CN111223080A - Wafer detection method and device, electronic equipment and storage medium - Google Patents
Wafer detection method and device, electronic equipment and storage medium Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G06F18/00—Pattern recognition
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- G06F18/22—Matching criteria, e.g. proximity measures
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V10/20—Image preprocessing
- G06V10/30—Noise filtering
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/48—Extraction of image or video features by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30148—Semiconductor; IC; Wafer
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Abstract
The disclosure provides a wafer detection method and device, an electronic device and a storage medium. The method comprises the following steps: collecting images of wafers in the processing process, wherein the images comprise defect points and coordinate information corresponding to the defect points, sequentially performing noise reduction processing, transformation processing and feature extraction processing on the images to obtain feature information corresponding to the images, scratch information corresponding to the wafer is generated according to the characteristic information, the characteristic information is obtained by adopting an image recognition technology to recognize the image, the problems of low accuracy and the like caused by manual recognition can be avoided, thereby realizing the technical effects of improving the accuracy and the reliability of the identification, improving the identification efficiency and saving the labor cost, and the scratch information is generated based on the characteristic information, so that the problems of low efficiency and low accuracy caused by manually combining an Excel marking tool in the prior art are solved, and the technical effects of improving the efficiency and accuracy of determining the scratch information are further realized.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for detecting a wafer, an electronic device, and a storage medium.
Background
Wafers (wafers), which are carriers used in the production of integrated circuits, are referred to as single crystal silicon wafers. In a semiconductor manufacturing process, wafers need to go through a series of processes such as illumination, etching, plasma implantation, etc., and the wafers are transferred by various robots of a machine station when entering and exiting different machine stations, and the robots may scratch the wafers to form scratches.
In the prior art, scratches are mainly identified manually. For example, in some prior arts, a map corresponding to a wafer is generated, a scratch in the map is recognized by a worker through eyes, and parameters of the scratch recognized by the eyes, such as the direction and length of the scratch, can be determined through an Excel scribing tool.
However, in the process of implementing the present disclosure, the inventors found that at least the following problems exist: the recognition efficiency and recognition accuracy caused by manually recognizing the scratch are low.
Disclosure of Invention
The present disclosure provides a wafer detection method and apparatus, an electronic device, and a storage medium, which are used to solve the problems of low recognition efficiency and low recognition accuracy caused by manually recognizing scratches in the prior art.
In one aspect, an embodiment of the present disclosure provides a method for inspecting a die, where the method includes:
acquiring an image of a wafer in a machining process, wherein the image comprises defect points and coordinate information corresponding to the defect points;
sequentially carrying out noise reduction processing, transformation processing and feature extraction processing on the image to obtain feature information corresponding to the image;
and generating scratch information corresponding to the wafer according to the characteristic information.
In some embodiments, denoising the image comprises:
determining distribution information of the defect points based on the coordinate information;
dividing the image into a plurality of regions according to the distribution information;
determining a density of defect point correspondences in each of the regions;
and filtering the defect points of the area with the density smaller than the preset first threshold value.
In some embodiments, after the generating of the scratch information corresponding to the wafer according to the feature information, the method further comprises:
acquiring fingerprint information respectively set for a plurality of machines;
matching the fingerprint information with the scratch information to obtain a matching degree;
and determining the machine corresponding to the fingerprint information with the matching degree larger than a preset second threshold value as a suspected abnormal machine.
In some embodiments, before the acquiring fingerprint information respectively set for a plurality of machines, the method further includes:
acquiring attribute information corresponding to each machine table, wherein one machine table corresponds to at least one piece of attribute information, and the attribute information at least comprises mechanical arm information;
and fingerprint information of each machine is constructed according to each attribute information, wherein one machine corresponds to at least one piece of fingerprint information.
In some embodiments, after the generating of the scratch information corresponding to the wafer according to the feature information, the method further comprises:
calculating the scratching rate of the wafers in the same batch;
judging the size of the scratching rate and a preset third threshold value;
if the scratching rate is greater than the third threshold value, generating and pushing first prompt information, wherein the first prompt information is used for prompting the suspension of the use of the wafers in the same batch; and/or the presence of a gas in the gas,
in response to the continuous plurality of wafers being scratched, judging the quantity of the continuous scratched wafers and the size of a preset fourth threshold value;
and if the number of the continuously scratched wafers is larger than the fourth threshold value, generating and pushing second prompt information, wherein the second prompt information is used for prompting the suspension of the use of each machine in the machining process.
