Chip detection data processing method and device, computer equipment and computer readable storage medium

Abstract

This application relates to a chip testing data processing method, apparatus, computer device, and computer-readable storage medium. The method includes: acquiring the raw test results output by an optical testing device for performance testing of a target chip; obtaining test result labels corresponding to multiple test points on the target chip and the original coordinates of each test point in the raw test results; generating and displaying a test result preview file corresponding to the target chip; acquiring view adjustment parameters for the test result preview file; adjusting the original coordinates according to the view adjustment parameters to obtain the target coordinates of each test point in the display interface of the target device; and combining the target coordinates and test result labels to obtain a target test result file recognizable by the target device. This method can improve the efficiency and accuracy of chip testing data conversion.

Description

Technical Field

[0001] This application relates to the field of chip testing technology, and in particular to a chip testing data processing method, apparatus, computer equipment, and computer-readable storage medium. Background Technology

[0002] With the continuous advancement of semiconductor manufacturing processes, chip feature sizes are shrinking while wafer sizes are increasing, placing higher demands on quality inspection during chip manufacturing. In the semiconductor manufacturing process, Automated Optical Inspection (AOI) technology is widely used in wafer inspection due to its non-contact, high-efficiency, and highly repeatable characteristics, enabling the rapid detection of physical defects on the chip surface. AOI equipment, through high-resolution optical imaging and image recognition algorithms, can automatically detect defects in individual chip units on the wafer and output inspection result files containing information such as defect location and type.

[0003] The inspection result files output by AOI equipment can be in unstructured text formats defined by the equipment manufacturer, and different manufacturers have different file format specifications. In related technologies, the current method of manually collecting and analyzing these unstructured text inspection result data by engineers suffers from low efficiency and accuracy. Summary of the Invention

[0004] Therefore, it is necessary to provide a chip detection data processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can improve the processing efficiency and accuracy of chip detection result files, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a chip detection data processing method, including:

[0006] Obtain the raw test results output by the optical inspection equipment for performance testing of the target chip;

[0007] The original detection results are parsed to obtain the detection result labels corresponding to multiple detection points on the target chip and the original coordinates of each detection point in the original detection results;

[0008] Based on the detection result labels and the original coordinates, generate and display a preview file of the detection results corresponding to the target chip;

[0009] Obtain view adjustment parameters for the test result preview file; the view adjustment parameters are used to adjust the test result preview file to fit the display interface of the target device; the target device is used to perform performance retesting on the target point among the multiple test points;

[0010] The original coordinates are adjusted according to the view adjustment parameters to obtain the target coordinates of each detection point in the display interface of the target device;

[0011] According to the file format standard corresponding to the target device, the target coordinates and the detection result labels are combined to obtain a target detection result file that can be recognized by the target device.

[0012] The target detection result file is sent to the target device so that the target device can locate the target point based on the target detection result file.

[0013] Secondly, this application also provides a chip detection data processing apparatus, comprising:

[0014] The first acquisition module is used to acquire the raw test results output by the optical inspection equipment for performance testing of the target chip;

[0015] The parsing module is used to parse the original detection results to obtain the detection result labels corresponding to multiple detection points on the target chip and the original coordinates of each detection point in the original detection results;

[0016] The preview module is used to generate and display a preview file of the detection results corresponding to the target chip based on the detection result labels and the original coordinates.

[0017] The second acquisition module is used to acquire view adjustment parameters for the detection result preview file; the view adjustment parameters are used to adjust the detection result preview file to fit the display interface of the target device; the target device is used to perform performance retesting on the target point among the multiple detection points;

[0018] The adjustment module is used to adjust the original coordinates according to the view adjustment parameters to obtain the target coordinates of each detection point in the display interface of the target device;

[0019] The combination module is used to combine the target coordinates and the detection result labels according to the file format standard corresponding to the target device to obtain a target detection result file that can be recognized by the target device.

[0020] The sending module is used to send the target detection result file to the target device, so that the target device can locate the target point based on the target detection result file.

[0021] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps included in any of the foregoing method embodiments.

[0022] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps included in any of the foregoing method embodiments.

[0023] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps included in any of the foregoing method embodiments.

[0024] The aforementioned chip testing data processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product, through automated parsing and coordinate transformation, replace traditional manual recording and coordinate conversion methods, solving the problem of low efficiency in manually processing massive amounts of point data. Even when dealing with tens of thousands or even hundreds of thousands of chips, this method can quickly complete parsing, conversion, and export, significantly shortening the file conversion processing cycle and improving production efficiency. By generating and displaying a preview file of the test results, the distribution of points after conversion is intuitively shown, solving the problem of high error rates in manual processing. The preview file graphically presents the spatial layout of good and bad points, facilitating verification before formal export and avoiding positioning errors of the probe testing equipment due to coordinate transformation errors, thereby improving the accuracy of retest results. By obtaining view adjustment parameters and adjusting the original coordinates according to these parameters, the technical challenge of recalculating coordinates for different product types of chips is solved. The view adjustment parameters can flexibly adapt to the step parameters, origin position, and coordinate system direction differences of different target devices, eliminating the need for manual recalculation and reducing technical difficulty and error risk. By sending the target detection result file to the target device, the target device, such as the probe testing equipment, can automatically locate the target point for performance retesting based on the target coordinates and detection result labels in the file. This achieves automated data flow from initial optical screening to precise electrical testing, reducing manual labor intensity and allowing engineers to focus on higher value-added analysis and decision-making. In summary, this embodiment effectively overcomes the problems of low efficiency, high error rate, high labor intensity, and difficulty in flexibly adapting to different product types in traditional manual processing methods, realizing automation, visualization, and intelligence in chip testing data processing. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is an application environment diagram of a chip detection data processing method in one embodiment;

[0027] Figure 2 This is a flowchart illustrating a chip detection data processing method in one embodiment;

[0028] Figure 3 This is a structural block diagram of a chip detection data processing device in one embodiment;

[0029] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0031] Before describing the embodiments of this application, the relevant technologies and their existing problems will be further explained:

[0032] In semiconductor manufacturing processes, Automated Optical Inspection (AOI) equipment is widely used in wafer inspection. It uses high-resolution cameras to photograph each die on the wafer, automatically detecting defects on the die surface, such as scratches, stains, foreign objects, and circuit defects, and recording the location coordinates and type of each defect. However, AOI equipment produces files in unstructured text format, and different manufacturers (such as Camtak) have their own proprietary file format specifications, making them difficult for downstream equipment to directly recognize.

[0033] In the chip probing (CP) stage, the CP probe station needs to perform electrical performance tests on each chip on the wafer. The CP probe station needs to read files in a specific format to identify which chip locations are defective, allowing it to skip or mark these defective points during testing and perform detailed retesting for subsequent packaging processes. In related technologies, engineers manually collect chip-related data for preview and analysis, and then submit the results to the customer for review. This is not only inefficient and labor-intensive, but also difficult to handle the massive amounts of data in terms of file format conversion, and has a high error rate. Furthermore, the inconsistent step sizes of AOI equipment for different product types further increase the technical difficulty of manual processing.

[0034] Therefore, a chip testing data processing method that can be executed efficiently and automatically is needed to solve the technical problems of low efficiency, high error rate and difficulty in adapting to the step size differences of different products in the traditional method.

[0035] In related technologies, engineers can manually handle the aforementioned file format conversion tasks. Specifically, engineers need to examine each AOI device's output test result file, manually record the coordinate information of any defective points, and then convert this coordinate information into a format recognizable by the probe testing equipment based on experience. When adapting to chips of different product types, due to the different size specifications of the chips, the step distance parameter of the probe testing equipment (i.e., the physical distance covered by each probe movement) also needs to be adjusted accordingly, requiring engineers to recalculate the coordinates.

[0036] However, the aforementioned manual processing method has at least the following technical problems: First, it is inefficient. When the number of chips on a wafer reaches tens of thousands or even hundreds of thousands, it is almost impossible to manually process massive amounts of data point by point. The processing cycle is long, which seriously affects the production schedule. Second, the error rate is high. In the process of manual recording and coordinate transformation, problems such as copying errors and calculation errors are prone to occur, causing the probe testing equipment to locate the wrong position, which in turn affects the accuracy of the retest results. Third, the manual labor intensity is high. Engineers need to concentrate on repetitive operations for a long time, which is not only easy to get tired, but also consumes the energy that should be used for higher value-added work. Fourth, for chips of different product types, coordinate transformation needs to be recalculated when the step size parameter changes, which further increases the technical difficulty and error risk of manual processing.

[0037] Therefore, how to achieve efficient and accurate conversion of AOI detection results into probe testing equipment input files, and avoid the inefficiency and error risks caused by manual processing, has become a technical problem that urgently needs to be solved by those skilled in the art.

[0038] It should be noted that the terms "first," "second," etc., used in this application may be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application includes two or more. The term "and / or" used in this application includes one of the embodiments, or any combination of multiple embodiments.

[0039] The chip detection data processing method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located on the cloud or other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0040] For example, the chip inspection data processing method provided in this application embodiment can be applied to a Manufacturing Execution System (MES). The MES system is communicatively connected to both an AOI (Automated Optical Inspection) device and a CP (Probe Center) probe station. The AOI device outputs inspection result files, the MES system parses, converts, and previews these files, and the CP probe station receives the converted target inspection result files and uses them to locate and test the chip. The MES system can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0041] In one exemplary embodiment, such as Figure 2 As shown, a chip detection data processing method is provided, which can be applied to... Figure 1 Taking terminal 102 or server 104 as an example, the following steps are included:

[0042] Step 202: Obtain the raw test results output by the optical inspection equipment for performance testing of the target chip.

