Part list generation method and device, equipment and medium

Abstract

The invention discloses a part list generation method and device, equipment and a medium, and relates to the technical field of automobiles, the method is executed by a first client, and the method comprises the following steps: obtaining part main data marked with key part labels, the part main data comprising parameter information of whole vehicle parts of at least two types of vehicles, the key part labels are used for indicating key parts; obtaining specification number information corresponding to the key part; the specification number information is added to the position, corresponding to the key part, in the part main data, and updated part main data is obtained; a query condition is obtained, a first part list is obtained through screening based on the query condition and the updated part main data, the query condition is used for indicating to obtain parameter information of key parts of the first vehicle type vehicle, and the parameter information comprises specification number information of the key parts of the first vehicle type vehicle. The acquisition of the list of key parts of the vehicle and the automation of the data processing process can be realized.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of automotive technology, and in particular to a method, apparatus, device, and medium for generating a parts list. Background Art

[0002] Before mass production of new models, automakers must submit a variety of regulatory documents to relevant authorities. One of the core submission materials is a list of critical parts, detailing the parts' model, specifications, suppliers, and applicable vehicle models. As consumer demand diversifies and vehicle configurations become increasingly complex, the variety of parts has surged, significantly increasing the workload involved in compiling the list.

[0003] In related technologies, the compilation of critical parts lists relies primarily on manual labor: certification managers coordinate with various specialized departments to fill in part data according to a fixed template, repeatedly collecting and summarizing this information via email or paper documents. To ensure accuracy, the list must be signed and reviewed by multiple people.

[0004] However, the manual organization and filling process is prone to errors, the accuracy of the data depends on the engineer's familiarity with the product, multiple rounds of signature verification are inefficient, and the process is cumbersome, making it difficult to meet the needs of efficiently and quickly generating a list of key parts. Summary of the Invention

[0005] The embodiments of the present application provide a method, apparatus, device, and medium for generating a parts list, which can automate the acquisition and data processing of a vehicle's key parts list. The technical solution is as follows:

[0006] In one aspect, a method for generating a parts list is provided, which is executed by a first client, and the method includes:

[0007] Obtaining part master data marked with a key component label, the part master data including parameter information of vehicle parts for at least two vehicles, the key component label being used to indicate a key component, and the key component being a predetermined component;

[0008] Obtain specification number information corresponding to the key components;

[0009] Adding the specification number information to the position corresponding to the key component in the part master data to obtain updated part master data;

[0010] Obtain query conditions, and obtain a first parts list based on the query conditions and the updated parts master data through screening, wherein the query conditions are used to indicate obtaining parameter information of key components of a first vehicle model, the parameter information including the specification number information of the key components of the first vehicle model.

[0011] In another aspect, a device for generating a parts list is provided, the device comprising:

[0012] an acquisition module, configured to acquire part master data labeled with a key component tag, the part master data comprising parameter information of vehicle parts for at least two vehicles, the key component tag being used to indicate a key component, the key component being a predetermined component;

[0013] The acquisition module is further used to obtain specification number information corresponding to the key components;

[0014] An updating module, configured to add the specification number information to a position corresponding to the key component in the part master data to obtain updated part master data;

[0015] The acquisition module is further used to obtain query conditions and filter out a first parts list based on the query conditions and the updated parts master data, wherein the query conditions are used to indicate the acquisition of parameter information of key components of a first model vehicle, and the parameter information includes the specification number information of the key components of the first model vehicle.

[0016] In an optional embodiment, the acquisition module is further used to obtain preset key component requirements; perform matching analysis on the vehicle parts based on the key component requirements to determine the key components in the vehicle parts; and label the part master data based on the part identification of the key components to obtain the part master data labeled with the key component label.

[0017] In an optional embodiment, the acquisition module is further used to determine the at least one part in the vehicle parts as the key component in response to the matching degree between the at least one part and the key component requirement reaching a preset matching threshold.

[0018] In an optional embodiment, the acquisition module is also used to send the part master data to a second client, and the second client is used to review the part master data based on preset rules and generate the specification number information if the review is passed; and receive the specification number information sent by the second client.

[0019] In an optional embodiment, the acquisition module is further used to receive a bill of materials generation operation, which includes the query conditions; based on the query conditions, the updated parts master data is filtered to obtain the first bill of materials, which includes parameter information of the whole vehicle parts of the first model vehicle; based on the key component labels, the first parts list is obtained by filtering from the first bill of materials.

[0020] In an optional embodiment, the acquisition module is further used to obtain a parts list template, which is used to instruct the generation of the first parts list; based on the key component labels, the material list lines corresponding to the key components of the first vehicle model are filtered from the first material list; and the part parameter information in the material list lines is synchronized to the parts list template to obtain the first parts list.

[0021] In an optional embodiment, the acquisition module is also used to obtain historical traffic event data of the at least two vehicles, and the historical traffic event data is used to indicate the situations in which traffic events occurred in the at least two vehicles within a historical time period; perform fault analysis based on the historical traffic event data to obtain the parts failure probabilities corresponding to the vehicle parts of the at least two vehicles; based on the parts failure probabilities, determine at least two forms of expression of parameter information of key components of the first vehicle model in the first parts list; obtain the first parts list based on the at least two forms of expression, wherein the strength of the prominent performance of the form is positively correlated with the numerical value of the parts failure probability.

[0022] On the other hand, a computer device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement a method for generating a parts list as described in any of the above-mentioned embodiments of the present application.

[0023] On the other hand, a computer-readable storage medium is provided, in which at least one instruction, at least one program, a code set or an instruction set is stored. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement the method for generating a parts list as described in any of the above-mentioned embodiments of the present application.

[0024] In another aspect, a computer program product or computer program is provided. The computer program product or computer program includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for generating a parts list described in any of the above embodiments.

