A semiconductor advanced packaging wafer map automatic management system and method

Abstract

The application discloses a kind of semiconductor advanced packaging wafer atlas automatic management system and method, it is related to production quality management technical field, including, obtaining the packaging test data and control atlas of semiconductor wafer, and the packaging test data is stored, classified and filed, and the atlas file is obtained;Atlas file analysis rule is generated based on historical atlas file, and the atlas file is parsed using analysis rule, and the standardized atlas is obtained;Quality assessment is carried out to the standardized atlas using control atlas, and any one evaluation result of quality qualified and quality to be reviewed is obtained, and quality management state is recorded, and quality report is generated when quality to be reviewed;The application realizes the self-adapting analysis and standardization conversion of structured record type atlas by correlating, checking and classifying and filing packaging test data and control atlas.

Description

Technical Field

[0001] This invention relates to the field of production quality management technology, and in particular to an automated management system and method for advanced semiconductor packaging wafer mapping. Background Technology

[0002] In multi-stage production processes, the spectral data generated during the inspection stage has become an important data carrier for quality judgment, anomaly tracing, and process optimization, with advanced semiconductor packaging being a representative example. Existing methods typically involve engineers storing and classifying spectral data from different sources according to object identifiers, and then using fixed templates, script rules, or manual comparison methods to complete spectral analysis, quality verification, and anomaly handling.

[0003] Existing methods still have room for improvement. First, the graph files generated by different equipment, processes, and data sources are often heterogeneous, making standardization difficult. Second, existing methods lack a reliable, end-to-end traceability mechanism for advanced packaging production quality management, resulting in insufficient quality control traceability and collaboration. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an automated management method for advanced semiconductor packaging wafer mapping to address the problems of standardization difficulties and insufficient quality control traceability and collaboration.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an automated management method for semiconductor advanced packaging wafer mapping, comprising: Acquire packaging test data and control graphs of semiconductor wafers, and store, classify and archive the packaging test data to obtain graph files; Based on the parsing rules for generating atlas files from historical atlas files, the atlas files are parsed using the parsing rules to obtain standardized atlases; The standardized chart is evaluated using control charts to obtain either a qualified quality or a quality pending review result, and the quality management status is recorded. A quality report is generated when the quality is pending review. Anomaly handling tasks are generated based on the quality report and the preset handling mapping table. These tasks are then assigned to each process node for execution, and the execution results are obtained. The quality management status is updated based on the execution results, and the graph files, standardized graphs, quality reports, anomaly handling tasks and execution results are stored on the blockchain to form a quality management log.

[0007] As a preferred embodiment of the automated management method for advanced semiconductor packaging wafer mapping described in this invention, the specific steps for storing, classifying, and archiving packaging test data are as follows: The packaging test data of the semiconductor wafer is read from the test output terminal, the control spectrum is read from the spectrum memory, the packaging test data and the control spectrum are correlated to obtain the correlated spectrum data, the format and content integrity of the correlated spectrum data are checked, and the correlated spectrum data that passes the check is obtained. The relevant spectral data that has passed the inspection are classified and archived according to semiconductor wafer identification, process type and data source to form spectral files.

[0008] As a preferred embodiment of the automated management method for semiconductor advanced packaging wafer mapping described in this invention, the specific steps for performing format checks and content integrity checks on the associated mapping data are as follows: Read the field arrangement content, coordinate record content, point status content, and defect identification content from the associated map data in sequence, and then merge and arrange them. After merging and arranging, the field arrangement content is compared with the preset format to obtain either the same format or the different format. The control chart is used to check the coordinate record content for coordinate anomalies to obtain either the coordinate anomaly or the coordinate normality check result. Match the location status content and coordinate record content to obtain any matching result, such as a match or a non-match. Verify the defect identifier content and location status content to obtain any verification result, such as content matching or content inconsistency. Only when the format is the same, the coordinates are normal, the matching is correct, and the content is consistent, will the corresponding association map data be used as the association map data that passes the check.

[0009] As a preferred embodiment of the automated management method for semiconductor advanced packaging wafer mapping described in this invention, the specific steps for generating mapping files based on historical mapping files are as follows: Extract the field order, field name, field position, field value content, and coordinate expression order from the historical atlas file, and organize them into rule samples; Statistical induction processing is performed on the rule samples to obtain the field positional relationships and attribute correspondences; The field position relationships and attribute correspondences are combined and organized to obtain field parsing rules, coordinate parsing rules, point status parsing rules, and defect identifier parsing rules, which are then merged into a single parsing rule.