[0043] Optical inspection equipment includes devices that use non-contact optical imaging technology (such as automated optical inspection (AOI) equipment) to quickly and comprehensively scan the surface of chips, detecting defects at the physical level. The target chip refers to a single chip product requiring inspection data processing; this chip product can be an uncut, unpackaged chip unit (die) on a wafer. Different product types of chips can have different dimensions. The raw inspection result is a data file output by the equipment after inspection, recording the raw information of each point on the target chip (i.e., each independent chip unit). This file can be in a manufacturer-defined unstructured text format, which cannot be directly recognized by downstream probe testing equipment. For example, the raw inspection result can be a text file output by an AOI device, containing information such as bad pixel coordinates and defect types.

[0044] Understandably, the original inspection result file may be in unstructured text format. For example, the original inspection result file records the coordinates of bad spots (e.g., "37225.6380887552" is the X coordinate, "-30175.8032751516" is the Y coordinate, both in micrometers) and other auxiliary information. This original inspection result file is obtained from the AOI device via a file transfer protocol (such as FTP) or read from a shared storage path.

[0045] This embodiment acquires the raw detection results output by the optical inspection equipment, transforms the wafer inspection data in the physical world into digital data that can be processed by the algorithm, and provides a unified input benchmark for all subsequent calculation steps.

[0046] Step 204: Analyze the original detection results to obtain the detection result labels corresponding to multiple detection points on the target chip and the original coordinates of each detection point in the original detection results.

[0047] In this system, each detection point corresponds to a specific chip unit on the target chip, and each chip unit corresponds to an independent detection location. The detection result label is an identifier characterizing the quality of that point; for example, it can be a binary label ("good point" or "bad point"). The raw coordinates are the positional expression of the detection point in the coordinate system of the optical detection device itself. These coordinates can be based on physical distance (such as micrometer values) or on indexed logical coordinates, depending on the device output.

[0048] In this embodiment, the original detection result file can be read and the file format type identified. For Camtak's AOI devices, the file format has a specific field arrangement pattern. According to preset parsing rules, the set of bad pixel coordinates (DefectList) is extracted from the file. The specific parsing process may include locating and extracting the lines recording bad pixel information from the file, and then obtaining the original coordinates of the bad pixels according to preset rules (such as using spaces to separate the 10th and 11th fields). At the same time, by analyzing the distribution range of all bad pixel coordinates (such as the minimum / maximum values ​​of the X and Y axes), the complete coordinate space of all detection points (including unrecorded good points) on the entire target chip can be deduced, and the point with the minimum coordinate value is determined as the logical origin of the coordinate system.

[0049] Step 206: Generate and display a preview file of the detection results corresponding to the target chip based on the detection result labels and the original coordinates.

[0050] A test result preview file is an electronic file used to visually display the distribution of test points on a target chip. This file graphically presents the spatial layout of good and bad points, facilitating intuitive viewing, verification, and adjustment. Specifically, the test result preview file is in Excel format. For example, a spreadsheet (like an Excel file) can be dynamically created based on the coordinate range of all points obtained from parsing (e.g., X: -9 to 8, Y: -9 to 4). The row and column dimensions of the spreadsheet correspond to the coordinate range. Then, based on the original coordinates and test result labels of each point, preset markers are entered into the corresponding cells of the spreadsheet (e.g., "1" for good points, "4" for bad points, and "." for no points). Additionally, statistical information (such as total number of points and number of bad points) can be attached to the preview file, ultimately generating a visual Excel preview file for engineers to review.

[0051] Specifically, the process of generating the detection result preview file includes the following: Based on the distribution range of the original coordinates of all detection points, the view size information of the detection result preview file is determined. Specifically, the length of the view is determined by adding 1 to the difference between the maximum and minimum values ​​of the original coordinates on the X-axis, and the width of the view is determined by adding 1 to the difference between the maximum and minimum values ​​of the original coordinates on the Y-axis. For example, if the X-coordinate range is -9 to 8 (the difference between the maximum and minimum values ​​is 17), then the view length is 18; if the Y-coordinate range is -9 to 4 (the difference between the maximum and minimum values ​​is 13), then the view width is 14. Thus, an 18×14 target matrix is ​​constructed.

[0052] Next, a reference point is selected from multiple detection points based on the extreme values ​​of the original coordinate distribution. For example, the detection point with the smallest X-coordinate and the smallest Y-coordinate can be selected as the reference point, which is the point corresponding to the origin (-9, -9) of the coordinate system mentioned above. Using this reference point as the base point, a target view is constructed according to the view size information, and the reference point is rendered into the target view accordingly. Then, based on the relative positional relationship of the original coordinates between the other detection points and the reference point, the other detection points are rendered into the target view accordingly. Specifically, for a detection point with original coordinates (x, y), its logical coordinates relative to the reference point (-9, -9) are calculated as: (x - (-9), y - (-9)), i.e., (x+9, y+9). For example, if the source file contains a point (-8, -5), the converted logical coordinates are (1, 4). The converted logical coordinates are stored as a target point set.

[0053] Then, based on the detection result labels of each detection point, the corresponding detection result labels are rendered in the target view. The rendering rules can include the following: starting from the first point in the first row of the target matrix, if the current point is not in the target point set, it is marked with the first label (e.g., a period "."); if the current point is in the target point set and the detection result label indicates a good point, it is marked with the second label (e.g., the number "1"); if the current point is in the target point set and the detection result label indicates a bad point, it is marked with the third label (e.g., the number "4"). The method for determining good and bad points is: if the coordinates of the detection point exist in DefectList (the set of bad point coordinates), it is determined to be a bad point; if it does not exist in DefectList, it is determined to be a good point.

[0054] Optionally, statistical information for the detection points displayed in the target view can be added to the detection result preview file. This statistical information should include at least: generation time (e.g., "2025 / 12 / 9 15:30:25"), display mode (e.g., "full display"), preview size (e.g., "18×17 cells"), scaling ratio (e.g., "1:1 full display"), matrix range (e.g., "18×17 cells"), and total number of points (e.g., "274"). After rendering, the generated Excel file is saved to a specified path and displayed through an interactive interface. By generating and displaying the preview file, the distribution of defective points on the target chip can be visually displayed, eliminating the need for manual visual localization and drawing of result atlases, thus significantly improving data verification efficiency.

[0055] Step 208: Obtain view adjustment parameters for the test result preview file; the view adjustment parameters are used to adjust the test result preview file to fit the display interface of the target device; the target device is used to perform performance retesting on the target point among the multiple test points.

[0056] In the semiconductor manufacturing process, the quality inspection of chips on wafers (dies) can be divided into several stages: a rapid, non-contact, comprehensive initial screening is performed using optical inspection equipment to efficiently detect physical defects on the chip surface (such as scratches and blemishes). Then, probe testing equipment is used to perform precise retesting of the chip's electrical performance to verify its functionality.

[0057] Among them, optical inspection equipment (initial screening equipment) performs broad-spectrum, rapid initial screening. Its coordinate system is based on the equipment's own physical measurements and may not be consistent with the actual physical layout of the chip or the logic layout of downstream devices. Target equipment (such as probe test stations) performs high-precision, high-granularity performance retesting. In order to perform more accurate electrical performance analysis on the "bad pixels" identified in the initial screening, or to retest specific points, the target equipment needs a coordinate system based on its own physical step distance (i.e., the physical distance covered by each probe step) and logical addressing method.

[0058] Due to significant differences in detection principles, accuracy, and granularity between optical inspection and electrical performance retesting, their data formats and coordinate systems are often incompatible. Optical inspection equipment (such as AOI) can produce raw files in a manufacturer-defined, unstructured text format, with its coordinate system based on the equipment's physical coordinate system. In contrast, probe testing equipment (such as CP probe stations) requires a structured file based on logical row and column indexes to control the precise movement of probes in a specific order. In related technologies, engineers manually read reports from optical inspection equipment, manually record the coordinates of defective points, and then convert them to the format required by the probe testing equipment based on experience. This process is not only inefficient and error-prone, but also, when encountering chips of different specifications, the step size (i.e., the distance the probe covers in each movement) of the probe testing equipment varies, requiring complex coordinate conversions to further increase the technical difficulty and risk of errors.

[0059] Due to the inherent differences in detection accuracy, granularity, and coordinate system between optical inspection equipment and target equipment, without coordinate transformation between the two, the coordinates output by the optical inspection equipment (e.g., "There is a defective pixel at wafer physical coordinates (37225.6, -30175.8) micrometers") may be difficult for the target equipment to understand. For example, the target equipment may find it difficult to move the probe directly based on these physical coordinates, as it requires logical instructions such as "There is a defective pixel at the position of row 5, column -5". Therefore, to achieve this set of parameters for transformation from "source coordinate system" to "target coordinate system", this embodiment introduces view adjustment parameters to define how to translate, rotate, scale, or flip the original coordinates to match them with relevant parameters of the target equipment, such as step size, origin position, and addressing direction.

