A method and system for precise regression management of vehicle parts

Abstract

This application discloses a method and system for precise regression management of vehicle parts, relating to the field of product data management technology. The method includes constructing a comprehensive product structure tree for the entire vehicle; configuring vehicle identifier definitions for each instantiated model, with each functional configuration having an identifier code; using the identifier code to configure configuration expressions for blocks, representing the logical relationship between the block and the vehicle's functional configurations; upon receiving an externally sent part query command, using a recursive calculation method to query the block to which the part belongs according to the hierarchical structure, using the configuration expression to calculate the instantiated model to which the block belongs, and using the recursive calculation method to query the vehicle series to which the instantiated model belongs. This application can query the attribution information of parts using a combination of recursive calculation and configuration calculation, reducing the computational load in the block-to-instanced model query stage and improving the management efficiency of parts.

Description

Technical Field

[0001] This application relates to the field of product data management technology, specifically to a method and system for precise regression management of vehicle parts. Background Technology

[0002] A car company typically has several vehicle series, each vehicle series has several base models, each base model has several instantiated neutral models, each instantiated neutral model has several instantiated models, each instantiated model has several modules, and each module has several assemblies and parts. An instantiated model usually has around 4,000 parts. Therefore, it's clear that parts management is a very complex undertaking for a car company.

[0003] In automotive R&D and data management, there is a significant need for attribution information of vehicle components under specific conditions. This places higher demands on the timeliness and accuracy of data attribution information acquisition. Three common scenarios are illustrated below:

[0004] (1) Product Data Attribution Inquiry. During the development of new car models, designers need to select design schemes and identify special parts for the components they are responsible for. This requires designers to have a thorough understanding of the existing design schemes (already used in car models) for the components they are responsible for. Since there are usually multiple design schemes for the same component name, designers need to know which car models these schemes are used on in order to analyze whether these design schemes can be reused, modified, or redesigned in conjunction with environmental factors. The process of finding component attribution is difficult for designers through offline management. At the same time, due to changes in responsible personnel or untimely tracking and control, there may be omissions in component design scheme information and misjudgments of special part information, resulting in duplicate research and development design and seriously affecting the efficiency of research and development design.

[0005] (2) Manufacturing Data Attribution Query. During the design change control process, data management engineers need to analyze the vehicle models to which the assemblies or parts involved in the design change belong on the current date. This allows for further analysis of whether the design change affects new or mass-produced models, determining the affected models and developing control measures. This requires generating and exporting the MBOM (Model Name, Manufacturing Organization Name) for all new and mass-produced models effective on the current date. The engineers then search the MBOM for the assemblies or parts involved in the design change and match them to their respective vehicle models. The entire process requires manual offline querying, which is very inefficient.

[0006] (3) Manufacturing data attribution query. When tracing issues related to the implementation and control of vehicle design changes, it is necessary to determine the usage of the target assembly or component on a specific vehicle model within a certain production center and time period. Currently, this can only be achieved by querying and analyzing the offline product evolution implementation and control table. However, the query and analysis efficiency is low, and it cannot intuitively express the usage of the target assembly or component on various vehicle models, including information such as adoption, cancellation, and time.

[0007] The following technical problems exist in the prior art:

[0008] (1) It is impossible to calculate the assembly, block, basic vehicle model, instantiated neutral vehicle, instantiated vehicle model, or vehicle series to which the target component belongs at the set time point (product data release time), and it cannot support rapid design scheme selection and special part identification.

[0009] (2) It is impossible to calculate the assembly, block, instantiated vehicle model, instantiated neutral vehicle model, base vehicle model, or vehicle series to which the target component belongs at the set production center and time point (manufacturing data effective time), thus making it impossible to achieve rapid and accurate control and impact analysis of design changes.

[0010] (3) It is impossible to calculate the usage of target components in various vehicle models at the set production center and time period (manufacturing data effective time), and it cannot provide fast, accurate and intuitive data support for the source analysis and handling of on-site problems in the implementation of vehicle design and control. Summary of the Invention

[0011] To address the shortcomings of existing technologies, the purpose of this application is to provide a method and system for accurate regression management of vehicle parts, which can use a combination of recursive and configuration solutions to query the ownership information of parts, reduce the computational load from querying blocks to instantiating the vehicle model, and improve the management efficiency of parts.

[0012] To achieve the above objectives, the technical solution adopted is:

[0013] The first aspect of this application provides a method for precise regression management of vehicle parts, including:

[0014] Construct a comprehensive product structure tree for the entire vehicle; configure a vehicle identifier definition for each instantiated model in the comprehensive product structure tree, the vehicle identifier definition includes all functional configurations of the model, each functional configuration has an identifier code, the identifier code includes a basic identifier code, a description identifier code, and a color identifier code; using the identifier code, configure a configuration expression for each block in the comprehensive product structure tree, the configuration expression is used to represent the logical relationship between the block and the functional configuration of the entire vehicle;

[0015] Upon receiving a part query command from an external source, the system uses a recursive calculation method to query the product comprehensive structure tree according to the hierarchical structure to obtain the first belonging information of the part. The first belonging information includes the block to which the part belongs. The system uses the configuration expression to solve for the instantiated vehicle model to which the block belongs. Using a recursive calculation method, the system queries the product comprehensive structure tree according to the hierarchical structure to obtain the second belonging information of the instantiated vehicle model. The second belonging information includes the vehicle series to which the instantiated vehicle model belongs. The first belonging information, the instantiated vehicle model, and the second belonging information of the part are then output as the query results.