[0025] The beneficial effects of the technical solutions provided in the embodiments of the present application include at least:

[0026] By pre-determining key components from all vehicle parts, automatically generating their corresponding specification numbers and adding them to the parts master data, and filtering the parts list for a specific vehicle based on query criteria, this system automates the acquisition and data processing of vehicle key parts lists. Users can quickly and accurately obtain the required key parts list by entering query criteria, reducing the amount of duplication and unnecessary manual effort involved in collecting and processing vehicle key parts lists, and addressing the inefficiency and error-proneness of manual processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0028] Figure 1 is a schematic diagram of a system for generating a parts list provided by an exemplary embodiment of the present application;

[0029] Figure 2 is a flowchart of a method for generating a parts list provided by an exemplary embodiment of the present application;

[0030] Figure 3 It is a structural block diagram of a device for generating a parts list provided by an exemplary embodiment of the present application;

[0031] Figure 4 It is a structural block diagram of a computer device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0033] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0034] It should be noted that the information and data involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0035] First, a brief introduction to the terms involved in the embodiments of this application is given:

[0036] Bill of Materials (BOM): It is a list that describes the composition structure of a product, listing all the raw materials, parts, semi-finished products and their quantity relationships required to produce the product, and is used to guide production, procurement, cost accounting and logistics management.

[0037] The vehicle's BOM is a structured list of all the parts required for a complete vehicle, including part name, number, quantity, hierarchical relationship and other information. It is used to guide the production, procurement, assembly and cost accounting of the vehicle. It covers the complete assembly structure from the vehicle to the screws, and supports the management of different configurations (such as high- and low-end models).

[0038] The BOM system is a software platform for managing BOM data throughout the entire life cycle of a vehicle. It integrates multiple BOMs, supports version control, configuration management, and multi-system collaboration, and ensures data consistency and traceability from design to production and after-sales.

[0039] The first client in this application corresponds to the BOM system.

[0040] Engineering BOM (EBOM): A bill of materials generated during the product design phase that reflects the product structure and design intent from the engineer's perspective.

[0041] A vehicle's EBOM is a list of vehicle parts defined from an engineering design perspective, reflecting design intent and product structure. EBOM is a list of vehicle parts defined during the design phase, containing technical parameters (such as materials and dimensions) and functional system divisions (such as power systems and electrical systems), and is used for vehicle R&D, design verification, and engineering change management.

[0042] In this application, the first bill of materials refers to the engineering bill of materials for the first model vehicle.

[0043] Critical Components List: This is a document submitted by vehicle manufacturers to relevant departments when applying for product announcements and product certification. It lists the core components (such as batteries and braking systems) that affect vehicle safety, environmental protection, and energy consumption, as well as their models, suppliers, and certification information. The data is derived from the EBOM, but additional qualifications and parameters required by regulations must be supplemented.

[0044] In this application, the first parts list refers to a list of key parts, which includes, in addition to the data in the EBOM (first bill of materials), specification number information (i.e., information such as specifications and models that require regulatory certification).

[0045] Next, the system for generating the parts list involved in the embodiment of the present application is described. For schematic illustration, please refer to Figure 1 The system 100 involves a first client 110 and a second client 120, wherein the first client 110 corresponds to a first data platform and the second client 120 corresponds to a second data platform.

[0046] The first data platform refers to the BOM system, which is the core data platform used by automobile manufacturers to manage the composition relationship of all vehicle components. The first data platform uses a tree structure to completely record the hierarchical relationship from the entire vehicle to the smallest screw, including the technical parameters, supplier information and assembly requirements of each component. During the vehicle development process, the design department uses this system to establish an engineering bill of materials, and the production department converts it into a manufacturing bill of materials to ensure accurate conversion from drawings to actual vehicles. The first data platform can achieve precise control of tens of thousands of parts, support the rapid production scheduling of vehicles with different configurations, and play a key role in cost accounting, quality traceability and other aspects.

[0047] The Second Data Platform refers to the regulatory management system, a professional management platform used by automotive companies to ensure product compliance with the laws and regulations of various countries. The Second Data Platform comprehensively documents automotive technical standards, environmental requirements, and safety regulations for different regional markets, including functions such as product announcement management, mandatory certification submissions, and regulatory change tracking. During the product development phase, the Second Data Platform automatically compares design parameters with regulatory requirements; before mass production, it automatically generates the complete documentation required for MIIT product announcement and mandatory certification submissions; and after sales, it continuously monitors the impact of regulatory changes on in-production models. The Second Data Platform is a crucial guarantee for the compliant launch of automotive products.

[0048] In system 100, the first data platform provides complete vehicle component data, while the second data platform verifies and approves this data according to relevant rules and requirements. Working together, the two platforms ensure both the feasibility of product design and the full compliance of all components and vehicle configurations with legal and regulatory requirements, forming an efficient closed-loop management system from product design to compliance certification.

[0049] In some embodiments, the first data platform corresponds to the first data server 111, and the second data platform corresponds to the second data server 121. The first data server 111 and the second data server 121 are used to provide computing support in the process of generating the parts list.

[0050] There is a communication connection between the first client 110 and the second client 120 .

[0051] The system 100 includes multiple data processing modules, which correspond to different locations of the first data platform and the second data platform respectively, and data interaction can be performed between the data processing modules.

[0052] 1. Key parts library management module: This functional module is created in the first data platform. Its main function is to define the parts in the vehicle that meet the requirements as key parts according to relevant laws, regulations and type certification requirements, and form a key parts library.

[0053] 2. Parts master data module: In the first data platform, it is a core functional module used to centrally manage the basic information of all parts of the enterprise, providing a unique, accurate and unified parts data source for product design, production, procurement, finance and other businesses.

[0054] 3. Parts master data management module: This functional module expands the model and specification-related attributes of the parts master data based on the parts master data module of the first data platform. It is mainly used to manage the application of part numbers, the necessary attribute definitions when applying for part numbers, and automatically associate key parts attributes according to the key parts library, such as: whether the part is a key part, the name of the key part, etc.