[0060] View adjustment parameters refer to parameters used to adjust the coordinates of points in the inspection result preview file. The purpose is to ensure that the converted coordinates are compatible with the coordinate system and display interface of the target device (such as a CP probe station). The target device is the equipment used to retest the performance of the inspection points, specifically the CP probe station. The CP probe station uses microneedles on a precision probe card to precisely contact the pads of the chip on the wafer, connecting to an external test equipment (ATE) to perform various functional tests on the chip. View adjustment parameters may include coordinate offset parameters and / or view flip parameters. Coordinate offset parameters include X-axis and Y-axis offsets, used to correct the origin difference between the AOI device coordinate system and the CP probe station coordinate system. View flip parameters include slope and intercept, used to construct the linear equation y=kx+b to perform symmetrical coordinate flipping, adapting to the coordinate system orientation differences of different product types.

[0061] Optionally, view adjustment parameters can be obtained through a pre-defined interactive interface integrated into the MES system. This interface includes multiple interactive controls, such as: a source file path input box, an X offset input box, a Y offset input box, a left / right flip control (including flip axis parameter input), a right / left flip control (including Y-axis parameter input), and other flip controls (including slope k and intercept b input). Users can input or adjust view adjustment parameters through these interactive controls. The view adjustment parameters are determined based on the user's actions on the interactive controls. It should be noted that obtaining view adjustment parameters is not limited to manual user input; they can also be automatically determined through a sampling trial-and-error mechanism or a knowledge solidification and reuse mechanism.

[0062] Step 210: Adjust the original coordinates according to the view adjustment parameters to obtain the target coordinates of each detection point in the display interface of the target device.

[0063] Target coordinates are the new coordinates of the original detection point in the target device's own logical coordinate system after being transformed by view adjustment parameters (such as translation and flipping). These coordinates can be directly recognized and executed by the target device. Taking a CP probe station as an example, the CP probe station can use logical coordinates (row and column indices) instead of physical coordinates for positioning. For example, with the wafer center as the origin (0,0) and upward / right as the positive direction, each chip corresponds to an integer coordinate pair (row index, column index).

[0064] Specifically, when the view adjustment parameters include coordinate offset parameters, the original coordinates of each detection point are translated and adjusted based on the X-axis and Y-axis offsets in the offset parameters. For example, if the original coordinates are (x, y), the X-axis offset is dx, and the Y-axis offset is dy, then the adjusted coordinates are (x+dx, y+dy). Translation adjustment is used to correct the origin offset between the AOI device coordinate system and the CP probe station coordinate system.

[0065] Optionally, when the view adjustment parameters include view flip parameters, a symmetry axis equation y=kx+b is constructed based on the slope k and intercept b in the flip parameters. Then, the original coordinates of each detection point are symmetrically flipped according to this symmetry axis equation. Symmetrical flipping is used to adapt to the coordinate system orientation differences of different product types. For example, when the coordinate orientation of the AOI device is a mirror image of the coordinate orientation of the CP probe station, it needs to be corrected by flipping. In a specific implementation, the flip parameters are configured by the user through the front-end interface (e.g., selecting "Horizontal Flip" and entering the intercept b, or selecting "Vertical Flip" and entering the X-axis intercept x).

[0066] It should be noted that offset adjustment and flip adjustment can be used in combination. Offset adjustment can be performed first, followed by flip adjustment, or vice versa. The specific order can be configured according to the actual application scenario. The adjusted coordinates are the target coordinates of the detection point in the target device's display interface.

[0067] Step 212: According to the file format standard corresponding to the target device, combine the target coordinates and the detection result label to obtain a target detection result file that the target device can recognize.

[0068] The file format standard corresponding to the target device refers to the specified format specification that the CP probe station can read. Different manufacturers' CP probe stations may have their own file format requirements, such as specific file headers, field order, delimiters, etc. The target detection result file refers to the file that can be directly read and parsed by the CP probe station after format conversion.

[0069] The file format standard corresponding to the target device is a specific file specification that the target device (such as a probe test station) can parse and execute. Different target device manufacturers or models may have different format requirements. The target detection result file is the final file generated after processing by this method, conforming to the target device specification. It is understandable that target devices from different manufacturers may have their own file format requirements, such as requiring specific file headers, field orders, delimiters, etc. For example, the target device may require a plain text file with a header containing chip ID and size information, and a body of the file that is a matrix where each cell uses "1" to represent a good point and "4" to represent a bad point. All target coordinates and their corresponding labels obtained in the previous step are reorganized and filled according to this matrix format to generate this text file.

[0070] Optionally, header information can be added to the target detection result file. This header information should include at least: the target chip's identification information (e.g., WAFER_ID), the current date, and the length and width of the target matrix. The target coordinates of each detection point and the corresponding detection result labels are written to the target detection result file in row and column order of the target matrix. The writing rules are consistent with the rendering rules of the preview file: for each position in the matrix, if it corresponds to a good point, write "1"; if it corresponds to a bad point, write "4"; if there is no corresponding detection point, write a period ".".

[0071] Step 214: Send the target detection result file to the target device so that the target device can locate the target point based on the target detection result file.

[0072] In this embodiment, the generated target detection result file is sent to the target device (e.g., transferred to a network folder specified by the probe test station via FTP). Upon receiving the file, the target device parses its contents and, based on the target coordinates and detection result labels in the file, automatically controls the probe to move to the location of the defective point requiring retesting, performing high-precision electrical performance testing. For example, after receiving the target detection result file, the CP probe station locates each detection point according to the marking information in the file ("1" indicates a good point, and "4" indicates a defective point). Specifically, for defective points marked "4", the CP probe station can skip or mark this point during testing and perform refined retesting of the defective point for subsequent graded processing in the packaging process. For good points marked "1", the CP probe station performs electrical performance testing according to the normal procedure.

[0073] Alternatively, the target device can be instructed to obtain the target detection result file by specifying a file path by the user. This embodiment of the invention does not limit the way the target device obtains the target detection result file.

[0074] Through the above steps, this embodiment achieves fully automated conversion from raw AOI equipment inspection results to files recognizable by the CP probe station. Engineers can use the MES system to perform one-click parsing and export of AOI files. The converted files can be directly read and parsed by the CP probe station, significantly improving the efficiency of file processing. Simultaneously, the preview function allows for flexible adjustment of the offset parameters corresponding to new products, enabling visual viewing of chip defect distribution and rapid location of problem points. This meets the dual needs of production line operations and customer reviews, resolving the incompatibility issues between different inspection equipment coordinate systems. It not only avoids the inefficiency and errors of manual conversion but also enhances the reliability and flexibility of the entire process through the visual preview files.

[0075] In some embodiments, to transform discrete, unstructured detection point data into a structured, visualized matrix preview file, thereby intuitively displaying the distribution and quality status of each detection point on the target chip and providing a visual reference for subsequent view adjustment parameter configuration, the step of generating and displaying the detection result preview file corresponding to the target chip based on the detection result labels and the original coordinates includes:

[0076] Based on the distribution range of the original coordinates of all the detection points, determine the view size information of the detection result preview file;

[0077] Based on the distribution extreme values ​​of the original coordinates, a reference point is selected from the plurality of detection points. Using the reference point as the reference point, a target view is constructed according to the view size information, and the reference point is rendered into the target view accordingly.

[0078] Based on the relative positional relationship of the original coordinates between the other detection points and the reference point, the other detection points are rendered into the target view accordingly.

[0079] Based on the detection result labels of each detection point, the detection result labels of the corresponding points are rendered in the target view, and statistical information of the detection points displayed in the target view is added to obtain the detection result preview file; wherein, the detection points of different types of detection results correspond to different detection result labels.

[0080] The view size information refers to a set of parameters that define the space occupied by the preview file of the detection results when it is displayed. This parameter determines the "canvas" size of the preview file, ensuring that all detection points can be fully contained within the preview interface, avoiding point overflow or incomplete display. The view size information includes at least the length and width of the view.

[0081] Specifically, the view length refers to the number of cells to be displayed along the horizontal axis (X-axis) in the preview file. This number is determined based on the distribution range of the original coordinates of all detection points along the horizontal axis. For example, the maximum X-coordinate (X_max) and minimum X-coordinate (X_min) among the original coordinates of all detection points can be counted, and the difference between X_max and X_min plus 1 can be used as the view length. The addition of 1 converts the coordinate range into a count length; for example, coordinate values ​​from -9 to 8 contain 18 integer coordinate points, and the difference 17 plus 1 gives a length of 18. Similarly, the view width refers to the number of cells to be displayed along the vertical axis (Y-axis) in the preview file, determined by adding 1 to the difference between the maximum Y-coordinate (Y_max) and the minimum Y-coordinate (Y_min).

[0082] The target view refers to a blank matrix structure created in memory or a spreadsheet based on the above view size information. Each cell of the matrix corresponds to a detection point or an empty space on the target chip. It can be understood that the target view is the basic canvas for rendering all detection points in the subsequent process.

[0083] For example, assuming that among the original coordinates of all detection points obtained through parsing, the minimum X-coordinate is -9 and the maximum is 8, then the distribution range of the X-coordinate is -9 to 8, with a difference of 17. Adding 1 makes the view length 18. The minimum Y-coordinate is -9 and the maximum is 4, then the distribution range of the Y-coordinate is -9 to 4, with a difference of 13. Adding 1 makes the view width 14. Therefore, an empty target matrix of 18 rows × 14 columns (or 18 columns × 14 rows, depending on the coordinate axis definition) is constructed as the target view. The method for determining the view size information is not limited to the above method of adding 1 to the extreme value difference. In other embodiments, a preset margin can be added to the extreme value difference (e.g., adding one cell on each side as a margin) to improve the visual effect of the preview file, ensuring that the detection points distributed at the edges do not tightly adhere to the preview boundary. This embodiment, by dynamically determining the view size information and constructing the target view, can automatically adapt to the point distribution range of different chip products without requiring manual preset of the view size, thereby improving the versatility and automation of the method.

