Defect image file processing methods, apparatus, terminal equipment and storage media

Abstract

This application discloses a defect image file processing method, apparatus, terminal device, and storage medium, comprising: performing a first operation according to a first preset timing rule: acquiring at least two standard structured data and generating at least one defect image raw data based on the at least two standard structured data; performing a second operation according to a second preset timing rule: generating at least one defect image file based on at least one defect image raw data and storing at least one defect image file in a file server; when a request for acquiring a defect image file is received, outputting at least one target defect image file associated with the index field based on at least one defect image file stored in the file server, according to the index field included in the request for indexing the defect image file. The defect image file has fast drawing and calling speed, strong reusability, and strong applicability.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and in particular to a method, apparatus, terminal device, and storage medium for processing defect image files. Background Technology

[0002] Wafer defect detection and analysis is a crucial step in the wafer semiconductor manufacturing industry. The key to improving wafer semiconductor detection speed lies in how to quickly generate wafer defect images based on raw wafer scanning data.

[0003] In existing technologies, wafer defect detection and analysis using raw wafer data requires technicians to process tens to hundreds of millions of wafer data points on office computers. When processing raw wafer data, technicians often need to acquire large amounts of raw wafer data simultaneously and generate a large number of wafer defect map files based on this data. This results in a delay of several hours from the time a technician initiates a defect map file drawing request to the time the files are received. The slow drawing speed leads to slow file retrieval speed; furthermore, the generated defect map files can only be used once, making them difficult to reuse or be used by other devices, resulting in poor reusability and applicability. Summary of the Invention

[0004] This application provides a method, apparatus, terminal device, and storage medium for processing defect diagram files, which features fast drawing and retrieval speeds, strong reusability, and wide applicability.

[0005] In a first aspect, this application provides a method for processing defect image files. The method includes: performing a first operation at regular intervals according to a first preset timing rule: acquiring at least two standard structured data sets, and generating at least one defect image raw data set based on the at least two standard structured data sets; one of the standard structured data sets is used to indicate at least one dimension of a wafer feature; the defect image raw data set is used to indicate the graphic features of the defect image; performing a second operation at regular intervals according to a second preset timing rule: generating at least one defect image file based on the at least one defect image raw data set, and storing the at least one defect image file on a file server; when a request for acquiring a defect image file is received, outputting at least one target defect image file associated with the index field based on the at least one defect image file stored on the file server, according to the index field included in the request for indexing the defect image file. Using this application, original defect image data for indicating graphic features of defect images can be generated periodically based on standard structured data according to a first preset timing rule. Generating defect image files from the original defect image data improves the drawing speed of defect image files. Furthermore, defect image files can be drawn periodically based on the original defect image data according to a second preset timing rule. Different timing rules avoid processing large batches of standard structured data and drawing large batches of defect image files simultaneously, thus avoiding computational pressure. Therefore, it is suitable for products with low computational power and has strong applicability. By storing the timed defect image files on a file server, when a request to retrieve a defect image file is received, the target defect image file can be directly output based on the already drawn defect image files stored on the file server, saving the time spent temporarily drawing defect image files when a request is received. Therefore, the retrieval speed of defect image files is fast. In addition, defect image files on the file server can be repeatedly retrieved, exhibiting strong reusability.

[0006] In one possible implementation of the first aspect, the timing duration for executing the first operation according to a first preset timing rule is a first duration; the timing duration for executing the second operation according to a second preset timing rule is a second duration; the first duration is less than or equal to the second duration. By employing this application, since the first duration is less than or equal to the second duration, the real-time nature and continuity of the original defect image data generated by the first operation can be guaranteed, thereby providing sufficient input of original defect image data for the second operation. Furthermore, the differentiated configuration of the first and second durations can avoid process blocking caused by synchronous operations, making it suitable for multi-dimensional data fusion scenarios and allowing for flexible allocation of computing resources, thereby further improving computational efficiency and applicability.

[0007] In one possible implementation of the first aspect, after generating at least one defect image file based on the at least one original defect image data, the method further includes: generating index information for each of the defect image files; establishing at least one calling link for each of the at least one defect image file based on the at least one defect image file and the index information corresponding to each of the defect image files; each of the index information includes at least one index field, each index field is associated with at least one calling link, and each calling link corresponds to one of the defect image files; and generating a defect image file index table based on the at least one index field and the at least one calling link. By generating the index information and calling links for defect image files, the index information, defect image files, and calling links can be bound together. By establishing the defect image file index table, a connection can be established between the defect image file, the calling link, and at least one index field in the index information. This allows for rapid indexing of the calling link associated with the index field through the defect image file index table, improving indexing speed and further increasing the calling speed of the defect image file. Furthermore, since one index field can be associated with multiple calling links, and different index fields can be associated with the same calling link, the defect image file processing system is applicable to various indexing scenarios and has strong applicability.

[0008] In one possible implementation of the first aspect, the method of outputting at least one target defect map file associated with the index field based on the at least one defect map file stored on the file server, according to the index field for indexing defect map files included in the request, includes: obtaining at least one calling link associated with the at least one index field based on the defect map file index table and the at least one index field in the request; calling at least one target defect map file corresponding to the at least one calling link from the file server based on the at least one calling link, and outputting the at least one target defect map file. Using this application, at least one calling link associated with the at least one index field can be quickly obtained from the defect map file index table through the at least one index field in the request, so as to call and output at least one target defect map file corresponding to the at least one calling link. The indexing speed through the defect map file index table is fast, and multiple target defect map files can be called simultaneously through one or more index fields, further improving the calling speed of defect map files.

[0009] In one possible implementation of the first aspect, acquiring at least two standard structured data includes: acquiring at least one standard structured data of wafer information and at least one standard structured data of defect information to obtain the at least two standard structured data. The standard structured data of wafer information includes original data corresponding to a product model and a first dimension set, wherein the first dimension set includes at least the wafer size. The standard structured data of defect information includes original data corresponding to a product model and a second dimension set, wherein the second dimension set includes at least the defect location. Using this application, by separating the standard structured data of defect information and the standard structured data of wafer information, the standard structured data can be classified to improve the processing speed of the standard structured data. Furthermore, by associating the standard structured data of wafer information and defect information with the product model, associated standard structured data can be quickly filtered, thereby further improving the processing speed of the standard structured data.

[0010] In one possible implementation of the first aspect, generating at least one defect image raw data based on the at least two standard structured data includes: determining at least two target dimensions for drawing the defect image file from the first dimension set and the second dimension set based on the generation requirements of the defect image file; acquiring at least two image feature data based on the at least two target dimensions and the at least two standard structured data, wherein one target dimension corresponds to at least one image feature data, and the at least two target dimensions include at least the wafer size and the defect location; and concatenating the at least two image feature data corresponding to the at least two target dimensions to generate at least one defect image raw data, wherein each target dimension used to generate one defect image raw data corresponds to one image feature data. Using this application, by filtering the standard structured data and removing raw data unrelated to drawing the defect image file, the amount of data that needs to be analyzed when generating the defect image file is reduced, thereby improving the drawing speed of the defect image file; and by using data concatenation, the image feature data can be converted into defect image raw data more suitable for drawing the defect image file, thereby further improving the drawing speed of the defect image file.

[0011] In one possible implementation of the first aspect, before acquiring at least two standard structured data, the method further includes: performing a third operation periodically according to the first preset timing rule: acquiring at least one raw data file from a wafer scanning device, parsing the at least one raw data file to obtain at least three raw data; each of the raw data corresponds to one dimension, and the dimensions of the at least three raw data include at least the product model, the wafer size, and the defect location, the wafer size belonging to the first dimension set, and the defect location belonging to the second dimension set; classifying the at least three raw data based on the product model, the first dimension set, and the second dimension set for structured processing to generate the at least two standard structured data, and storing the at least two standard structured data in a database; each of the standard structured data includes at least one of the raw data corresponding to at least one dimension in the product model and the first dimension set, or includes at least one of the raw data corresponding to at least one dimension in the product model and the second dimension set. By employing this application, unstructured raw data files can be converted into structured standard structured data through data parsing and classification. Since the analysis speed of structured standard structured data is higher than that of raw data files when generating defect image raw data, the generation speed of defect image raw data can be improved, thereby further improving the drawing speed of defect image files. In addition, standard structured data can be called up multiple times by storing it in a database, which has strong reusability.

[0012] In one possible implementation of the first aspect, storing the at least two standard structured data in a database includes: generating at least one wafer configuration data table based on the product model and the first dimension set in the at least two standard structured data; generating at least one wafer defect data table based on the product model and the second dimension set in the at least two standard structured data to obtain at least two standard structured data tables; recording at least one standard structured data corresponding to the first dimension set in the wafer configuration data table based on the product model and the first dimension set; and recording at least one standard structured data corresponding to the second dimension set in the wafer defect data table based on the product model and the second dimension set to record the at least two standard structured data; and storing the at least one wafer defect data table and the at least one wafer configuration data table in a database to store the at least two standard structured data. By using this application, at least two standard structured data tables can be generated to achieve classified storage of standard structured data, thereby avoiding repeated reading of standard structured data, improving the analysis speed of standard structured data, and reducing the storage space occupied by standard structured data; in addition, storing standard formatted data tables with different themes can improve the indexing speed of standard structured data.

[0013] Secondly, this application provides a defect image file processing apparatus, which includes modules or units for performing the defect image file processing method provided by the first aspect or any possible embodiment of the first aspect.

[0014] For example, the device includes: a first processing module and a second processing module;

[0015] The first processing module is used to perform a first operation according to a first preset timing rule: acquire at least two standard structured data, and generate at least one defect image raw data based on the at least two standard structured data; one of the standard structured data is used to indicate the features of at least one dimension of the wafer; the defect image raw data is used to indicate the graphic features of the defect image;

[0016] The second processing module is used to perform a second operation according to a second preset timing rule: after the first processing module generates the original data of the at least one defect image at a time, it generates at least one defect image file based on the original data of the at least one defect image and stores the at least one defect image file on a file server.

