Vehicle manufacturing management method, device and equipment and readable storage medium

Abstract

The application relates to the technical field of data processing, and discloses a vehicle manufacturing management method, device and equipment and a readable storage medium. A vehicle assembly process file comprises an assembly control plan file and an assembly process special feature list. The method comprises the following steps: based on a preset review model, preprocessing the assembly control plan file to obtain a first data model, and based on the review model, preprocessing the assembly process special feature list to obtain a second data model; based on the review model, performing data screening processing on the first data model and the second data model to obtain a process group set; based on the review model, reviewing the process group set to obtain a review result of the process group set, and based on the review result, generating a review report corresponding to the vehicle assembly process file. Through preprocessing, data screening processing and review of the vehicle assembly process file by the review model, reliance on manual review by engineers is avoided, and the review reliability of the assembly process file is improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a vehicle manufacturing management method, apparatus, equipment, and readable storage medium. Background Technology

[0002] In the process planning of modern automobile manufacturing final assembly, the vehicle assembly process documents prepared by process engineers include two core process documents: the final assembly control plan document and the list of special characteristics of the final assembly process. These two process documents play a crucial role in the overall vehicle manufacturing quality control system.

[0003] According to automotive industry quality management standards and internal quality control requirements, the final assembly control plan document and the final assembly process special characteristics list must meet strict data consistency requirements. Current review methods primarily rely on manual review by engineers, which is extremely inefficient, has inconsistent accuracy, and is costly. It also suffers from fundamental flaws such as poor responsiveness to design changes and quality risks under development cycle pressure, affecting the reliability of vehicle final assembly process document review and ultimately impacting the design quality of these documents. Summary of the Invention

[0004] In view of this, the purpose of this application is to overcome the shortcomings of the prior art and provide a vehicle manufacturing management method. Vehicle manufacturing relies on vehicle final assembly process documents, which include final assembly control plan documents and a list of special characteristics of the final assembly process. The method includes: The final assembly control plan document is preprocessed based on a preset review model to obtain a first data model, and the final assembly process special characteristic list is preprocessed based on the review model to obtain a second data model. Based on the review model, data filtering processing is performed on the first data model and the second data model to obtain a set of process groups; The process group set is reviewed based on the review model to obtain the review result of the process group set, and a review report corresponding to the vehicle final assembly process document is generated based on the review result.

[0005] In one embodiment, the step of preprocessing the final assembly control plan document based on a preset review model to obtain a first data model includes: Based on a preset review model, the assembly control plan document is classified and identified using semantic worksheets to determine the corresponding table structure metadata. The final assembly control plan document is parsed using a review model to determine the mapping relationship between the fields and values ​​in the final assembly control plan document. Based on the table structure metadata and the mapping relationship between the fields and values, a first data model is determined.

[0006] In one embodiment, the step of the vehicle performing data filtering processing on the first data model and the second data model based on the review model to obtain a set of process groups includes: The process number field in the first data model and the second data model is standardized based on the review model; Based on the standardized process number, the first data model, and the second data model, determine the process group data corresponding to each process number field; The process group set is determined based on process group data that includes preset key characteristic representations or preset important characteristic identifiers.

[0007] In one embodiment, the step of reviewing the process group set based on the review model to obtain the review result of the process group set includes: For each target process group in the process group set, a paired process group is determined in the process group set based on the review model, and a target process group pair is determined based on the target process group and the paired process group; The target process pair is reviewed based on the review model to obtain the review result of the target process pair; When reviewing each target process pair in the process group set, the review result of the process group set is obtained based on the review result of each target process pair in the review model.

[0008] In one embodiment, the step of reviewing the target process group based on the review model to obtain the review result of the target process group includes: Based on the review model, a consistency review is conducted on the target process group to obtain the consistency review results; If the consistency review result meets the preset consistency conditions, then the review result of the target process group is obtained; If the consistency review result does not meet the preset consistency conditions, then a difference review is conducted on the target process pair based on the review model to obtain the difference review result; Based on the review model and the results of the difference review, the target process pair is reviewed for the impact of the difference, and the results of the difference impact review are obtained. Based on the review model, the review results of the target process group are obtained according to the difference review results and the difference impact review results.

[0009] In one embodiment, the step of reviewing the process group set based on the review model to obtain the review result of the process group set further includes: Based on the first data model, the process group set of the second data model is reviewed according to the review model to obtain the first review result; Based on the second data model, the process group set of the first data model is reviewed according to the review model to obtain the second review result; Based on the first review result and the second review result, the review result of the process group set is obtained.

[0010] In one embodiment, the step of generating a review report corresponding to the vehicle assembly process document based on the review results includes: Based on the review results, quality indicators are calculated, including: total number of processes, number of missing processes, total number of inspection items, total number of inconsistent fields, and ratio of consistent fields. Based on the review results, improvement measures are determined, and based on the improvement measures and the quality indicators, a review report corresponding to the vehicle assembly process documents is generated.