In another aspect, an embodiment of the present disclosure further provides a device for detecting a wafer, where the device includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an image of a wafer in the processing process, and the image comprises defect points and coordinate information corresponding to the defect points;
the processing module is used for sequentially carrying out noise reduction processing, transformation processing and feature extraction processing on the image to obtain feature information corresponding to the image;
and the generating module is used for generating scratch information corresponding to the wafer according to the characteristic information.
In some embodiments, the processing module is configured to determine distribution information of the defect points based on the coordinate information, divide the image into a plurality of regions according to the distribution information, determine a density corresponding to the defect point in each of the regions, and filter the defect points of the region having the density smaller than a preset first threshold.
In some embodiments, the apparatus further comprises:
the first acquisition module is used for acquiring fingerprint information which is respectively set for a plurality of machines;
the matching module is used for matching the fingerprint information with the scratch information to obtain a matching degree;
and the determining module is used for determining the machine corresponding to the fingerprint information with the matching degree larger than a preset second threshold as a suspected abnormal machine.
In some embodiments, the apparatus further comprises:
a second obtaining module, configured to obtain attribute information corresponding to each machine, where one machine corresponds to at least one piece of attribute information, and the attribute information at least includes information about a mechanical arm;
and the construction module is used for constructing the fingerprint information of each machine according to each attribute information, wherein one machine corresponds to at least one piece of fingerprint information.
In some embodiments, the apparatus further comprises:
the calculating module is used for calculating the scratching rate of the wafers in the same batch;
the first judgment module is used for judging the scratch rate and the size of a preset third threshold value;
the first pushing module is used for generating and pushing first prompt information if the scratching rate is greater than the third threshold value, wherein the first prompt information is used for prompting the suspension of the use of the wafers in the same batch; and/or the presence of a gas in the gas,
the second judging module is used for responding to the fact that the plurality of continuous wafers are scratched, and judging the number of the continuously scratched wafers and the size of a preset fourth threshold value;
and the second pushing module is used for generating and pushing second prompt information if the number of the continuously scratched wafers is greater than the fourth threshold, wherein the second prompt information is used for prompting the suspension of the use of each machine in the machining process.
In another aspect, an embodiment of the present disclosure further provides an electronic device, including: a memory, a processor;
a memory for storing the processor-executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement a method as in any of the embodiments above.
In another aspect, the disclosed embodiments also provide a computer-readable storage medium, in which computer-executable instructions are stored, and when executed by a processor, the computer-executable instructions are used to implement the method according to any one of the above embodiments.
The present disclosure provides a wafer detection method and apparatus, an electronic device, and a storage medium, including: collecting images of wafers in the processing process, wherein the images comprise defect points and coordinate information corresponding to the defect points, sequentially performing noise reduction processing, transformation processing and feature extraction processing on the images to obtain feature information corresponding to the images, generating scratch information corresponding to the wafer according to the characteristic information, identifying the image by adopting an image identification technology to obtain the characteristic information, but not the prior art which adopts a manual mode to identify, can avoid the problems of low accuracy and the like caused by manual mode identification, thereby realizing the technical effects of improving the accuracy and the reliability of the identification, improving the identification efficiency and saving the labor cost, and the scratch information is generated based on the characteristic information, so that the problems of low efficiency and low accuracy caused by manually combining an Excel marking tool in the prior art are solved, and the technical effects of improving the efficiency and accuracy of determining the scratch information are further realized.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a schematic view of an application scenario of a wafer inspection method according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating a wafer inspection method according to an embodiment of the present disclosure;
fig. 3 is a flowchart illustrating a method for denoising an image according to an embodiment of the disclosure;
FIG. 4 is a schematic flow chart illustrating a wafer inspection method according to another embodiment of the present disclosure;
FIG. 5 is a schematic diagram of an apparatus for inspecting a wafer according to an embodiment of the present disclosure;
FIG. 6 is a schematic diagram of an apparatus for inspecting a wafer according to another embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure;
with the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
In the prior art, scratches are mainly identified manually, so that on one hand, the accuracy of identification is not high because workers are easily influenced by personal subjective factors in the identification process; on the other hand, a general production line is mass production, so the number of wafers to be detected is large, and due to various factors such as physical constitution of workers, the problems of low detection efficiency and high labor cost are easily caused. In order to solve the above problems caused by manual identification in the prior art, the inventor obtains the technical scheme implemented by the disclosure through creative labor. In this embodiment of the disclosure, through adopting the image recognition technology to discern the image of wafer to avoid because of the not high scheduling problem of the degree of accuracy that manual identification caused, and then realize improving the degree of accuracy and the efficiency of discernment, and realize practicing thrift human cost's technological effect.