[0017] The second processing module is further configured to, when receiving a request to obtain a defect map file, output at least one target defect map file associated with the index field, based on the at least one defect map file stored on the file server, according to the index field included in the request for indexing the defect map file.

[0018] Thirdly, this application provides a terminal device, including: a processor and a memory; the processor is connected to the memory, wherein the memory is used to store program code, and the processor is used to call the program code from the memory to execute the defect image file processing method provided in the first aspect or any possible implementation of the first aspect.

[0019] Fourthly, this application provides a computer-readable storage medium storing a computer program for being loaded by a processor and executing the defect image file processing method provided in the first aspect or any possible implementation thereof.

[0020] Fifthly, this application provides a computer program product comprising computer instructions for being loaded by a processor and executed as provided in the first aspect or any possible implementation thereof. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the architecture of the defect image file processing system provided in this application;

[0022] Figure 2 This is another schematic diagram of the defect image file processing system provided in this application;

[0023] Figure 3 This is a flowchart illustrating the defect image file processing method provided in this application;

[0024] Figure 4 This is a page view of the defect diagram file provided in this application;

[0025] Figure 5 This is a schematic diagram of the defect image file processing device provided in this application;

[0026] Figure 6 This is a schematic diagram of the terminal device provided in this application.

[0027] Explanation of reference numerals in the attached figures:

[0028] 1-Defect diagram file processing system;

[0029] 1a - Wafer scanning equipment; 1b - Defect image file processing module; 1c - Data analysis platform; 1d - File server;

[0030] 101b - Data Acquisition Module; 102b - Database; 103b - Data Analysis Module; 104b - Chart Drawing Module;

[0031] 10-Defect image file processing device;

[0032] 101 - First processing module; 102 - Second processing module; 103 - Third processing module; 104 - Fourth processing module; 105 - Parsing module; 106 - Structured module;

[0033] 1011 - Determine Unit; 1012 - Select Unit; 1013 - Concatenate Unit; 1021 - Acquire Unit; 1022 - Output Unit; 1061 - Generate Unit; 1062 - Record Unit; 1063 - Store Unit;

[0034] 100 - Terminal device; 1001 - Processor; 1002 - Communication bus; 1003 - User interface; 1004 - Network interface; 1005 - Memory; 1006 - Controller. Detailed Implementation

[0035] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0036] For ease of understanding, this application first describes the defect image file processing system. The wafer image alignment method can be applied to the defect image file processing system, which can be used in scenarios such as wafer defect map generation and wafer defect analysis. Taking the wafer defect map generation scenario as an example, for a better understanding of the architecture of the defect image file processing system, please refer to [link to relevant documentation]. Figure 1 , Figure 1 This is a schematic diagram of the architecture of the defect image file processing system provided in this application. For example... Figure 1 As shown, the defect image file processing system 1 may include a defect image file processing module 1b, a wafer scanning device 1a, a file server 1d, and a data analysis platform 1c. The defect image file processing module 1b can be used to perform data interaction via wired or wireless connection with the wafer scanning device 1a, the file server 1d, and the data analysis platform 1c; this application does not impose any limitations on this.

[0037] In some feasible implementations, the wafer scanning device 1a can be a machine or other equipment used to scan wafers, and is used to scan wafers to obtain at least one raw data file of the wafer. The file server 1d can be a server or storage device used to store files, or it can be other storage space hosted on a terminal device (such as a mobile phone, computer, tablet, etc.), and this application does not impose any limitations. The file server 1d can be used to store defect image files to enable multiple accesses to the defect image files. The data analysis platform 1c can be an application, a webpage, or a terminal device capable of sending requests to obtain defect image files, and this application does not impose any limitations. The data analysis platform 1c is used to send requests to the defect image file processing system 1 to obtain defect image files or other types of requests, in order to perform data analysis based on the defect image files.

[0038] In some feasible implementations, the aforementioned defect image file processing module 1b can be a software application or implemented in hardware. In other words, the aforementioned defect image file processing module 1b can be carried in software on a terminal device, or the functions implemented by the defect image file processing module 1b can be implemented through at least one server or terminal device. This application does not impose any limitations. The aforementioned defect image file processing module 1b can periodically execute a first operation according to a first preset timing rule to periodically generate raw defect image data, or periodically execute a second operation according to a second preset timing rule to periodically generate defect image files. The timing duration for periodically executing the first operation according to the first preset timing rule is the first duration; the timing duration for periodically executing the second operation according to the second preset timing rule is the second duration; the first duration is less than or equal to the second duration. For example, the defect image file processing module 1b can be used to store a pre-set first preset timing rule and a second preset timing rule. The first duration and the second duration can be a few seconds, a few minutes, or a few hours, etc. That is, the first preset timing rule can specify that the first operation is executed once every few seconds, a few minutes, or a few hours; the second preset timing rule can specify that the second operation is executed once every few seconds, a few minutes, or a few hours. For example, the defect image file processing module 1b can execute the first operation once every five minutes and the second operation once every ten minutes. The specific values ​​of the first duration and the second duration should be determined according to the actual product form, and this application does not impose any restrictions. It can be understood that since the first duration is less than or equal to the second duration, the real-time and continuous nature of the original defect image data generated by the first operation can be guaranteed, thereby providing sufficient original defect image data input for the second operation. In addition, through the differentiated configuration of the first duration and the second duration, process blocking caused by synchronous operation can be avoided, which is suitable for multi-dimensional data fusion scenarios and can also flexibly allocate computing resources, thereby further improving computing efficiency and applicability.

[0039] In some feasible implementations, the aforementioned defect image file processing module 1b may also include multiple modules, and these modules interact to achieve the functions implemented by the defect image file processing module 1b. In other words, the aforementioned defect image file processing module 1b can be integrated into a single software application, or it can achieve the functions implemented by the defect image file processing module 1b through interaction between multiple software applications; alternatively, the aforementioned defect image file processing module 1b can be integrated into a single terminal device, or it can achieve the functions implemented by the defect image file processing module 1b through interaction between multiple terminal devices. To facilitate understanding of the architecture of the aforementioned defect image file processing module 1b, in... Figure 1 Based on the provided implementation, please also refer to Figure 2 , Figure 2 This is another schematic diagram of the architecture of the defect image file processing system 1 provided in this application. For example... Figure 2 As shown, the defect image file processing module 1b includes a data acquisition module 101b, a database 102b, a data analysis module 103b, and a chart drawing module 104b. The functions of the defect image file processing module 1b, as well as the functions and interactions of the data acquisition module 101b, the database 102b, the data analysis module 103b, and the chart drawing module 104b, are described below.

[0040] In some feasible implementations, the defect image file processing module 1b can be used to perform a first operation at regular intervals according to a first preset timing rule. The first operation may include: acquiring at least two standard structured data sets, and generating at least one original defect image data set based on the at least two standard structured data sets. One of the standard structured data sets is used to indicate at least one dimension of the wafer's features (such as defect location, wafer size, etc.). For example, the defect image file processing module 1b may acquire standard structured data every five minutes. The defect image file processing module 1b may acquire at least two standard structured data sets from an external memory or storage space; or, the defect image file processing module 1b may receive at least two standard structured data sets transmitted from other devices or applications; or, the defect image file processing module 1b may acquire the original data file of the wafer from the wafer scanning device 1a and generate at least two standard structured data sets based on the original data file. This application does not impose any limitations.

[0041] In some feasible implementations, the aforementioned standard structured data is data obtained after parsing and structuring the raw data file of the scanned wafer. Each standard structured data set includes, in addition to the product model, at least one dimension of the raw data for the wafer. This raw data, obtained by parsing the raw data file of the scanned wafer, can be used to indicate at least one dimension of the wafer's characteristics. This dimension may include: batch identifier, wafer identifier, chip identifier, wafer size, data acquisition time, defect location, etc., which are not limited in this application. It should be noted that since the format of the generated defect image raw data is usually unchanged without altering the settings of the defect image file processing module 1b, and this format includes at least two different dimensions (e.g., at least wafer size and defect location), at least two standard structured data sets are required to generate one defect image raw data set.

[0042] In some feasible implementations, the at least two standard structured data acquired by the aforementioned defect image file processing module 1b include at least one standard structured data of wafer information and at least one standard structured data of defect information. The standard structured data of wafer information includes original data corresponding to the product model and a first dimension set, where the first dimension set includes at least the wafer size. The standard structured data of defect information includes original data corresponding to the product model and a second dimension set, where the second dimension set includes at least the defect location. In other words, one set of the aforementioned standard structured data includes at least one set of original data corresponding to at least one dimension in the first dimension set, or includes at least one set of original data corresponding to at least one dimension in the second dimension set. It is understood that both the standard structured data of wafer information and the standard structured data of defect information include the product model; therefore, the standard structured data of wafer information and the standard structured data of defect information can be associated through the product model, thereby improving the retrieval efficiency of the standard structured data.

[0043] In some feasible implementations, after obtaining at least two standard structured data sets, the defect image file processing module 1b can be used to generate at least one original defect image data set based on these two sets of standard structured data sets. The original defect image data set indicates the graphic features of the defect image, and the defect image can be stored in the form of a defect image file. The defect image file processing module 1b can generate the original defect image data according to the format required for drawing the defect image file by filtering and splicing the at least two sets of standard structured data sets. The defect image file processing module 1b can quickly identify the graphic features of the defect image using the original defect image data. For example, the defect image file processing module 1b can filter the standard structured data of wafer information and the standard structured data of defect information using the product model to obtain the wafer size and defect location for the same product model, and then generate the original defect image data based on the wafer size and defect location. It should be noted that if the standard structured data is not converted into original defect image data, the drawing time for the defect image will be long if the order of the various dimensions in the standard structured data does not meet the requirements for generating the defect image. Furthermore, when analyzing standard structured data, the defect image file processing module 1b analyzes all standard structured data. However, standard structured data may include data unrelated to drawing defect images, which can lead to additional analysis time and reduce the speed of defect image drawing. Since the format of the original defect image data required by the defect image file processing module 1b to draw defect image files usually remains unchanged without changing the settings, the standard structured data can be converted into the aforementioned format of original defect image data according to the first preset timing rule. This improves the data analysis speed and defect image drawing speed of the defect image file processing module 1b, thereby increasing the generation speed of defect image files. It can be understood that the process of converting standard structured data into original defect image data according to the first preset timing rule can also be called a preprocessing process.

