Defective product management and control method and system based on E-Mapping system

Abstract

The invention relates to the technical field of semiconductor manufacturing, and discloses a defective product management and control method and system based on an E-Mapping system, and the method comprises the following steps: S1, data collection and processing: obtaining the detection data of each die on each wafer through a detection device; s2, data storage optimization: transmitting the CSV file to a database system; s3, data analysis: the CSV file data of different devices are analyzed; s4, identification code conversion: carrying out standardization processing on the analyzed identification codes through a unified conversion rule; s5, generating a yield map: calculating the passing rate of each die on different wafers; s6, marking defective products; and S7, data backup and export. According to the method, data are stored in a sub-table mode through batch numbers or device sources, and an automatic table generation module is introduced. When the new batch is detected, the system can automatically create the corresponding data table and bind the data table with the batch number, so that the data storage and retrieval efficiency is improved, and the phenomena of data mixing and slow query are avoided.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor manufacturing technology, and in particular to a defective product control method and system based on an E-Mapping system. Background Art

[0002] In high-precision manufacturing industries such as semiconductor manufacturing and electronic packaging, product quality control has always been a core link in the production process. Especially in the wafer inspection process, multiple dies (grains) on each wafer need to be inspected to ensure production quality.

[0003] However, existing wafer inspection systems usually generate a large amount of inspection data, including inspection results of tens of thousands of dies on each wafer. Traditional systems mostly use a single database table storage mode for data storage. When the data volume is large, the query and retrieval efficiency of the system is significantly reduced. In addition, the mixed storage of data from different batches leads to difficulties in data management and subsequent analysis. Summary of the invention

[0004] In order to make up for the above shortcomings, the present invention provides a defective product control method and system based on the E-Mapping system, aiming to improve the problem that traditional systems mostly use a single database table storage mode for data storage, and when the data volume is huge, the query and retrieval efficiency of the system is significantly reduced.

[0005] In a first aspect, the present invention provides the following technical solution, a defective product control method based on an E-Mapping system, comprising the following steps:

[0006] S1. Data acquisition and processing: Obtain the detection data of each die on each wafer through the detection equipment, and convert the data into a CSV format file;

[0007] S2. Data storage optimization: The CSV format file is transmitted to the database system, and the database system stores the data in the corresponding table according to the batch number or the source of the equipment. If there is no corresponding batch data table, the system automatically generates a new data table by calling the batch table creation module and binds the batch number to the table name.

[0008] S3, data parsing: Parse the CSV file data of different devices by calling parsing packages, where each parsing package contains a set of parsing rules for a specific device, and automatically selects the corresponding parsing package for parsing according to the device type;

[0009] S4, identification code conversion: the parsed identification code is standardized through a unified conversion rule;

[0010] S5. Generate yield map: Extract the test data of the same batch of wafers from the database, call the yield map generation module, calculate the pass rate of each die on different wafers; generate a heat map to show the yield distribution of each coordinate point, and use color gradient to show the high and low yields;

[0011] S6. Defective product marking: Automatically identify defective products through the data in the yield map, and generate a defective product processing report based on the detected defective product location and related information;

[0012] S7. Data backup and export: Set the automatic backup cycle, and regularly export the historical data in the database as CSV files through the automatic backup module. The backup files are stored in the specified external storage path, and a data export report is generated according to user needs.

[0013] Preferably, in step S1, the detection data includes the position, detection result and identification code of the die, and the CSV file includes the detection position, detection status and batch number information of each die;

[0014] In the step S3, the parsing rules include interpretation of the identification code, adjustment of the data direction and standardization of the format;

[0015] In the step S4, the conversion rule includes mapping specific identification codes used by different devices into a system standard identification code format;

[0016] In the step S5, the pass rate is obtained by dividing the number of dies that pass the test by the total number of dies;

[0017] In the step S6, the report includes the specific location of the defective product, the test results, the defect type and the relevant batch number.