The wafer detection method provided by the embodiment of the disclosure can be applied to the application scenario shown in fig. 1.
In the application scenario shown in fig. 1, the production line 100 includes an image capture device (not shown in fig. 1), wherein the image capture device includes, but is not limited to, an electron microscope, a radio microscope, a video camera, and a still camera. The image capturing device captures an image of a wafer (i.e., a wafer during a process) on the production line 100, the image includes defect points, and the defect points include but are not limited to defect points caused by the transfer of a robot arm on the machine to the wafer.
The image acquisition device sends the image including the defect point to the server 200, and the server 200 executes the wafer detection method according to the embodiment of the present disclosure to obtain scratch information corresponding to the wafer.
In some embodiments, a processor may also be disposed in the image capturing device, for example, the image capturing device includes a camera and a processor, and the camera and the processor are in communication connection, so that after the camera captures an image, the image may be input to the processor, and the processor executes the method for detecting a wafer according to the embodiments of the present disclosure, and identifies the image by using an image identification technology, so as to obtain scratch information.
In other embodiments, as can be seen in conjunction with fig. 1, the server 200 is communicatively connected to the display device 300 to push scratch information to the display device 300.
The display device 300 displays the scratch information so that the staff can obtain the visual scratch information and further take corresponding coping strategies, such as production suspension and the like.
In some embodiments, the server 200 may also be communicatively coupled to a voice device (not shown in fig. 1) to push the scratch information, or the voice information converted from the scratch information, to the voice device.
The voice device performs voice broadcast based on scratch information or voice information.
In some embodiments, a voice device may be integrated with the display device 300, i.e., the display device 300 may be used for both displaying and voice broadcasting scratch information.
Of course, in other embodiments, a terminal identifier (e.g., a telephone number) of the worker may be set in the server 200, and when the scratch information is detected, the scratch information is sent to the terminal corresponding to the terminal identifier; and/or the presence of a gas in the gas,
the mailbox identifier of the staff may be set in the server 200, and when the scratch information is detected, the scratch information is sent to the mailbox corresponding to the mailbox identifier.
The following describes the technical solutions of the present disclosure and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
In one aspect, the embodiment of the present disclosure provides a method for detecting a wafer suitable for the above application scenario.
Referring to fig. 2, fig. 2 is a schematic flow chart illustrating a wafer inspection method according to an embodiment of the disclosure.
As shown in fig. 2, the method includes:
s101: and acquiring an image of the wafer in the machining process, wherein the image comprises defect points and coordinate information corresponding to the defect points.
The main body for executing the method for detecting a wafer according to the embodiment of the present disclosure may be a device for detecting a wafer, and the device may be a terminal, a server, or the like.
The general process includes a plurality of processes, and the wafer inspection is a sampling inspection. If sixty processes are total, the wafers can be sampled from the sixty processes based on the preset sampling rule, and the sampled wafers can be detected.
The image (defect map) includes defect points, the defect points are caused by various processing technologies, including but not limited to scratching the wafer when the wafer is transferred by the mechanical arm, and the image (defect map) also includes coordinate information corresponding to the defect points.
S102: and sequentially carrying out noise reduction processing, transformation processing and feature extraction processing on the image to obtain feature information corresponding to the image.
In the prior art, scratches in an image are identified manually, and in order to solve the problem of low accuracy and the like caused by manual identification, in the embodiment of the present disclosure, an image is identified by an image identification technology. In particular, the amount of the solvent to be used,
and carrying out noise reduction processing on the image to obtain an image subjected to noise reduction processing, carrying out transformation processing on the image subjected to noise reduction processing to obtain an image subjected to transformation processing, and carrying out feature extraction processing on the image subjected to transformation processing to obtain feature information.
In some embodiments, the transform processing may be implemented based on a hough transform, and may also be implemented based on deep learning.
For example, the image after the noise reduction processing is processed by hough transform to determine the shape, such as a straight line, corresponding to the defect point.