[0044] Optionally, in some feasible implementations, the data analysis module 103b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can execute the first operation at regular intervals according to the first preset timing rule through the data analysis module 103b, so as to generate at least one defect image raw data based on the acquired at least two standard structured data and transmit the above defect image raw data to the chart drawing module 104b.

[0045] In some feasible implementations, the defect image file processing module 1b can perform a second operation according to a second preset timing rule. This second operation may include: generating at least one defect image file based on at least one original defect image data, and storing the at least one defect image file on the file server 1d. Each defect image file is generated from at least one original defect image data. The original defect image data should at least include information about the wafer size and the defect location. The wafer size information cannot be empty, while the information indicating the defect location can be empty. When the original defect image data only includes wafer size information, and all other data is empty, it can be used to indicate that the wafer corresponding to the original defect image data has no defects, and the defect image file output does not display defects in the original wafer defect image. After generating the defect image, the defect image processing module 1b can output and store the defect image in the form of a defect image file. It is understandable that the second operation is executed periodically according to the second preset timing rule. The timed defect map files can be stored on file server 1d. This allows the defect map file processing module 1b to directly retrieve the already drawn defect map file from file server 1d when it receives a request to obtain the file. This saves the time spent temporarily drawing the defect map file upon receiving the request, thus resulting in faster retrieval of the defect map file. Furthermore, the defect map files in file server 1d can be repeatedly retrieved, demonstrating strong reusability.

[0046] Optionally, in some feasible implementations, the chart drawing module 104b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can use the chart drawing module 104b to perform the second operation according to the second preset timing rule, so as to receive the original defect image data from the data analysis module 103b, generate at least one defect image file based on at least one original defect image data, and store at least one defect image file in the file server 1d.

[0047] In some feasible implementations, when the defect image file processing module 1b receives a request to obtain a defect image file, it can output at least one target defect image file associated with the index field, based on at least one defect image file stored on the file server 1d, according to the index field included in the request for indexing the defect image file. The index field can be an identifier indicating a dimension in standard structured data, such as product model, batch identifier, wafer identifier, chip identifier, defect location, etc. The target defect image file associated with the index field can be retrieved through the index field.

[0048] Optionally, in some feasible implementations, the chart drawing module 104b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can be implemented by the chart drawing module 104b as follows: when receiving a request from the data analysis platform 1c or other terminal device to obtain a defect image file, the module outputs at least one target defect image file associated with the index field based on at least one defect image file stored on the file server 1d, according to the index field included in the request for indexing the defect image file.

[0049] Understandably, the defect image file processing module 1b can periodically generate original defect image data based on standard structured data to indicate the graphic features of the defect image according to the first preset timing rule. Generating defect image files from the original defect image data can improve the drawing speed of defect image files. Furthermore, it can periodically draw defect image files based on the original defect image data according to the second preset timing rule. By using different timing rules, it avoids the computational pressure caused by processing a large amount of standard structured data and drawing a large number of defect image files at the same time. Therefore, it is suitable for products with low computing power and has strong applicability. By storing the defect image files drawn periodically to the file server 1d, the defect image file processing module 1b can directly output the target defect image file based on the already drawn defect image files stored in the file server 1d when a request to retrieve a defect image file is received. This saves the time spent temporarily drawing defect image files when a request to retrieve a defect image file is received, so the retrieval speed of defect image files is fast. In addition, the defect image files in the file server 1d can be repeatedly retrieved, which has strong reusability.

[0050] In some feasible implementations, after generating at least one defect image file based on at least one original defect image data, the defect image file processing module 1b can also be used to generate index information for each defect image file, and establish at least one calling link for at least one defect image file based on the at least one defect image file and the corresponding index information. The index information may include at least one index field, which may be an identifier or parameter indicating the dimension of the wafer, such as: product model, batch identifier, wafer identifier, chip identifier, wafer size, wafer scan time, defect location, etc. Each defect image file corresponds one-to-one with a calling link, and the defect image file processing module 1b can call the defect image file corresponding to the calling link through the calling link. The calling link of a defect image file is associated with any index field in the index information of that defect image file; in other words, the defect image file processing module 1b can obtain the calling link associated with any index field in the index information.

[0051] In some feasible implementations, the defect image file processing module 1b can also generate a defect image file index table based on at least one index field and at least one calling link. Through the aforementioned defect image file index table, the index link associated with the index field can be quickly obtained based on the index field, thereby further improving the calling speed of the defect image file.

[0052] Optionally, in some feasible implementations, the chart drawing module 104b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can generate index information for each defect image file through the chart drawing module 104b, establish at least one calling link for at least one defect image file based on at least one defect image file and the corresponding index information, and then generate a defect image file index table based on at least one index field and at least one calling link. The aforementioned defect image file index table can be stored in the chart drawing module 104b.

[0053] It is understandable that by generating index information and calling links for defect diagram files, the index information, defect diagram files, and calling links can be bound together. By establishing a defect diagram file index table, a connection can be established between at least one index field in the defect diagram file, calling links, and index information. Thus, the calling links associated with the index fields can be quickly indexed through the defect diagram file index table, improving the indexing speed and further improving the calling speed of defect diagram files. In addition, since one index field can be associated with multiple calling links, and different index fields can also be associated with the same calling link, the defect diagram file processing system 1 is applicable to a variety of indexing scenarios and has strong applicability.

[0054] In some feasible implementations, the defect image file processing module 1b can be used to obtain at least one calling link associated with at least one index field based on the defect image file index table and at least one index field in the request, thereby calling at least one target defect image file corresponding to at least one calling link from the file server 1d based on the at least one calling link, and outputting at least one target defect image file. The defect image file processing module 1b can analyze the request for obtaining the defect image file to obtain at least one index field included in the request. Optionally, the defect image file processing module 1b can provide index fields that can be effectively indexed to the data analysis platform 1c or other terminal device that sent the request for obtaining the defect image file according to the defect image file index table, avoiding the inclusion of index fields of unassociated defect image files in the request, thereby improving indexing efficiency. The defect image file processing module 1b can index at least one calling link associated with the at least one index field from the defect image file index table based on the at least one index field in the request. Further, the defect image file processing module 1b can call at least one target defect image file corresponding to at least one calling link from the file server 1d according to the at least one calling link determined from the defect image index table, and output the at least one target defect image file. It is understandable that a call link can indicate the storage address of a defect diagram file. Therefore, the defect diagram file processing module 1b can quickly determine the defect diagram file corresponding to the call link based on the call link, and the call speed is fast.

[0055] Optionally, in some feasible implementations, the chart drawing module 104b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can obtain at least one call link associated with at least one index field based on the defect image file index table and at least one index field in the request through the chart drawing module 104b, and then call at least one target defect image file corresponding to at least one call link from the file server 1d based on the at least one call link, and output the at least one target defect image file to the data analysis platform 1c or other terminal devices.

[0056] It is understood that the defect image file processing module 1b can quickly obtain at least one call link associated with the at least one index field in the defect image file index table through at least one index field in the request, so as to call and output at least one target defect image file corresponding to the at least one call link. The indexing speed through the defect image file index table is fast, and multiple target defect image files can be called simultaneously through one or more index fields, which further improves the calling speed of defect image files.

[0057] In some feasible implementations, the defect image file processing module 1b can be used to acquire at least two standard structured data sets, which include image feature data of at least two dimensions of the wafer, and determine at least two target dimensions for drawing the defect image file from these at least two dimensions. For example, the defect image file processing module 1b can acquire at least two standard structured data sets from an external application or terminal device, or it can acquire raw wafer data from the wafer scanning device 1a to generate at least two standard structured data sets; this application does not impose any limitations. The at least two standard structured data sets may include image feature data of at least two dimensions, such as wafer size and defect location. This application does not limit the number and content of dimensions included in the standard structured data sets, but in practical application scenarios, the at least two standard structured data sets should include at least image feature data of wafer size and defect location. The defect image file processing module 1b can determine at least two target dimensions for drawing the defect image file from these at least two dimensions according to the generation requirements of the defect image file (e.g., data format). For example, if the defect image file processing module 1b acquires three standard structured data sets, these three sets of standard structured data include image feature data in three dimensions: "wafer size," "defect location," and "batch." The "batch" dimension can be used to indicate the batch information of the defect image of the wafer corresponding to the standard structured data, but it is irrelevant to the drawing of the wafer defect image; therefore, the "batch" dimension can be discarded. If the requirement for generating the defect image file is that the data format is "wafer size" and "defect location," then the defect image file processing module 1b can determine the "wafer size" and "defect location" dimensions as the two target dimensions for drawing the defect image file.

[0058] In some feasible implementations, the defect image file processing module 1b can be used to obtain at least two image feature data from at least two standard structured data based on at least two target dimensions, wherein one target dimension corresponds to at least one image feature data. The aforementioned image feature data is a portion of the original data included in the standard structured data that indicates the graphic features of the defect image. Specifically, the defect image file processing module 1b can be used to determine at least two image feature data corresponding to the at least two target dimensions determined based on the generation requirements of the defect image file. One of the aforementioned target dimensions may correspond to one or more image feature data, wherein the image feature data can be empty (represented by parameters such as "0" or "NULL").

[0059] In some feasible implementations, the defect image file processing module 1b can be used to stitch together at least two image feature data corresponding to at least two target dimensions to generate at least one original defect image data. Each target dimension used to generate one original defect image data corresponds to a standard structured data set. It is understood that multiple image feature data sets of the same dimension can be arranged in columns during storage, and at least two standard structured data sets obtained from the same wafer scan can be arranged in rows during storage. Therefore, the defect image file processing module 1b can select multiple image feature data sets of different dimensions row by row, thereby stitching together at least two image feature data sets of different dimensions obtained from the same wafer scan to generate one original defect image data set. It is understood that the defect image file processing module 1b can simultaneously select multiple image feature data sets of the same target dimension when selecting image feature data, but during stitching, it needs to ensure that each target dimension corresponds to one standard structured data set when generating one original defect image data set, rather than stitching together multiple standard structured data sets of one target dimension.