[0018] Preferably, the data storage optimization in step S2 includes: by querying the batch number table records in the database, the system calls the table generation module to automatically generate a new table when storing new data, and realizes fast retrieval of data through the mapping relationship between the batch number and the table name;

[0019] The data analysis in the S3 step includes: configuring a corresponding analysis package for each device, the analysis package includes the device's specific data format, identification code analysis rules and data direction adjustment parameters, and the system automatically selects the corresponding analysis package according to the device model and source and analyzes and standardizes the data.

[0020] Preferably, the identification code conversion in step S4 includes: establishing a mapping table between device and system standard identification codes, and uniformly converting the identification codes of different devices through a system internal conversion module, so that data generated by all devices can be processed in accordance with the standard identification code format.

[0021] Preferably, the yield map generation in the S5 step includes: extracting the detection data of each die from the database, calculating the pass rate of each coordinate point through the heat map generation module, and generating a heat map showing the yield distribution through a color gradient effect, wherein the color change range in the heat map is from red to green, intuitively showing the yield situation of each area.

[0022] Preferably, the defective product marking step in step S6 includes: marking each die that fails the inspection through the parsed data, recording the specific location information, batch number and cause of the defective product, and automatically generating a defective product report containing defective product statistical information.

[0023] Preferably, the data backup and export in step S7 includes: setting an automatic backup cycle, exporting the data into CSV format by calling the automatic backup module, and storing it in a specified backup path; the backup file is securely stored through an encryption algorithm, and the user can re-import the backup file through the export interface as needed for data analysis.

[0024] In a second aspect, the present invention provides the following technical solution: a defective product control system based on an E-Mapping system, the system comprising:

[0025] Data acquisition module: used to collect the inspection data of each die on each wafer from the inspection equipment and convert the data into a standard CSV format file;

[0026] Data storage module: storing the data in the CSV file into the corresponding data table of the database according to the batch number or the source of the equipment; the data storage module includes a table generation submodule for automatically creating a new data table when a new batch is detected and binding the batch number to the table name;

[0027] Data parsing module: used to parse the data in the CSV file according to the parsing rules of different devices. The data parsing module includes a parsing package management submodule, which is used to configure corresponding parsing packages for different devices and dynamically adjust the parsing rules to perform standardized processing of data;

[0028] Identification code conversion module: used to convert identification codes generated by different devices into standard identification codes of the system through a mapping table;

[0029] Yield map generation module: used to generate a yield map based on the test data stored in the database. The module calculates the pass rate of each die and displays the yield distribution of each coordinate point in the form of a color gradient heat map;

[0030] Defective product marking module: used to automatically mark defective products in the test results and generate defective product processing reports;

[0031] Data backup and export module: used to set the automatic backup cycle, regularly export the data in the database as CSV files and store them in encrypted form. Users can generate backup reports through the export interface and re-import them into the system for data analysis.

[0032] In a third aspect, the invention provides the following technical solution: a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned defective product control method based on the E-Mapping system when executing the computer program.

[0033] In a fourth aspect, the present invention provides the following technical solution: a readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the above-mentioned defective product control method based on the E-Mapping system.

[0034] The present invention has the following beneficial effects:

[0035] 1. The present invention stores data in separate tables by batch number or equipment source, and introduces an automatic table generation module. When a new batch is detected, the system automatically creates a corresponding data table and binds it to the batch number. This method greatly improves the efficiency of data storage and retrieval, and avoids data confusion and slow query.

[0036] 2. In the present invention, the present invention can configure corresponding parsing packages for different devices through the parsing package management submodule, and dynamically select parsing rules according to the model or source of the device. This method ensures that the data generated by different devices can be parsed and processed according to a unified standard, simplifies the data conversion process, reduces maintenance costs, and enhances the scalability of the system.

[0037] 3. In the present invention, by establishing a mapping table between equipment and system standard identification codes, the present invention ensures that identification codes generated by different equipment can be uniformly converted into the system standard format. In this way, the detection data of different equipment can be seamlessly connected in subsequent processes, which improves data utilization and reduces additional processing workload.