If the shape of the defect point is a straight line, feature extraction processing is performed on the straight line to obtain feature information of the defect point on the straight line, wherein the feature information includes, but is not limited to, coordinate information.
In the embodiment of the disclosure, the image is identified according to the image identification technology, so that the labor cost in the prior art for identification in a manual mode is reduced; compared with manual detection, the method avoids the influence of artificial subjective factors and improves the accuracy of identification; and the influence of factors such as artificial physique is avoided, and the identification efficiency is improved.
S103: and generating scratch information corresponding to the wafer according to the characteristic information.
In this step, after the characteristic information is acquired, calculation or the like may be performed based on the characteristic information, thereby obtaining the scratch information corresponding to the wafer.
Wherein, the scratch information comprises the position, the angle, the length, the width, the chord center distance and the like of the scratch.
In the prior art, an image is recognized by human eyes, and scratch information of the recognized scratch is calculated by an Excel scribing tool. In the embodiment of the present disclosure, based on the feature information obtained in S102, calculation may be performed based on the feature information, so as to obtain scratch information. Therefore, the problems of low efficiency and low accuracy caused by manual combination of an Excel marking tool are solved, and the technical effects of improving the efficiency and accuracy of determining scratch information are achieved.
The embodiment of the present disclosure provides a new wafer inspection method, which includes: collecting images of wafers in the processing process, wherein the images comprise defect points and coordinate information corresponding to the defect points, sequentially performing noise reduction processing, transformation processing and feature extraction processing on the images to obtain feature information corresponding to the images, generating scratch information corresponding to the wafer according to the characteristic information, identifying the image by adopting an image identification technology to obtain the characteristic information, but not the prior art which adopts a manual mode to identify, can avoid the problems of low accuracy and the like caused by manual mode identification, thereby realizing the technical effects of improving the accuracy and the reliability of the identification, improving the identification efficiency and saving the labor cost, and the scratch information is generated based on the characteristic information, so that the problems of low efficiency and low accuracy caused by manually combining an Excel marking tool in the prior art are solved, and the technical effects of improving the efficiency and accuracy of determining the scratch information are further realized.
As can be seen from fig. 3 (fig. 3 is a schematic flow chart of a method for denoising an image according to an embodiment of the present disclosure), in some embodiments, denoising an image includes:
s21: distribution information of the defect points is determined based on the coordinate information.
S22: the image is divided into a plurality of regions according to the distribution information.
The distribution information refers to the distribution condition of each defect point in the image, for example, more defect points are distributed in a certain part of the image, and less defect points are distributed in a certain part of the image.
The image is divided into regions based on the distribution information to obtain a plurality of regions including the defective dot associated with the distribution information.
S23: the corresponding density of defect points in each region is determined.
Since the distribution information of defect points is different for different regions, the density of defect points is also different in different regions.
For example, if the density of defect points in a certain area is relatively high, the density of defect points in the area is relatively high; if the defect points in a certain area are sparse, the density of the defect points in the area is relatively small.
The specific method for determining the density may be a method in the prior art, and is not described herein again.
S24: and filtering the defect points of the area with the density smaller than the preset first threshold value.
Wherein the first threshold may be set based on demand.
The steps may specifically include: determining the density of the defect points of each area, comparing each obtained density with a first threshold value respectively, determining the density smaller than the first threshold value so as to determine the area with the density smaller than the first threshold value, and deleting the defect points in the determined area.
In the embodiment of the disclosure, the density of the defect points in different areas is determined according to the distribution information, and then the noise reduction processing is performed on the defect points in the image according to the density, so that the reliability and accuracy of the noise reduction processing can be improved, and the technical effect of subsequently determining the reliability of the scratch information is further improved.
Referring to fig. 4, fig. 4 is a schematic flow chart illustrating a wafer inspection method according to another embodiment of the present disclosure.
As shown in fig. 4, the method includes:
s201: and acquiring an image of the wafer in the machining process, wherein the image comprises defect points and coordinate information corresponding to the defect points.
For the description of S201, reference may be made to S101, which is not described herein again.
S202: and sequentially carrying out noise reduction processing, transformation processing and feature extraction processing on the image to obtain feature information corresponding to the image.
The description of S202 can refer to S102, which is not described herein again.
S203: and generating scratch information corresponding to the wafer according to the characteristic information.
The description of S203 may refer to S103, which is not described herein again.