[0060] Optionally, in some feasible implementations, the data analysis module 103b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can obtain at least two standard structured data from the database 102b through the data analysis module 103b, and then determine at least two target dimensions for drawing defect image files from the first dimension set and the aforementioned second dimension set; obtain at least two image feature data based on the at least two target dimensions and at least two standard structured data; stitch together the at least two image feature data corresponding to the at least two target dimensions to generate at least one original defect image data, and transmit the aforementioned original defect image data to the chart drawing module 104b.

[0061] It is understandable that the defect image file processing module 1b can filter standard structured data, remove some original data that is irrelevant to the drawing of defect image files, reduce the amount of data that needs to be analyzed when generating defect image files, and thus improve the drawing speed of defect image files; and by using data stitching, it can convert image feature data into defect image original data that is more suitable for drawing defect image files, thereby further improving the drawing speed of defect image files.

[0062] In some feasible implementations, the defect image file processing module 1b can be used to perform a third operation according to a first preset timing rule before acquiring at least two standard structured data files. The third operation includes: acquiring at least one raw data file from the wafer scanning device 1a, parsing the at least one raw data file, and obtaining at least three parsed raw data files. For example, the defect image file processing module 1b can acquire at least one raw data file obtained from scanning the wafer from the wafer scanning device 1a (e.g., a machine) according to the first preset timing rule (e.g., every five minutes). The time interval for the defect image file processing module 1b to acquire the raw data file should be determined according to the actual product form, and this application does not impose any limitations. Wherein, by parsing the at least one raw data file, the defect image file processing module 1b can obtain at least three parsed raw data files. The dimensions of the at least three raw data files include at least product model, wafer size, and defect location. The wafer size belongs to the first dimension set, and the defect location belongs to the second dimension set. For example, if the defect image file processing module 1b needs to obtain standard structured data for the two dimensions of "wafer size" and "defect location", then the defect image file processing module 1b can obtain at least one raw data file from the wafer scanning device 1a and parse the at least one raw data file to obtain the raw data for the two dimensions of "wafer size" and "defect location". In some feasible embodiments, the raw data file can also be empty. When the raw data file is empty, the parsed raw data is also empty, which can be represented by parameters such as "0" or "NULL", and this application does not impose any restrictions. The defect image file processing module 1b can parse the at least one raw data file by decoding or data segmentation through an application program to obtain at least three parsed raw data.

[0063] In some feasible implementations, the third operation further includes: classifying at least three raw data sets based on product model, a first dimension set, and a second dimension set for structured processing to generate at least two standard structured data sets, and storing the at least two standard structured data sets in a database. The defect graph file processing module 1b can be used to classify at least three parsed raw data sets based on product model, a first dimension set, and a second dimension set for structured processing to generate at least two standard structured data sets, and store the at least two standard structured data sets in a database. A standard structured data set includes at least one raw data set corresponding to at least one dimension in the product model and the first dimension set, or includes at least one raw data set corresponding to at least one dimension in the product model and the second dimension set. Optionally, the database can also be other types of storage space or memory. The database can be a distributed database, which can be constructed using big data analytics components, improving data entry and acquisition capabilities and supporting the elastic scalability of database resources. The defect graph file processing module 1b can classify at least three parsed raw data sets by dimension for structured processing.

[0064] Optionally, in some feasible implementations, the data acquisition module 101b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can perform a third operation at regular intervals according to the first preset timing rule through the data acquisition module 101b, to receive at least one raw data file of the wafer from the wafer scanning device 1a, and to parse the at least one raw data file to obtain at least three parsed raw data. The at least three parsed raw data are classified according to at least two dimensions of the wafer for structured processing to generate at least two standard structured data, and the at least two standard structured data are stored in the database 102b.

[0065] It is understandable that the defect image file processing module 1b can convert unstructured raw data into structured standard structured data by parsing and classifying the raw data. Since the defect image file processing module 1b analyzes the structured standard structured data faster than it analyzes the raw data file when generating defect image raw data, it can improve the generation speed of defect image raw data, thereby further improving the drawing speed of defect image files. In addition, the standard structured data can be called up multiple times by storing it in the database, which has strong reusability.

[0066] In some feasible implementations, the defect image file processing module 1b can be used to generate at least one wafer configuration data table based on the product model and the first dimension set in the at least two standard structured data sets, and to generate at least one wafer defect data table based on the product model and the second dimension set in the at least two standard structured data sets, thus obtaining at least two standard structured data tables. The at least two standard structured data sets include standard structured data containing defect information, and the at least two standard structured data tables include at least one wafer defect data table. The wafer defect data table is used to store the standard structured data containing defect information. Optionally, the defect image file processing module 1b can also generate other types of standard structured data tables based on the product model and the first dimension set, such as a scan configuration data table. The multiple standard structured data tables can be associated through dimension identifiers (such as product model identifiers, wafer identifiers, batch identifiers), thereby enabling the association of data in one standard structured data table with data in another standard structured data table, and thus reducing the storage space of the standard formatted data. Because the amount of standard structured data for defect information is enormous, typically reaching tens of millions or even hundreds of millions of data points, if all the data is combined into a single standard structured data table, the defect image file processing module 1b needs to read all the data, including the standard structured data for defect information, before proceeding to the next step, which greatly increases the data analysis time of the defect image file processing module 1b.

[0067] In some feasible implementations, the defect image file processing module 1b can also be used to record at least one standard structured data corresponding to the first dimension set into a wafer configuration data table based on the product model and the first dimension set, and to record at least one standard structured data corresponding to the second dimension set into a wafer defect data table based on the product model and the second dimension set, so as to record at least two standard structured data. For example, the defect image file processing module 1b can record multiple standard structured data for the same product model based on the product model, such as recording multiple standard structured data corresponding to the first dimension set into the wafer configuration table data based on the product model, or recording multiple standard structured data corresponding to the second dimension set into the wafer defect data table based on the product model.

[0068] In some feasible implementations, the defect image file processing module 1b can also be used to store at least one wafer defect data table and at least one wafer configuration data table into a database to store at least two standard structured data sets. To improve the data analysis speed of the defect image file processing module 1b, it can store standard formatted data of defect information and other types of standard formatted data separately; that is, the standard structured data table can include the wafer defect data table and other types of standard structured data tables. Furthermore, since storing all standard structured data in the same standard formatted data table requires a fixed dimension format, multiple standard formatted data sets with the same dimension and value need to occupy separate storage locations, resulting in redundant storage of standard formatted data and increasing the storage space required for standard formatted data. Therefore, this application further saves storage space by classifying and storing data through multiple standard formatted data tables.

[0069] Optionally, in some feasible implementations, the data acquisition module 101b can implement the functions of the defect image file processing module 1b mentioned above. The defect image file processing module 1b can generate at least one wafer configuration data table based on the product model and the first dimension set in at least two standard structured data, and generate at least one wafer defect data table based on the product model and the second dimension set in at least two standard structured data; record at least one standard structured data corresponding to the first dimension set into the wafer configuration data table based on the product model and the first dimension set, and record at least one standard structured data corresponding to the second dimension set into the wafer defect data table based on the product model and the second dimension set; and store at least one wafer defect data table and at least one wafer configuration data table into the database 102b to store at least two standard structured data.

[0070] It is understandable that the defect image file processing module 1b, by generating at least one wafer configuration data table and at least one wafer defect data table, can achieve classified storage of standard structured data, thereby avoiding repeated reading of standard structured data, improving data analysis speed, and reducing the storage space occupied by standard structured data. Furthermore, storing data through standard formatted data tables of different themes can improve the indexing speed of standard structured data.

[0071] Optionally, in some feasible implementations, the defect map file processing module 1b can also be used to directly generate at least one defect map file from at least one original data file of the wafer and output the aforementioned defect map file when at least one original data file of the obtained wafer cannot be converted into standard formatted data (i.e., data parsing or classification cannot be performed).

[0072] Optionally, in some feasible implementations, the defect image file processing module 1b can also be used to receive real-time rendering requests for defect image files sent by the data analysis platform 1c or other terminal devices or software. When the defect image file processing module 1b receives a real-time rendering request for a defect image file, it can obtain at least one raw data file of the wafer from the wafer scanning device 1a. If the at least one raw data file can be converted into standard structured data, the defect image file processing module 1b can perform data parsing and classification on the at least one raw data file to generate at least two standard formatted data, and generate at least one defect image raw data based on the at least two standard formatted data, thereby generating a defect image file based on the at least one defect image raw data and outputting the defect image file. If the at least one raw data file cannot be converted into standard structured data, the defect image file processing module 1b can generate at least one defect image file based on the at least one raw data file and output the at least one defect image file.

[0073] Using this application, the defect image file processing module in the defect image file processing system can periodically generate original defect image data indicating the graphic features of the defect image based on standard structured data according to a first preset timing rule. Generating defect image files from the original defect image data can improve the drawing speed of defect image files. Furthermore, it can periodically draw defect image files based on the original defect image data according to a second preset timing rule. By using different timing rules, it can avoid the computational pressure caused by processing large batches of standard structured data and drawing a large number of defect image files at the same time. Therefore, it is suitable for products with low computing power and has strong applicability. By storing the defect image files drawn periodically to a file server, when a request to obtain a defect image file is received, the target defect image file can be directly output based on the already drawn defect image files stored in the file server, thereby saving the time spent on temporarily drawing defect image files when a request to obtain a defect image file is received. Therefore, the defect image file retrieval speed is fast. The defect image files in the file server can be repeatedly retrieved, and have strong reusability. Furthermore, by implementing the functions of the aforementioned defect image file processing module through multiple modules, the steps of generating defect image files by the defect image file processing module can be decoupled. These multiple modules can be loaded into multiple applications on multiple terminal devices, or the functions of each of the above modules can be implemented by multiple terminal devices, making them applicable to a variety of application scenarios and highly adaptable.