[0038] 4. In the present invention, through the yield map generation module, the present invention can automatically generate a heat map to display the yield distribution of each wafer in real time. The heat map intuitively displays the yield level of each area through color gradient, helping engineers to quickly identify bad areas and adjust the process, greatly improving the efficiency and accuracy of yield analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of a defective product control method based on the E-Mapping system proposed by the present invention;

[0040] Figure 2 This is an architecture diagram of a defective product control system based on an E-Mapping system proposed in the present invention. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Embodiment 1

[0043] Reference Figure 1 In the first embodiment of the present invention, the present invention provides a defective product control method based on the E-Mapping system, comprising the following steps:.

[0044] S1. Data collection and processing

[0045] The detection data of each die on each wafer is obtained through the detection equipment. The detection data includes the position, detection results and identification code of the die. The detection equipment can detect each die on the wafer one by one through optical detection or electrical detection means. After the detection is completed, the system converts the detection results into a CSV format file. The CSV file records the detection information of each die, including the physical position (i.e. coordinates) of the die, the detection status (such as pass / fail) and the identification code generated by the equipment. Relevant batch number information is also attached to the file for subsequent data management and retrieval. The data acquisition process is implemented through the automation equipment interface, and the equipment is connected to the system through an API or communication protocol.

[0046] S2, Data Storage Optimization

[0047] The CSV file is transferred to the database system for storage. The database system will store the data in the corresponding database table according to the batch number or equipment source of each batch of data. In order to ensure the efficiency of data storage, in the database, if the table of the current batch data does not exist yet, the system will call the batch table creation module to automatically generate a new data table. The generated new table will be bound to the batch number, and the mapping relationship between the batch number and the table name will enable fast retrieval and efficient management of the stored data. When querying data, the system can quickly locate the table where the batch data is located, and then retrieve detailed wafer inspection data.

[0048] S3. Data analysis

[0049] In order to parse the CSV files generated by different devices, the system calls the data parsing module. Each detection device will have its own unique detection data format and parsing rules. Therefore, the system configures a corresponding parsing package for each device, which contains the specific data format, identification code parsing rules and data direction adjustment parameters of the device. The parsing package will be dynamically allocated according to the model and source of the device, and the system will automatically select the parsing package suitable for the device for data parsing. During the parsing process, the identification codes generated by different devices will be standardized, and the data direction will be adjusted according to the unified standards of the system to ensure that the format and direction of all data are consistent, which is convenient for subsequent processing and analysis.

[0050] S4, Identification code conversion

[0051] After the data is parsed, the system standardizes the identification codes generated by each device through a unified conversion rule. To achieve this process, the system establishes a mapping table between the device and the system standard identification code. The mapping table records the correspondence between different types of identification codes of each device and the system's internal standard identification code. The system calls the internal conversion module and uses the mapping table to convert the parsed identification code into a unified standard identification code format, ensuring that the data of all devices can be shared and processed in the system. This step enables the device data from different sources to be uniformly identified and processed after conversion, improving the compatibility of the system.

[0052] S5. Generate yield map

[0053] The system extracts the inspection data of the same batch of wafers from the database and calls the yield map generation module for processing. The module first calculates the pass rate of each die on different wafers. The pass rate is calculated by counting the number of dies that pass the inspection at a certain coordinate point and dividing it by the total number of inspected dies at that coordinate point. Based on the calculated pass rate, the system generates a heat map to show the yield distribution of each coordinate point. The heat map uses a color gradient to show the change of yield from low to high. The color range is from red (low yield) to green (high yield), which intuitively shows the yield situation in different areas on the wafer. This provides process engineers with efficient tools for analyzing inspection data and identifying problem areas in production.

[0054] S6. Defective product marking

[0055] After generating the yield map, the system automatically identifies defective products through the data in the yield map. Specifically, the system will mark the detected defective products, record the specific location information of each defective die (including coordinates and batch number), test results (such as failure reasons), and defective types. Based on this marking information, the system generates a defective product processing report, which lists in detail the number, location information, batch number, and reasons for defective products, providing data support for subsequent production adjustments and defective product processing. The report is automatically generated and saved in the system, and users can view and export it at any time for analysis and decision-making.