[0084] A reference point is a specific detection point selected as the coordinate reference among all detection points. This reference point is used to establish the mapping relationship between the original coordinate system and the target view coordinate system, so that all other detection points can be correctly rendered to their corresponding positions in the target view according to their relative positional relationship with the reference point.

[0085] Specifically, the reference point is selected based on the extreme values ​​of the original coordinate distribution. The detection point with the smallest X-coordinate and Y-coordinate values ​​in the original coordinate system can be selected as the reference point. This point corresponds to the "bottom left corner" or "starting point" of the target chip in the original coordinate system. The advantage of selecting this extreme point as the reference point is that the original coordinate values ​​of all other detection points are greater than or equal to the coordinate value of the reference point, thus avoiding negative indices during coordinate transformation and facilitating subsequent matrix rendering operations. For example, if the minimum X-coordinate and minimum Y-coordinate among all detection points are -9, then the detection point with original coordinates (-9, -9) is selected as the reference point. Using this reference point as the base point, the reference point is mapped to the starting position of the target view (e.g., the first row and first column), and the corresponding detection marker is rendered at that position (e.g., rendered as "1" or "4" based on its detection result label).

[0086] It is understandable that the selection of reference points is not limited to choosing points with both the smallest X and Y coordinates. Optionally, a point with the smallest X coordinate and the largest Y coordinate can be selected as the reference point (corresponding to the "top left" starting point) according to the actual coordinate system definition, or other identifiable points can be selected as reference points, as long as a consistent mapping rule can be established.

[0087] The relative positional relationship refers to the difference vector between the original coordinates of other detection points and the original coordinates of the reference point. This vector represents the offset of other detection points relative to the reference point in the horizontal and vertical directions. Through this relative positional relationship, any detection point in the original coordinate system can be mapped to a unique and definite position in the target view.

[0088] Specifically, for any detection point, its relative position to a reference point can be calculated as follows: subtract the original X-coordinate of the reference point from the original X-coordinate of the detection point to obtain the offset in the horizontal axis direction; subtract the original Y-coordinate of the reference point from the original Y-coordinate of the detection point to obtain the offset in the vertical axis direction. The calculated offset is the logical coordinate of the detection point in the target view.

[0089] For example, suppose the original coordinates of the reference point are (-9, -9). For a detection point with original coordinates (-8, -5), its horizontal axis offset relative to the reference point is (-8) - (-9) = 1, and its vertical axis offset is (-5) - (-9) = 4. Therefore, the logical coordinates of this detection point in the target view are (1, 4), which is the 1st row and 4th column (or the 1st column and 4th row, depending on the coordinate axis definition).

[0090] After calculating the logical coordinates of all detection points, these logical coordinates are stored as a target point set, which records which locations in the target view contain detection points. Then, based on the detection result label of each detection point, the corresponding detection marker is rendered at the corresponding logical coordinate position in the target view (e.g., good points are rendered as "1", and bad points are rendered as "4").

[0091] It is understandable that the above rendering process can also include handling positions where no detection points exist. For cell positions in the target view that are not covered by the target point set (i.e., there are no detection points within the original coordinate range corresponding to that position), they can be rendered as empty space markers (e.g., a period ".") to form a complete matrix preview file. In this embodiment, by calculating the relative positional relationships, discrete points in the original coordinate system are accurately mapped to the matrix structure of the target view, realizing the transformation from arbitrarily distributed point coordinates to a regular matrix, laying a structured data foundation for subsequent visualization and data export.

[0092] Test result markers are graphics or symbols used to visually distinguish different test result types in the preview file. By using different markers, users can easily identify the distribution of good and bad pixels on the target chip without having to click through each one to view detailed information. For example, good pixels can be marked with one type of marker (such as the number "1" or filled in green), bad pixels can be marked with another type of marker (such as the number "4" or filled in red), and empty spaces can be marked with a third type of marker (such as a period "." or filled in colorless).

[0093] Statistical information refers to the summarized data obtained after quantitative analysis of the test points displayed in the target view. Statistical information provides users with a quantitative description of the overall quality of the target chip, helping them quickly grasp the level of risk and prioritize modifications. Statistical information may include: generation time (recording the creation time of the preview file for version traceability), display mode (e.g., "full display" indicates all test points are displayed, "zoomed display" indicates only some points are displayed), preview size (target view size expressed in cells, e.g., "18×17 cells"), scaling ratio (e.g., "1:1 full display" indicates no scaling, "1:2" indicates 50% scaling), matrix range (expressed in the original coordinate range, e.g., "X:-9~8, Y:-9~4"), total number of points (total number of test points included in the target view), number of good points, number of bad points, and bad point ratio, etc.

[0094] Specifically, the rendering of detection result labels can adopt the following rules: traverse each cell position in the target view and check if the position exists in the constructed target point set. If it does not exist, fill in the first label (e.g., a period ".") in the cell. If it exists, further obtain the detection result label of the detection point corresponding to that position: if the detection result label indicates a good point, fill in the second label (e.g., the number "1"); if the detection result label indicates a bad point, fill in the third label (e.g., the number "4").

[0095] Adding statistical information can be done after the detection results are marked and rendered. For example, information such as generation time and display mode can be added to the top area of ​​the preview file, preview size, scaling ratio, and matrix range can be added to the right area, and total number of points, number of good points, number of bad points, and bad point ratio can be added to the bottom area. The display position and format of the statistical information can be flexibly configured according to the actual application scenario. By differentiating the detection results marking and rendering and adding statistical information, the original binary detection data is transformed into an intuitive and information-rich visual preview file, allowing users to quickly understand the detection results of the target chip without having professional data analysis skills. This lowers the technical threshold and improves the efficiency of reviewing chip detection results data.

[0096] In some embodiments, the view size information includes the length and width of the view; determining the view size information of the detection result preview file based on the distribution range of the original coordinates of all the detection points includes:

[0097] The length is determined based on the difference between the extreme values ​​of the original coordinates on the horizontal axis and a preset margin.

[0098] The width is determined based on the difference between the extreme values ​​of the original coordinates on the vertical axis and a preset margin.

[0099] The step of selecting a reference point from the plurality of detection points based on the distribution extreme values ​​of the original coordinates includes:

[0100] The smallest detection point on the horizontal and vertical axes of the original coordinates is selected as the reference point.

[0101] In this coordinate system, the horizontal axis (X-axis) represents the horizontal position. The vertical axis (Y-axis) represents the vertical position. Extreme values ​​are the maximum and minimum values ​​along a specific coordinate axis among all the original coordinates of the detection points. Specifically, extreme values ​​on the horizontal axis include the maximum and minimum X-coordinate values ​​(X_max and X_min); extreme values ​​on the vertical axis include the maximum and minimum Y-coordinate values ​​(Y_max and Y_min). The difference between extreme values ​​reflects the distribution span of the detection points along that coordinate axis. For example, the difference between extreme values ​​on the horizontal axis is X_max - X_min, and the difference between extreme values ​​on the vertical axis is Y_max - Y_min.

[0102] Preset margin refers to the number of redundant cells added beyond the extreme value difference to improve the visual effect of the preview file. Preset margin can be a fixed preset value (e.g., adding one cell at the top, bottom, left, and right) or a dynamically calculated percentage value based on the view size (e.g., rounding up from 10% of the extreme value difference). The purpose of introducing preset margin is that when detection points are distributed at the edges of the coordinate range, without adding margin, these edge points will be right next to the boundaries of the preview file, potentially causing visual crowding or partial obscuring of markers. By adding an appropriate number of blank cells at the edges of the view, the preview file can be displayed more aesthetically pleasingly and clearly.

[0103] Specifically, the length is determined by adding a preset margin (e.g., adding 2, i.e., adding a margin of 1 cell on each side) to the difference between the extreme values ​​on the horizontal axis, or by adding twice the preset margin (i.e., adding a preset number of cells on each side). The width is determined similarly by adding a preset margin to the difference between the extreme values ​​on the vertical axis.

[0104] For example, assuming the minimum X-coordinate value among all the original coordinates of the detection points is -9 and the maximum value is 8, then the difference between the extreme values ​​on the horizontal axis is 8 - (-9) = 17. If the preset margin is set to 2 (i.e., adding 1 cell on each side), then the view length is 17 + 2 = 19. If the preset margin is set to 4 (i.e., adding 2 cells on each side), then the view length is 17 + 4 = 21. Similarly, if the minimum Y-coordinate value is -9 and the maximum value is 4, then the difference between the extreme values ​​on the vertical axis is 4 - (-9) = 13, and the view width is 13 + 2 = 15 or 13 + 4 = 17.