[0074] In some feasible implementations, the defect image file processing method can be applied to the above. Figures 1 to 2 The defect image file processing system 1 provided in the corresponding embodiment, for ease of description, will be described below using the defect image file processing module as the execution subject to describe the above-mentioned defect image file processing method. Figure 1 and Figure 2 Based on the provided implementation, please refer to Figure 3 , Figure 3 This is a flowchart illustrating the defect image file processing method provided in this application. The defect image file processing method described above may include the following steps:

[0075] Step S101: Perform the first operation according to the first preset timing rule: acquire at least two standard structured data, and generate at least one defect image raw data based on the above at least two standard structured data; one of the above standard structured data is used to indicate the features of at least one dimension of the wafer; the above defect image raw data is used to indicate the graphic features of the defect image.

[0076] In some feasible implementations, the defect image file processing module can be used to periodically acquire at least two standard structured data according to a first preset timing rule, and the timing duration for performing the first operation according to the first preset timing rule is the first duration. For example, the first duration can be five minutes, then the defect image file processing module can acquire standard structured data once every five minutes. The defect image file processing module can acquire at least two standard structured data from an external memory or storage space; or, the defect image file processing module can receive at least two standard structured data transmitted from other devices or applications; or, the defect image file processing module can acquire the original data file of the wafer from the wafer scanning device and generate at least two standard structured data based on the original data file, which is not limited in this application.

[0077] In some feasible implementations, the defect image file processing module can acquire at least one set of standard structured data for wafer information and at least one set of standard structured data for defect information to obtain at least two sets of standard structured data. The standard structured data for wafer information includes the original data corresponding to the product model and a first dimension set, where the first dimension set includes at least the wafer size. The standard structured data for defect information includes the original data corresponding to the product model and a second dimension set, where the second dimension set includes at least the defect location. It should be noted that the defect image file processing module can index the aforementioned standard structured data for wafer information and standard structured data for defect information using the product model. For example, the aforementioned standard structured data for defect information and standard structured data for wafer information can be stored in tabular form. For ease of understanding the format of the aforementioned standard structured data for wafer information, please refer to Table 1, which is a wafer configuration data table provided in this application.

[0078] Table 1

[0079]

[0080] Table 1 contains standard structured data that can be used to store wafer information. As shown in Table 1, it records the wafer dimensions corresponding to product model A and product model B, where the wafer size for product model A is 200 mm and the wafer size for product model B is 300 mm. It is understood that Table 1 only shows standard structured data for two dimensions: product model and wafer size. In practical applications, the wafer configuration data table may include standard structured data for other dimensions, and the number of standard structured data in each dimension is not limited in this application. In some feasible implementations, the defect image file processing module can retrieve the wafer size corresponding to the product model from the wafer configuration data table, thereby obtaining standard structured data used to indicate the wafer information for the product model and wafer size.

[0081] To facilitate understanding of the standard structured data format of the above defect information, please refer to Table 2, which is a wafer defect data table.

[0082] Table 2

[0083]

[0084] As shown in Table 2, Table 2 records the defect locations corresponding to product model A and product model B, respectively. The defect location for product model A is (1, 1), and the defect location for product model B is (2, 2). It is understood that Table 2 only shows standard structured data for two dimensions: product model and defect location. In practical applications, the standard structured data table for defect information may include standard structured data for other dimensions, and this application does not limit the number of standard structured data in each dimension. In some feasible implementations, the defect image file processing module can retrieve the defect location corresponding to the product model from the standard structured data table of defect information, thereby obtaining standard structured data for indicating the product model and defect location.

[0085] In conjunction with Tables 1 and 2 above, in some feasible implementations, the defect image file processing module can obtain the wafer size and defect location corresponding to product model A by retrieving the standard structured data of wafer information associated with product model A and the standard structured data of defect information. For example, based on product model A, it can retrieve the wafer size and defect location corresponding to product model A from Tables 1 and 2 above, and then obtain the two standard structured data corresponding to product model A.

[0086] In some feasible implementations, the defect image file processing module can generate at least one original defect image data based on the aforementioned at least two standard structured data sets. One standard structured data set indicates at least one dimension of the wafer's features, and the original defect image data indicates the graphic features of the defect image. For example, the defect image file processing module can determine at least two target dimensions for drawing the defect image file from the aforementioned at least two dimensions based on the requirements for generating the defect image file. The defect image file processing module can obtain at least two standard structured data sets from an external application or terminal device, or it can obtain the original wafer data file from a wafer scanning device to generate at least two standard structured data sets; this application does not impose any limitations on this. The aforementioned at least two standard structured data sets include at least two dimensions of image feature data, such as wafer size and defect location. This application does not impose any limitations on the number or content of dimensions included in the aforementioned standard structured data sets, but in practical application scenarios, the aforementioned at least two standard structured data sets should at least include image feature data in the dimensions of wafer size and defect location. The defect image file processing module can determine at least two target dimensions for drawing the defect image file from the aforementioned at least two dimensions based on the generation requirements (e.g., data format). These at least two target dimensions include at least wafer size and defect location. For example, if the standard structured data obtained by the defect image file processing module includes raw data for three dimensions: "wafer size," "defect location," and "batch," then when the generation requirements for the defect image file are: data format of "wafer size" and "defect location," the defect image file processing module can determine the aforementioned "wafer size" and "defect location" as the two target dimensions for drawing the defect image file.

[0087] In some feasible implementations, the defect image file processing module can select at least two image feature data from at least two original data including at least two standard structured data based on the above-mentioned at least two target dimensions, wherein one target dimension corresponds to at least one image feature data. The defect image file processing module can determine at least two image feature data corresponding to at least two target dimensions based on the at least two target dimensions determined based on the generation requirements of the defect image file. For example, the selection of image feature data can be achieved by algorithms such as convolution algorithm and farthest point sampling compression algorithm. For example, the above-mentioned target dimensions may include "wafer size" and "defect location", and the standard structured data p includes: "product model A", "200mm", and "(1,1)". Among them, the standard structured data p includes the "product model" dimension, the "wafer size" dimension, and the "defect location" dimension; the original data corresponding to the "product model" dimension is "product model A", the original data corresponding to the "wafer size" dimension is "200mm", and the original data corresponding to the "defect location" dimension is "(1,1)". The defect image file processing module can determine the original data corresponding to the two target dimensions, "wafer size" and "defect location", in the above standard structured data p as image feature data. That is, the image feature data obtained by the defect image file processing module is "200mm" and "(1,1)".

[0088] In some feasible implementations, after obtaining at least two standard structured data sets, the defect image file processing module can generate at least one original defect image data set based on these two sets of structured data. For example, if the original defect image data set includes wafer dimensions and defect locations, the defect image file processing module can determine the wafer dimensions in the defect image file based on the wafer dimensions in the original defect image data set, and determine the defect locations in the defect image file based on the defect locations. The defect image file processing module can stitch together at least two image feature data sets corresponding to at least two target dimensions to generate at least one original defect image data set, wherein each target dimension used to generate one original defect image data set corresponds to one image feature data set. It should be noted that original data sets belonging to the same dimension can be stored column-wise, and at least two original data sets obtained from the same wafer scan can be stored row-wise. Therefore, the defect image file processing module can select at least two image feature data sets from the at least two original data sets row-wise and stitch them together, thereby stitching together at least two image feature data sets from different dimensions obtained from the same wafer scan to generate one original defect image data set. For example, the defect image file processing module obtains image feature data in the dimensions of "wafer size" and "defect location". For example, the obtained image feature data is "200mm", "(1,1)", "300mm" and "(2,2)", where "200mm" and "(1,1)" are image feature data located in the same row, and "300mm" and "(2,2)" are image feature data located in the same row. If the target format for drawing the defect image file is "wafer size"; "defect location", the defect image file processing module can stitch together "200mm" and "(1,1)" located in the same row (i.e., image feature data obtained from the same wafer scan) to obtain one original defect image data as "200mm; (1,1)"; and stitch together "300mm" and "(2,2)" to obtain another original defect image data as "300mm; (2,2)". It is understandable that the defect image file processing module can filter the raw data in the standard structured data, remove raw data that is irrelevant to the drawing of the defect image file, reduce the amount of data that needs to be analyzed when generating the defect image file, and thus improve the drawing speed of the defect image file; and by using data stitching, it can convert image feature data into defect image raw data that is more suitable for the drawing of the defect image file, thereby further improving the drawing speed of the defect image file.

[0089] In some feasible implementations, the defect image file processing module can perform a third operation at regular intervals according to a first preset timing rule before acquiring at least two standard structured data files. This operation involves acquiring at least one raw data file from the wafer scanning device, parsing the raw data file to obtain at least three raw data files. For example, the defect image file processing module can acquire at least one raw data file obtained from scanning the wafer from the wafer scanning device (e.g., a machine) at regular intervals (e.g., once every minute). The time interval for acquiring the raw data file should be determined according to the actual product form, and this application does not impose any limitations. For example, the defect image file processing module can acquire at least one raw data file from the wafer scanning device and then parse the at least one raw data file (e.g., through decoding or data segmentation by an application) to obtain at least three parsed raw data files. For example, the parsing process can convert the file format from ".ilm" to ".txt", or segment the raw data using spaces, delimiters, semicolons, etc. For example, the defect image file processing module obtains a raw data file. After parsing the raw data file, the following can be obtained: Scan start time: 2025-1-1; Operating platform: A1; Product model: B; Wafer size: 300mm; Defect location: (2, 2). The above raw data file can be parsed to obtain five parsed raw data sets, with each pair of adjacent parsed raw data sets separated by a semicolon.