S204: fingerprint information respectively set for a plurality of machines is acquired.
Wherein, a board corresponds at least one fingerprint information.
S205: and matching the fingerprint information with the scratch information to obtain the matching degree.
For example, the method includes n pieces of scratch information and m pieces of fingerprint information, and each piece of scratch information in the n pieces of scratch information is matched with each piece of fingerprint information in the m pieces of fingerprint information to obtain a corresponding matching degree.
S206: and determining the machine corresponding to the fingerprint information with the matching degree larger than the preset second threshold value as a suspected abnormal machine.
Similarly, the second threshold may be set based on the requirement.
The suspected abnormal machine refers to a machine which may be abnormal.
The steps may specifically include: and comparing each matching degree with a second threshold value respectively, determining the matching degree larger than the second threshold value, determining the fingerprint information corresponding to the matching degree larger than the second threshold value, determining the machine table corresponding to the determined fingerprint information, and determining the determined machine table as a suspected abnormal machine table.
One machine table comprises at least one mechanical arm, and when the suspected abnormal machine table is determined, the suspected mechanical arm can be determined.
Because the similarity between the machines is relatively high, one or more machines may be suspected to be abnormal.
In the prior art, correlation is found according to the identified scratch information in a manual mode so as to determine suspected abnormal machine stations, and because the similarity between the machine stations is high, the time for determining the suspected abnormal machine stations by workers is long, and the accuracy of the determined result is low. In the embodiment of the disclosure, the suspected abnormal machine is determined by combining the fingerprint information and the scratch information, so that the problem of low time consumption and low efficiency of manually determining the suspected abnormal machine is solved, the efficiency of determining the suspected abnormal machine is improved, and the technical effect of determining the accuracy of the suspected abnormal machine is improved.
In some embodiments, prior to S204, the method further comprises:
s01: and acquiring attribute information corresponding to each machine, wherein one machine corresponds to at least one attribute information, and the attribute information at least comprises mechanical arm information.
The attribute information is used for characterizing characteristics of the machines, and the attribute information corresponding to different machines is generally different, but the attribute information corresponding to different machines may have high similarity.
In some embodiments, the attribute information further includes manufacturer of the machine, manufacturing module, and device information (e.g., code, etc.).
S02: and fingerprint information of each machine is constructed according to each attribute information, wherein one machine corresponds to at least one fingerprint information.
In the embodiment of the present disclosure, by constructing the fingerprint information of each machine according to the attribute information, a corresponding relationship between the fingerprint information and each machine can be established, so that the suspected abnormal machine can be quickly locked based on the fingerprint information in the following.
In some embodiments, after generating the scratch information corresponding to the wafer from the characteristic information, the method further comprises:
s1: and calculating the scratching rate of the wafers in the same batch.
As can be seen from the above example, the wafer inspection is generally a sampling inspection, and therefore, in this step, the scratch rate of the wafers in a certain lot is counted.
For example: if there are a total of a wafers in a batch and there are scratches on b wafers, the scratch rate is (b/a) × 100%.
S2: and judging the scratch rate and the preset third threshold value, and if the scratch rate is greater than the third threshold value, executing S3.
Similarly, the third threshold may be set based on demand.
S3: and generating and pushing first prompt information, wherein the first prompt information is used for prompting the suspension of the use of the same batch of wafers.
In the embodiment of the present disclosure, if the scratching rate is greater than the third threshold, it indicates that the scratching rate is relatively high due to a problem of the wafer itself, and therefore, the first prompt information that the use of the wafer of the batch is suspended is generated and pushed, so as to avoid enlarging a fault, affecting subsequent production, and causing more cost waste, thereby achieving the technical effects of saving cost and the like.
And/or the presence of a gas in the gas,
s4: and responding to the continuous plurality of scratched wafers, judging the number of the continuous scratched wafers and the preset fourth threshold value, and if the number of the continuous scratched wafers is greater than the fourth threshold value, executing S5.
Similarly, the fourth threshold may be set based on demand.
The steps may specifically include: and counting the number of scratched wafers, and when a plurality of wafers are scratched continuously, comparing the number of scratched wafers with a fourth threshold value to determine the size between the number of scratched wafers and the fourth threshold value.
S5: and generating and pushing second prompt information, wherein the second prompt information is used for prompting the pause of the use of each machine in the machining process.