[0056] S7. Data backup and export

[0057] In order to ensure the security and integrity of data, the system provides an automatic backup function. Users can set the backup cycle through the system. The system calls the automatic backup module according to the set cycle to export the historical data in the database as a CSV file. The exported file will be stored in the specified external storage path. The backup file is processed by an encryption algorithm during storage to ensure the security of the data. Users can generate data export reports as needed, and the exported data can be re-imported into the system for further data analysis or integration with other systems. This step ensures the long-term safe storage of data and enables data recovery or cross-system use when needed.

[0058] Detailed description

[0059] S2 data storage optimization: In order to improve storage efficiency, the system automatically generates a database table corresponding to the batch number by calling the batch table creation module, and realizes fast data retrieval and management through the binding relationship between the batch number and the table name. This can avoid confusion in the database table, ensure that data from different batches will not be cross-stored, and facilitate subsequent data processing and analysis.

[0060] S3 data analysis: Data analysis is an important part of the system. Through the dynamic adjustment of the analysis package management system, it ensures that the data of different devices can be processed in a standardized manner. The analysis package contains the data structure, analysis rules and direction adjustment parameters of each device. The system automatically selects the analysis package and performs the analysis operation according to the model and source of the device to ensure data consistency.

[0061] S4 ID conversion: Through the mapping table of device and system standard IDs, the system can unify the IDs of different devices. This step is crucial for data compatibility, ensuring that device data from different sources can be seamlessly connected and processed in the system.

[0062] S5 yield map generation: The yield map is an important tool for process engineers to analyze production data. The heat map displays the yield level of different areas of the wafer through color gradients, which can help engineers quickly locate problem areas in production and improve the efficiency of process adjustment.

[0063] S6 Defective Product Marking: The system automatically identifies defective products and generates defective product processing reports to ensure that every defective product in production is recorded and processed. Defective product reports can provide an important basis for process improvement.

[0064] S7 data backup and export: The automatic data backup function ensures the long-term preservation of data in the system and improves data security through encryption algorithms. Users can export and restore data as needed for data analysis or docking with other systems.

[0065] Embodiment 2:

[0066] Reference Figure 2 In a second embodiment of the present invention, the present invention provides a defective product control system based on an E-Mapping system, the system comprising:

[0067] 1. Data acquisition module

[0068] The data acquisition module is used to collect the detection data of each die on each wafer from the detection equipment. The detection equipment may include optical detection equipment, electronic detection equipment, etc., which can accurately detect the position, status and identification code of each die on the wafer. The data acquisition module communicates with the detection equipment through the device interface to obtain real-time detection data. After the collection is completed, the data acquisition module converts the detected data into a standard CSV format file, which contains the detection position (i.e., XY coordinates) of each die, the detection status (such as "pass" or "fail"), and the identification code generated by the device. The CSV file will also attach relevant batch number information to ensure that subsequent processing can be classified and managed according to batches.

[0069] 2. Data storage module

[0070] The data storage module is responsible for storing the data in the CSV file into the corresponding data table of the database according to the batch number or device source. This module can automatically select the appropriate database table for data writing according to the batch number or device source of the data. When a new batch of data is detected, the system automatically creates a new data table by calling the table generation submodule and binds the table to the batch number. The table generation submodule uses the database query mechanism to determine whether the current batch data table exists. If not, a new data table is dynamically created to ensure that the data is reasonably classified and stored. Through this sub-table storage method, the system can greatly improve the efficiency of data retrieval and processing.

[0071] 3. Data analysis module

[0072] The data parsing module is responsible for parsing the data in the CSV files generated by different detection devices. Since the detection data formats and parsing rules of different devices are different, the system configures corresponding parsing packages for each device. The data parsing module contains a parsing package management submodule, which is used to manage and select parsing packages for different devices. Each parsing package contains the data structure, identification code parsing rules, and data direction adjustment parameters for a specific device. During parsing, the system dynamically selects the corresponding parsing package based on the device model and source to ensure that the data can be shared and interoperable in the system after being standardized. The parsing package management submodule can dynamically adjust the parsing rules according to user needs or device updates to adapt to the data generated by different devices.