[0010] As a preferred embodiment of the automated management method for advanced semiconductor packaging wafer maps described in this invention, the specific steps for statistically summarizing the regular samples are as follows: Count the number of times the field name appears, determine the field position relationship based on the number of occurrences, and read the field values ​​corresponding to the point status and defect identifier in the field position relationship as the point status value and defect identifier value. Point status values ​​with the same defect identifier are merged into point attribute merge items, and defect identifier values ​​with the same point attribute merge items are merged into defect identifier merge items, thus forming an attribute correspondence.

[0011] As a preferred embodiment of the automated management method for semiconductor advanced packaging wafer mapping described in this invention, the specific steps for parsing the mapping file using parsing rules are as follows: Extract the row coordinates, column coordinates, point status, and defect identification from the atlas file according to the parsing rules; The row and column coordinate contents are restored to coordinate positions according to the coordinate parsing rules, the point status contents are converted into point status parsing results according to the point status parsing rules, and the defect identification contents are converted into defect types according to the defect identification parsing rules. The coordinate location, point status analysis results, and defect type are merged into a standardized map.

[0012] As a preferred embodiment of the automated management method for semiconductor advanced packaging wafer mapping described in this invention, the specific steps for using control maps to perform quality assessment on standardized maps are as follows: The standardized maps and control maps are checked for map size, reference point location, coordinate position, point attribute consistency, defect identification consistency, and basic map information consistency, and the results are obtained. When all inspection results are normal, the quality is deemed acceptable; when any inspection result is abnormal, the quality is deemed to be pending review. When quality is pending review, record the anomaly type, location, number, and scope of the anomaly as a quality report.

[0013] As a preferred embodiment of the automated management method for advanced semiconductor packaging wafer mapping described in this invention, the specific steps for generating anomaly handling tasks based on quality reports and preset handling mapping tables are as follows: When the map size is abnormal, the standard map archiving will be prohibited and the standard map will be regenerated as an exception handling task. When the reference point is abnormal, the reference point will be checked as an anomaly handling task. When the coordinate position is abnormal, the coordinate position will be corrected according to the control map and a standardized map will be regenerated as an anomaly handling task. When the location attribute is abnormal, the location status content will be reviewed and the location status parsing result will be updated as an exception handling task. When the defect identifier is abnormal, the defect identifier content will be reviewed and the defect type will be updated as an exception handling task. When the basic information of the map is abnormal, the standardized map will be prevented from taking effect and the basic information of the map will be corrected as an abnormal handling task. An exception threshold is set based on the number of historical exceptions. When the number of exceptions is less than the exception threshold, the exception handling task is identified as a first-level exception handling task and assigned to the corresponding process node for exception handling. The execution result is recorded. When the number of exceptions is not less than the exception threshold, the exception handling task is identified as a second-level exception handling task and assigned to the review node for re-analysis and quality assessment. The execution result is recorded.

[0014] As a preferred embodiment of the automated management method for semiconductor advanced packaging wafer mapping described in this invention, the specific steps for on-chain storage of mapping files, standardized mappings, quality reports, anomaly handling tasks, and execution results are as follows: Record the generation time, processing batch, and semiconductor wafer identifier of the spectral files, standardized spectral data, quality reports, anomaly handling tasks and execution results; Calculate the hash values ​​of atlas files, standardized atlases, quality reports, anomaly handling tasks, and execution results; The hash value and generation time are merged into an associated record according to the semiconductor wafer identifier and processing batch. An index is assigned to the associated record, and the associated record and index are written to the blockchain with the writing time recorded to form a quality management log.

[0015] Secondly, the present invention provides an automated management system for semiconductor advanced packaging wafer mapping, comprising, The classification module acquires packaging test data and control graphs of semiconductor wafers, and stores, classifies, and archives the packaging test data to obtain graph files; The parsing module generates parsing rules for the atlas files based on historical atlas files, and uses these rules to parse the atlas files to obtain standardized atlases. The evaluation module uses control charts to evaluate the quality of standardized charts, obtaining either a qualified quality or a quality pending review result, and records the quality management status. When the quality is pending review, a quality report is generated. The execution module generates exception handling tasks based on the quality report and the preset handling mapping table, assigns the exception handling tasks to each process node to perform exception handling, and obtains the execution results. The evidence storage module updates the quality management status based on the execution results, and stores the graph files, standardized graphs, quality reports, anomaly handling tasks and execution results on the blockchain to form a quality management log.

[0016] The beneficial effects of this invention are as follows: by associating, checking, and classifying packaging test data with control charts, the standardization and data integrity of the chart input are improved, enabling adaptive parsing and standardized conversion of structured record-type charts, reducing manual dependence and improving parsing accuracy and compatibility; in addition, by implementing quality assessment of standardized charts through control charts, a closed-loop management process covering detection, handling, and traceability is formed, improving the real-time assessment capability, anomaly handling efficiency, and full-process auditable traceability capability of chart data quality management in advanced packaging production scenarios. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart for an automated management method for semiconductor advanced packaging wafer map.