[0011] This application also provides a vehicle manufacturing management device, the vehicle manufacturing management device comprising: The preprocessing module is used to preprocess the final assembly control plan document based on the preset review model to obtain the first data model, and to preprocess the list of special characteristics of the final assembly process based on the review model to obtain the second data model. The data filtering module is used to perform data filtering processing on the first data model and the second data model based on the review model to obtain a set of process groups. The review module is used to review the process group set based on the review model, obtain the review result of the process group set, and generate a review report corresponding to the vehicle final assembly process document based on the review result.

[0012] This application also provides a computer device, which includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the above-described vehicle manufacturing management method.

[0013] This application also provides a computer-readable storage medium storing a computer program that, when run on a processor, executes the above-described vehicle manufacturing management method.

[0014] The embodiments of this application have the following beneficial effects: This application embodiment preprocesses the final assembly control plan document based on a preset review model to obtain a first data model, and preprocesses the list of special characteristics of the final assembly process based on the review model to obtain a second data model. Data filtering is then performed on the first and second data models based on the review model to obtain a process group set. The process group set is then reviewed based on the review model to obtain the review results, and a review report corresponding to the vehicle final assembly process document is generated based on the review results. By using a review model to preprocess, filter, and review the vehicle final assembly process document, reliance on manual review by engineers is avoided. This not only improves efficiency and accuracy and reduces costs, but also overcomes fundamental shortcomings such as poor response to design changes and quality risks under development cycle pressure. It improves the reliability of the review of vehicle final assembly process documents and helps to improve the design quality of vehicle final assembly process documents. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and therefore should not be considered as a limitation on the scope of protection of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the first embodiment of the vehicle manufacturing management method provided in this application; Figure 2 A flowchart illustrating a second embodiment of the vehicle manufacturing management method provided in this application; Figure 3 A flowchart illustrating the third embodiment of the vehicle manufacturing management method provided in this application; Figure 4 A flowchart illustrating the fourth embodiment of the vehicle manufacturing management method provided in this application; Figure 5 A flowchart illustrating the fifth embodiment of the vehicle manufacturing management method provided in this application; Figure 6 A flowchart illustrating the sixth embodiment of the vehicle manufacturing management method provided in this application; Figure 7 A schematic diagram of the vehicle manufacturing management device provided in this application. Detailed Implementation

[0017] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0018] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0019] In the following, the terms “comprising,” “having,” and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as excluding, firstly, the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations thereof.

[0020] Furthermore, the terms "first," "second," and "third" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0021] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0022] It is understood that the method of this application is applied to a vehicle manufacturing management system, which can be mounted on terminal equipment, PC equipment, smart terminals and other devices, and is not limited thereto.

[0023] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0024] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a first embodiment of the vehicle manufacturing management method provided in this application. Vehicle manufacturing relies on vehicle assembly process documents, which include an assembly control plan document and a list of special characteristics of the assembly process. The method includes: Step S101: Based on the preset review model, the final assembly control plan document is preprocessed to obtain a first data model, and based on the review model, the list of special characteristics of the final assembly process is preprocessed to obtain a second data model.

[0025] In this embodiment, the vehicle manufacturing management system is equipped with a review model. This review model is trained before being used to review vehicle assembly process documents. The review model is a large language model. Based on the review model, the vehicle manufacturing management system preprocesses the assembly control plan document in the vehicle assembly process documents to obtain a first data model. It then preprocesses the list of special characteristics of the assembly process in the vehicle assembly process documents based on the review model to obtain a second data model.

[0026] It should be noted that the final assembly control plan document is the control blueprint for the entire final assembly process, recording the detailed control requirements for each workstation in the production process. This document is usually in Excel format and contains the following key information: workstation information (defining specific assembly workstations or work locations), process number (such as a unique identifier like "T11210"), process name (such as a specific operation description like "fastening compressor bracket"), product characteristics (defining the technical requirements that the assembled product should meet), process characteristics (describing the key control points in the assembly process), special characteristic classification (using symbols such as CC for critical characteristics and SC for significant characteristics), and product / process specifications / tolerances (specific technical specifications and allowable deviation ranges, such as "assembly torque: 25 (+2.5 / -1.25) Nm").

[0027] It should be noted that the final assembly special characteristics list specifically records the key characteristics that affect product safety, regulatory compliance, and functional performance during the final assembly process. This document is also in Excel format and includes the following: workstation address (the specific workstation location corresponding to the special characteristic), process number (the process identifier consistent with the control plan), process name / operation description (specific operating instructions), product characteristics (special characteristic requirements at the product level), process characteristics (special characteristic control points at the process level), special characteristic symbols (CC / SC and other classification identifiers), and specifications / tolerances (precise technical specification requirements).

[0028] It should be noted that the first data model is a structured, computable, and semantically analysis-oriented in-memory data model built upon the general assembly control plan document. This in-memory data model explicitly defines the correspondence between field names (keys) and standardized values ​​(values) in the general assembly control plan document, and the CC / SC identifiers and process numbers have been normalized. Similarly, the second data model is a structured, computable, and semantically analysis-oriented in-memory data model built upon the general assembly special characteristics list.

[0029] Step S102: Based on the review model, perform data filtering processing on the first data model and the second data model to obtain a process group set.