[0105] Understandably, the specific value of the preset margin can be adjusted according to the actual application scenario. For example, when generating a preview file for a formal report, a larger preset margin can be set to achieve a more spacious display; when generating a preview file for quick verification, a smaller preset margin or even no margin can be set to display more information within a limited space. The preset margin can also be set with different values ​​for the horizontal and vertical axes to adapt to display needs in different directions. By introducing a preset margin based on extreme value differences to determine view size information, the generated preview file has good visual margins, avoiding the problem of edge points being too close to the boundary, thus improving the readability and user experience of the preview file.

[0106] The smallest detection point on the horizontal and vertical axes refers to the detection point whose original X-coordinate equals X_min (minimum value on the horizontal axis) and original Y-coordinate equals Y_min (minimum value on the vertical axis) among all detection points. This point is located at the "minimum angle" position of the target chip in the original coordinate system, equivalent to the starting point or anchor point of the entire detection point distribution. Since the original coordinates of all other detection points are greater than or equal to the coordinate values ​​of this reference point (X ≥ X_min, Y ≥ Y_min), the horizontal and vertical offsets obtained when calculating the relative positional relationship are both non-negative integers. Non-negative offsets can be directly used as row and column indices (or column and row indices) in the target view without additional negative number processing or coordinate translation, thereby reducing computational complexity and error probability.

[0107] Using extreme points as reference points establishes a clear correspondence between the original coordinate system and the target view coordinate system: the smallest corner point in the original coordinate system maps to the starting corner point of the target view (e.g., the first row and first column). This one-to-one mapping rule is easy to understand and maintain, and also facilitates problem localization during debugging. Furthermore, because the reference point is the smallest corner point, the starting position of the target view is aligned with this point, preventing the creation of additional blank areas in the starting direction. Combined with preset margins, users can flexibly control whether to add blank areas at the edges as needed, without creating unnecessary forced blank areas due to the selection of the reference point.

[0108] For example, assuming that the minimum X-coordinate and minimum Y-coordinate among all the original coordinates of the detection points are -9, then the detection point with original coordinates (-9, -9) is selected as the reference point. Using this reference point as the base point, the offsets of other points in the original coordinate system (such as (-8, -5)) relative to this reference point are all non-negative values ​​(1 and 4), and can be directly used as logical coordinates in the target view.

[0109] Understandably, under certain coordinate system definitions, the positive direction of the horizontal axis may point to the left, or the positive direction of the vertical axis may point downwards. In these cases, the meaning of "minimum" may need to be adjusted accordingly. For example, if the positive direction of the vertical axis points downwards, then a smaller Y-coordinate value indicates a higher position. In this case, the point with the smallest Y-coordinate can still be selected as the reference point to keep the "starting point" at the top of the view. Therefore, the rules for selecting the reference point should be logically consistent with the definition of the original coordinate system and the rendering direction of the target view.

[0110] By selecting the smallest detection point on both the horizontal and vertical axes as the reference point, a simple and consistent coordinate mapping rule was established, which reduced the computational complexity of coordinate transformation and ensured the minimization of the view size (without setting a preset margin), laying the foundation for efficient and accurate point rendering in the future.

[0111] In some embodiments, obtaining view adjustment parameters for the detection result preview file includes:

[0112] The system displays a preview file of the detection results corresponding to the target chip through a preset interactive interface; the interactive interface includes at least one interactive control; the interactive control is used to receive interactive operations on the preview file of the detection results.

[0113] The step of obtaining view adjustment parameters for the preview file of the detection results includes:

[0114] In response to the interaction operation for the interactive control, the interaction operation parameters are parsed, and the view adjustment parameters are determined based on the interaction operation parameters.

[0115] The interactive interface refers to a graphical user interface (GUI) that displays a visual representation of the inspection result preview file and provides interactive elements for receiving user input. The interactive interface can be integrated into a Manufacturing Execution System (MES) as a functional module. Through the graphical interface, users can intuitively view the inspection result preview file and configure view adjustment parameters without having to memorize complex command-line commands or manually edit configuration files.

[0116] Interactive controls are visual elements in an interactive interface used to receive user input, such as buttons, input boxes, sliders, radio buttons, checkboxes, and drop-down menus. The function of interactive controls is to capture user interactions and convert them into identifiable parameter values. Different types of interactive controls are suitable for different types of parameter input: for example, numeric parameters (such as offsets) can use input boxes or sliders; Boolean parameters (such as whether to flip) can use checkboxes or radio buttons; and selection parameters (such as the type of axis to flip) can use drop-down menus or radio buttons.

[0117] Interactive operations refer to various user actions performed on interactive controls through input devices (such as mouse, keyboard, touchscreen), including: entering values ​​in input boxes, dragging sliders to change values, checking or unchecking checkboxes, clicking radio buttons, selecting options from drop-down menus, and clicking buttons to execute commands. The interactive interface may include the following interactive controls: **Source File Path Input Box:** This receives the storage path of the original detection result file entered by the user. Users can directly enter the path text or select the file by clicking the browse button. **X Offset Input Box:** This receives the X-axis offset value entered by the user. This value can be a positive integer, a negative integer, or zero. Users can directly enter the value or adjust the value using the up and down arrow buttons. **Y Offset Input Box:** This receives the Y-axis offset value entered by the user, similar in usage to the X offset input box. **Left / Right Flip Control:** This receives the user's selection regarding whether to perform a left / right flip and the flip axis parameters. This control may include a checkbox to enable / disable the left / right flip function and an input box for entering the Y-axis coordinate value (for horizontal flip axes) or X-axis coordinate value (for vertical flip axes). Vertical Flip Control: Receives user selections regarding vertical flipping and the flip axis parameters; usage is similar to the horizontal flip control. Other Flip Controls: Receive user input parameters for custom flip operations, including a slope (k) input box and an intercept (b) input box, used to construct the linear equation y=kx+b as the flip axis of symmetry. Preview Button: Triggers the generation and display of a preview file of the detection results based on the parameter values ​​in the current interactive control. Export Button: Triggers the generation of a target detection result file based on the currently confirmed view, adjusting parameters and sending it to the target device.

[0118] Understandably, the specific types and layouts of the interactive controls mentioned above can be flexibly designed according to the actual application scenario. For example, for touch screen devices, larger controls can be used to facilitate touch operation; for application scenarios that require frequent parameter adjustments, slider controls can be used to provide a smoother adjustment experience.

[0119] Interactive operation parameter parsing refers to the process of converting user actions performed through interactive controls into structured parameters with explicit numerical values ​​or states. Different interactive controls correspond to different parsing rules: for input box controls, the parsing rule is to read the text content in the input box and convert it into the corresponding data type (such as integer, floating-point number, string); for checkbox controls, the parsing rule is to obtain the selected state of the checkbox (checked or unchecked) and convert it into a boolean value (true or false); for slider controls, the parsing rule is to obtain the current numerical position of the slider and convert it into the corresponding parameter value.

[0120] View adjustment parameters refer to a set of parameter values ​​obtained after parsing. These values ​​will be used to adjust the original coordinates in subsequent steps. As mentioned earlier, view adjustment parameters may include coordinate offset parameters (X-axis offset, Y-axis offset) and / or view flip parameters (slope k, intercept b). The specific values ​​of the view adjustment parameters are determined by the user's interactive operations.

[0121] For example, when a user enters the value "2" in the X offset input box and the value "-1" in the Y offset input box, in response to the user's input operation, the text content "2" and "-1" in the input box are read, parsed into integers 2 and -1 respectively, and these two values ​​are used as coordinate offset parameters (dx=2, dy=-1) in the view adjustment parameters.

[0122] Optionally, when the user checks the "Flip Left / Right" checkbox and enters the value "0" in the flip axis input box, in response to the user's check and input operations, the checked state of the checkbox is determined to be true, the text content "0" in the input box is read and parsed as the integer 0. According to preset rules, for left / right flip, the flip axis is the horizontal axis, and its equation is y=b, where b is the intercept. Therefore, the parsed view adjustment parameters include the flip parameters: slope k=0, intercept b=0 (or b=0 corresponds to the y=0 horizontal axis).

[0123] Optionally, when the user enters "1" in the slope input box and "2" in the intercept input box of the "Other Flip" control, in response to the user's input operation, the text content "1" and "2" in the input box are read, parsed into floating-point numbers 1.0 and 2.0 respectively, and these two values ​​are used as the flip parameters (k=1, b=2) in the view adjustment parameters to construct the straight line equation y=x+2 as the flip symmetry axis.

[0124] Understandably, interactive parameter parsing can also include parameter validity validation. For example, when a user enters a non-numeric character in a numeric input box, an error message can pop up, prompting the user to re-enter the value; when the user's input offset value exceeds a reasonable range (e.g., the absolute value exceeds 1000), a warning message can be issued, prompting the user to confirm whether the input is correct. Validation can prevent coordinate transformation anomalies caused by incorrect parameters.

[0125] After determining the view adjustment parameters, the coordinate transformation and preview file generation can be re-executed based on the newly determined parameters, and the updated preview file can be displayed in real time on the interactive interface. For example, when the user adjusts the X offset, the target coordinates are automatically recalculated based on the new offset, the preview file is re-rendered, and the preview display area in the interactive interface is refreshed. This real-time feedback mechanism allows users to see the effect of parameter adjustments immediately, thus quickly finding suitable parameter values.

[0126] In some embodiments, obtaining view adjustment parameters for the detection result preview file includes:

[0127] A correlation analysis is performed on the detection results and the original coordinates, and sampling points are selected from the multiple detection points based on the analysis results;

[0128] Obtain the chip size information of the target chip and the measurement layout information of the target device, and determine the predicted coordinates of the sampling point in the display interface based on the chip size information and the measurement layout information;

[0129] The view adjustment parameters are determined based on the deviation between the preview coordinates and the predicted coordinates of the sampling points in the detection result preview file.