In the embodiment of the present disclosure, if the number of the continuously scratched wafers is greater than the fourth threshold, it indicates that the wafer may be a problem of the machine, and therefore, the second prompt information indicating that the use of each machine in the machining process is suspended is generated and pushed, so as to avoid that the fault is enlarged, more wafers are scratched, the subsequent production is affected, more cost is wasted, and technical effects such as saving cost are achieved.
According to another aspect of the embodiments of the present disclosure, there is also provided a device for inspecting a wafer.
Referring to fig. 5, fig. 5 is a schematic diagram of a wafer inspection apparatus according to an embodiment of the disclosure.
As shown in fig. 5, the apparatus includes:
the system comprises an acquisition module 1, a processing module and a processing module, wherein the acquisition module is used for acquiring an image of a wafer in the processing process, and the image comprises defect points and coordinate information corresponding to the defect points;
the processing module 2 is used for sequentially performing noise reduction processing, transformation processing and feature extraction processing on the image to obtain feature information corresponding to the image;
and a generating module 3, configured to generate scratch information corresponding to the wafer according to the feature information.
In some embodiments, the processing module 2 is configured to determine distribution information of the defect points based on the coordinate information, divide the image into a plurality of regions according to the distribution information, determine a density corresponding to the defect point in each of the regions, and filter the defect points of the region having the density smaller than a preset first threshold.
As can be seen in conjunction with fig. 6, in some embodiments, the apparatus further comprises:
the first acquisition module 4 is used for acquiring fingerprint information which is respectively set for a plurality of machines;
the matching module 5 is used for matching the fingerprint information with the scratch information to obtain a matching degree;
and the determining module 6 is configured to determine the machine corresponding to the fingerprint information with the matching degree greater than a preset second threshold as a suspected abnormal machine.
As can be seen in conjunction with fig. 6, in some embodiments, the apparatus further comprises:
a second obtaining module 7, configured to obtain attribute information corresponding to each machine, where one machine corresponds to at least one piece of attribute information, and the attribute information at least includes information about a mechanical arm;
and the constructing module 8 is configured to construct fingerprint information of each machine according to each attribute information, where one machine corresponds to at least one piece of fingerprint information.
As can be seen in conjunction with fig. 6, in some embodiments, the apparatus further comprises:
the calculating module 9 is used for calculating the scratching rate of the wafers in the same batch;
the first judging module 10 is used for judging the scratch rate and the magnitude of a preset third threshold value;
the first pushing module 11 is configured to generate and push first prompt information if the scratching rate is greater than the third threshold, where the first prompt information is used to prompt that the use of the wafers in the same batch is suspended; and/or the presence of a gas in the gas,
the second judging module 12 is configured to, in response to that a plurality of consecutive wafers are scratched, judge the number of consecutive scratched wafers and a preset fourth threshold value;
and the second pushing module 13 is configured to generate and push second prompt information if the number of the continuously scratched wafers is greater than the fourth threshold, where the second prompt information is used to prompt that the use of each machine in the machining process is suspended.
According to another aspect of the embodiments of the present disclosure, there is also provided an electronic device, including: a memory, a processor;
a memory for storing processor-executable instructions;
wherein, when executing the instructions in the memory, the processor is configured to implement the method of any of the embodiments above.
Referring to fig. 7, fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
As shown in fig. 7, the electronic device includes a memory and a processor, and the electronic device may further include a communication interface and a bus, wherein the processor, the communication interface, and the memory are connected by the bus; the processor is used to execute executable modules, such as computer programs, stored in the memory.
The Memory may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Via at least one communication interface, which may be wired or wireless), the communication connection between the network element of the system and at least one other network element may be implemented using the internet, a wide area network, a local network, a metropolitan area network, etc.
The bus may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc.
The memory is used for storing a program, and the processor executes the program after receiving an execution instruction.
The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. The steps of the method disclosed in connection with the embodiments of the present disclosure may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
According to another aspect of the embodiments of the present disclosure, there is also provided a computer-readable storage medium having stored therein computer-executable instructions, which when executed by a processor, are configured to implement the method according to any one of the embodiments.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present disclosure.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present disclosure may be substantially or partially contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should also be understood that, in the embodiments of the present disclosure, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
While the present disclosure has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (12)
1. A method of inspecting a die, the method comprising:
acquiring an image of a wafer in a machining process, wherein the image comprises defect points and coordinate information corresponding to the defect points;
sequentially carrying out noise reduction processing, transformation processing and feature extraction processing on the image to obtain feature information corresponding to the image;
and generating scratch information corresponding to the wafer according to the characteristic information.