[0030] In this embodiment, the vehicle manufacturing management system performs data filtering processing on the first data model and the second data model based on the review model to obtain a set of process groups. It can be understood that the review model performs data filtering processing on the first data model and the second data model respectively, identifying all process groups in the first data model and all process groups in the second data model, and obtaining the set of process groups based on all process groups.

[0031] It should be noted that both the Excel-formatted assembly control plan document and the assembly special characteristics list contain a "Special Characteristics" column. This column can include process numbers identified by CC, process numbers identified by SC, or a blank field. The review model performs data filtering on both the first and second data models, selecting rows where the "Special Characteristics" column contains process numbers identified by CC or SC. Information from these rows is extracted (the same CC or SC may contain multiple rows). The information from each row containing a process number identified by CC or SC forms a process group.

[0032] Step S103: Review the process group set based on the review model to obtain the review result of the process group set, and generate a review report corresponding to the vehicle final assembly process document based on the review result.

[0033] In this embodiment, the vehicle manufacturing management system reviews the process group set based on the review model, obtains the review results of the process group set, and generates a review report corresponding to the vehicle final assembly process documents based on the review results.

[0034] It should be noted that the process group review mainly examines whether the final assembly control plan document and the final assembly process special characteristics list meet strict data consistency requirements. This includes: 1. Process number consistency requirements; Requirements: Process numbers marked as CC (critical characteristics) or SC (significant characteristics) in the final assembly control plan must have corresponding records in the final assembly special characteristics list; conversely, each process number in the special characteristics list should exist in the control plan and be marked as a special characteristic; Review criteria: Process numbers must be complete and without omissions. Process number formats may differ (e.g., "T1-1210" vs. "T11210"), but they should be identifiable as the same process, and the format differences should be pointed out. 2. Special characteristic identification consistency requirements; Requirements: The special characteristic classification identification for the same process number must be consistent in both documents. CC (critical characteristics) typically involves safety, regulatory, and functionally critical requirements; SC (significant characteristics) involves important functional and performance requirements. Review criteria: Special characteristic identification must be completely consistent. Permitted identification formats include "CC", "SC", "critical characteristics", "significant characteristics", etc. 3. Technical Specification Consistency Requirements; Requirements: Product characteristics, process characteristics, specification tolerances, and other technical content must be consistent in both documents. Technical specifications are the core basis for production control; any inconsistency may lead to quality problems. Review Standard: 100% consistency rate of technical specifications. Format differences are allowed, but the technical meaning must be the same. For example, "torque: 25 (+2.5 / -1.25) Nm" and "torque: 25 N.m (+2.5 / -1.25)" are considered consistent, but the format difference must be pointed out. 4. Content Completeness Requirements; Requirements: Each characteristic item in the special characteristic list should have a clear product characteristic description, process characteristic description, and technical specification requirements. Blank or incomplete key information is not allowed. Review Standard: Key field completeness rate ≥100%. Key fields include product characteristics, process characteristics, special characteristic symbols, and specification tolerances. 5. Data Quality Requirements; Requirements: There should be no obvious data quality problems in the documents, such as duplicate records, format errors, logical contradictions, etc. Review Standard: Data quality pass rate ≥100%. These documents exhibit extremely complex data characteristics: multi-level merged cell structure, data distribution across worksheets, variable header positions, diverse process number formats, and differences in content description.

[0035] The vehicle manufacturing management system in this embodiment preprocesses the final assembly control plan document based on a preset review model to obtain a first data model, and preprocesses the special characteristic list of the final assembly process based on the review model to obtain a second data model. It then performs data filtering on the first and second data models based on the review model to obtain a process group set. Finally, it reviews the process group set based on the review model to obtain the review results, and generates a review report corresponding to the vehicle final assembly process document based on the review results. By using a review model to preprocess, filter, and review the vehicle final assembly process document, reliance on manual review by engineers is avoided. This not only improves efficiency and accuracy and reduces costs, but also overcomes fundamental shortcomings such as poor response to design changes and quality risks under development cycle pressure. It enhances the reliability of the review of vehicle final assembly process documents and helps improve the design quality of these documents.

[0036] Please refer to Figure 2 , Figure 2 The flowchart illustrates a second embodiment of the vehicle manufacturing management method provided in this application. The difference between the second embodiment and the first embodiment is that the step of preprocessing the final assembly control plan document based on a preset review model to obtain a first data model includes: Step S201: Based on the preset review model, the assembly control plan document is classified and identified using semantic worksheets to determine the table structure metadata corresponding to the assembly control plan document.

[0037] In this embodiment, the vehicle manufacturing management system performs semantic worksheet classification and identification on the final assembly control plan document based on the review model, determining the corresponding table structure metadata. It should be noted that the semantic classification and identification of worksheets by the vehicle manufacturing management system based on the review model is based on deep language understanding technology. This enables the review model to have a deep understanding of the semantic meaning of worksheet names and to make comprehensive judgments based on contextual information, overcoming the limitations of traditional methods based on simple string matching.

