method for automatically inspecting crystal defects according to any one of claims 1 to 4 , wherein the method is carried out using a mixed solution of water and water. A crystal defect automatic inspection apparatus for inspecting a parabolic pattern defect (FPD) appearing after selectively etching a surface of a semiconductor crystal, at least a holding stage for holding the semiconductor crystal to be inspected, and a held semiconductor crystal Imaging means for obtaining image data by imaging the surface of the image, image processing means for performing image processing on the captured image data to convert a parabolic pattern defect (FPD) on the image data into an independent parabola, and the image the converted independent parabola with processing means to automatically determine have a measuring means for quantifying the crystal defect, the image processing means binarizes the captured image data, defect parabolic pattern (FPD ) As a parabolic skeleton line, and the end points, vertices, and intersections of the skeleton lines of the parabolic skeleton line are detected. When there is no intersection between skeleton lines on the skeleton line, the parabolic skeleton line is converted into an independent parabola as it is, and when there is an intersection between the skeleton lines on the skeleton line, the separation and connection processing means is used. An apparatus for automatically inspecting a crystal defect, characterized in that the parabolic skeleton line is converted into an independent parabola by separation and connection processing . 7. The crystal defect automatic according to claim 6 , wherein the imaging means for obtaining image data by imaging the surface of the semiconductor crystal is means for obtaining image data by imaging the surface of the semiconductor crystal with a CCD camera. Inspection device. The separation and connection processing means enlarges the end point of the parabolic skeleton line and the intersection of the skeleton lines by a set pixel, erases the skeleton line of the area enlarged by the set pixel (as an erase circle), After separation, the XY axes are set with the intersection (center of the erased circle) between the skeleton lines as the origin, the range from 0 ° to 90 ° is the first area, and the range from 90 ° to 180 ° is the second area The area where the separated skeleton lines exist (separated state) is confirmed with the range of 180 ° to 270 ° as the third area and the range of 270 ° to 360 ° as the fourth area, and the separated skeleton lines This is a means of connecting skeleton lines that have symmetric lines that are connected to each other by the shortest straight line and the angle formed by each separated skeleton line is less than half of the set value. 8. The method according to claim 6 or 7 , wherein Automatic inspection device for crystal defects. The measuring means for automatically determining the independent parabola converted by the image processing means and quantifying the crystal defect lowers the perpendicular from the position separated from the vertex on the horizontal line passing through the vertex of the independent parabola. The angle between the straight line intersecting the independent parabola and connecting the intersection of the perpendicular and the parabola and the apex of the parabola and the horizontal line passing through the apex of the parabola is 20 ° to 65 °. independent parabola automatic inspection system of the crystal defects according to any one of claims 6 to 8 characterized in that it is a means to quantify the by automatically determining crystal defects as a crystal defect is. A stocking means capable plurality stock semiconductor crystal to be the test, any of claims 6 to 9, characterized in that it has a conveying means for supplying and recovering the holding stage automatically the semiconductor crystal from the stock unit An automatic inspection device for crystal defects according to claim 1. The reading means for reading the ID attached to the semiconductor crystal to be inspected, the collating means for collating the measurement condition based on the read ID of the semiconductor crystal, and the measurement condition of the semiconductor crystal as the collated measurement condition The automatic inspection device for crystal defects according to any one of claims 6 to 10 , further comprising switching means for automatically switching.

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