[0055] 4. Model and specification management module: This functional module is created in the second data platform. Its main function is to apply for the model and specifications of vehicle parts through electronic processes and obtain specification number information. This module is integrated with the parts master data module in the first data platform. The parts master data module pushes the part numbers of key components to this module according to the rules, including part numbers, key component names, etc.

[0056] 5. Key parts query and pre-processing module: This functional module is created in the first data platform. Its main function is to define the query conditions for the key parts list. It supports multiple composite conditions and fuzzy queries, such as vehicle model, project, market, powertrain (including three electrics: power battery, drive motor, electronic control system), version, effective time, etc. It also obtains the vehicle's EBOM based on the query conditions entered and adds key parts-related attributes to the EBOM.

[0057] 6. Key parts list post-processing and report output module: This functional module is created in the first data platform. Its main function is to convert the pre-processed EBOM into a key parts list report (i.e., the first parts list) according to the key parts list template (i.e., the parts list template), and display it through the key parts report interface. It also supports users to export the parts list in EXCEL (table) format.

[0058] By setting up the above-mentioned multiple modules in system 100, the process of obtaining the list of key vehicle parts and processing data is automated. System 100 can quickly and correctly provide the user with the list of key vehicle parts required by the specified vehicle model, reducing a large amount of repetition and unnecessary manual input in the collection and data processing of the list of key vehicle parts, and solving the problems of low efficiency and easy errors in manual processing.

[0059] Exemplarily, the process of generating a parts list executed by the system 100 mainly includes the following steps:

[0060] Step S1: According to the key component management rules, the product engineer defines the key component requirements in the vehicle product architecture and function name library (which divides the vehicle according to its functional structure and includes a standard library of systems and components at all levels of the vehicle) on the first data platform through the first client 110 to clarify the key components and key component names in the vehicle parts and form a key component library.

[0061] When a new type of vehicle component is added, it is necessary to fill in whether the part is a key component and the name of the key component in the first data platform through the first client 110.

[0062] Among them, the vehicle product architecture and function name library contains two key attributes: the system code and function location code of the parts. The combination of the two can determine the parts of a unique vehicle.

[0063] Step S2: Based on the requirements of vehicle product development, newly developed parts require a new part number and the necessary part attributes. The attributes most relevant to regulations are the part's system code and function location code. First client 110 can automatically determine whether the part is a key component and associate the key component name based on the combination of the system code and function location code entered by the user.

[0064] Based on the above step S2, the system 100 also includes an interface between the first client 110 and the second client 120 (ie, an interface is defined between the first data platform and the second data platform), which is mainly used to transfer part master data.

[0065] Taking the first component as an example, if the first component is a key component, the first data platform automatically transmits the part number, part name, key component name, etc. of the first component to the second data platform through the integrated interface between the first data platform and the second data platform.

[0066] If the first component is not a key component, the part number and attribute transfer process will not be performed.

[0067] Step S3: The product engineer applies for the specification number information (i.e., model specifications) of the parts through the electronic process in the second data platform through the second client 120. The application process requires filling in necessary information such as the part number and supplier code, which includes attributes such as the part name and key component name, all of which are transmitted from the first data platform in step S2.

[0068] In some embodiments, to integrate data scattered across various data platforms and enable unified storage, management, and analysis, companies will simultaneously store all vehicle parts-related data generated during the production process on the big data platform. By accumulating and standardizing raw data, companies can more efficiently conduct big data analysis. A big data platform is a centralized data infrastructure built by an enterprise for the collection, storage, computation, and analysis of massive amounts of heterogeneous data, supporting intelligent decision-making across all business scenarios, from R&D to after-sales service.

[0069] Based on the above step S3, the second data platform regularly transmits the newly added or changed model specification data to the big data platform through the integrated interface between the first data platform and the big data platform. The transmitted data includes part number, specification number information (model specification), supplier code, etc.

[0070] Based on the above steps S1 to S3, the model and specifications of vehicle parts can be defined and filled in the corresponding attributes of the part master data.

[0071] Step S4: Based on the vehicle information to be declared, query conditions such as vehicle model, project, market, powertrain, version, and effective time are entered in the key component query interface of the first data platform. The first data platform obtains the vehicle's EBOM based on the entered query conditions.

[0072] The first data platform obtains the corresponding specification number information (model specification), key component name, supplier code, supplier name, etc. from the big data platform through the part number, and adds it to the EBOM.

[0073] Step S5: Based on step S4, the first data platform obtains a preset parts list template (which includes key component names, model specifications, manufacturer, applicable vehicle model, etc.), processes the corresponding data according to predefined rules, and then fills it into the parts list template to obtain a first parts list. The first parts list is a list of key components for the specified vehicle model. The processed first parts list is displayed to the user through the interface of the first data platform / first client 110.

[0074] Based on the above steps S1 to S5, the acquisition and processing of the vehicle key parts list are completed, and the required vehicle key parts list is provided to the user.

[0075] The terminals running the first client 110 and the second client 120 can be various forms of terminal devices such as mobile phones, tablet computers, desktop computers, portable laptops, smart TVs, car terminals, smart home devices, etc., and the embodiments of the present application are not limited to this.

[0076] It is worth noting that the above-mentioned first data server 111 and second data server 121 can be independent physical servers, or a server cluster or distributed system composed of multiple physical servers. They can also be cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0077] In some embodiments, the first data server 111 and the second data server 121 may also be implemented as nodes in a blockchain system.

[0078] In combination with the above-mentioned noun introduction and application scenarios, the method for generating a parts list provided by this application is described. This method can be executed by a server or a terminal, or by both a server and a terminal. In the embodiment of this application, the method is described as being executed by a terminal (first client). Figure 2 As shown, Figure 2 FIG1 is a flowchart of a method for generating a parts list provided by an exemplary embodiment of the present application. The method includes the following steps.