[0038] It should be noted that the vehicle manufacturing management system first loads the final assembly control plan file, extracts its basic information, constructs input data for the review model based on this basic information, and then calls the review model to perform semantic worksheet classification and identification on the input data. The review model automatically classifies and identifies the valid worksheets carrying core process data, filtering out irrelevant forms such as table of contents, description pages, and template pages, and determines the table structure metadata corresponding to the final assembly control plan file. This table structure metadata includes the structural metadata of each valid worksheet (e.g., header row number, starting row of data, whether it contains merged cells, field column name coordinates, etc.).

[0039] Step S202: Based on the review model, perform table cell parsing processing on the final assembly control plan document to determine the mapping relationship between the fields and values ​​corresponding to the final assembly control plan document.

[0040] In this embodiment, the vehicle manufacturing management system uses an audit model to parse the valid worksheets in the final assembly control plan file identified in the previous steps, determining the mapping relationship between fields and values ​​in the final assembly control plan file. It should be noted that table cells include ordinary cells and merged cells; the mapping relationship between fields and values ​​(e.g., `[{"Workstation Information":"Final Assembly Line A", "Process Number":"T11210", "Process Name":"Fasten Compressor Bracket", ...}]`) determines what value each cell truly represents and which process it belongs to.

[0041] It should be noted that the review model uses a coordinate mapping algorithm to process ordinary and merged cell structures in a valid worksheet. Its core principle is based on a spatial coordinate system and numerical inheritance mechanism. This technology treats the Excel spreadsheet as a two-dimensional coordinate system, with each cell having a unique coordinate identifier. For ordinary cell ranges, the system can directly identify the mapping relationship between fields and values. For merged cell ranges, the system establishes a mapping relationship from coordinates to values. The coordinate mapping function is defined as follows: {F_merge(r, c) = {value(r_min^j, c_min^j), if there exists a merge region j such that r_min^j ≤ r ≤ r_max^j and c_min^j ≤ c ≤ c_max^j} value(r, c), otherwise NULL, if the cell is empty or invalid. Understandably, for multi-level merged cells commonly found in Excel (such as header areas spanning multiple rows and columns, and grouped summary areas), the system no longer relies on manual rules or heuristic splitting. Instead, it constructs a two-dimensional coordinate mapping mechanism: each cell is abstracted as a coordinate point (row number r, column number c); for any merged area, its top-left corner (r_min, c_min) and bottom-right corner (r_max, c_max) coordinates are recorded, and a mapping function F_merge(r,c) is established so that all coordinates within the area point to the same semantic value (e.g., all merged cells under the "Workstation Information" column header are mapped to the "Workstation Address" field identifier). This algorithm achieves lossless restoration of non-standard table structures, ensuring that subsequent field extraction does not lose contextual relevance due to formatting issues.

[0042] Step S203: Determine the first data model based on the table structure metadata and the mapping relationship between the fields and values.

[0043] In this embodiment, the vehicle manufacturing management system determines the first data model based on the table structure metadata and the mapping relationship between fields and values. It should be noted that the specific implementation process of the review model in preprocessing the list of special characteristics of the final assembly process to obtain the second data model is the same as the process of preprocessing the final assembly control plan document to obtain the first data model, and will not be repeated here.

[0044] The vehicle manufacturing management system in this embodiment performs semantic worksheet classification and identification on the final assembly control plan document based on a preset review model, determines the corresponding table structure metadata of the final assembly control plan document, performs table cell parsing processing on the final assembly control plan document based on the review model, determines the mapping relationship between the fields and values ​​of the final assembly control plan document, and determines a first data model based on the table structure metadata and the mapping relationship between the fields and values. This process filters out valid worksheets in the final assembly control plan document and sorts out the mapping relationship between fields and values ​​in the valid worksheets, resulting in a first data model. This facilitates the subsequent review model to quickly obtain relevant data from the final assembly control plan document for review, thus improving review efficiency.

[0045] Please refer to Figure 3 , Figure 3 This is a flowchart illustrating a third embodiment of the vehicle manufacturing management method provided in this application. The difference between the third embodiment and the first to second embodiments lies in the step of performing data filtering processing on the first data model and the second data model based on the review model to obtain a process group set, including: Step S301: Standardize the process number field in the first data model and the second data model based on the review model.

[0046] In this embodiment, the vehicle manufacturing management system standardizes the process number field in the first and second data models based on the review model. The process number standardization function is defined as: F_normalize(code_string) = UPPER(REMOVE_SEPARATORS(TRIM(code_string))). This function receives the process number in the original string form (such as t1-1210, T1_1210, or T11210) and performs three deterministic text operations in sequence; TRIM(code_string))) `de_string`: Removes leading and trailing whitespace characters (including spaces, tabs, etc.) from the string, ensuring no redundant boundary spaces; `REMOVE_SEPARATORS(...)`: Removes all non-alphanumeric separators (such as hyphens, underscores, forward slashes, parentheses, periods, etc.), keeping only English letters and numbers, converting both T1-1210 and T1_1210 to T11210; `UPPER(...)`: Converts the remaining characters to uppercase, eliminating matching ambiguity caused by mixed case (e.g., converting t11210 to T11210).