[0016] In some embodiments, the product integrated structure tree, from the root node to the leaf node, consists of vehicle series, base vehicle model, instantiated mid-size vehicle model, instantiated vehicle model, module, assembly, and part.

[0017] In some embodiments, the functional configurations that the corresponding instantiated vehicle model has in the vehicle identification definition are marked as S, and the functional configurations that the corresponding instantiated vehicle model does not have are marked as empty.

[0018] In some embodiments, when the relationship between a block and the overall vehicle function configuration is expressed by a flag encoding, the configuration expression of that block does not contain the logical relationship.

[0019] In some embodiments, when the relationship between a block and the overall vehicle function configuration is expressed by multiple flags, the configuration expression of the block includes AND, OR, and NOT relationships.

[0020] In some embodiments, the method further includes:

[0021] Each node in the product's comprehensive structure tree is configured with a product data release time and a manufacturing data effective time period. The product data release time is the release time of the corresponding node, and the manufacturing data effective time period is the application time period of the corresponding node.

[0022] In some embodiments, the method further includes:

[0023] Upon receiving a part query command from an external source, the system queries the release status of the corresponding part and its parent node at or after that time, based on the query time specified in the command; and...

[0024] When a part query command is received from an external source, the application status of the corresponding part and its parent node during the specified time period is queried according to the query time period contained in the part query command.

[0025] In some embodiments, the method further includes:

[0026] Configure a production center for the instantiated vehicle model node in the product's comprehensive structure tree, where the production center is the application location of the corresponding node.

[0027] In some embodiments, the method further includes:

[0028] When a part query command is received from an external source, the application status of the corresponding part in that production center is queried based on the production center included in the part query command.

[0029] A vehicle parts precision regression management system includes:

[0030] The preprocessing module is used to construct a comprehensive product structure tree for the entire vehicle; it is also used to configure a vehicle identifier definition for each instantiated model in the comprehensive product structure tree, wherein the vehicle identifier definition includes all functional configurations of the model, and each functional configuration has an identifier code, wherein the identifier code includes a basic identifier code, a description identifier code, and a color identifier code; it is also used to configure a configuration expression for each block in the comprehensive product structure tree based on the identifier code, wherein the configuration expression is used to represent the logical relationship between the block and the functional configuration of the entire vehicle;

[0031] The query module, upon receiving a part query command from an external source, uses a recursive calculation method to query the product comprehensive structure tree according to the hierarchical structure to obtain the first belonging information of the part, which includes the block to which the part belongs. It then uses the configuration expression to calculate the instantiated vehicle model to which the block belongs, and uses a recursive calculation method to query the product comprehensive structure tree according to the hierarchical structure to obtain the second belonging information of the instantiated vehicle model, which includes the vehicle series to which the instantiated vehicle model belongs. The module is also used to output the first belonging information, the instantiated vehicle model, and the second belonging information of the part as the query result.

[0032] The beneficial effects of the technical solution provided in this application include:

[0033] (1) By using product data regression calculation, the assembly, module, instantiated vehicle model, instantiated neutral vehicle model, basic vehicle model, and vehicle series to which the target component belongs at a set time point (product data release time) can be accurately calculated with one click, supporting rapid design scheme selection and special part identification, significantly improving the efficiency of vehicle R&D and reducing R&D costs.

[0034] (2) By using manufacturing data regression calculation, the assembly, module, instantiated vehicle model, instantiated neutral vehicle model, base vehicle model, and vehicle series to which the target component belongs at the set production center and time point (manufacturing data effective time) can be accurately calculated with one click. This supports rapid and accurate control and impact analysis of design changes, significantly improving the efficiency of vehicle design change implementation and control, and reducing the control error rate.

[0035] (3) By using manufacturing data regression calculation, the usage of target parts in each vehicle model at the set production center and time period (manufacturing data effective time) can be accurately calculated with one click. This provides fast, accurate and intuitive data support for the source analysis and handling of on-site problems in the implementation and control of vehicle design changes, and significantly improves the efficiency of source analysis and handling of problems in the implementation and control of vehicle design changes. Attached Figure Description

[0036] Figure 1 This is a flowchart of the precise regression management method for vehicle parts in an embodiment of the present invention.

[0037] Figure 2 This is a schematic diagram of the functional modules of the vehicle parts precision regression management system in an embodiment of the present invention. Detailed Implementation

[0038] The present application will be further described in detail below with reference to the accompanying drawings and embodiments.