[0079] Step 210: Obtain part master data marked with key component labels.

[0080] Among them, the parts master data contains parameter information of vehicle parts of at least two vehicles, and the key component labels are used to indicate key components, which are predetermined components.

[0081] For example, the parts master data includes vehicle parts parameter information for model A vehicles and model B vehicles respectively.

[0082] Among them, vehicle type A is a pure electric vehicle, and its vehicle parts parameter information includes at least one of the following: (1) the type, cooling method, supplier information, weight range and operating temperature requirements of the drive motor; (2) the chemical system, charge and discharge performance indicators, cycle life characteristics and safety certification status of the power battery; (3) the material type and corrosion resistance level of the body structure, as well as the detection range and installation location parameters of intelligent driving related sensors (such as cameras and radars).

[0083] Vehicle type B is a hybrid electric vehicle, and its vehicle parts parameter information includes at least one of the following:

[0084] (1) Engine displacement specifications, fuel efficiency standards, and emission compliance levels;

[0085] (2) The energy density range and external discharge function support of the hybrid battery;

[0086] (3) The transmission's architecture type, torque carrying capacity, and insulation protection requirements for parts that differ from traditional fuel vehicles (such as high-voltage wiring harnesses).

[0087] Key components refer to the parts in the whole vehicle that need to undergo compliance review and generate specified specification number information. For example, the parts master data corresponds to the parameter information of all parts corresponding to three vehicle models. The total number of parts is 30,000, of which 500 parts are key components and the remaining parts are not key components.

[0088] The part master data includes sub-data corresponding to these 500 key components, and the sub-data is marked with key component labels.

[0089] That is, there are 500 key component tags in the part master data.

[0090] In some embodiments, the key component label can be expressed as a part attribute that only exists in the key component. For example, only the part attributes of the key component include the attribute of "key component", and the part attributes of the remaining parts do not include this attribute.

[0091] Alternatively, the key component label can also be expressed as the attribute "whether it is a key component" shared by each part. The attribute value of the key component is Y (yes), and the attribute value of the remaining parts is N (no). The attribute with the value Y is determined as the key component label.

[0092] Exemplarily, the first client corresponds to the first data platform (BOM system), establishes a key component library management module in the first data platform, labels the key components in the vehicle product architecture library, and generates / obtains corresponding key component names, etc.

[0093] The vehicle product architecture library is standardized and hierarchical according to the functional structure of the automobile, from the whole vehicle to the parts. Every part in the vehicle can be found in the vehicle product architecture library. Each part is represented by a unique set of codes, which are the functional system code and the functional position code.

[0094] For example, the function system code of the left front seat belt assembly is 461 and the function position code is A00F. That is, the left front seat belt assembly of all vehicles can be found through the combination of 461 and A00F.

[0095] Set preset requirements for each component to define whether it is a key component and the attributes of the key component name to form a key component library.

[0096] Schematically, Table 1 below is a table of key component properties.

[0097] Table 1

[0098]

[0099] Create part master data in the part master data management module of the first data platform, and match key parts information according to the key parts library. The user fills in the part master data attributes in the part master data management module, including part name, function system code, function location code, etc. The system traverses the key parts library according to the filled-in function system code and function location code, and assigns the key parts and key parts name attribute values matched from the key parts library to the corresponding attributes of the part master data, completing the key parts labeling process. Optionally, the process of determining key parts is as follows: obtain the preset key parts requirements, perform matching analysis on the whole vehicle parts based on the key parts requirements, and determine the key parts in the whole vehicle parts.

[0100] The part master data is labeled based on the part identification of the key parts to obtain the part master data labeled with the key parts labels.

[0101] Among them, key components usually refer to components that have a decisive impact on vehicle safety performance, environmental compliance, and core functions. Their failure or non-compliance may lead to serious safety hazards, legal risks, or loss of product functions.

[0102] Optionally, the preset key component requirements include at least one of the following: (1) Safety: the component is directly related to driving safety; (2) Endurance impact: the component is directly related to the vehicle's endurance; (3) Cost ratio: the component's cost ratio in the vehicle's overall parts must meet a fixed requirement; (4) Repairability: whether the component is repairable / replaceable; (5) Supply chain risk: whether the supply chain quantity of the component reaches a specified quantity threshold, etc. Exemplarily, in response to at least one component in the overall vehicle having a matching degree with the key component requirements that reaches a preset matching threshold, the at least one component is determined to be a key component.

[0103] For example, the matching degree (percentage) is converted into a score (full score is 100 points), the preset matching threshold is 85 points, and the score between each part and the key component requirements is calculated separately.

[0104] The hierarchical analysis method is used to determine the five dimensions and weights of key component requirements as follows: safety (30%), endurance impact (25%), cost share (20%), maintainability (15%), and supply chain risk (10%).

[0105] Using a pre-trained scoring model, each part is scored on a scale of 0-100 based on different dimensions, generating quantifiable data that is then normalized. For each part, a weighted score is calculated: Safety score × 30% + Range impact score × 25% + Cost contribution score × 20% + Maintainability score × 15% + Supply chain risk score × 10%.

[0106] For example, the component is a battery pack: safety is 95 points, battery life impact is 100 points, cost is 90 points, maintainability is 80 points, and supply chain risk is 85 points. The calculated weighted score is 92 points, which exceeds 85 points and is a key component.

[0107] For example, the component is a door interior panel: safety is 60 points, battery life impact is 50 points, cost is 65 points, maintainability is 70 points, and supply chain risk is 75 points. The calculated weighted score is 65 points, which is lower than 85 points and is a non-critical component.

[0108] In some embodiments, critical components can be determined based on other conditions, such as failure risk. For non-critical components whose weighted score differs from the preset matching threshold by less than a difference threshold (e.g., 1 point), the failure risk of the component is calculated. If the failure risk result indicates that the component has a failure risk higher than a preset frequency, the component is still determined to be a critical component. For example, the weighted score of a chassis connector is 84.5 points, which is lower than the preset matching threshold of 85 points. The difference between the two is 0.5 points, which is less than the difference threshold of 1 point. However, the analysis shows that its failure risk is high, so it is determined to be a critical component.