[0130] Correlation analysis refers to the statistical analysis of the spatial distribution relationship between the detection result labels and the original coordinates. The purpose of correlation analysis is to identify representative and regular detection points whose coordinate information effectively reflects the mapping relationship between the original coordinate system and the target device coordinate system. Correlation analysis can include: spatial clustering analysis of detection result labels, edge point identification, and symmetry analysis.

[0131] Sampling points refer to a subset selected from all detection points for subsequent deviation calculations and view adjustment parameter determination. The number of sampling points can be much smaller than the total number of detection points (for example, selecting only a few dozen sampling points from tens of thousands of chips). Selecting sampling points significantly reduces computational complexity while ensuring parameter determination accuracy, avoiding the need to process massive numbers of points one by one. Especially when the number of detection points may reach hundreds of thousands or even millions, calculating for all points would consume a large amount of computational resources and time, while sampling can achieve efficient processing within an acceptable range of accuracy loss.

[0132] Specifically, the selection of sampling points can be based on various strategies. The following examples illustrate several possible selection methods: Method 1: Edge Point Priority Strategy: Considering that detection points located at the edge of the target chip may have extreme coordinates, these points are highly sensitive to coordinate system origin shifts and axial flips, and can more sensitively reflect coordinate transformation deviations. Therefore, detection points where the X-coordinate and Y-coordinate in the original coordinate system are at their minimum or maximum values ​​can be preferentially selected as sampling points. For example, the four corner points (X_min, Y_min), (X_min, Y_max), (X_max, Y_min), and (X_max, Y_max) can be selected as sampling points.

[0133] Method 2: Uniform Sampling Strategy: To ensure that the sampling points represent the distribution characteristics of the entire target chip, detection points can be selected uniformly along the horizontal and vertical axes according to a preset sampling interval. For example, if the X-coordinate range is -100 to 100, a sampling interval of 20 can be set, selecting detection points with X coordinates of -100, -80, -60, ..., 80, 100; the Y-coordinate is similar. The horizontal and vertical axis sampling points are combined to form a grid-like set of sampling points. The uniform sampling strategy ensures that the sampling points cover the entire target chip area, avoiding the over-amplification or neglect of local deviations due to concentrated sampling.

[0134] Method 3: Defect Pixel Priority Strategy: Since defective pixels are the key focus of subsequent performance retesting of the target device, the accuracy of their coordinate transformation directly affects the effectiveness of the retest. Therefore, detection points labeled "defective pixels" can be prioritized as sampling points. When the number of defective pixels is small, all can be selected; when the number of defective pixels is large, edge-priority or uniform sampling strategies can be further used for sub-sampling within the defective pixels.

[0135] Alternatively, the above strategies can be combined. For example, first, four corner points can be selected as the basic sampling points, then several points can be evenly selected from the bad points, and then several points can be evenly selected from the good points to form a comprehensive set of sampling points. The comprehensive strategy can take into account edge sensitivity, global representativeness, and coverage of key objects of interest.

[0136] Understandably, the number of sampling points and the selection strategy can be configured according to the actual application scenario. For scenarios with high accuracy requirements, the number of sampling points can be increased (e.g., selecting all bad pixels plus the four corner points); for scenarios with high efficiency requirements, the number of sampling points can be reduced (e.g., selecting only the four corner points). The sampling point selection strategy can also be dynamically optimized based on historical data or machine learning models.

[0137] Chip size information refers to the physical dimensions and specifications of a target chip, specifically including chip pitch parameters (the physical distance between the centers of adjacent chips), the number of rows, and the number of columns. Chip size information reflects the actual physical layout of the target chip on the wafer. Different product types of chips have different size information.

[0138] Measurement layout information refers to the coordinate system, addressing method, and stepping rules used by the target device (such as a probe test station) during performance retesting. Specifically, it may include: the origin of the target device's coordinate system (e.g., the wafer center or lower left corner), the positive directions of the coordinate axes (e.g., X-axis to the right, Y-axis upwards), and step distance parameters (the physical distance covered by each probe step). Measurement layout information determines where the original test points should be mapped within the target device's coordinate system.

[0139] Predicted coordinates refer to the target coordinates that the sampling points should display on the target device's interface, calculated theoretically based on chip size information and the target device's measurement layout information. Predicted coordinates serve as a "standard answer" or "reference benchmark," used to compare with the preview coordinates in the current preview file to calculate the deviation. The formula for calculating predicted coordinates can be expressed as:

[0140] For a sampling point with original coordinates (x, y), its predicted coordinates (X_pred, Y_pred) can be calculated as follows: First, the original coordinates (which can be physical coordinates or index coordinates based on the AOI device coordinate system) are converted into coordinates based on the chip physical layout. Then, based on the origin position and step size parameters of the target device, the physical coordinates are converted into the logical coordinates of the target device. For example, assuming the step size parameter d = 10 micrometers for the target chip, the origin of the target device's coordinate system corresponds to the physical coordinates (0,0) of the wafer center. For a detection point with original physical coordinates (50, 30) micrometers, its predicted coordinates are (5, 3). If there is an offset in the origin (e.g., the origin corresponds to physical coordinates (-100, -100)), corresponding translation correction is required. It is understood that chip size information and measurement layout information can be read from the device configuration file, obtained through user input, or read in real time from the device through automatic detection.

[0141] Preview coordinates refer to the logical coordinates of the sampled points rendered in the detection result preview file under the current view adjustment parameters (or default parameters). Specifically, the original coordinates of the sampled points are obtained after transformation using the current view adjustment parameters (initially default values, such as offset of 0 and no flip). Deviation refers to the difference between the preview coordinates and the predicted coordinates, specifically including the deviation in the horizontal axis (ΔX = X_preview - X_pred) and the deviation in the vertical axis (ΔY = Y_preview - Y_pred). For multiple sampled points, multiple deviations can be obtained, forming a set of deviations. Deviation can be further statistically analyzed into the mean, median, maximum, and minimum values ​​of the deviations.

[0142] The determination of view adjustment parameters can be based on the following principle: If the current view adjustment parameters are correct (i.e., they can correctly map the original coordinate system to the target device coordinate system), then for any sampling point, its preview coordinates should be equal to the predicted coordinates, with a deviation of zero. If a deviation exists, it indicates that the current view adjustment parameters need to be adjusted, and the goal of the adjustment is to make the deviation approach zero.

[0143] Specifically, when the deviation analysis shows a roughly consistent translation between the preview coordinates and predicted coordinates of all sampling points (i.e., ΔX is approximately equal, ΔY is approximately equal), it indicates an origin offset between the original coordinate system and the target device coordinate system. In this case, the negative of this translation can be used as the offset parameter. For example, if the average deviation of multiple sampling points is (ΔX_avg, ΔY_avg), the offset parameter can be set to (-ΔX_avg, -ΔY_avg). This is because if the current preview coordinates are offset 2 units to the right relative to the predicted coordinates (i.e., X_preview = X_pred + 2), it means that the original coordinates need to be shifted 2 units to the left (i.e., setting the X offset to -2) to obtain the correct predicted coordinates.

[0144] Correspondingly, when the deviation indicates a mirror relationship between the preview coordinates and the predicted coordinates (e.g., preview coordinates are (5, -3) while predicted coordinates are (-5, 3)), it indicates an axial flip between the original coordinate system and the target device coordinate system. In this case, the slope and intercept of the flip symmetry axis can be fitted by analyzing the coordinate transformation relationship of multiple sampling points. For example, if for multiple sampling points X_preview ≈ -X_pred and Y_preview ≈ -Y_pred, then a centrally symmetric flip around the origin (0,0) is required. The corresponding flip parameters are a straight line passing through the origin with k = any value and b = 0. The specific flip method can be a flip around the y=x axis or other equivalent flips.

[0145] Understandably, in practical applications, deviations may involve both translation and flipping. In such cases, the flipping parameters can be determined first (by analyzing the sign and scale relationships of the coordinates), followed by the offset parameters (calculated after flipping correction to determine the remaining translation deviation). An iterative optimization approach can be used to gradually approximate more accurate view adjustment parameters.

[0146] In some embodiments, obtaining view adjustment parameters for the detection result preview file includes:

[0147] Obtain the chip type identifier of the target chip and the step size parameters taken by the optical inspection device when measuring the target chip;

[0148] Based on the chip type identifier and the step distance parameter, a preset mapping relationship library is queried; wherein, the mapping relationship library records historical view adjustment parameters corresponding to different combinations of chip types and step distance parameters; the construction process of the mapping relationship library includes: recording the chip type identifier, step distance parameter, and finally confirmed view adjustment parameter used in each chip detection process; using the chip type identifier and the step distance parameter as keys and the finally confirmed view adjustment parameter as values, establishing a mapping relationship and storing it in the mapping relationship library;

[0149] If a matching historical view adjustment parameter is found, the current view adjustment parameter is determined based on the matching historical view adjustment parameter.

[0150] The chip type identifier is a unique identifier used to identify different chip product types. Different chip product types may differ significantly in size specifications, circuit layout, and testing standards, which can affect the view adjustment parameters required for coordinate transformation. The chip type identifier can be a string (such as the product model "FDF730S120N"), a numerical code, or a combination of both. The chip type identifier can be parsed from the original test result file (e.g., the product information field in the file header) or obtained through user input or transmission from an upstream system.