[0073] 4. Identification code conversion module

[0074] The identification code conversion module is used to uniformly convert the identification codes generated by different devices through the system standard identification code. This module performs the identification code conversion operation by calling a mapping table between a device and a system standard identification code. The mapping table records the correspondence between the different identification codes of each device and the system standard identification code. During the parsing process, the system calls the identification code conversion module to convert the device identification code of each die into a standard identification code format to ensure that the data generated by all detection devices can be stored and processed in a unified standard format. This step greatly improves the compatibility of the system and ensures that subsequent processes can share data seamlessly.

[0075] 5. Yield map generation module

[0076] The yield map generation module generates a yield map for each wafer using the test data stored in the database. The module first extracts the test data of each die on the same batch of wafers from the database and calculates the pass rate of each die. The pass rate refers to the ratio of the number of dies that pass the test to the total number of dies tested at that coordinate point. The yield map generation module generates a heat map based on the calculated pass rate to display the yield distribution of each coordinate point. In order to intuitively show the difference in yield, the heat map is displayed in a color gradient, ranging from red (low yield) to green (high yield). Through this graphical display, users can clearly see the yield levels of different areas of the wafer, making it easier for engineers to quickly locate bad areas and make process optimization adjustments.

[0077] 6. Defective product marking module

[0078] The defective product marking module is used to automatically mark defective products in the test results. The module extracts the information of the unqualified dies from the yield map generation module or the parsed data, and marks this information as defective products. The module records the specific location information (including coordinates and batch number), test results and defect type of each defective product. Based on these data, the system automatically generates a defective product processing report, which includes detailed information of the defective products, such as the cause of the defect, the specific location, the batch number and the classification statistics of the defective products. This report provides a basis for subsequent process improvement, equipment maintenance and quality control. The report can also be exported as a standard format file for users to further analyze or archive.

[0079] 7.Data backup and export module

[0080] The data backup and export module is used to ensure the security and integrity of the data stored in the system. This module allows users to set an automatic backup cycle, and the system automatically exports the historical data in the database as a CSV file according to the set cycle. The exported file will be stored in the specified external storage path, and the system will encrypt the backup file through an encryption algorithm to ensure data security. Users can generate data backup reports through the data export interface as needed, and re-import the backup file when necessary to perform data recovery or analysis. This module not only supports long-term data preservation, but also provides a secure storage mechanism to ensure the security of data in long-term storage.

[0081] The beneficial effects of the above embodiment 1 and embodiment 2 are as follows:

[0082] 1. A large amount of data is inserted at a time, and storage is slow: Use the sqllar tool to convert the files generated by the device or the reported data into a fixed-format csv file and directly import it into the database, which can significantly improve storage efficiency.

[0083] 2. The amount of data is large, and the database table is under great pressure: When storing data, it is stored in different tables according to the data source. For example, according to the batch distinction, after parsing the data, it is first determined whether the data table of the batch to which this wafer belongs exists. If the data table does not exist, it is automatically generated first, and the binding relationship between the batch number and the table name is recorded, and then the detailed information of the wafer is inserted. When querying, first query the data table name of the batch to which the wafer belongs, and then query the detailed information of the wafer in the corresponding data table.

[0084] 3. Scalability: Because the devices come from different manufacturers, the parsing rules are naturally completely different, so the scalability requirements for the system are very high. In order to facilitate system expansion, we have refined the parsing function into separate modules and formed separate parsing packages. At the same time, we provide data modeling. Users can configure it on the web page and specify that the corresponding device only uses the corresponding parsing package. When expanding in the future, you only need to develop the corresponding parsing package for the newly added device, and then configure it on the web page, without modifying the system code itself.

[0085] 4. Unified modeling: Different equipment manufacturers have different definitions of identification codes (binCode), which results in the data generated in the previous process being unable to be applied to the next process. In order to achieve data sharing, our system supports the establishment of a set of unified rules to convert different identification codes (binCode) of different devices into our unified identification code (binCode). At the same time, the conversion rules and modeling support user customization on the web page.

[0086] For example:

[0087] For device A, 0 represents no operation, 1 represents pass, and 2 represents fail. The map direction in the generated measurement file is upward.