[0047] Understandably, the standardization process converts the process number field into a normalized, case-consistent, delimiter-free, and space-free pure alphanumeric string, serving as the unique benchmark for subsequent cross-file process number comparisons. This design not only solves the problem of missed matches caused by "different code forms" in process numbers (such as `T11210` vs `T1-1210`) in actual engineering, but also provides a structured and robust input foundation for model-driven semantic consistency judgment through deterministic, reversible (at the semantic level), and lossless (without changing the encoding essence) cleaning logic. This is the key technical feature that distinguishes it from traditional regular expression fuzzy matching or simple string hashing.

[0048] Step S302: Based on the standardized process number, the first data model, and the second data model, determine the process group data corresponding to each process number field.

[0049] In this embodiment, the vehicle manufacturing management system, through a review model, determines the process group data corresponding to each process number field based on the standardized process number, the first data model, and the second data model. It can be understood that the review model performs clustering based on the standardized number. For the first data model, it aggregates all related rows (including product characteristics, process characteristics, special characteristic symbols, specification tolerances, etc.) under the same process number into one process group data. Similarly, for the second data model, it aggregates all related rows (including product characteristics, process characteristics, special characteristic symbols, specification tolerances, etc.) under the same process number into one process group data, thus determining the process group data corresponding to each process number field in the first data model and the process group data corresponding to each process number field in the second data model.

[0050] Step S303: Determine the process group set based on process group data containing preset key characteristic representations or preset important characteristic identifiers.

[0051] In this embodiment, the vehicle manufacturing management system, through the review model based on the built-in special characteristic filtering function, retains only process group data containing preset key characteristic representations or preset important characteristic identifiers (such as semantic identifiers such as CC, SC, key characteristics, important characteristics, etc.), and eliminates ordinary process group data, thereby determining the process group set.

[0052] For example, the special characteristic filtering function is: F_special_characteristic(row_data) = {True, if it contains a CC (critical characteristic) or SC (significant characteristic) identifier; False, otherwise}.

[0053] The vehicle manufacturing management system in this embodiment standardizes the process number fields in the first and second data models based on the review model. Based on the standardized process numbers, the first and second data models, it determines the process group data corresponding to each process number field. Based on the process group data containing preset key characteristic representations or preset important characteristic identifiers, it determines the process group set. Standardizing the process number field provides a structured and robust input foundation for model-driven semantic consistency judgment. By determining the process group data corresponding to each process number field and filtering for special characteristics, it determines the process group set to be compared, avoiding interference from ordinary process group data in the review process. This helps improve the efficiency and accuracy of reviewing final assembly process documents.

[0054] Please refer to Figure 4 , Figure 4This is a flowchart illustrating a fourth embodiment of the vehicle manufacturing management method provided in this application. The difference between the fourth embodiment and the first to third embodiments is that the step of reviewing the process group set based on the review model to obtain the review result of the process group set includes: Step S401: For each target process group in the process group set, determine a paired process group in the process group set based on the review model, and determine a target process group pair based on the target process group and the paired process group.

[0055] In this embodiment, the vehicle manufacturing management system, for each target process group in the process group set, determines paired process groups in the process group set based on a review model, and determines target process group pairs based on the target process group and the paired process groups. It is understood that the process group set includes all process groups in the final assembly control plan document and all process groups in the final assembly process special characteristics list. Generally, process groups with the same process number will exist simultaneously in all process groups in the final assembly control plan document and the final assembly process special characteristics list; that is, the process group set will include two process groups with the same process number, and these two process groups constitute a target process group pair.

[0056] It should be noted that all process groups in the final assembly control plan document and all process numbers in the final assembly process special characteristics list must be consistent. That is, process groups with the same process number will exist in all process groups in the final assembly control plan document and in the final assembly process special characteristics list. If a target process group in the process group set does not have a matching process group, it means that the target process group does not exist in both the final assembly control plan document and the final assembly process special characteristics list. The vehicle manufacturing management system will record this anomaly and include it in the subsequent review report.

[0057] Step S402: Review the target process pair based on the review model to obtain the review result of the target process pair.

[0058] In this embodiment, the vehicle manufacturing management system reviews each identified target process group pair based on the review model, obtaining the review result for each target process group. It should be noted that for each target process group, the review model sequentially performs a consistency review, a difference review, and a difference impact review to obtain the review result for the target process group. The consistency review focuses on determining whether two process groups are semantically consistent, without performing detailed difference analysis. This macro-level assessment can quickly identify consistent process groups, improving overall processing efficiency. The difference review involves a detailed, item-by-item difference identification for process groups that fail the consistency review, focusing on accurately locating specific differences. This technology uses a field-by-field comparison method to accurately identify the differences in CC (critical characteristics) and SC (significant characteristics) between two process groups. The difference impact review performs a professional impact assessment and severity classification for each specific difference item identified in the difference review, focusing on technical impact analysis, particularly the impact of CC (critical characteristics) and SC (significant characteristics) related differences on product safety, regulatory compliance, and functional performance.

[0059] Step S403: When reviewing each target process pair in the process group set, the review result of the process group set is obtained based on the review result of each target process pair in the review model.

[0060] In this embodiment, the vehicle manufacturing management system reviews each identified target process pair based on the review model. After completing the review of each target process pair in the process group set and obtaining the review result of each target process pair, the review results of each target process pair are integrated based on the review model to obtain the review result of the process group set.