[0109] In some embodiments, historical traffic event data of at least two vehicles can be obtained, and a pre-trained artificial intelligence model can automatically analyze the types of components that are prone to failure and cause traffic accidents, and identify components that meet preset failure requirements as key components.

[0110] For example, historical traffic event data includes information such as accident details and vehicle maintenance records. First, this data is organized into a format suitable for model analysis, mapping information such as the vehicle's condition at the time of the accident, the damaged area, and the parts replaced during repairs.

[0111] The converted data is fed into a pre-trained model, which outputs the names of key components. The model then mines the input data for associations. For example, if a certain component frequently appears in maintenance records of vehicles involved in accidents due to failure, and the failure scenarios are similar, such as frequent accidents caused by the same component at high speeds, the model will identify it as a component prone to failure.

[0112] The preset failure requirements include at least one of the following: (1) the number of component failures reaches a preset value, (2) the severity of the accident caused by the component failure reaches a preset range, etc. Analyze the components that are prone to failures leading to accidents. If there is a component that meets at least one of the above failure requirements, it will be determined as a critical component.

[0113] Step 220: Obtain specification number information corresponding to key components.

[0114] Specification number information refers to the compliance parameters generated by matching according to product industry standards, which is used to indicate the specification model range of the component.

[0115] For example, the thickness of a component should be between 2-3 mm. The specification number information of the component refers to the model code that contains this compliance parameter. The specification number information code will be marked in the key parts list.

[0116] Optionally, the part master data is sent to a second client, which is used to review the part master data based on preset rules and generate specification number information if the review is passed.

[0117] Receive the specification number information sent by the second client.

[0118] Among them, the second client corresponds to the second data platform (regulations management system), and there is an interface between the first data platform and the second data platform, and data interaction can be carried out through the interface.

[0119] For example, the first client transfers the part master data from the first data platform to the second data platform. The transferred information mainly includes at least one of the following attribute fields:

[0120] 1. Part number: A unique number assigned to each part to facilitate identification, management and tracking of automotive parts.

[0121] 2. Part name: It is the specific name of the auto parts, used to describe the function, shape or position of the part in the car and other characteristics.

[0122] 3. First applicable vehicle model: refers to the specific vehicle model for which the component was originally designed and applied.

[0123] 4. First applicable project: The specific project name or production batch and other information where the component is first used in automobile manufacturing or related projects.

[0124] 5. Is it a key component? The value includes two situations: "Yes" / "No", which is used to indicate whether the current component is a key component.

[0125] 6. Name of key component: If the current component is a key component, its specific name will be clearly written here.

[0126] 7. Engineer Name: refers to the name of the engineer responsible for the design, development, testing, etc. of the automotive parts.

[0127] In some embodiments, the first data platform periodically transmits newly added or changed part master data to the second data platform.

[0128] A model specification management module is established in the second data platform to generate model specifications of key components and obtain specification number information. The model specification management module defines the application process for model specifications.

[0129] Users initiate the model specification application process through the Model Specification Management Module on the Second Data Platform, entering information such as the part numbers of key components. Once the application is submitted, the Model Specification Management Module automatically assigns the model specification based on the model specification coding rules. After approval, the model specification is published and the specification number information is obtained.

[0130] At this time, the second client returns the specification number information to the first client through the interface between the second data platform and the first data platform.

[0131] In some embodiments, the second data platform will periodically transmit the incremental data in the model and specification management module to the enterprise's big data management platform (hereinafter referred to as the big data platform). The incremental data includes newly added, changed, and invalid part numbers and model specifications. The transmitted data includes part numbers, part number names, model specifications, supplier codes, supplier names, etc. This process can be called data entry into the lake (referring to the enterprise data lake, which is an ultra-large-scale repository that centrally stores various types of raw data and can accommodate data streams from various enterprise systems without filtering. These data include structured database tables, semi-structured log files, unstructured images and videos, etc., all saved in their original formats).

[0132] Step 230 , adding the specification number information to the position corresponding to the key component in the part master data to obtain updated part master data.

[0133] Exemplarily, a new data column is added to the parts master data: a specification information column, which is used to store the specification number information corresponding to the key parts.

[0134] For example, part master data stores various parameter information for 30,000 parts in a data table format, corresponding to 30,000 data rows and 10 data columns. Each data row is used as a data item to store the parameter information of a part, and each data column is used as a parameter type to represent different part properties. An 11th data column is added to the part master data as a specification information column. Based on the key component tags, the corresponding position of the key component in the part master data is indexed. The specification number information corresponding to each key component is filled in the 11th column of the corresponding data row to obtain the updated part master data.

[0135] Exemplarily, in the key component query and pre-processing module in the first data platform, at least one query condition is input to obtain specification number information and complete data pre-processing. After the first data platform receives the bill of materials generation operation, it matches the corresponding configuration and performs engineering solution to obtain the vehicle EBOM.

[0136] Obtain the part numbers in the EBOM, delete duplicate part numbers, form a unique parts list, and send this list to the big data platform through the interface between the BOM system and the big data platform.

[0137] After the big data platform receives the parts uniqueness list sent by the first data platform, it matches the specification number information according to the part number in the parts uniqueness list, such as model specifications, supplier code, supplier name, etc., and returns the specification number information to the first data platform.

[0138] The first data platform receives the specification number information returned by the big data platform, matches the corresponding attributes according to the part number, and completes the matching of data such as the part number and the specification number information.

[0139] Step 240 , obtaining query conditions, and filtering to obtain a first parts list based on the query conditions and the updated parts master data.