[0088] For device B, X represents not working, A represents passing, and B represents failing. The map direction in the generated measurement file is leftward.

[0089] For device C, * represents not working, √ represents passing, and × represents failing. The map direction in the generated measurement file is rightward.

[0090] At this point, we first establish a set of unified rules: X represents unsuccessful operation, A represents passed, B represents failed, and the map direction is downward; then set conversion rules for each device:

[0091] Device A: Convert 0 to X, 1 to A, 2 to B, and rotate the map to the downward direction;

[0092] Device B: No conversion, but the map rotates to the downward direction;

[0093] Device C: Convert * to X, √ to A, × to B, and rotate the map to the downward direction;

[0094] In this way, the data collected in the system will be unified, and data sharing can be achieved between different devices.

[0095] 5. Yield map: The system supports overlaying several wafers from the same batch to obtain a yield map, which can intuitively show the yield of each coordinate point of the wafer. At the same time, gradient colors are used to represent the yield range from 0% to 100%. In this way, the yield map shows the effect of a heat map, which can intuitively show which areas of the wafer have a higher yield, making it easier for process engineers to analyze and adjust equipment parameters.

[0096] The specific method of calculating the yield map is as follows: retrieve the detailed information of each wafer from the database table, calculate the number of wafers that have passed the measurement at each coordinate point, and then divide the number of wafers that have passed by the total number of wafers to get the yield of each point. Calculate the RGB value of the gradient color based on the yield, and get the color that needs to be rendered at each point. Finally, combine the yield and color information of all points together to get the yield map.

[0097] 6. Import and export: The system supports automatic monitoring of the path of the measurement file generated by the device for parsing, and also supports manual uploading from the web page for parsing. It also supports the device reporting to EAP, and then EAP reporting to the system for storage. At the same time, the system supports exporting data from the database into files. Based on point 4, the system can export the map generated by the previous process into files for the next process to use, so that the next process can selectively process and directly skip those scrapped dies, thereby saving material costs.

[0098] 7. Automatic backup: Because the amount of data generated is relatively large, even if the tables are divided, the pressure on the entire database will increase day by day, and eventually it will be overwhelmed. However, in fact, some data that is relatively old, or when the wafers are processed into finished products and sold, the data stored in the database can actually be backed up and deleted. In order to reduce the user's long-term manual database backup work, our system supports the configuration of automatic backup cycles on the front end. When the system expires, the data in the database will be automatically exported into files and saved to the corresponding path. If you need to use it later, just take out the file and manually import it into the system.

[0099] Embodiment 3

[0100] The third embodiment of the present invention is based on the same inventive concept. The present invention proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the defective product control method based on the E-Mapping system of the above embodiment are implemented.

[0101] Embodiment 4

[0102] The fourth embodiment of the present invention is based on the same inventive concept. The present invention proposes a terminal, which includes: a processor and a memory; the processor and the memory communicate with each other; the memory is used to store instructions; the processor is used to execute the instructions in the memory, and execute the defective product control method based on the E-Mapping system of the above embodiment.

[0103] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0104] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A defective product control method based on E-Mapping system, characterized in that: The following steps are involved: S1. Data acquisition and processing: Obtain the detection data of each die on each wafer through the detection equipment, and convert the data into a CSV format file; S2. Data storage optimization: The CSV format file is transmitted to the database system, and the database system stores the data in the corresponding table according to the batch number or the source of the equipment. If there is no corresponding batch data table, the system automatically generates a new data table by calling the batch table creation module and binds the batch number to the table name. S3, data analysis: by calling the analysis package, the CSV format file data of different devices is analyzed, where each analysis package contains a set of analysis rules for a specific device, and the corresponding analysis package is automatically selected for analysis according to the device type; S4, identification code conversion: the parsed identification code is standardized through a unified conversion rule; S5. Generate yield map: Extract the test data of the same batch of wafers from the database, call the yield map generation module, calculate the pass rate of each die on different wafers; generate a heat map to show the yield distribution of each coordinate point, and use color gradient to show the high and low yields; S6. Defective product marking: Automatically identify defective products through the data in the yield map, and generate a defective product processing report based on the detected defective product location and related information; S7. Data backup and export: Set the automatic backup cycle, and regularly export the historical data in the database as CSV files through the automatic backup module. The backup files are stored in the specified external storage path, and a data export report is generated according to user needs.