[0151] Step distance refers to the physical distance covered by the probe or detection head with each step when the optical inspection equipment (or target device) measures a chip. The unit of step distance can be micrometers (μm). Step distance determines the conversion relationship between physical coordinates and logical coordinates: Logical coordinates = Physical coordinates ÷ Step distance. Different chip product types may correspond to different step distance parameters because different chip sizes require different measurement resolutions. Step distance parameters can be read from the configuration file of the optical inspection equipment, parsed from the raw inspection result file, or input by the user.

[0152] Chip type identification reflects differences in chip product specifications, while step pitch parameters reflect differences in measurement accuracy. Even for chips of the same product type, the required view adjustment parameters may differ if different step pitch parameters are used for measurement. Therefore, combining both as a query key allows for more accurate matching of historical records.

[0153] A mapping relation library is a data storage structure used to store historical view adjustment parameters. This structure records the view adjustment parameters that were finally confirmed for a specific chip type and step parameter combination during past chip testing data processing. A mapping relation library can be implemented in various forms, such as relational database tables, key-value stores, configuration files, or in-memory hash tables.

[0154] In the semiconductor manufacturing process, chips of the same product type often need to be repeatedly inspected multiple times (e.g., across different batches). Traditionally, each inspection requires engineers to reconfigure the view and adjust parameters, resulting in repetitive work. By recording the successfully configured parameters each time, subsequent encounters with the same chip type and step size parameter combination can directly reuse these historical parameters, eliminating the need for recalculation or manual trial and error.

[0155] Specifically, the mapping database can be organized in key-value pairs. The key is a combination of the chip type identifier and the step size parameter; for example, "FDF730S120N_10" represents a chip type of FDF730S120N and a step size parameter of 10 micrometers. The value corresponds to the historical view adjustment parameters, which may include coordinate offset parameters (X-axis offset dx, Y-axis offset dy) and / or view flipping parameters (slope k, intercept b). It is understandable that the construction of the mapping database is a dynamic and continuously accumulating process. As the system processes more and more chip inspection tasks, the records in the mapping database become increasingly rich, and the success rate of reuse in subsequent tasks also improves.

[0156] Matching refers to the existence of a record in the mapping database whose chip type identifier is the same as that of the current target chip, and whose step distance parameter is the same as (or equal to) the step distance parameter used by the current optical inspection equipment. When a match is successful, it means that the view adjustment parameters have been successfully configured historically for the same chip type and step distance parameter combination, so the parameters can be directly reused. Reuse means directly using the retrieved historical view adjustment parameters as the view adjustment parameters in the current processing flow, without the need for manual input or trial-and-error calculation. Specifically, reuse can be achieved by directly assigning the historical values ​​of parameters such as X offset, Y offset, flip slope k, and flip intercept b to the corresponding parameter variables in the current flow.

[0157] For example, suppose the target chip being processed is identified as "FDF730S120N" and the optical inspection equipment uses a step size of 10 micrometers. A matching record is found in the mapping database based on these two parameters, with an X offset of 2, a Y offset of -1, a flip slope k=0, and a flip intercept b=0 (indicating no flip). The parameter values ​​in this record can be directly used as the current view adjustment parameters for subsequent coordinate transformations and preview file generation.

[0158] Understandably, after reusing historical view adjustments, a preview file of the detection results can still be (optionally) generated and displayed to the user for confirmation. Users can fine-tune the parameters based on the reused data and store the adjusted parameters back into the mapping database as updated records to continuously optimize parameter accuracy, allowing the mapping database to adaptively improve with increased usage. Specifically, after a chip detection data processing flow is completed (e.g., the user confirms the view adjustment parameters through the interactive interface and successfully exports the target detection result file), the following operations can be performed: obtain the chip type identifier and step size parameters used in this processing. These parameters can be parsed from the original detection result file or obtained from user input.

[0159] Retrieve the final confirmed view adjustment parameters during this processing. These parameters can be manually adjusted by the user through the interactive interface, automatically calculated through a sampling and trial-and-error mechanism, or reused historical parameters and confirmed by the user. Construct a mapping record using the chip type identifier and step size parameter combination as the key and the final confirmed view adjustment parameters as the value. Store this mapping record in the mapping relationship library. If the same key already exists in the mapping relationship library, a preset update strategy can be used to determine whether to overwrite it: for example, a "latest overwrite" strategy (always using the latest parameter value), a "majority vote" strategy (selecting the parameter value with the highest frequency when multiple records are inconsistent), or a "manual confirmation" strategy (prompting the user to make a choice when a conflict occurs).

[0160] For example, suppose when processing a batch of "FDF730S120N" chips, the step size is 10 micrometers. After manual adjustment, the final confirmed view adjustment parameters are X offset = 2, Y offset = -1, and no flip. The mapping relationship database is stored with ("FDF730S120N", 10) as the key and (dx=2, dy=-1, k=0, b=0) as the value. The next time the same chip type and step size parameter combination is encountered, the system can directly reuse these parameters. It's understandable that the mapping relationship database can include more dimensions of information, such as timestamps (recording the time of parameter confirmation, used to determine if the parameter is outdated), operator identifiers (used to trace the source of the parameter), and production batch numbers (used to distinguish parameter differences between different batches). This additional information can be used for more refined query and update strategies.

[0161] In some embodiments, the view adjustment parameters include coordinate offset parameters and / or view flip parameters; adjusting the original coordinates according to the view adjustment parameters to obtain the target coordinates of each detection point in the target coordinate system corresponding to the target device includes:

[0162] When the view adjustment parameters include the coordinate offset parameters, the target offset of the detection result preview file in the target direction is determined according to the coordinate offset parameters;

[0163] The original coordinates of each detection point are translated and adjusted according to the target offset to obtain the target coordinates of each detection point;

[0164] And / or, when the view adjustment parameters include the view flip parameters, the slope and intercept of the axis of symmetry on which the flip operation of the detection result preview file is based are determined according to the view flip parameters;

[0165] Based on the slope and the intercept, a symmetry axis equation is constructed. The original coordinates of each detection point are then symmetrically flipped according to the symmetry axis equation to obtain the target coordinates of each detection point.

[0166] The coordinate offset parameter refers to the set of parameters used to translate and adjust the original coordinates. This parameter is used to correct the difference in the origin position between the coordinate system of the optical inspection equipment and the coordinate system of the target equipment. As mentioned earlier, the origin of the coordinate system of the optical inspection equipment may be located at a certain physical location on the wafer (such as the mechanical origin of the equipment), while the origin of the coordinate system of the target equipment may be located at another location (such as the center or lower left corner of the wafer). This inconsistency in the origin position will cause the same inspection point to have different coordinate values ​​in the two coordinate systems, which needs to be corrected by translation adjustment.

[0167] The target direction refers to the coordinate axis direction that needs to be translated, which can include the horizontal axis (X-axis) and the vertical axis (Y-axis). In practical applications, the horizontal and vertical axes can be translated independently, meaning the offsets in the X-axis and Y-axis directions can be different values. The target offset refers to the magnitude of the translation of the original coordinates in the target direction. The target offset can be a positive integer, a negative integer, or zero. A positive offset indicates movement in the positive direction of the coordinate axis, and a negative offset indicates movement in the negative direction of the coordinate axis. The target offset is determined by coordinate offset parameters, specifically, the coordinate offset parameters can include the X-axis offset (denoted as dx) and the Y-axis offset (denoted as dy).

[0168] Translation adjustment refers to adding the corresponding target offset to the original coordinates of each detection point to obtain new coordinate values. It can be understood that translation adjustment can be applied independently to the X and Y axes. For example, in some applications, only the X-axis direction may need adjustment, without adjusting the Y-axis direction; in this case, dy can be set to 0. The order of translation adjustment relative to flip adjustment can be either before or after it, depending on the actual requirements, as long as the combination of offset and flip parameters correctly maps the original coordinates to the target coordinate system. Through translation adjustment, the origin offset between the coordinate system of the optical detection device and the coordinate system of the target device can be corrected, ensuring that the coordinate position of the detection point in the target device matches its actual physical position.

[0169] View flip parameters refer to a set of parameters used to symmetrically flip and adjust the original coordinates. These parameters are used to correct the axial direction differences between the coordinate systems of the optical inspection device and the target device. In practical applications, the coordinate system definitions of different devices may differ: for example, the positive X-axis of the optical inspection device may point to the right, while the positive X-axis of the target device may point to the left (mirror image); or the positive Y-axis of the optical inspection device may point upwards, while the positive Y-axis of the target device may point downwards (upside down). This inconsistency in axial direction needs to be corrected through symmetrical flipping.

[0170] The axis of symmetry refers to the axis used for symmetrical flipping operations. Using this axis as a reference, the original coordinate points are mapped to the other side of the axis, forming a mirror image. The axis of symmetry can be a horizontal line (slope of 0), a vertical line (slope of infinity), or a straight line with any slope. The choice of axis of symmetry depends on the type of axial difference between the original coordinate system and the target device coordinate system. Slope and intercept are two parameters used to uniquely determine a straight line. In a Cartesian coordinate system, a straight line can be represented by the slope-intercept equation y = kx + b, where k is the slope and b is the intercept. The slope k represents the inclination of the line, and the intercept b represents the ordinate of the intersection point of the line and the Y-axis. For a vertical line (slope of infinity), a special representation can be used, such as x = c, where c is a constant.