[0019] Figure 2 This is a schematic diagram of an automated management system for advanced semiconductor packaging wafer mapping.

[0020] Figure 3 A schematic diagram for generating a standardized map.

[0021] Figure 4 This is a schematic diagram for quality assessment and the generation of anomaly handling tasks. Detailed Implementation

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0025] Reference Figures 1-4This is one embodiment of the present invention, which provides an automated management method for semiconductor advanced packaging wafer mapping, comprising the following steps: S1: Obtain packaging test data and control graphs of semiconductor wafers, and store, classify and archive the packaging test data to obtain graph files.

[0026] S1.1: Read the packaging test data of the semiconductor wafer from the test output terminal, read the semiconductor wafer identifier from the packaging test data, and read the control spectrum corresponding to the semiconductor wafer identifier from the spectrum memory.

[0027] The packaging test data and control graphs are associated with semiconductor wafer identifiers to form associated graph data.

[0028] Semiconductor wafer packaging test data refers to the data generated during the testing process of semiconductor wafers in the corresponding process, which is used to characterize the inspection results of each pattern position.

[0029] The control map includes map location distribution, reference points, point attributes, and defect identifiers. The map location distribution and reference points are used for location verification, while the point attributes and defect identifiers are used for consistency checks.

[0030] S1.2: Read the field arrangement content, coordinate record content, point status content, and defect identification content in the associated map data in sequence.

[0031] The field arrangement content is used to characterize the order of appearance and field names of fields that represent semiconductor wafer identification, coordinate record content, point status content, and defect identification content.

[0032] Read the order and names of the fields in the sorted content, and compare each field order and name with the preset format. If the order and names of the fields are the same as the preset format, it is determined that the format is the same. If the order and names of the fields are different from the preset format, it is determined that the format is different.

[0033] The default format is: "Semiconductor wafer identifier, process type, data source, coordinate record content, location status content, defect identifier content".

[0034] The default format is the pre-configured basic field format of the association map data, which is used to perform format checks on the association map data before it is entered into the database.

[0035] The system reads the position distribution of the control graph and compares the coordinate positions in the coordinate records with the position distribution of the graph one by one. If the coordinate position in the coordinate records is not a subset of the position distribution of the graph, it is determined that the coordinate position is out of bounds. If the coordinate position in the coordinate records is not unique, it is determined that the coordinate position is duplicated. If the position in the position distribution of the graph is not a subset of the coordinate records, it is determined that the coordinate position is missing.

[0036] If any of the following conditions are met: out-of-bounds coordinate position, duplicate coordinate position, or missing coordinate position, the coordinates are considered abnormal. If none of these conditions are met, the coordinates are considered normal.

[0037] When each coordinate position in the coordinate record corresponds to only one point status in the point status content, it is determined to be a match. When the coordinate position in the coordinate record does not correspond to a point status, or when the coordinate position in the coordinate record corresponds to more than one point status, or when the point status in the point status content does not correspond to a coordinate position in the coordinate record, it is determined to be a mismatch.

[0038] When the location status content indicates a normal state and the defect identification content indicates no defect information, or when the location status content indicates an abnormal state and the defect identification content indicates the presence of defect information, the content is considered to be consistent.

[0039] When the location status content indicates a normal state while the defect identification content indicates the presence of defect information, or when the location status content indicates an abnormal state while the defect identification content indicates the absence of defect information, the content is judged to be inconsistent.

[0040] For example, if the status of a point is "defective" and the defect label is "cracked, contaminated, or malfunctioning," or if the status of a point is "good" and the defect label is "blank, no defect, or normal," the content is considered consistent. If the status of a point is "good" and the defect label is "cracked, contaminated, or malfunctioning," or if the status of a point is "defective" and the defect label is "blank, no defect, or normal," the content is considered inconsistent.

[0041] Only when the format is the same, the coordinates are normal, the matching is corresponding, and the content is consistent, will the corresponding merged and arranged association map data be used as the association map data that passes the check.

[0042] By merging the correlation map data that have passed the inspection and have the same semiconductor wafer identification, process type, and data source, a map file is obtained.

[0043] It should also be noted that the process type and data source are recorded in the packaging and testing data.

[0044] S2: Parsing rules for generating atlas files based on historical atlas files. The atlas files are parsed using the parsing rules to obtain standardized atlases.

[0045] S2.1: Extract historical map files from map files that have been classified and archived in local storage and record defect types, and have the same process type and data source.