[0140] The query condition is used to instruct acquisition of parameter information of key components of the first vehicle model, and the parameter information includes specification number information of the key components of the first vehicle model.

[0141] That is, the query condition is used to instruct to obtain a list of key parts (a first parts list) of a vehicle of a specified model.

[0142] Exemplarily, the query condition includes at least one of the following information:

[0143] 1. Vehicle type: refers to the basic model classification of a vehicle, representing a complete product series, including specific exterior design, chassis platform and core configuration.

[0144] 2. Project: The internal code name during vehicle development, used for R&D stage management (e.g., the first vehicle model corresponds to Project E28), usually containing model iteration information (e.g., generation change, mid-term facelift).

[0145] 3. Market: The target area for vehicle sales, divided according to regulations and demand. Different markets may involve different safety standards, charging interfaces and other adaptation requirements.

[0146] 4. Powertrain (including three electric systems: power battery, drive motor, and electronic control system): The vehicle's power system combination. New energy vehicles specifically refer to the "three electric systems". The power battery is an energy storage device, the drive motor is a device that converts electrical energy into mechanical energy, and the electronic control system is the core of managing energy distribution.

[0147] 5. Version: The specific configuration version of the same car model (such as standard version and smart driving version), which distinguishes price levels through differences in seat materials, smart driving hardware and other configurations.

[0148] 6. Effective date: The date when the configuration begins to apply (e.g. the effective date of the "2024 model" vehicle configuration is September 2023).

[0149] Optionally, a bill of materials generation operation is received, where the bill of materials generation operation includes a query condition.

[0150] The updated parts master data is filtered based on the query condition to obtain a first bill of materials, which includes parameter information of vehicle parts for a first vehicle model.

[0151] A first parts list is obtained by filtering the first bill of materials based on key component tags.

[0152] That is, based on the query conditions, it is determined that the vehicle type for which the key parts list needs to be obtained is the first model. Since the parts master data includes part parameter information of at least two models of vehicles, it is necessary to first filter out the data corresponding to the first model of vehicle from the parts master data and organize it to obtain the first bill of materials.

[0153] For example, the BOM generation operation includes the following query conditions: (1) Model: Brand A Z Series 2025, indicating that the vehicle model is a new model in the Z series launched by Brand A and released in 2025; (2) Project: Project Z, specifying that the production project name of the vehicle is Z; (3) Market: Region 2340, specifying that the sales market of the vehicle is the region numbered 2340. The region number is generated based on a preset rule and each region has a different number; (4) Powertrain: 2.0L naturally aspirated engine with CVT (Continuously Variable Transmission) transmission, specifying that the engine displacement of the vehicle is 2 liters and the intake mode is "naturally aspirated". The transmission type is a continuously variable transmission. This transmission transmits power through a transmission belt and a master and slave wheel with variable working diameters, which can achieve continuous change of the transmission ratio, thereby obtaining the best match between the transmission system and the engine operating conditions; (5) Effective time: January 1, 2025, indicating the effective time of the first BOM.

[0154] After receiving the BOM generation request, the first data platform automatically integrates the above query conditions to produce the query statement: "Search for EBOM information for 2025 Z-series models of Brand A, in Project Z, targeting Region 2340 markets, equipped with a 2.0L naturally aspirated engine and CVT transmission, effective January 1, 2025." This query statement guides the first data platform to automatically generate the first BOM.

[0155] Then, based on the key component labels, relevant data of the required key components are filtered out from the first bill of materials and integrated to obtain the first parts list.

[0156] Exemplarily, a parts list template is obtained, where the parts list template is used to instruct generation of a first parts list.

[0157] Based on the key component tags, the first bill of materials is filtered to obtain bill of materials lines corresponding to the key components of the first vehicle model.

[0158] Synchronize the part parameter information in the material list row to the parts list template to obtain the first parts list.

[0159] Indicatively, the parts list template is shown in Table 2 below. Using the key component name as the keyword, the model specification, manufacturer, and applicable vehicle model announcement number of the material list line with the same key component name are filled in the corresponding row, and the date is the date of the parts list query.

[0160] The form obtained by synchronously filling in the information based on Table 2 below is the first parts list.

[0161] The first client can display the first parts list online to the user through a display interface. The user can also choose to export the first parts list in a specified format to obtain a first parts list file, which is not limited in this embodiment.

[0162] Table 2

[0163]

[0164] In some embodiments, during the process of filling the contents of the bill of materials line into the parts list template, or after obtaining the first bill of materials, the parts information belonging to different key components in the first parts list can be displayed using different styles to intuitively understand the importance of each key component in the first parts list.

[0165] Optionally, historical traffic event data of at least two vehicles is obtained, where the historical traffic event data is used to indicate situations in which traffic events occurred in at least two vehicles within a historical time period.

[0166] Based on the historical traffic incident data, fault analysis is performed to obtain the corresponding part failure probabilities of at least two vehicle parts.

[0167] Based on the probability of component failure, at least two representations of parameter information of key components of the first vehicle model in the first parts list are determined.

[0168] A first parts list is obtained based on at least two representation forms, wherein the strength of the representation form is positively correlated with the value of the part failure probability.

[0169] Exemplarily, at least two vehicles are models developed and produced by a certain enterprise, including 10 vehicles that have been sold and a new vehicle to be inspected for compliance (the first model vehicle corresponding to the first parts list).

[0170] Obtain after-sales maintenance record data for sold cars. After-sales maintenance record data refers to the public maintenance records synchronized to the enterprise big data platform when sold cars undergo after-sales maintenance.

[0171] Among them, the after-sales maintenance record data includes the reasons for maintenance (for example, replacement due to natural factors due to the service life of parts, replacement due to non-natural factors caused by historical traffic incidents) and part parameters of the repaired parts (such as part number).

[0172] Part parameters of repair parts replaced due to non-natural factors when historical traffic incidents occurred are screened out from after-sales maintenance record data to obtain historical traffic incident data.