[0171] The equation of the axis of symmetry is a linear equation constructed based on the slope and intercept, used to describe the specific position of the axis of symmetry in the coordinate system. It is constructed as follows: when the slope k is a finite value, the equation is y = kx + b; when the slope is infinite (i.e., a vertical line), the equation is x = c, where c is a constant (in this case, the intercept parameter b can be reused as c, or a separate vertical axis parameter can be used). Symmetry flipping refers to mirroring the original coordinates of each detection point relative to the axis of symmetry to obtain new coordinate values. For a given axis of symmetry line L, the symmetric point P' of point P satisfies the condition that line L is the perpendicular bisector of line segment PP'. It is understandable that in practical applications, coordinate offset parameters and view flipping parameters can be used simultaneously. When both exist, translation adjustment can be performed first, followed by flip adjustment, or vice versa. Mathematically, these two orders are not interchangeable; therefore, a fixed execution order needs to be determined based on actual needs. Alternatively, the order of "flip first, then translate" can be adopted, because the flip operation can be used to correct the axial direction, while the translation operation is used to correct the origin position. It is more intuitive to perform position correction after the direction correction.

[0172] By performing symmetrical flipping, the axial direction difference between the coordinate system of the optical inspection equipment and the coordinate system of the target equipment can be corrected, so that the spatial arrangement direction of the inspection points is consistent with the expected direction of the target equipment.

[0173] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0174] Based on the same inventive concept, this application also provides a chip detection data processing apparatus for implementing the chip detection data processing method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the chip detection data processing apparatus provided below can be found in the limitations of the chip detection data processing method described above, and will not be repeated here.

[0175] In one exemplary embodiment, such as Figure 3 As shown, a chip detection data processing device 300 is provided, the device comprising:

[0176] The first acquisition module 302 is used to acquire the raw test results output by the optical inspection equipment for performance testing of the target chip;

[0177] The parsing module 304 is used to parse the original detection result to obtain the detection result labels corresponding to multiple detection points on the target chip and the original coordinates of each detection point in the original detection result;

[0178] The preview module 306 is used to generate and display a preview file of the detection results corresponding to the target chip based on the detection result labels and the original coordinates.

[0179] The second acquisition module 308 is used to acquire view adjustment parameters for the detection result preview file; the view adjustment parameters are used to adjust the detection result preview file to fit the display interface of the target device; the target device is used to perform performance retesting on the target point among the plurality of detection points;

[0180] The adjustment module 310 is used to adjust the original coordinates according to the view adjustment parameters to obtain the target coordinates of each detection point in the display interface of the target device;

[0181] The combination module 312 is used to combine the target coordinates and the detection result labels according to the file format standard corresponding to the target device to obtain a target detection result file that the target device can recognize;

[0182] The sending module 314 is used to send the target detection result file to the target device so that the target device can locate the target point according to the target detection result file.

[0183] Each module in the aforementioned chip detection data processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0184] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a chip detection data processing method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0185] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0186] In one exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps included in any of the aforementioned chip detection data processing method embodiments.

[0187] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps included in any of the aforementioned chip detection data processing method embodiments.

[0188] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps included in any of the aforementioned chip detection data processing method embodiments.

[0189] It should be noted that the user information (including user device information, user personal information, etc.) and data (including data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0190] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0191] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0192] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A chip detection data processing method, characterized by, The method includes: Obtain the raw test results output by the optical inspection equipment for performance testing of the target chip; The original detection results are parsed to obtain the detection result labels corresponding to multiple detection points on the target chip and the original coordinates of each detection point in the original detection results; Based on the detection result labels and the original coordinates, generate and display a preview file of the detection results corresponding to the target chip; Obtain view adjustment parameters for the test result preview file; the view adjustment parameters are used to adjust the test result preview file to fit the display interface of the target device; the target device is used to perform performance retesting on the target point among the multiple test points; The original coordinates are adjusted according to the view adjustment parameters to obtain the target coordinates of each detection point in the display interface of the target device; According to the file format standard corresponding to the target device, the target coordinates and the detection result labels are combined to obtain a target detection result file that can be recognized by the target device. The target detection result file is sent to the target device so that the target device can locate the target point based on the target detection result file.

2. The method of claim 1, wherein, The step of generating and displaying a preview file of the detection results corresponding to the target chip based on the detection result labels and the original coordinates includes: Based on the distribution range of the original coordinates of all the detection points, determine the view size information of the detection result preview file; Based on the distribution extreme values ​​of the original coordinates, a reference point is selected from the plurality of detection points. Using the reference point as the reference point, a target view is constructed according to the view size information, and the reference point is rendered into the target view accordingly. Based on the relative positional relationship of the original coordinates between the other detection points and the reference point, the other detection points are rendered into the target view accordingly. Based on the detection result labels of each detection point, the detection result labels of the corresponding points are rendered in the target view, and statistical information of the detection points displayed in the target view is added to obtain the detection result preview file; wherein, the detection points of different types of detection results correspond to different detection result labels.

3. The method of claim 2, wherein, The view size information includes the length and width of the view; determining the view size information of the detection result preview file based on the distribution range of the original coordinates of all the detection points includes: The length is determined based on the difference between the extreme values ​​of the original coordinates on the horizontal axis and a preset margin. The width is determined based on the difference between the extreme values ​​of the original coordinates on the vertical axis and a preset margin. The step of selecting a reference point from the plurality of detection points based on the distribution extreme values ​​of the original coordinates includes: The smallest detection point on the horizontal and vertical axes of the original coordinates is selected as the reference point.

4. The method of claim 1, wherein, The step of obtaining view adjustment parameters for the preview file of the detection results includes: The system displays a preview file of the detection results corresponding to the target chip through a preset interactive interface; the interactive interface includes at least one interactive control; the interactive control is used to receive interactive operations on the preview file of the detection results. The step of obtaining view adjustment parameters for the preview file of the detection results includes: In response to the interaction operation for the interactive control, the interaction operation parameters are parsed, and the view adjustment parameters are determined based on the interaction operation parameters.

5. The method of claim 1, wherein, The step of obtaining view adjustment parameters for the preview file of the detection results includes: A correlation analysis is performed on the detection results and the original coordinates, and sampling points are selected from the multiple detection points based on the analysis results; Obtain the chip size information of the target chip and the measurement layout information of the target device, and determine the predicted coordinates of the sampling point in the display interface based on the chip size information and the measurement layout information; The view adjustment parameters are determined based on the deviation between the preview coordinates and the predicted coordinates of the sampling points in the detection result preview file.

6. The method of claim 1, wherein, The step of obtaining view adjustment parameters for the preview file of the detection results includes: Obtain the chip type identifier of the target chip and the step size parameters taken by the optical inspection device when measuring the target chip; Based on the chip type identifier and the step distance parameter, a preset mapping relationship library is queried; wherein, the mapping relationship library records historical view adjustment parameters corresponding to different combinations of chip types and step distance parameters; the construction process of the mapping relationship library includes: recording the chip type identifier, step distance parameter, and finally confirmed view adjustment parameter used in each chip detection process; using the chip type identifier and the step distance parameter as keys and the finally confirmed view adjustment parameter as values, establishing a mapping relationship and storing it in the mapping relationship library; If a matching historical view adjustment parameter is found, the current view adjustment parameter is determined based on the matching historical view adjustment parameter.

7. The method according to claim 1, characterized in that, The view adjustment parameters include coordinate offset parameters and / or view flip parameters; adjusting the original coordinates according to the view adjustment parameters to obtain the target coordinates of each detection point in the target coordinate system corresponding to the target device includes: When the view adjustment parameters include the coordinate offset parameters, the target offset of the detection result preview file in the target direction is determined according to the coordinate offset parameters; The original coordinates of each detection point are translated and adjusted according to the target offset to obtain the target coordinates of each detection point; And / or, when the view adjustment parameters include the view flip parameters, the slope and intercept of the axis of symmetry on which the flip operation of the detection result preview file is based are determined according to the view flip parameters; Based on the slope and the intercept, a symmetry axis equation is constructed. The original coordinates of each detection point are then symmetrically flipped according to the symmetry axis equation to obtain the target coordinates of each detection point.

8. A chip detection data processing device, characterized in that, The device includes: The first acquisition module is used to acquire the raw test results output by the optical inspection equipment for performance testing of the target chip; The parsing module is used to parse the original detection results to obtain the detection result labels corresponding to multiple detection points on the target chip and the original coordinates of each detection point in the original detection results; The preview module is used to generate and display a preview file of the detection results corresponding to the target chip based on the detection result labels and the original coordinates. The second acquisition module is used to acquire view adjustment parameters for the detection result preview file; the view adjustment parameters are used to adjust the detection result preview file to fit the display interface of the target device; the target device is used to perform performance retesting on the target point among the multiple detection points; The adjustment module is used to adjust the original coordinates according to the view adjustment parameters to obtain the target coordinates of each detection point in the display interface of the target device; The combination module is used to combine the target coordinates and the detection result labels according to the file format standard corresponding to the target device to obtain a target detection result file that can be recognized by the target device. The sending module is used to send the target detection result file to the target device, so that the target device can locate the target point based on the target detection result file.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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