[0046] Read the field order, field name, field position, field value content, and coordinate expression order in the historical map file in sequence.

[0047] Field order refers to the order in which fields are arranged in the historical graph file. Field name is used to represent the name of each field in the historical graph file. Field position refers to the position where each field appears in the historical graph file. Field value is used to represent the actual recorded content of each field. Coordinate expression order refers to the order in which row coordinates and column coordinates are expressed in the historical graph file.

[0048] The field order, field name, field position, field value content, and coordinate expression order in the historical map file are organized according to the original record relationship to form corresponding rule samples.

[0049] The original record relationship refers to the correspondence and arrangement relationship that already existed in the original record of the field order, field name, field position, field value content and coordinate expression order in the same historical map file.

[0050] S2.2: Count the number of times each field name appears in the field position in the statistical rule sample, and take the field position with the most occurrences as the corresponding field position. After the corresponding field positions of all field names are determined, the field position relationship is formed.

[0051] It should also be noted that when there are multiple field positions where the field names appear the same number of times, the corresponding preceding field name, the corresponding field name, and the corresponding following field name are taken as a field name group. The occurrence count of the field name group is counted, and the field position corresponding to the field name group with the most occurrences is taken as the corresponding field position.

[0052] Read the field values ​​corresponding to the point status and defect identifier in the field position relationship as the point status value and defect identifier value. Defect identifier values ​​of the same defect type are determined to have the same defect identifier meaning. Different point status values ​​corresponding to the same defect identifier meaning are determined to have the same point attribute meaning.

[0053] The field values ​​corresponding to the same location attribute meaning are merged into a location attribute merge item, and the field values ​​corresponding to the same defect identifier meaning are merged into a defect identifier merge item. The location attribute merge item is then associated with the corresponding defect identifier merge item to form an attribute correspondence.

[0054] Read the field positions corresponding to each field name in the field position relationship, arrange the field names according to the index order of the field positions, and obtain the field parsing rules.

[0055] The order in which the row and column coordinates in the field name are read in the field parsing rules will be used as the coordinate parsing rules.

[0056] The order in which the location status is read in the field name in the field parsing rules, and the corresponding location attribute merging items are used as the location status parsing rules.

[0057] The order in which defect identifiers in the field name are read in the field parsing rules, and the corresponding defect identifier merging items are used as the defect identifier parsing rules.

[0058] The field parsing rules, coordinate parsing rules, point status parsing rules, and defect identifier parsing rules are merged into a single parsing rule.

[0059] For example, the field position relationship is: "Field 1 is the semiconductor wafer identifier, Field 2 is the column coordinate content, Field 3 is the row coordinate content, Field 4 is the point status content, and Field 5 is the defect identifier content."

[0060] The field parsing rule is "semiconductor wafer identifier - column coordinate content - row coordinate content - point status content - defect identifier content".

[0061] The coordinate analysis rule is "column first, then row," and the point status analysis rule is "GOOD and PASS are converted to good products, FAIL and NG are converted to bad products." Good products and bad products are the point status analysis results.

[0062] The defect identification resolution rule is "CR is converted to crack, CT is converted to contamination, and blank is converted to no defect".

[0063] S2.3: Extract the row coordinates, column coordinates, point status, and defect identification from the map file according to the parsing rules.

[0064] The row and column coordinate contents are arranged into coordinate positions according to the coordinate parsing rules. The point status contents are converted into point status parsing results according to the point status parsing rules. The defect identifier contents are converted into defect types according to the defect identifier parsing rules.

[0065] The coordinate location, point status analysis results, and defect type are merged into a standardized map.

[0066] For example, if the map file is "W001, 08, 12, FAIL, CR", then the coordinate position is "12th row, 08th column", the point status analysis result is "defective product", the defect type is "crack", and the standardized map is "12th row, 08th column - defective product - crack".

[0067] S3: Use control charts to assess the quality of standardized charts, obtain either a quality pass or quality pending review assessment result, record the quality management status, and generate a quality report when quality is pending review.

[0068] S3.1: Based on the semiconductor wafer identifier, process type, and data source of the standardized pattern, read the number of rows and columns, process type, and data source of the pattern from the packaging and testing data, and use the semiconductor wafer identifier, number of rows and columns, process type, and data source corresponding to the standardized pattern as the basic information of the pattern.

[0069] When the number of rows and columns in the basic information of the spectral chart is the same as that in the control chart, the dimensional check result is judged as normal. When the number of rows and columns in the basic information of the spectral chart is different from that in the control chart, the dimensional check result is judged as abnormal.