[0061] In one embodiment, the step of reviewing the target process group based on the review model to obtain the review result of the target process group includes: Step S4021: Perform a consistency review on the target process group based on the review model to obtain the consistency review result.

[0062] In this embodiment, the vehicle manufacturing management system performs a consistency review on the target process pair based on the review model to obtain the consistency review result. Specifically, the consistency review process is as follows: extract complete information of the target process pair, construct consistency review input data, call the review model to review the consistency review input data, parse the consistency review output, determine whether the two process pairs in the process pair are consistent, and record the consistency review result. Specifically, the template for the consistency assessment prompt in the review model is: "You are an automotive process consistency assessment expert. Please assess the overall consistency of the following process number in two files. Process number: {process_code}, Special characteristics list process group: {special_list_group}, Control plan process group: {control_plan_group}. Assessment requirements: 1. Determine whether the two process groups are substantially consistent in technical content; 2. Focus on the consistency of CC (critical characteristics) and SC (significant characteristics); 3. Assess the overall consistency level. Please strictly follow the following JSON format for output: { "is_consistent": true / false, "consistency_level": "Completely consistent" / "Mostly consistent" / "Partially consistent" / "Severely inconsistent", "requires_detailed_analysis": true / false; "analysis_dimensions": ["Content differences" / "Format differences" / "Missing items" / "Redundant items"]; "confidence": 0.0-1.0}.

[0063] Step S4022: If the consistency review result meets the preset consistency conditions, the review result of the target process group is obtained.

[0064] In this embodiment, if the review model determines that the consistency review result of the target process group meets the preset consistency conditions, the review result of the target process group is obtained. Subsequent discrepancy reviews and discrepancy impact reviews are no longer performed.

[0065] Step S4023: If the consistency review result does not meet the preset consistency conditions, then a difference review is performed on the target process group based on the review model to obtain the difference review result.

[0066] In this embodiment, if the review model determines that the consistency review result of the target process pair does not meet the preset consistency conditions, it performs a difference review on the target process pair to obtain the difference review result. Specifically, the difference review process is as follows: extract the content of the target process pair that fails the consistency review line by line, call the review model to identify specific differences, parse the difference identification results, extract the list of difference items, verify the completeness of the difference items, and obtain the difference review result. Specifically, the prompt template for the review model to conduct difference reviews is: "You are an automotive process content comparison expert. Please accurately identify the specific differences in the following process groups. Analysis requirements: 1. Compare field by field to accurately locate the differences; 2. Focus on the differences in CC (Critical Characteristic) and SC (Significant Characteristic); 3. Identify missing and redundant items; 4. Distinguish between substantive differences and format differences. Please strictly adhere to the following JSON format for output: {"difference_items": [{"difference_id": "Unique identifier", "difference_type": "Content inconsistency" / "Missing item" / "Redundant item" / "Format difference", "field_name": "Difference field name", "special_list_value": "Value in the special characteristic list", "control_plan_value": "Value in the control plan", "difference_description": "Detailed description of the difference"}], "total_differences": Total number of differences}".

[0067] Step S4024: Based on the review model and the difference review results, conduct a difference impact review on the target process group pair to obtain the difference impact review results.

[0068] In this embodiment, the review model performs a difference impact review on the target process pairs based on the difference review results, and obtains the difference impact review results. Specifically, the difference impact review process is as follows: obtain specific difference items, construct impact assessment inputs, call the review model to perform difference impact review, determine the severity level, impact analysis content, and improvement suggestions, and obtain the difference impact review results. Specifically, the prompt template for the review model's difference impact review is: "You are a senior automotive process quality expert. Please conduct a professional impact assessment of the following specific differences. Assessment requirements: 1. Assess the impact on product quality, paying particular attention to differences related to CC (Critical Characteristics) and SC (Significant Characteristics); 2. Assess the impact on the production process; 3. Assess safety and compliance risks; 4. Determine the severity level. The severity standards are: High: Affects safety, regulatory requirements, critical functions, CC-related differences, missing process numbers; Medium: Affects product performance, SC-related differences, differences in measurement accuracy; Low: Format differences but the same technical meaning. Please strictly follow the following JSON format for output: {"severity_level": "High" / "Medium" / "Low", "quality_impact": "Specific impact on product quality", "safety_risk": "Safety risk assessment", "compliance_risk": "Compliance risk assessment", "improvement_actions": ["Specific improvement measures"], "confidence_score": 0.0-1.0}.

[0069] Step S4025: Based on the review model, obtain the review results of the target process group according to the difference review results and the difference impact review results.

[0070] In this embodiment, the vehicle manufacturing management system obtains the review results of the target process group based on the review model, the difference review results, and the difference impact review results.

[0071] The vehicle manufacturing management system in this embodiment, for each target process group in the process group set, determines paired process groups in the process group set based on a review model, and determines target process group pairs based on the target process groups and paired process groups. Based on the review model, it sequentially performs consistency review, difference review, and difference impact review on the target process group pairs to obtain the review results of the target process group pairs. When completing the review of each target process group pair in the process group set, it obtains the review result of the process group set based on the review results of each target process group pair. By pairing process groups and sequentially performing consistency review, difference review, and difference impact review, the efficiency and accuracy of reviewing vehicle final assembly process documents are improved.