[0090] In some feasible implementations, the defect image file processing module can perform data classification on at least three parsed raw data according to product model, a first dimension set, and a second dimension set for structured processing, generating at least two standard structured data sets, and storing the at least two standard structured data sets in a database. A standard structured data set includes at least one raw data set corresponding to at least one dimension in the product model and the first dimension set, or includes at least one raw data set corresponding to at least one dimension in the product model and the second dimension set. For example, the defect image file processing module can classify at least three raw data sets by dimension. For instance, the defect image file processing module obtains six parsed raw data sets: “Product Model A”, “200mm”, “(1,1)”, “Product Model B”, “300mm”, and “(2,2)”. Based on the dimensions, the above six raw data sets can be divided into three categories: “Product Model”, “Wafer Size”, and “Defect Location”, for example: “Product Model A” and “Product Model B” in the “Product Model” dimension, “200mm” and “300mm” in the “Wafer Size” dimension, and “(1,1)” and “(2,2)” in the “Defect Location” dimension. The data in the "Product Model" dimension is used to associate data from other dimensions. For example, "Product Model A" is associated with "200mm" and "(1,1)", and "Product Model B" is associated with "300mm" and "(2,2)", thus obtaining standard structured data: "Product Model A; 200mm", "Product Model A; (1,1)", "Product Model B; 300mm" and "Product Model B; (2,2)".

[0091] It is understandable that the defect image file processing module can convert unstructured raw data files into structured standard structured data by parsing and classifying the raw data files. Since the defect image file processing module analyzes the structured standard structured data faster than it analyzes the raw data files when generating defect image raw data, it can improve the generation speed of defect image raw data, thereby further improving the drawing speed of defect image files. By associating product model with wafer information and defect information through standard structured data, related standard structured data can be quickly filtered, thereby further improving the processing speed of standard structured data. In addition, by storing standard structured data in a database, standard structured data can be called up multiple times, which is highly reusable.

[0092] In some feasible implementations, the defect image file processing module can generate at least two standard structured data tables based on at least two standard structured data sets. Specifically, the defect image file processing module can generate at least one wafer configuration data table based on the product model and the first dimension set in the at least two standard structured data sets, and generate at least one wafer defect data table based on the product model and the second dimension set in the at least two standard structured data sets, to obtain at least two standard structured data tables. Further, the defect image file processing module can record at least one standard structured data set corresponding to the first dimension set into the wafer configuration data table based on the product model and the first dimension set, and record at least one standard structured data set corresponding to the second dimension set into the wafer defect data table based on the product model and the second dimension set, to record at least two standard structured data sets. Finally, the defect image file processing module can store the at least one wafer defect data table and the at least one wafer configuration data table in a database to store the at least two standard structured data sets. The aforementioned wafer configuration data table may include standard structured data in dimensions such as wafer size, milling edge width, product model, chip width, chip height, number of chips in the horizontal axis direction of a single exposure, number of chips in the vertical axis direction of a single exposure, horizontal axis width of the spacing between chips, vertical axis width of the spacing between chips, horizontal axis offset distance of the center chip from the wafer center, and vertical axis offset distance of the center chip from the wafer center. The aforementioned wafer defect data table may include standard structured data in dimensions such as product model, batch identifier, wafer identifier, scan start time, scan end time, horizontal axis defect location, and vertical axis defect location. This application does not limit the dimensions included in the aforementioned standard structured data tables such as wafer defect data tables and wafer configuration data tables, but the wafer defect data table should at least include standard structured data of product model and defect information, and the wafer configuration data table should at least include standard structured data of product model and wafer size. The aforementioned multiple standard structured data tables can be linked through dimension identifiers (such as product model, wafer identifier, batch identifier), thereby enabling the association of data in one standard structured data table with data in another, and thus reducing the storage space of the standard structured data. For example, the dimensions that need to be stored include: defect location, wafer size, and product model. If the standard structured data obtained from the first wafer scan is "(1,1)", "200mm", and "Product Model A", and the standard structured data obtained from the second wafer scan is "(2,2)", "200mm", and "Product Model A", then the standard structured data obtained from the second wafer scan is "(2,2)", "200mm", and "Product Model A".If the standard structured data of defect information is stored separately in a wafer defect data table, the wafer defect data table can store "(1,1)" and "Product Model A" in the first row, "(2,2)" and "Product Model A" in the second row, and "200mm" and "Product Model A" in another standard structured data table. Among them, "(1,1)", "(2,2)" and "200mm" are associated through "Product Model A", and the standard structured data "200mm" that appears twice is stored only once.

[0093] It can be seen that storing data in multiple standard structured tables allows for the merging of duplicate data, reducing the amount of standard structured data that would otherwise need to be stored. This saving is even more significant when the amount of standard structured data related to defect information is large. In essence, the defect image file processing module, by generating at least two standard structured data tables, can categorize and store the standard structured data, thereby avoiding repeated readings and improving data analysis speed while reducing the storage space occupied by the standard structured data.

[0094] Step S102: Perform the second operation according to the second preset timing rule: generate at least one defect image file based on the above at least one defect image raw data, and store the above at least one defect image file on the file server.

[0095] In some feasible implementations, the defect image file processing module can periodically execute a second operation according to a second preset timing rule to identify graphic features indicated by at least one original defect image data, thereby generating at least one defect image file based on the aforementioned graphic features, and storing the at least one defect image file on a file server. Each defect image file is generated from at least one original defect image data, which should at least include graphic features indicating wafer size and graphic features indicating defect location. The graphic features indicating wafer size cannot be empty, while the information indicating defect location can be empty. When the original defect image data only includes wafer size and all other data is empty, it indicates that the wafer corresponding to the original defect image data has no defects, and the defect image output by the defect image file processing module does not display any defects. After generating the defect image, the defect image file processing module can output and store the defect image in the form of a defect image file; for example, the defect image generation module can store the defect image file on a file server.

[0096] It should be noted that the timing duration for executing the second operation according to the second preset timing rule is the second duration; the first duration is less than or equal to the second duration. Since the first duration is less than or equal to the second duration, the real-time nature and continuity of the original defect image data generated by the first operation can be guaranteed, thus providing sufficient original defect image data input for the second operation. Furthermore, the differentiated configuration of the first and second durations can avoid process blockages caused by synchronous operations, making it suitable for multi-dimensional data fusion scenarios and allowing for flexible allocation of computing resources, thereby further improving computational efficiency and applicability. It can be understood that the defect image file processing module can store the periodically generated defect image files on a file server. When the defect image file processing module receives a request to retrieve a defect image file, it can directly call the already drawn defect image file from the file server, thus saving the time spent temporarily drawing the defect image file when receiving the request. Therefore, the defect image file retrieval speed is fast. In addition, the defect image files in the file server can be repeatedly retrieved, exhibiting strong reusability.

[0097] Step S103: When a request to obtain a defect map file is received, at least one target defect map file associated with the index field is output based on the at least one defect map file stored on the file server, according to the index field for indexing the defect map file included in the request.

[0098] In some feasible implementations, the defect image file processing module, upon receiving a request to obtain a defect image file, can output at least one target defect image file associated with the index field included in the request, based on at least one defect image file stored on the file server. For example, the file server may include defect image file j and defect image file k, where defect image file j is a defect image of wafer a from batch m, and defect image file k is a defect image of wafer b from batch m. When the index field in the request for obtaining a defective image file is "wafer a", the defective image file processing module can use defective image file j as the target defective image file and output the aforementioned defective image file j. When the index field in the request for obtaining a defective image file is "batch m", the defective image file processing module can use defective image file j and defective image file k as target defective image files and output the aforementioned defective image file j and defective image file k. When the index field in the request for obtaining a defective image file is "chip q", a defective image file indicating "chip q" cannot be retrieved from the file server. Therefore, the index field "chip q" can be associated with a defective image file indicating "empty" (e.g., a blank image) so that the defective image file processing module outputs the aforementioned defective image file indicating "empty". Optionally, if a defective image file indicating "chip q" cannot be retrieved from the file server, it may not be output, and this application does not impose any restrictions.

[0099] In some feasible implementations, after generating at least one defect image file based on at least one original defect image data, the defect image file processing module can also generate index information for each defect image file, and establish at least one calling link for the at least one defect image file based on the at least one defect image file and the corresponding index information. The index information may include at least one index field, which may be an identifier or parameter indicating the dimension of the wafer, such as batch identifier, wafer identifier, chip identifier, wafer size, wafer scan time, etc. For example, if the batch identifier of a defect image file is "batch m", the wafer identifier is "wafer a", and the wafer size is "200mm", then the index information of the defect image file may be: "batch m, wafer a, 200mm". The index information may be separated by commas, spaces, semicolons, etc., or it may be directly concatenated without separating the index fields; this application does not impose any restrictions. If the index information of defect image file j is "batch m, wafer a, 200mm", then the index fields contained in this index information are "batch m", "wafer a", and "200mm". The defect image file processing module can obtain the calling link of defect image file j through one or more of the index fields "batch m", "wafer a", and "200mm". It should be noted that one of the above index fields can be associated with multiple calling links. For example, if the index information of defect image file j is "batch m, wafer a, 200mm", and the index information of defect image file k is "batch m, wafer b, 200mm", then the index field "batch m" is associated with the calling link of defect image file j and the calling link of defect image file k, and the index field "200mm" is also associated with the calling link of defect image file j and the calling link of defect image file k.

[0100] In some feasible implementations, the defect image file processing module can also generate a defect image file index table based on at least one index field and at least one calling link. Through this index table, the associated index links can be quickly retrieved based on the index fields, thereby further improving the retrieval speed of defect image files. It can be understood that by generating index information and calling links for defect image files, the defect image file processing module can bind the index information, defect image file, and calling links. By establishing a defect image file index table, a connection can be established between the defect image file, the calling link, and at least one index field in the index information. This allows for rapid retrieval of the calling links associated with the index fields through the defect image file index table, improving indexing speed and further enhancing the retrieval speed of defect image files. Furthermore, since one index field can be associated with multiple calling links, and different index fields can be associated with the same calling link, the defect image file processing system is applicable to various indexing scenarios and has strong applicability.