[0173] Based on historical traffic event data, the part types and part numbers of all parts appearing therein are obtained, and the number of occurrences of each part in the historical traffic event data is counted separately. The historical traffic event data includes the total number of data. For each part, the part failure probability of the part is calculated based on "number of occurrences / total number of data".

[0174] For example, the representation is the order of the key components in the first parts list. The key components are sorted in descending order based on the probability of component failure, and the key components with higher probability of component failure are positioned higher in the first parts list.

[0175] For example, there are four key components with the following corresponding part failure probabilities: Part 1 is 0.23, Part 2 is 0.04, Part 3 is 0.50, and Part 4 is 0.12. The order of arrangement is as follows: Part 3 (serial number 1), Part 1 (serial number 2), Part 4 (serial number 3), Part 2 (serial number 4), arranged from top to bottom in the first parts list. In this example, the strength of the performance is the position of the key component information in the first parts list; the higher the position, the stronger the strength of the performance.

[0176] In some embodiments, the expression form also includes at least one of the following: the font / font size / color, etc. of the key component information in the first parts list, and the corresponding expression form's highlighting intensity is the font type / font size / color type, etc.

[0177] For example, taking the highlighting intensity expressed in the form of font size as an example, the probability of part failure is divided into a intervals, each interval corresponds to a different font size, wherein the value of the right endpoint of the interval is positively correlated with the font size.

[0178] For example, a is 3, corresponding to interval 1 [0, 0.1], interval 2 [0.1, 0.3], and interval 3 [0.3, 1]. Interval 1 corresponds to a font size of 20, interval 2 corresponds to a font size of 24, and interval 3 corresponds to a font size of 28. The display font size of the key component information in the first parts list is determined according to the probability interval to which the part failure probability of each key component belongs.

[0179] In summary, the parts list generation method provided in this application predetermines the key components among all vehicle parts, automatically generates the corresponding specification number information for these key components, and simultaneously adds it to the parts master data. Based on query criteria, the parts list for a specific vehicle is obtained, thereby automating the acquisition and data processing of the vehicle's key parts list. Users can quickly and accurately obtain the required key parts list by entering query criteria, reducing the amount of duplication and unnecessary manual effort involved in collecting and processing the vehicle's key parts list, and resolving the inefficiency and error-proneness inherent in manual processing.

[0180] Figure 3 This is a structural block diagram of a device for generating a parts list provided by an exemplary embodiment of the present application. Figure 3 As shown, the device includes the following parts.

[0181] An acquisition module 310 is configured to acquire part master data labeled with a key component tag, wherein the part master data includes parameter information of vehicle parts for at least two vehicles, wherein the key component tag is used to indicate a key component, and the key component is a predetermined component;

[0182] The acquisition module 310 is further configured to acquire specification number information corresponding to the key components;

[0183] An updating module 320 is configured to add the specification number information to a position corresponding to the key component in the part master data to obtain updated part master data;

[0184] The acquisition module 310 is further used to obtain query conditions and filter out a first parts list based on the query conditions and the updated parts master data, wherein the query conditions are used to indicate the acquisition of parameter information of key components of a first model vehicle, and the parameter information includes the specification number information of the key components of the first model vehicle.

[0185] In an optional embodiment, the acquisition module 310 is further used to obtain preset key component requirements; perform matching analysis on the vehicle parts based on the key component requirements to determine the key components in the vehicle parts; and label the part master data based on the part identification of the key components to obtain the part master data labeled with the key component label.

[0186] In an optional embodiment, the acquisition module 310 is further configured to determine the at least one part in the vehicle parts as the key component in response to the matching degree between the at least one part and the key component requirement reaching a preset matching threshold.

[0187] In an optional embodiment, the acquisition module 310 is also used to send the part master data to a second client, and the second client is used to review the part master data based on preset rules and generate the specification number information if the review is passed; and receive the specification number information sent by the second client.

[0188] In an optional embodiment, the acquisition module 310 is further used to receive a bill of materials generation operation, which includes the query conditions; based on the query conditions, the updated parts master data is filtered to obtain the first bill of materials, which includes parameter information of the whole vehicle parts of the first model vehicle; based on the key component labels, the first parts list is filtered from the first bill of materials.

[0189] In an optional embodiment, the acquisition module 310 is further used to obtain a parts list template, which is used to instruct the generation of the first parts list; based on the key component labels, the material list lines corresponding to the key components of the first vehicle model are filtered from the first material list; and the part parameter information in the material list lines is synchronized to the parts list template to obtain the first parts list.

[0190] In an optional embodiment, the acquisition module 310 is further used to obtain historical traffic event data of the at least two vehicles, the historical traffic event data being used to indicate situations in which traffic events occurred in the at least two vehicles within a historical time period; perform fault analysis based on the historical traffic event data to obtain part failure probabilities corresponding to the vehicle parts of the at least two vehicles; determine at least two forms of expression of parameter information of key components of the first vehicle model in the first parts list based on the part failure probabilities; obtain the first parts list based on the at least two forms of expression, wherein the strength of the prominent performance of the form is positively correlated with the numerical value of the part failure probability.

[0191] In summary, the parts list generation device provided by this application predetermines the key components among all vehicle parts, automatically generates the corresponding specification number information for these key components, and simultaneously adds it to the parts master data. Based on query criteria, it then filters and obtains the parts list for a specified vehicle, thereby automating the acquisition and data processing of the vehicle's key parts list. Users can quickly and accurately obtain the required key parts list by entering query criteria, reducing the significant duplication and unnecessary manual effort involved in collecting and processing the vehicle's key parts list, and resolving the inefficiency and error-prone nature of manual processing.