[0072] Please refer to Figure 5 , Figure 5 This is a flowchart illustrating a fifth embodiment of the vehicle manufacturing management method provided in this application. The difference between the fifth embodiment and the first to fourth embodiments is that the step of reviewing the process group set based on the review model to obtain the review result of the process group set further includes: Step S501: Based on the first data model, the process group set of the second data model is reviewed according to the review model to obtain the first review result.

[0073] Step S502: Based on the second data model, the process group set of the first data model is reviewed according to the review model to obtain the second review result.

[0074] Step S503: Based on the first review result and the second review result, obtain the review result of the process group set.

[0075] In this embodiment, the vehicle manufacturing management system performs two rounds of review. The first round uses a first data model as a benchmark and reviews the process group set of the second data model based on the review model, yielding a first review result. The second round uses the second data model as a benchmark and reviews the process group set of the first data model based on the review model, yielding a second review result. Finally, based on the first and second review results, the review result for the process group set is obtained.

[0076] Understandably, the first round of checks uses the final assembly control plan document as a benchmark to verify the process groups in the final assembly process special characteristics list, checking whether all process groups in the final assembly process special characteristics list exist in the final assembly control plan document and whether they are consistent. The second round uses the final assembly process special characteristics list as a benchmark to verify the process groups in the final assembly control plan document, checking whether all process groups in the final assembly control plan document exist in the final assembly process special characteristics list and whether they are consistent. Through this two-way cross-checking, it can be determined which process groups exist only in the final assembly control plan document, which process groups exist only in the final assembly process special characteristics list, and whether the process groups present in both documents are consistent.

[0077] It should be noted that both the first and second rounds of review are the same as the review process described in the above embodiments, and will not be repeated here.

[0078] The vehicle manufacturing management system in this embodiment uses a first data model as a benchmark and reviews the process group set of a second data model based on the review model to obtain a first review result. Then, using the second data model as a benchmark, it reviews the process group set of the first data model based on the review model to obtain a second review result. Based on the first and second review results, the review result of the process group set is obtained. A two-way cross-validation mechanism is employed to ensure the comprehensiveness of the review, and maintaining a set of processed process numbers avoids duplicate processing, thus improving the comprehensiveness and accuracy of the review of vehicle assembly process documents.

[0079] Please refer to Figure 6 , Figure 6 This is a flowchart illustrating a sixth embodiment of the vehicle manufacturing management method provided in this application. The difference between the sixth embodiment and the first to fifth embodiments is that the step of generating a review report corresponding to the vehicle final assembly process document based on the review result includes: Step S601: Calculate quality indicators based on the review results. The quality indicators include: total number of processes, number of missing processes, total number of inspection items, total number of inconsistent fields, and consistent field ratio.

[0080] Step S602: Based on the review results, determine improvement measures, and based on the improvement measures and the quality indicators, generate a review report corresponding to the vehicle assembly process documents.

[0081] In this embodiment, the vehicle manufacturing management system calculates quality indicators based on the review results. These quality indicators include: total number of processes, number of missing processes, total number of inspection items, total number of inconsistent fields, and consistency field ratio. Improvement measures are determined based on the review results, and a review report corresponding to the vehicle assembly process documents is generated based on these improvement measures and the quality indicators. Specifically, the total number of processes is calculated as: N_total = |P_special ∪ P_control|, where P_special is the total number of processes in the special characteristics list, and P_control is the total number of processes in the control plan. The number of missing processes is calculated as: N_missing = the number of issues of the "missing process number" type. The total number of inspection items is calculated as: N_check = the total number of valid fields in the special characteristics list. The consistency ratio is calculated as: R_consistency = max(0, min(1, 1 - N_inconsistent / N_check)), where N_inconsistent is the total number of inconsistent fields detected by the large model validation.

[0082] The vehicle manufacturing management system in this embodiment calculates quality indicators based on the review results, determines improvement measures based on the review results, and generates a review report corresponding to the vehicle final assembly process documents based on the improvement measures and quality indicators. The generated review report visually displays the differences between the final assembly control plan document and the list of special characteristics of the final assembly process, facilitating relevant personnel to modify the final assembly control plan document and the list of special characteristics of the final assembly process, thereby improving the efficiency of revising the vehicle final assembly process documents.

[0083] Please refer to Figure 7 , Figure 7 This is a schematic diagram of the vehicle manufacturing management device provided in this application. The vehicle manufacturing management device includes: The preprocessing module 10 is used to preprocess the final assembly control plan document based on a preset review model to obtain a first data model, and to preprocess the list of special characteristics of the final assembly process based on the review model to obtain a second data model.

[0084] The data filtering module 20 is used to perform data filtering processing on the first data model and the second data model based on the review model to obtain a process group set.

[0085] The review module 30 is used to review the process group set based on the review model, obtain the review result of the process group set, and generate a review report corresponding to the vehicle assembly process document based on the review result.