[0101] In some feasible implementations, the defect image file processing module can obtain at least one calling link associated with at least one index field based on the defect image file index table and at least one index field in the request, thereby calling at least one target defect image file corresponding to at least one calling link from the file server based on the at least one calling link, and outputting at least one target defect image file. The defect image file processing module can analyze the request for obtaining the defect image file to obtain at least one index field included in the request. Optionally, the defect image file processing module can provide the data analysis platform or other terminal device that sends the request for obtaining the defect image file with an effectively indexable index field according to the defect image file index table, avoiding the inclusion of index fields not associated with defect image files in the request, thereby improving indexing efficiency. The defect image file processing module can index at least one calling link associated with the at least one index field from the defect image file index table based on the at least one index field in the request. For example, the index fields included in the aforementioned defect image file index table can be "batch m", "wafer a", and "wafer b". The call links associated with "batch m" are "call link n" and "call link o", the call link associated with "wafer a" is "call link n", and the call link associated with "wafer b" is "call link o". Therefore, when the index field in the request is "wafer a", the defect image file processing module can use the defect image file index table to find that the call link associated with "wafer a" is "call link n", and so on. Further, the defect image file processing module can use the call link determined from the defect image index table to call and output the target defect image file corresponding to that call link from the file server. For example, if the aforementioned "call link n" corresponds to "defect image file j", then the defect image file processing module can use "call link n" to call the aforementioned "defect image file j" from the file server as the target defect image file and output the aforementioned "defect image file j". It is understood that the defect image file processing module can quickly obtain at least one call link associated with at least one index field from the defect image file index table through at least one index field in the request, so as to call and output at least one target defect image file corresponding to the at least one call link. The indexing speed through the defect image file index table is fast, and multiple target defect image files can be called simultaneously through one or more index fields, which further improves the calling speed of defect image files.

[0102] In some feasible implementations, the target defect image file output by the above-described defect image file processing method can be used for defect tracing analysis during wafer fabrication. For a better understanding of the effect of the target defect image file output by the above-described defect image file processing method, please refer to [the relevant documentation / reference]. Figure 4 , Figure 4This is a page view of the defect diagram file provided in this application. It should be noted that... Figure 4 As a feasible example diagram, this application does not impose restrictions on the display page layout of the defect diagram file, the display rules of the index information, etc.

[0103] like Figure 4 The illustrated page diagram of the defect image file shows how the data analysis platform receives and displays the defect image file after sending a request to the defect image file processing module to obtain the defect image file. For example... Figure 4 The illustrated page may include multiple defect image files and corresponding index information for each file. For example, wafer identifiers may include wafer a, wafer b, and wafer c, used to indicate the defect image files for the wafers corresponding to wafer a, wafer b, and wafer c, respectively. Index information may include acquisition time d, scanning device e, defect location f, acquisition time g, scanning device h, and defect location i. Figure 4 Each defect image file shown can display the location and number of defects on the wafer. Optionally, the page illustration of the above defect image file can also provide one or more annotation boxes. When the data analysis platform receives a click instruction for a defect image file, it can display an annotation box on the defect image file to indicate that the click is complete. When the data analysis platform receives a pending annotation instruction for a defect image file, it can display an annotation box on the defect image file to indicate that the defect image file is pending confirmation. When the data analysis platform receives a confirmed annotation instruction for a defect image file, it can display an annotation box on the defect image file to indicate that the defect image file has been confirmed. This application does not limit the style of the above annotation boxes.

[0104] Using this application, original defect image data for indicating graphic features of defect images can be generated periodically based on standard structured data according to a first preset timing rule. Generating defect image files from the original defect image data improves the drawing speed of defect image files. Furthermore, defect image files can be drawn periodically based on the original defect image data according to a second preset timing rule. Different timing rules avoid processing large batches of standard structured data and drawing large batches of defect image files simultaneously, thus avoiding computational pressure. Therefore, it is suitable for products with low computational power and has strong applicability. By storing the timed defect image files on a file server, when a request to retrieve a defect image file is received, the target defect image file can be directly output based on the already drawn defect image files stored on the file server, saving the time spent temporarily drawing defect image files when a request is received. Therefore, the retrieval speed of defect image files is fast. In addition, defect image files on the file server can be repeatedly retrieved, exhibiting strong reusability.

[0105] This application also provides a defect diagram file processing device; please refer to [link to device]. Figure 5 , Figure 5 This is a schematic diagram of the defect image file processing device provided in this application. For example... Figure 5 The defect image file processing apparatus 10 shown can be a computer device having a computer program (including program code) that implements the above-described wafer image alignment method. The defect image file processing apparatus 10 can also be a computer program, such as an application software. This apparatus can be used to perform the corresponding steps in the wafer image alignment method provided in this application. Figure 5 As shown, the above-mentioned defect image file processing device 10 may include: a first processing module 101 and a second processing module 102.

[0106] The first processing module 101 is configured to perform a first operation according to a first preset timing rule: acquire at least two standard structured data, and generate at least one defect image raw data based on the at least two standard structured data; one of the standard structured data is used to indicate at least one dimension of the wafer features; the defect image raw data is used to indicate the graphic features of the defect image.

[0107] The second processing module 102 is used to perform a second operation according to a second timing rule: generate at least one defect image file based on the original data of at least one defect image, and store the at least one defect image file to a file server;

[0108] The second processing module 102 is further configured to, when receiving a request to obtain a defect map file, output at least one target defect map file associated with the index field included in the request for indexing the defect map file, based on the at least one defect map file stored on the file server.

[0109] In some feasible implementations, the timing duration for executing the first operation according to the first preset timing rule is the first duration; the timing duration for executing the second operation according to the second preset timing rule is the second duration; and the first duration is less than or equal to the second duration.

[0110] In some feasible implementations, the above-mentioned defect image file processing device 10 further includes a third processing module 103 and a fourth processing module 104.

[0111] The third processing module 103 is used to generate index information for each of the above-mentioned defect diagram files, and to establish at least one calling link for the at least one defect diagram file based on the at least one defect diagram file and the index information corresponding to each of the above-mentioned defect diagram files; one of the above-mentioned index information includes at least one index field, one of the above-mentioned index fields is associated with at least one of the above-mentioned calling links, and one of the above-mentioned calling links corresponds to one of the above-mentioned defect diagram files.

[0112] The fourth processing module 104 is used to generate a defect map file index table based on at least one index field and at least one calling link mentioned above.

[0113] In some feasible implementations, the second processing module 102 described above includes an acquisition unit 1021 and an output unit 1022.

[0114] The acquisition unit 1021 is used to acquire the at least one call link associated with the at least one index field based on the defect graph file index table and the at least one index field in the request.

[0115] The output unit 1022 is used to call at least one target defect map file corresponding to the at least one call link from the file server based on the at least one call link, and output the at least one target defect map file.

[0116] In some feasible implementations, the first processing module 101 is further configured to acquire at least one standard structured data of wafer information and at least one standard structured data of defect information to obtain the at least two standard structured data, wherein the standard structured data of wafer information includes the original data corresponding to the product model and the first dimension set, the first dimension set including at least the wafer size, and the standard structured data of defect information includes the original data corresponding to the product model and the second dimension set, the second dimension set including at least the defect location.

[0117] In some feasible implementations, the first processing module 101 includes: a determining unit 1011, a selecting unit 1012, and a splicing unit 1013.

[0118] The determining unit 1011 is used to determine at least two target dimensions for drawing the defect map file from the first dimension set and the second dimension set based on the above-mentioned defect map file generation requirements.

[0119] The selection unit 1012 is used to obtain at least two image feature data based on the above at least two target dimensions and the above at least two standard structured data, wherein one of the above target dimensions corresponds to at least one of the above image feature data, and the above at least two target dimensions include at least the above wafer size and the above defect location;

[0120] The stitching unit 1013 is used to stitch together the at least two image feature data corresponding to the at least two target dimensions to generate at least one defective image raw data, wherein each of the target dimensions used to generate the defective image raw data corresponds to one of the image feature data.

[0121] In some feasible implementations, the defect image file processing device 10 further includes a parsing module 105 and a structuring module 106, which are used to perform a third operation according to the first preset timing rule before the first processing module 101 acquires at least two standard structured data.

[0122] The parsing module 105 is used to acquire at least one raw data file from the wafer scanning device according to the first preset timing rule, and to parse the at least one raw data file to obtain at least three raw data; one of the raw data corresponds to one dimension, and the dimensions of the at least three raw data include at least the product model, the wafer size and the defect location, the wafer size belongs to the first dimension set and the defect location belongs to the second dimension set.

[0123] The structuring module 106 is used to perform data classification and structuring processing on the at least three raw data based on the product model, the first dimension set, and the second dimension set according to the first preset timing rule, so as to generate at least two standard structured data and store the at least two standard structured data in the database; one of the standard structured data includes at least one of the raw data corresponding to at least one dimension in the product model and the first dimension set, or includes at least one of the raw data corresponding to at least one dimension in the product model and the second dimension set.

[0124] In some feasible implementations, the above-mentioned structured module 106 includes a generation unit 1061, a recording unit 1062, and a storage unit 1063.

[0125] The generation unit 1061 is used to generate at least one wafer configuration data table based on the product model in the at least two standard structured data and the first dimension set, and to generate at least one wafer defect data table based on the product model in the at least two standard structured data and the second dimension set, so as to obtain at least two standard structured data tables.

[0126] The recording unit 1062 is used to record at least one of the standard structured data corresponding to the first dimension set into the wafer configuration data table according to the product model and the first dimension set, and to record at least one of the standard structured data corresponding to the second dimension set into the wafer defect data table according to the product model and the second dimension set, so as to record at least two standard structured data.

[0127] Storage unit 1063 is used to store the above-mentioned at least one wafer defect data table and the above-mentioned at least one wafer configuration data table into a database to store the above-mentioned at least two standard structured data.

[0128] In some feasible implementations, the parsing module 105, structuring module 106, generation unit 1061, recording unit 1062, and storage unit 1063 in the defect image file processing device 10 can work together to achieve the above-mentioned... Figure 2 The data acquisition module 101b provided in the illustrated embodiment performs the functions described above; the first processing module 101, the determining unit 1011, the selecting unit 1012, and the splicing unit 1013 in the defect image file processing device 10 can work together to achieve the above. Figure 2 The data analysis module 103b provided in the illustrated embodiment performs the functions described above; the second processing module 102, the third processing module 103, the acquisition unit 1021, and the output unit 1022 in the defect image file processing device 10 can work together to achieve the above-mentioned functions. Figure 2 The diagram drawing module 104b provided in the illustrated embodiment implements the following functions. The implementation methods of each module and / or unit included in the above-described defect diagram file processing device 10 can be found in the above description. Figure 3 The implementation methods provided for each step in the wafer image alignment method shown are not elaborated here.