[0192] It should be noted that the parts list generation device provided in the above embodiment is merely exemplified by the division of the aforementioned functional modules. In actual applications, the aforementioned functions can be assigned to different functional modules as needed, i.e., the internal structure of the device can be divided into different functional modules to perform all or part of the functions described above. Furthermore, the parts list generation device provided in the above embodiment and the parts list generation method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0193] Figure 4 The following is a block diagram of a computer device 400 according to an exemplary embodiment of the present application. Computer device 400 may be a smartphone, a tablet computer, a Moving Picture Experts Group Audio Layer III (MP3) player, a Moving Picture Experts Group Audio Layer IV (MP4) player, a laptop computer, or a desktop computer. Computer device 400 may also be referred to as a user device, a portable terminal, a laptop terminal, a desktop terminal, or other similar names.

[0194] Typically, the computer device 400 includes a processor 401 and a memory 402 .

[0195] The processor 401 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 401 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 401 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 401 may be integrated with a graphics processing unit (GPU), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 401 may also include an artificial intelligence (AI) processor, which is used to process computing operations related to machine learning.

[0196] Memory 402 may include one or more computer-readable storage media, which may be non-transitory. Memory 402 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in memory 402 is used to store at least one instruction, which is executed by processor 401 to implement the parts list generation method provided in the method embodiment of the present application.

[0197] In some embodiments, the computer device 400 further includes some other components 403, and the type and quantity of the other components 403 can be selected based on the functional requirements of the computer device 400. It will be understood by those skilled in the art that Figure 4 The structure shown in the figure does not constitute a limitation on the computer device 400, and the computer device 400 may include more or fewer components than shown in the figure, or combine some components, or adopt a different component arrangement.

[0198] Optionally, the computer-readable storage medium may include: Read Only Memory (ROM), Random Access Memory (RAM), Solid State Drives (SSD), or an optical disk. Among them, the random access memory may include resistance random access memory (ReRAM) and dynamic random access memory (DRAM). The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0199] An embodiment of the present application also provides a computer device, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the method for generating a parts list as described in any of the above embodiments of the present application.

[0200] An embodiment of the present application also provides a computer-readable storage medium, in which at least one instruction, at least one program, a code set or an instruction set is stored. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement a method for generating a parts list as described in any of the above embodiments of the present application.

[0201] The present application also provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the parts list generation method described in any of the above embodiments.

[0202] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0203] The above description is merely an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for generating a parts list, characterized in that: Executed by a first client, the method includes: Obtaining part master data marked with a key component label, the part master data including parameter information of vehicle parts for at least two vehicles, the key component label being used to indicate a key component, and the key component being a predetermined component; Obtain specification number information corresponding to the key components; Adding the specification number information to the position corresponding to the key component in the part master data to obtain updated part master data; Obtain query conditions, and obtain a first parts list based on the query conditions and the updated parts master data through screening, wherein the query conditions are used to indicate obtaining parameter information of key components of a first vehicle model, the parameter information including the specification number information of the key components of the first vehicle model.

2. The method according to claim 1, characterized in that The obtaining of the part master data marked with key component labels includes: Obtain preset key component requirements; Perform matching analysis on the vehicle parts based on the key component requirements to determine the key components in the vehicle parts; The part master data is labeled based on the part identification of the key component to obtain the part master data labeled with the key component label.

3. The method according to claim 2, characterized in that The matching analysis of the vehicle parts based on the key component requirements to determine the key components in the vehicle parts includes: In response to at least one part in the complete vehicle parts having a matching degree with the key component requirement reaching a preset matching threshold, the at least one part is determined as the key component.

4. The method according to claim 1, wherein The obtaining of specification number information corresponding to the key components includes: Sending the part master data to a second client, the second client being configured to review the part master data based on preset rules and generating the specification number information if the review passes; Receive the specification number information sent by the second client.

5. The method according to any one of claims 1 to 4, characterized in that: The obtaining of query conditions and filtering to obtain a first parts list based on the query conditions and the updated parts master data includes: receiving a bill of materials generation operation, wherein the bill of materials generation operation includes the query condition; Filtering the updated parts master data based on the query condition to obtain the first bill of materials, wherein the first bill of materials includes parameter information of vehicle parts for the first vehicle model; The first parts list is obtained by screening the first bill of materials based on the key component tags.

6. The method according to claim 5, characterized in that The step of filtering the first parts list from the first bill of materials based on the key component tags includes: Obtaining a parts list template, where the parts list template is used to instruct generation of the first parts list; Filtering the first bill of materials based on the key component tags to obtain bill of materials rows corresponding to the key components of the first vehicle model; The part parameter information in the material list row is synchronized with the parts list template to obtain the first parts list.

7. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Acquiring historical traffic event data of the at least two vehicles, where the historical traffic event data is used to indicate situations in which traffic events occurred in the at least two vehicles within a historical time period; Performing fault analysis based on the historical traffic event data to obtain component failure probabilities corresponding to the vehicle components of the at least two vehicles; Based on the component failure probability, determining at least two representations of parameter information of key components of the first vehicle model in the first parts list; The first parts list is obtained based on the at least two forms of expression, wherein the prominence intensity of the form of expression is positively correlated with the numerical value of the part failure probability.

8. A device for generating a parts list, characterized in that: The device comprises: an acquisition module, configured to acquire part master data labeled with a key component tag, the part master data comprising parameter information of vehicle parts for at least two vehicles, the key component tag being used to indicate a key component, the key component being a predetermined component; The acquisition module is further used to obtain specification number information corresponding to the key components; An updating module, configured to add the specification number information to a position corresponding to the key component in the part master data to obtain updated part master data; The acquisition module is further used to obtain query conditions and filter out a first parts list based on the query conditions and the updated parts master data, wherein the query conditions are used to indicate the acquisition of parameter information of key components of a first model vehicle, and the parameter information includes the specification number information of the key components of the first model vehicle.

9. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one program, and the at least one program is loaded and executed by the processor to implement the method for generating a parts list according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The storage medium stores at least one program, and the at least one program is loaded and executed by the processor to implement the method for generating a parts list according to any one of claims 1 to 7.

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