[0070] When the coordinates of the reference points in the standardized graph are all the same as those in the control graph, the reference point check result is determined to be normal. When any coordinate is different between the reference points in the standardized graph and the reference points in the control graph, the reference point check result is determined to be abnormal.

[0071] Reference points are used to characterize the predetermined coordinate positions of the pattern direction and reference position. Reference points define the starting reference direction and positioning reference of the wafer pattern by occupying positions in the wafer pattern. When the reference point position is consistent with the reference point position in the control pattern, it indicates that the wafer pattern has not been rotated, mirrored or shifted overall.

[0072] When the coordinate positions in the standardized map are the same as the coordinate positions in the control map, the position check result is judged as normal. When the coordinate positions in the standardized map are different from the coordinate positions in the control map, the position check result is judged as abnormal.

[0073] When the position status analysis result of each coordinate position in the standardized map is exactly the same as the position attribute of the corresponding map position, the attribute check result is judged as normal. When the position status analysis result of each coordinate position is different from the position attribute of the corresponding map position in any way, the attribute check result is judged as abnormal.

[0074] When the defect type corresponding to each coordinate position in the standardized map is the same as the defect identifier at the corresponding map position, the identifier check result is judged as normal. When the defect type corresponding to each coordinate position is different from the defect identifier at the corresponding map position in any way, the identifier check result is judged as abnormal.

[0075] When the semiconductor wafer identifier, process type, and data source in the basic information of the spectrum are all the same as those in the control spectrum, the information check result is judged as normal. When any one of the semiconductor wafer identifier, process type, and data source in the basic information of the spectrum is different from that in the control spectrum, the information check result is judged as abnormal.

[0076] S3.2: Summarize and organize the size inspection results, reference point inspection results, location inspection results, attribute inspection results, identification inspection results, and information inspection results to form the inspection results.

[0077] When the dimensional inspection result is normal, the reference point inspection result is normal, the position inspection result is normal, the attribute inspection result is normal, the identification inspection result is normal, and the information inspection result is normal, the evaluation result is judged as qualified.

[0078] When the evaluation result determines that the quality is qualified, the quality management status will be recorded as "quality passed".

[0079] When the size inspection results show abnormalities in the map dimensions, the reference point inspection results show abnormalities in the reference point locations, the location inspection results show abnormalities in the coordinate locations, the attribute inspection results show abnormalities in the point attributes, the identification inspection results show abnormalities in the defect identification, or the information inspection results show abnormalities in the map basic information, the evaluation result is determined to be that the quality needs to be reviewed.

[0080] When the evaluation result determines that the quality needs to be reviewed, the quality management status is recorded as an abnormal status to be handled. The coordinate positions corresponding to the abnormal map size, abnormal reference point, abnormal coordinate position, abnormal point attribute, abnormal defect identification, and abnormal map basic information are recorded as abnormal locations.

[0081] Abnormalities are classified as follows: map size abnormality, reference point abnormality, coordinate position abnormality, point attribute abnormality, defect identification abnormality, and map basic information abnormality.

[0082] The number of abnormal records determined to be abnormal is taken as the number of abnormalities, and the union of the abnormal locations of all abnormal types is taken as the scope of the abnormality.

[0083] The anomaly type, location, number, and scope of the anomaly are included in the quality report.

[0084] It should also be noted that when there is more than one type of anomaly in the quality report, the anomaly types will be sorted in the following order: map size anomaly, reference point anomaly, location anomaly, information anomaly, attribute anomaly, and identification anomaly, and the anomaly handling tasks will be performed in sequence.

[0085] S4: Generate exception handling tasks based on the quality report and the preset handling mapping table, assign the exception handling tasks to each process node to perform exception handling, and obtain the execution results.

[0086] S4.1: The preset handling mapping table includes fields for exception type, exception quantity range, exception scope, corresponding node, exception handling task, and execution result.

[0087] The exception type field, the exception quantity range field, and the exception scope field are used together as mapping conditions. The corresponding node field is used to determine the execution node of the exception handling task, the exception handling task field is used to determine the specific handling content, and the execution result field is used to record the result content after the exception handling task is executed.

[0088] When the anomaly type is map size anomaly, the anomaly handling task is assigned to the map structure verification node. The anomaly handling task is as follows: prohibit the archiving of standardized maps, reread the row coordinate content, column coordinate content, point status content and defect identification content in the map file, delete the coordinate positions that exceed the number of map rows and columns and the corresponding point status analysis results and defect types, fill in the corresponding coordinate positions according to the missing map positions in the control map, set the point status analysis results of the filled coordinate positions to not collected, set the defect type to undetermined, and regenerate the standardized map according to the steps in S2.3.