2. The method of claim 1, wherein denoising the image comprises:
determining distribution information of the defect points based on the coordinate information;
dividing the image into a plurality of regions according to the distribution information;
determining a density of defect point correspondences in each of the regions;
and filtering the defect points of the area with the density smaller than the preset first threshold value.
3. The method according to claim 1 or 2, wherein after the generating of scratch information corresponding to the wafer from the characteristic information, the method further comprises:
acquiring fingerprint information respectively set for a plurality of machines;
matching the fingerprint information with the scratch information to obtain a matching degree;
and determining the machine corresponding to the fingerprint information with the matching degree larger than a preset second threshold value as a suspected abnormal machine.
4. The method according to claim 3, wherein before the acquiring fingerprint information respectively set for a plurality of machines, the method further comprises:
acquiring attribute information corresponding to each machine table, wherein one machine table corresponds to at least one piece of attribute information, and the attribute information at least comprises mechanical arm information;
and fingerprint information of each machine is constructed according to each attribute information, wherein one machine at least corresponds to one fingerprint information.
5. The method according to claim 1 or 2, wherein after the generating of scratch information corresponding to the wafer from the characteristic information, the method further comprises:
calculating the scratching rate of the wafers in the same batch;
judging the size of the scratching rate and a preset third threshold value;
if the scratching rate is greater than the third threshold value, generating and pushing first prompt information, wherein the first prompt information is used for prompting the suspension of the use of the wafers in the same batch; and/or the presence of a gas in the gas,
in response to the continuous plurality of wafers being scratched, judging the quantity of the continuous scratched wafers and the size of a preset fourth threshold value;
and if the number of the continuously scratched wafers is larger than the fourth threshold value, generating and pushing second prompt information, wherein the second prompt information is used for prompting the suspension of the use of each machine in the machining process.
6. An apparatus for inspecting a wafer, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an image of a wafer in the processing process, and the image comprises defect points and coordinate information corresponding to the defect points;
the processing module is used for sequentially carrying out noise reduction processing, transformation processing and feature extraction processing on the image to obtain feature information corresponding to the image;
and the generating module is used for generating scratch information corresponding to the wafer according to the characteristic information.
7. The apparatus according to claim 6, wherein the processing module is configured to determine distribution information of the defect points based on the coordinate information, divide the image into a plurality of regions according to the distribution information, determine a density corresponding to the defect point in each of the regions, and filter the defect points of the region having the density smaller than a preset first threshold.
8. The apparatus of claim 6 or 7, further comprising:
the first acquisition module is used for acquiring fingerprint information which is respectively set for a plurality of machines;
the matching module is used for matching the fingerprint information with the scratch information to obtain a matching degree;
and the determining module is used for determining the machine corresponding to the fingerprint information with the matching degree larger than a preset second threshold as a suspected abnormal machine.
9. The apparatus of claim 8, further comprising:
a second obtaining module, configured to obtain attribute information corresponding to each machine, where one machine corresponds to at least one piece of attribute information, and the attribute information at least includes information about a mechanical arm;
and the construction module is used for constructing the fingerprint information of each machine according to each attribute information, wherein one machine corresponds to at least one piece of fingerprint information.
10. The apparatus of claim 6 or 7, further comprising:
the calculating module is used for calculating the scratching rate of the wafers in the same batch;
the first judgment module is used for judging the scratch rate and the size of a preset third threshold value;
the first pushing module is used for generating and pushing first prompt information if the scratching rate is greater than the third threshold value, wherein the first prompt information is used for prompting the suspension of the use of the wafers in the same batch; and/or the presence of a gas in the gas,
the second judging module is used for responding to the fact that the plurality of continuous wafers are scratched, and judging the number of the continuously scratched wafers and the size of a preset fourth threshold value;
and the second pushing module is used for generating and pushing second prompt information if the number of the continuously scratched wafers is greater than the fourth threshold, wherein the second prompt information is used for prompting the suspension of the use of each machine in the machining process.
11. An electronic device, comprising: a memory, a processor;
a memory for storing the processor-executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement the method of any of claims 1 to 5.
12. A computer-readable storage medium having computer-executable instructions stored therein, which when executed by a processor, are configured to implement the method of any one of claims 1 to 5.
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