[0129] The defect image file processing device provided in this application can generate at least one original defect image data for indicating the graphic features of the defect image based on at least two standard structured data according to a preset timing rule. At least one defect image file is generated from at least one original defect image data, which improves the drawing speed of the defect image file. Furthermore, the method of acquiring the original defect image data and drawing the defect image file according to the preset timing rule avoids the computational pressure caused by processing large batches of standard structured data and drawing a large number of defect image files simultaneously. Therefore, it is suitable for products with low computing power and has strong applicability. By storing the timed defect image files to a file server, the device can directly output the target defect image file based on the already drawn defect image files stored in the file server when a request to retrieve a defect image file is received. This saves the time spent temporarily drawing defect image files when a request to retrieve a defect image file is received, resulting in fast defect image file retrieval speed. In addition, the defect image files in the file server can be repeatedly retrieved, demonstrating strong reusability.

[0130] Please see again Figure 6 , Figure 6 This is a structural schematic diagram of the terminal device provided in this application. For example... Figure 6 As shown, the terminal device 100 may include: a processor 1001, a network interface 1004, a memory 1005, and a controller 1006. Furthermore, the terminal device 100 may also include: a user interface 1003, and at least one communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 includes random access memory (RAM) and non-volatile memory (NVM), such as erasable programmable read-only memory (EPROM). The memory 1005 may optionally be at least one storage device located remotely from the processor 1001. The controller 1006 can be used to receive data sent by the processor and generate control instructions, which can execute the aforementioned... Figures 1 to 4 The functions implemented by the controller in the illustrated embodiment can be controlled, for example, by controller 1006. Figures 1 to 4 The defect image file processing module in the illustrated embodiment executes the step of generating defect image files periodically according to a preset timing rule. For example... Figure 6 As shown, the memory 1005, which is a computer-readable storage medium, may include an operating system, a network communication module, a user interface module, and a device control application program. Optionally, in this embodiment, the memory 1005 may also execute the above-described... Figures 1 to 2 The processor 1001 described in this embodiment can perform the functions of the memory in the defect image file processing system, or it can implement the functions of a file server in the defect image file processing system. Figures 1 to 2 The functions performed by the processor (such as the defect image file processing module) provided in the illustrated embodiment.

[0131] In such Figure 6 In the terminal device 100 shown, the network interface 1004 provides network communication functionality; the user interface 1003 is mainly used to provide an input interface for the user; and the processor 1001 can be used to call the device control application stored in the memory 1005 to implement the aforementioned functions. Figure 3 The defect image file processing method in the illustrated embodiment.

[0132] In some feasible implementations, the memory 1005 described above can achieve the functions outlined above. Figures 1 to 4 The file server mentioned in the illustrated embodiment implements the following functions: the memory 1005 can be used to store defect diagram files, and the processor 1001 is further used to retrieve the defect diagram files from the memory 1005 to perform the above-mentioned functions. Figure 3 The defect image file processing method of the embodiment shown.

[0133] It should be understood that the terminal device 100 described in the embodiments of this application can execute the foregoing text. Figure 3 The defect image file processing method of the illustrated embodiment will not be described in detail. Furthermore, the beneficial effects of using the same method will also not be described in detail.

[0134] Furthermore, it should be noted that this application embodiment also provides a computer-readable storage medium, which stores a computer program executed by the wafer measurement method based on measurement markers mentioned above. The computer program includes program instructions, and when the processor executes the program instructions, it can execute the aforementioned... Figure 3 The defect image file processing method provided in the illustrated embodiment will not be described in detail here. Furthermore, the beneficial effects of using the same method will not be elaborated upon. For technical details not disclosed in the computer-readable storage medium embodiments related to this application, please refer to the description of the method embodiments of this application.

[0135] The aforementioned computer-readable storage medium can be an internal storage unit of the terminal device provided in any of the foregoing embodiments, such as a hard disk or memory of the terminal device. The computer-readable storage medium can also be an external storage device of the terminal device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device. Furthermore, the computer-readable storage medium may include both internal storage units and external storage devices of the terminal device. The computer-readable storage medium is used to store the computer program and other programs and data required by the terminal device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0136] Furthermore, it should be noted that this application also provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of the terminal device loads and executes the computer instructions, enabling the terminal device to execute the aforementioned... Figures 3 to 4 The defect image file processing method provided in the illustrated embodiment.

[0137] Those skilled in the art will recognize that the system and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Those skilled in the art can implement the described functions using different methods for each specific application, but such implementations should not be considered beyond the scope of this application.

Claims

1. A method for processing defect image files, characterized in that, include: The first operation is performed according to the first preset timing rule: acquiring at least one standard structured data of wafer information and at least one standard structured data of defect information to obtain at least two standard structured data. Based on the requirements for generating the defect map file, at least two target dimensions for drawing the defect map file are determined from a first set of dimensions and a second set of dimensions, wherein the first set of dimensions includes at least the wafer size and the second set of dimensions includes at least the defect location; At least two image feature data are obtained based on the at least two target dimensions and the at least two standard structured data, wherein one of the target dimensions corresponds to at least one of the image feature data, and the at least two target dimensions include at least the wafer size and the defect location; The at least two image feature data corresponding to the at least two target dimensions are concatenated to generate at least one defective image raw data, wherein each target dimension used to generate one defective image raw data corresponds to one image feature data; The second operation is performed according to the second preset timing rule: at least one defect image file is generated based on the original data of the at least one defect image, and the at least one defect image file is stored in the file server; When a request to obtain a defect map file is received, at least one target defect map file associated with the index field is output based on the at least one defect map file stored on the file server, according to the index field included in the request for indexing the defect map file.

2. The method according to claim 1, characterized in that, The timing duration for executing the first operation according to the first preset timing rule is the first duration; the timing duration for executing the second operation according to the second preset timing rule is the second duration. The first duration is less than or equal to the second duration.

3. The method according to claim 2, characterized in that, After generating at least one defect image file based on the at least one original defect image data, the method further includes: Generate index information for each of the defect graph files, and establish at least one calling link for the at least one defect graph file based on the at least one defect graph file and the index information corresponding to each of the defect graph files; each index information includes at least one index field, each index field is associated with at least one calling link, and each calling link corresponds to one defect graph file. A defect graph file index table is generated based on the at least one index field and the at least one call link.

4. The method according to claim 3, characterized in that, The step of outputting at least one target defect map file associated with the index field based on the at least one defect map file stored on the file server, according to the index field included in the request for indexing defect map files, includes: Based on the defect graph file index table and the at least one index field in the request, obtain the at least one call link associated with the at least one index field; Based on the at least one call link, at least one target defect map file corresponding to the at least one call link is called from the file server, and the at least one target defect map file is output.

5. The method according to any one of claims 1-4, characterized in that, Before acquiring at least two standard structured data sets, the method further includes: The third operation will be executed according to the first preset timing rule: At least one raw data file is obtained from a wafer scanning device, and the at least one raw data file is parsed to obtain at least three raw data; each raw data corresponds to one dimension, and the dimensions of the at least three raw data include at least the product model, the wafer size, and the defect location, wherein the wafer size belongs to the first dimension set, and the defect location belongs to the second dimension set. Based on the product model, the first dimension set, and the second dimension set, the at least three raw data are classified for structured processing to generate the at least two standard structured data, and the at least two standard structured data are stored in the database; one of the standard structured data includes at least one of the raw data corresponding to at least one dimension in the product model and the first dimension set, or includes at least one of the raw data corresponding to at least one dimension in the product model and the second dimension set.

6. The method according to claim 5, characterized in that, The step of storing the at least two standard structured data into a database includes: At least one wafer configuration data table is generated based on the product model in the at least two standard structured data and the first dimension set, and at least one wafer defect data table is generated based on the product model in the at least two standard structured data and the second dimension set, so as to obtain at least two standard structured data tables. Based on the product model and the first dimension set, at least one of the standard structured data corresponding to the first dimension set is recorded in the wafer configuration data table, and based on the product model and the second dimension set, at least one of the standard structured data corresponding to the second dimension set is recorded in the wafer defect data table, so as to record the at least two standard structured data. The at least one wafer defect data table and the at least one wafer configuration data table are stored in a database to store the at least two standard structured data.

7. A defect image file processing device, characterized in that, include: The first processing module and the second processing module; The first processing module is used to perform a first operation according to a first preset timing rule: to obtain at least one standard structured data of wafer information and at least one standard structured data of defect information to obtain at least two standard structured data. Based on the requirements for generating the defect map file, at least two target dimensions for drawing the defect map file are determined from a first set of dimensions and a second set of dimensions, wherein the first set of dimensions includes at least the wafer size and the second set of dimensions includes at least the defect location; At least two image feature data are obtained based on the at least two target dimensions and the at least two standard structured data, wherein one of the target dimensions corresponds to at least one of the image feature data, and the at least two target dimensions include at least the wafer size and the defect location; The at least two image feature data corresponding to the at least two target dimensions are concatenated to generate at least one defective image raw data, wherein each target dimension used to generate one defective image raw data corresponds to one image feature data; The second processing module is used to perform a second operation according to a second preset timing rule: after the first processing module generates the original data of the at least one defect image at a time, it generates at least one defect image file based on the original data of the at least one defect image and stores the at least one defect image file on a file server; The second processing module is further configured to, when receiving a request for obtaining a defect map file, output at least one target defect map file associated with the index field included in the request for indexing the defect map file, based on the at least one defect map file stored on the file server.

8. A terminal device, characterized in that, include: Processor and memory; The processor is connected to the memory, wherein the memory is used to store program code, and the processor is used to call the program code from the memory to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program for being loaded by a processor and executing the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, The aforementioned computer program product includes computer instructions for being loaded by a processor and executing the method as described in any one of claims 1-6.

Images