[0089] When the anomaly type is reference point anomaly, the anomaly handling task is assigned to the reference point calibration node. The anomaly handling task is to calibrate the coordinate positions corresponding to the inconsistent reference points according to the reference point positions in the control chart.

[0090] When the anomaly type is coordinate position anomaly, the anomaly handling task is assigned to the coordinate correction node. The anomaly handling task is as follows: delete coordinate positions that are not located in the map position distribution and their corresponding point status analysis results and defect types; remove duplicate coordinate positions and their corresponding point status analysis results and defect types; fill in missing coordinate positions according to the corresponding map positions in the control map; set the point status analysis results of the filled coordinate positions to not collected and the defect type to not determined; and regenerate the standardized map according to the steps in S2.3.

[0091] When the anomaly type is a point attribute anomaly, the anomaly handling task is assigned to the point attribute review node. The anomaly handling task is to check the point status content corresponding to the anomaly location with the point status content in the map file. When the point status content corresponding to the anomaly location is different from the point status content in the map file, and the point status content in the map file is consistent with the content of the corresponding defect identifier, the point status content corresponding to the anomaly location is marked as pending review.

[0092] When the anomaly type is a defect identification anomaly, the anomaly handling task is assigned to the defect identification review node. The anomaly handling task is to check the defect identification content corresponding to the anomaly location against the defect identification content in the map file. If the defect identification content corresponding to the anomaly location is different from the defect identification content in the map file, or if the defect identification content corresponding to the anomaly location is consistent with the point status content in the map file, the defect identification content corresponding to the anomaly location is marked as pending review.

[0093] When the anomaly type is an anomaly in the basic information of the map, the anomaly handling task will be assigned to the basic information review node. The anomaly handling task is to: disable the standardized map from taking effect, and replace the semiconductor wafer identifier, process type and data source in the basic information of the map with the semiconductor wafer identifier, process type and data source in the packaging and testing data.

[0094] The graph structure verification node is an execution node that verifies and reconstructs the overall structure of the standardized graph.

[0095] Reference point calibration nodes are execution nodes for calibrating and repositioning reference points on standardized maps.

[0096] The coordinate correction node is the execution node that deletes, removes duplicates, and adds coordinate positions in the standardized map.

[0097] The point attribute verification node is the execution node that checks and corrects the point status content and point status analysis results in the standardized map.

[0098] The defect identification verification node is the execution node that checks and corrects the defect identification content and defect type in the standardized map.

[0099] The basic information verification node is the execution node that verifies and corrects the basic information of the map.

[0100] It should also be noted that anomalies where the location status analysis result is "not collected" or the defect type is set to "not determined" will not be included in the location status consistency determination and defect identifier consistency determination.

[0101] S4.2: Read the number of historical anomalies from the historical quality report from the local storage. Based on the number of historical anomalies, set the anomaly threshold using the percentile method. For example, sort the number of historical anomalies from smallest to largest and select the number of historical anomalies at the 95th percentile as the anomaly threshold.

[0102] The 95th percentile was chosen because it avoids triggering high-level handling due to frequent fluctuations and prevents a wide range of issues from being included in the routine handling scope. It is suitable for tiered processing in industrial data management scenarios. If the 95th percentile is too high, the number of anomalies that should enter the strict handling process will still be judged as normal fluctuations, which may lead to relaxed handling and delayed interception. If the 95th percentile is too low, the number of anomalies may be judged as high-level anomalies in advance, which may lead to excessive interception, frequent rollbacks and increased processing costs.

[0103] When the number of anomalies is less than the anomaly threshold, the anomaly handling task is identified as a level 1 anomaly handling task and assigned to the corresponding process node for anomaly handling, and the execution result is recorded.

[0104] When the number of anomalies is not less than the anomaly threshold, the anomaly handling task is designated as a level-two anomaly handling task and assigned to the review node for re-analysis and quality assessment, and the execution results are recorded.

[0105] The execution results include reference point verification results, coordinate correction results, point status analysis update results, defect type update results, map basic information correction results, standardized map regeneration results, real-time quality inspection results, standardized map prohibition results, and standardized map prohibition archiving results.

[0106] S5: Update the quality management status based on the execution results, and store the map files, standardized maps, quality reports, anomaly handling tasks and execution results on the chain to form a quality management log.

[0107] S5.1: When all execution results are complete, re-evaluate the quality of the standardized map after anomaly handling and update the quality management status.

[0108] Record the generation time, processing batch, and semiconductor wafer identifier of the spectrum file, standardized spectrum, quality report, anomaly handling task and execution result.

[0109] The SHA-256 algorithm is used to calculate the hash values ​​of graph files, standardized graphs, quality reports, anomaly handling tasks, and execution results.