[0086] It is understood that the vehicle manufacturing management device in this embodiment corresponds to the vehicle manufacturing management method in the above embodiment, and the options in the above embodiment are also applicable to this embodiment, so they will not be described again here.

[0087] This application also provides a computer device, exemplary of which includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to enable the computer device to perform the functions of the various modules in the above-described vehicle manufacturing management method or the above-described vehicle manufacturing management device.

[0088] The processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, including at least one of a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Network Processor (NP), Digital Signal Processor (DSP), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0089] The memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory is used to store computer programs, and the processor can execute the computer programs accordingly after receiving execution instructions.

[0090] This application also provides a data processing method, which includes a controller, such as a BMS (Power Management System) board, etc. The controller stores a computer program, wherein the data processing is used to execute the computer program during the charging process to implement the above-mentioned vehicle manufacturing management method.

[0091] This application also provides a computer storage medium for storing the computer program used in the aforementioned computer device. The computer storage medium can be a readable storage medium, a non-volatile storage medium, or a volatile storage medium. For example, the computer storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, in alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0093] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0094] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a smartphone, personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0095] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A vehicle manufacturing management method, characterized in that, Vehicle manufacturing relies on vehicle final assembly process documents, which include final assembly control plan documents and a list of special characteristics of the final assembly process. The method includes: The final assembly control plan document is preprocessed based on a preset review model to obtain a first data model, and the final assembly process special characteristic list is preprocessed based on the review model to obtain a second data model. Based on the review model, data filtering processing is performed on the first data model and the second data model to obtain a set of process groups; The process group set is reviewed based on the review model to obtain the review result of the process group set, and a review report corresponding to the vehicle final assembly process document is generated based on the review result.

2. The vehicle manufacturing management method according to claim 1, characterized in that, The step of preprocessing the final assembly control plan document based on a preset review model to obtain the first data model includes: Based on a preset review model, the assembly control plan document is classified and identified using semantic worksheets to determine the corresponding table structure metadata. The final assembly control plan document is parsed using a review model to determine the mapping relationship between the fields and values ​​in the final assembly control plan document. Based on the table structure metadata and the mapping relationship between the fields and values, a first data model is determined.

3. The vehicle manufacturing management method according to claim 1, characterized in that, The step of the vehicle performing data filtering processing on the first data model and the second data model based on the review model to obtain a set of process groups includes: The process number field in the first data model and the second data model is standardized based on the review model; Based on the standardized process number, the first data model, and the second data model, determine the process group data corresponding to each process number field; The process group set is determined based on process group data that includes preset key characteristic representations or preset important characteristic identifiers.

4. The vehicle manufacturing management method according to claim 1, characterized in that, The step of reviewing the process group set based on the review model to obtain the review result of the process group set includes: For each target process group in the process group set, a paired process group is determined in the process group set based on the review model, and a target process group pair is determined based on the target process group and the paired process group; The target process pair is reviewed based on the review model to obtain the review result of the target process pair; Upon completion of the review of each target process pair in the process group set, the review result of the process group set is obtained based on the review result of each target process pair.

5. The vehicle manufacturing management method according to claim 4, characterized in that, The step of reviewing the target process group based on the review model to obtain the review result of the target process group includes: Based on the review model, a consistency review is conducted on the target process group to obtain the consistency review results; If the consistency review result meets the preset consistency conditions, then the review result of the target process group is obtained; If the consistency review result does not meet the preset consistency conditions, then a difference review is conducted on the target process pair based on the review model to obtain the difference review result; Based on the review model and the results of the difference review, the target process pair is reviewed for the impact of the difference, and the results of the difference impact review are obtained. Based on the review model, the review results of the target process group are obtained according to the difference review results and the difference impact review results.

6. The vehicle manufacturing management method according to claim 1, characterized in that, The step of reviewing the process group set based on the review model to obtain the review result of the process group set further includes: Based on the first data model, the process group set of the second data model is reviewed according to the review model to obtain the first review result; Based on the second data model, the process group set of the first data model is reviewed according to the review model to obtain the second review result; Based on the first review result and the second review result, the review result of the process group set is obtained.

7. The vehicle manufacturing management method according to claim 1, characterized in that, The step of generating a review report corresponding to the vehicle assembly process documents based on the review results includes: Based on the review results, quality indicators are calculated, including: total number of processes, number of missing processes, total number of inspection items, total number of inconsistent fields, and ratio of consistent fields. Based on the review results, improvement measures are determined, and based on the improvement measures and the quality indicators, a review report corresponding to the vehicle assembly process documents is generated.

8. A vehicle manufacturing management device, characterized in that, The vehicle manufacturing management device includes: The preprocessing module is used to preprocess the final assembly control plan document based on the preset review model to obtain the first data model, and to preprocess the list of special characteristics of the final assembly process based on the review model to obtain the second data model. The data filtering module is used to perform data filtering processing on the first data model and the second data model based on the review model to obtain a set of process groups. The review module is used to review the process group set based on the review model, obtain the review result of the process group set, and generate a review report corresponding to the vehicle final assembly process document based on the review result.

9. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the vehicle manufacturing management method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when run on a processor, executes the vehicle manufacturing management method according to any one of claims 1-7.

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