2. The defective product control method based on the E-Mapping system according to claim 1 is characterized in that: In the step S1, the detection data includes the position, detection result and identification code of the die, and the CSV file includes the detection position, detection status and batch number information of each die; In the step S3, the parsing rules include interpretation of the identification code, adjustment of the data direction and standardization of the format; In the step S4, the conversion rule includes mapping specific identification codes used by different devices into a system standard identification code format; In the step S5, the pass rate is obtained by dividing the number of dies that pass the test by the total number of dies; In the step S6, the report includes the specific location of the defective product, the test results, the defect type and the relevant batch number.

3. The defective product control method based on the E-Mapping system according to claim 1 is characterized in that: The data storage optimization in step S2 includes: by querying the batch number table records in the database, the system calls the table generation module to automatically generate a new table when storing new data, and realizes fast retrieval of data through the mapping relationship between the batch number and the table name; The data analysis in the S3 step includes: configuring a corresponding analysis package for each device, the analysis package includes the device's specific data format, identification code analysis rules and data direction adjustment parameters, and the system automatically selects the corresponding analysis package according to the device model and source and analyzes and standardizes the data.

4. The defective product control method based on the E-Mapping system according to claim 1 is characterized in that: The identification code conversion in step S4 includes: establishing a mapping table between device and system standard identification codes, and uniformly converting the identification codes of different devices through a system internal conversion module, so that data generated by all devices can be processed in accordance with the standard identification code format.

5. The defective product control method based on the E-Mapping system according to claim 1 is characterized in that: The yield map generation in the S5 step includes: extracting the detection data of each die from the database, calculating the pass rate of each coordinate point through the heat map generation module, and generating a heat map showing the yield distribution through a color gradient effect. The color change range in the heat map is from red to green, which intuitively shows the yield situation of each area.

6. The defective product control method based on the E-Mapping system according to claim 1 is characterized in that: The defective product marking step in step S6 includes: marking each unqualified die through the parsed data, recording the specific location information, batch number and defect reason of the defective product, and automatically generating a defective product report containing defective product statistical information.

7. The defective product control method based on the E-Mapping system according to claim 1 is characterized in that: The data backup and export in step S7 includes: setting an automatic backup cycle, exporting data into CSV format by calling the automatic backup module, and storing it in the specified backup path; the backup file is securely stored through an encryption algorithm, and the user can re-import the backup file through the export interface for data analysis as needed.

8. A defective product control system based on E-Mapping system, characterized in that: The defective product control method based on the E-Mapping system according to any one of claims 1 to 7, wherein the system comprises: Data acquisition module: used to collect the inspection data of each die on each wafer from the inspection equipment and convert the data into a standard CSV format file; Data storage module: storing the data in the CSV file into the corresponding data table of the database according to the batch number or the source of the equipment; the data storage module includes a table generation submodule for automatically creating a new data table when a new batch is detected and binding the batch number to the table name; Data parsing module: used to parse the data in the CSV file according to the parsing rules of different devices. The data parsing module includes a parsing package management submodule, which is used to configure corresponding parsing packages for different devices and dynamically adjust the parsing rules to perform standardized processing of data; Identification code conversion module: used to convert identification codes generated by different devices into standard identification codes of the system through a mapping table; Yield map generation module: used to generate a yield map based on the test data stored in the database. The module calculates the pass rate of each die and displays the yield distribution of each coordinate point in the form of a color gradient heat map; Defective product marking module: used to automatically mark defective products in the test results and generate defective product processing reports; Data backup and export module: used to set the automatic backup cycle, regularly export the data in the database as CSV files and store them in encrypted form. Users can generate backup reports through the export interface and re-import them into the system for data analysis.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the defective product control method based on the E-Mapping system as described in any one of claims 1 to 7 is implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the defective product control method based on the E-Mapping system according to any one of claims 1 to 7 is implemented.

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