[0110] The hash values ​​and their corresponding generation times are merged according to the semiconductor wafer identifier and processing batch to form an associated record.

[0111] Sequentially number the associated records to obtain their indexes, write the associated records and their indexes into the consortium blockchain, and record the write time.

[0112] The associated records, their indexes, and write times are merged into a quality management log.

[0113] It should also be noted that the consortium blockchain is only one implementation method of this embodiment.

[0114] This embodiment also provides an automated management system for advanced semiconductor packaging wafer mapping, including: The classification module acquires packaging test data and control graphs of semiconductor wafers, and stores, classifies, and archives the packaging test data to obtain graph files; The parsing module generates parsing rules for the atlas files based on historical atlas files, and uses these rules to parse the atlas files to obtain standardized atlases. The evaluation module uses control charts to evaluate the quality of standardized charts, obtaining either a qualified quality or a quality pending review result, and records the quality management status. When the quality is pending review, a quality report is generated. The execution module generates exception handling tasks based on the quality report and the preset handling mapping table, assigns the exception handling tasks to each process node to perform exception handling, and obtains the execution results. The evidence storage module updates the quality management status based on the execution results, and stores the graph files, standardized graphs, quality reports, anomaly handling tasks and execution results on the blockchain to form a quality management log.

[0115] This embodiment also provides a computer device applicable to the automated management method of semiconductor advanced packaging wafer map, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the automated management method of semiconductor advanced packaging wafer map as proposed in the above embodiment.

[0116] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. 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 communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0117] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the method for automated management of semiconductor advanced packaging wafer maps as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0118] In summary, this invention improves the standardization and data integrity of input data by associating, checking, and classifying packaging test data and control graphs. It achieves adaptive parsing and standardized conversion of structured record-type graphs, reducing manual reliance and improving parsing accuracy and compatibility. Furthermore, by using control graphs to conduct quality assessments of standardized graphs, a closed-loop management process covering detection, handling, and traceability is formed, enhancing the real-time assessment capability, anomaly handling efficiency, and full-process auditability and traceability of graph data quality management in advanced packaging production scenarios.

[0119] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An automated management method for semiconductor advanced packaging wafer map, characterized in that, include: Acquire packaging test data and control graphs of semiconductor wafers, and store, classify and archive the packaging test data to obtain graph files; Based on the parsing rules for generating atlas files from historical atlas files, the atlas files are parsed using the parsing rules to obtain standardized atlases; The standardized chart is evaluated using control charts to obtain either a qualified quality or a quality pending review result, and the quality management status is recorded. A quality report is generated when the quality is pending review. Anomaly handling tasks are generated based on the quality report and the preset handling mapping table. These tasks are then assigned to each process node for execution, and the execution results are obtained. The quality management status is updated based on the execution results, and the graph files, standardized graphs, quality reports, anomaly handling tasks and execution results are stored on the blockchain to form a quality management log.

2. The automated management method for semiconductor advanced packaging wafer map as described in claim 1, characterized in that, The specific steps for storing, classifying, and archiving the packaging test data are as follows: The packaging test data of the semiconductor wafer is read from the test output terminal, the control spectrum is read from the spectrum memory, the packaging test data and the control spectrum are correlated to obtain the correlated spectrum data, the format and content integrity of the correlated spectrum data are checked, and the correlated spectrum data that passes the check is obtained. The relevant spectral data that has passed the inspection are classified and archived according to semiconductor wafer identification, process type and data source to form spectral files.

3. The automated management method for semiconductor advanced packaging wafer map as described in claim 2, characterized in that, The specific steps for performing format and content integrity checks on the correlation map data are as follows: Read the field arrangement content, coordinate record content, point status content, and defect identification content from the associated map data in sequence, and then merge and arrange them. After merging and arranging, the field arrangement content is compared with the preset format to obtain either the same format or the different format. The control chart is used to check the coordinate record content for coordinate anomalies to obtain either the coordinate anomaly or the coordinate normality check result. Match the location status content and coordinate record content to obtain any matching result, such as a match or a non-match. Verify the defect identifier content and location status content to obtain any verification result, such as content matching or content inconsistency. Only when the format is the same, the coordinates are normal, the matching is correct, and the content is consistent, will the corresponding association map data be used as the association map data that passes the check.

4. The automated management method for semiconductor advanced packaging wafer map as described in claim 1, characterized in that, The specific steps of the parsing rules for generating atlas files based on historical atlas files are as follows: Extract the field order, field name, field position, field value content, and coordinate expression order from the historical atlas file, and organize them into rule samples; Statistical induction processing is performed on the rule samples to obtain the field positional relationships and attribute correspondences; The field position relationships and attribute correspondences are combined and organized to obtain field parsing rules, coordinate parsing rules, point status parsing rules, and defect identifier parsing rules, which are then merged into a single parsing rule.

5. The automated management method for semiconductor advanced packaging wafer map as described in claim 4, characterized in that, The specific steps for statistical induction processing of the rule samples are as follows: Count the number of times the field name appears, determine the field position relationship based on the number of occurrences, and read the field values ​​corresponding to the point status and defect identifier in the field position relationship as the point status value and defect identifier value. Point status values ​​with the same defect identifier are merged into point attribute merge items, and defect identifier values ​​with the same point attribute merge items are merged into defect identifier merge items, thus forming an attribute correspondence.

6. The automated management method for semiconductor advanced packaging wafer map as described in claim 1, characterized in that, The specific steps for parsing the spectral file using parsing rules are as follows: Extract the row coordinates, column coordinates, point status, and defect identification from the atlas file according to the parsing rules; The row and column coordinate contents are restored to coordinate positions according to the coordinate parsing rules, the point status contents are converted into point status parsing results according to the point status parsing rules, and the defect identification contents are converted into defect types according to the defect identification parsing rules. The coordinate location, point status analysis results, and defect type are merged into a standardized map.

7. The automated management method for semiconductor advanced packaging wafer map as described in claim 1, characterized in that, The specific steps for using control charts to assess the quality of standardized charts are as follows: The standardized maps and control maps are checked for map size, reference point location, coordinate position, point attribute consistency, defect identification consistency, and basic map information consistency, and the results are obtained. When all inspection results are normal, the quality is deemed qualified and the quality management status is recorded as quality passed. When any abnormality is found in the inspection results, the quality is deemed to be pending review. When quality is pending review, the quality management status is recorded as an abnormal pending status, and the abnormality type, abnormality location, abnormality quantity, and abnormality scope are recorded as a quality report.

8. The automated management method for semiconductor advanced packaging wafer map as described in claim 1, characterized in that, The specific steps for generating an anomaly handling task based on the quality report and the preset handling mapping table are as follows: When the map size is abnormal, the standardized map will be archived and a new standardized map will be generated as an exception handling task. When the reference point is abnormal, the reference point will be checked as an exception handling task. When the coordinate position is abnormal, the coordinate position will be corrected according to the control map and a new standardized map will be generated as an exception handling task. When the location attribute is abnormal, the location status content will be reviewed and the location status parsing result will be updated as an exception handling task. When the defect identifier is abnormal, the defect identifier content will be reviewed and the defect type will be updated as an exception handling task. When the map basic information is abnormal, the standardized map will be disabled and the map basic information will be corrected as an exception handling task. An exception threshold is set based on the number of historical exceptions. When the number of exceptions is less than the exception threshold, the exception handling task is identified as a first-level exception handling task and assigned to the corresponding process node for exception handling. The execution result is recorded. When the number of exceptions is not less than the exception threshold, the exception handling task is identified as a second-level exception handling task and assigned to the review node for re-analysis and quality assessment. The execution result is recorded.

9. The automated management method for semiconductor advanced packaging wafer map as described in claim 1, characterized in that, The specific steps for on-chain notarization of the atlas file, standardized atlas, quality report, anomaly handling task, and execution result are as follows: Record the generation time, processing batch, and semiconductor wafer identifier of the spectral files, standardized spectral data, quality reports, anomaly handling tasks and execution results; Calculate the hash values ​​of atlas files, standardized atlases, quality reports, anomaly handling tasks, and execution results; The hash value and generation time are merged into an associated record according to the semiconductor wafer identifier and processing batch. An index is assigned to the associated record, and the associated record and index are written to the blockchain with the writing time recorded to form a quality management log.

10. An automated management system for advanced semiconductor packaging wafer mapping, based on the automated management method for advanced semiconductor packaging wafer mapping according to any one of claims 1 to 9, characterized in that: include, The classification module acquires packaging test data and control graphs of semiconductor wafers, and stores, classifies, and archives the packaging test data to obtain graph files; The parsing module generates parsing rules for the atlas files based on historical atlas files, and uses these rules to parse the atlas files to obtain standardized atlases. The evaluation module uses control charts to evaluate the quality of standardized charts, obtaining either a qualified quality or a quality pending review result, and records the quality management status. When the quality is pending review, a quality report is generated. The execution module generates exception handling tasks based on the quality report and the preset handling mapping table, assigns the exception handling tasks to each process node to perform exception handling, and obtains the execution results. The evidence storage module updates the quality management status based on the execution results, and stores the graph files, standardized graphs, quality reports, anomaly handling tasks and execution results on the blockchain to form a quality management log.

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