[0039] Parts regression calculation: refers to calculating the model or series to which a part belongs under set conditions.

[0040] Product data: The basic data expressing design attributes. Key attribute information includes functional group number, level, function code, Chinese name of function code, encoding, Chinese name, change mark, identification code, configuration expression, maturity level, type, material, color code, etc.

[0041] Manufacturing data: The basic data that expresses functions and processes. Based on product data, it assigns manufacturing attributes such as process route, start time, and end time to parts and components. It is one of the basic data that guides procurement, process, production, and finance.

[0042] An EBOM (Engineering Bill of Materials) is a data structure created based on product functions to manage the definitions and diversity of vehicle models / engine types and their constituent modules and components. It precisely describes the product's design specifications and the relationships between vehicle models / engine types and modules, modules and parts, and parts themselves. Key attributes of the EBOM include functional group number, level, function code, Chinese name of the function code, code, Chinese name, change flag, identifier, configuration expression, maturity level, type, material, and color code.

[0043] MBOM (Manufacturing Bill of Materials) is the basic data that expresses the function and process of manufacturing. It assigns manufacturing attributes to parts based on the product bill of materials and is one of the basic data that guides procurement, process, production and finance.

[0044] Vehicle series: A collective term for a group of basic vehicle models with the same brand and body style within the same product series. For confidentiality and ease of project management, vehicle models are named using project codes.

[0045] Basic model: Under the same model, the corresponding basic configurations such as different configuration levels and power units are called basic model codes, which are 11 digits long and consist of numbers and letters.

[0046] Instantiated neutral vehicle type: Under the same base vehicle type, different equipment corresponding to different vehicle types with optional features and without colors, the corresponding code consists of 14 digits and letters.

[0047] Instantiated vehicle models: Under the same base vehicle model, different equipment corresponding to different models with optional features and colors, the corresponding codes are composed of 18 digits and letters.

[0048] Production center: indicates the location where a vehicle model is produced or where its parts are manufactured or used.

[0049] like Figure 1 As shown, this invention provides a method for precise regression management of vehicle parts, including constructing a comprehensive product structure tree for the entire vehicle; configuring vehicle identifier definitions for each instantiated model, including all functional configurations of the model, each functional configuration having an identifier code, including a basic identifier code, a description identifier code, and a color identifier code. Using the identifier codes, configuration expressions are configured for blocks to represent the logical relationship between the blocks and the vehicle's functional configurations; upon receiving an externally sent part query command, a recursive calculation method is used to query the block to which the part belongs according to the hierarchical structure, the above configuration expression is used to solve for the instantiated model to which the block belongs, and the recursive calculation method is used to query the vehicle series to which the instantiated model belongs. This invention can query the attribution information of parts by combining recursive calculation and configuration calculation, reducing the computational load from querying blocks to instantiated models, and improving the management efficiency of parts. The first digit of the configuration expression is always the basic identifier code, used to indicate the vehicle series to which the block belongs; the other digits of the configuration expression are other identifier codes besides the first digit, which can be the basic identifier code, description identifier code, or color identifier code.

[0050] Based on their attributes, logos can be divided into three types: basic logos, color logos, and descriptive logos.

[0051] The basic logo includes brand and product (model) series, body style, configuration level, powertrain, transmission and drive type, design and customer base, model year and changes within the model year.

[0052] Color markings are a type of marking that indicates the technical characteristics of a vehicle's body coating type, color, and interior color.

[0053] Descriptive signs are used to complete the definition of a vehicle. In addition to basic signs and color markings, they indicate the vehicle's technical characteristics, which must be described when explaining different technical solutions. Descriptive signs supplement the basic signs; their addition does not change the meaning of the basic signs. Descriptive signs describe the vehicle's configuration features or technical characteristics, such as whether the main dashboard is hard or soft, whether it has sunshades, what type of sunshades they are, and where they are located. Color markings describe the various color options available for the vehicle.

[0054] In one specific embodiment, such as Figure 1 As shown, the above-mentioned precise regression management method for vehicle parts includes:

[0055] Step S1: Construct the comprehensive product structure tree for the entire vehicle. Configure a vehicle identifier definition for each instantiated model in the comprehensive product structure tree. This vehicle identifier definition includes all functional configurations for that model. Each functional configuration has an identifier code, which includes a basic identifier code, a description identifier code, and a color identifier code. Using these identifier codes, configure a configuration expression for each block in the comprehensive product structure tree. This configuration expression represents the logical relationship between the block and the vehicle's functional configurations.

[0056] Step S2: Upon receiving a part query command from an external source, a recursive calculation method is used to query the product comprehensive structure tree according to the hierarchical structure to obtain the first belonging information of the part. This first belonging information includes the block to which the part belongs. The configuration expression is used to calculate the instantiated vehicle model to which the block belongs. Then, using the recursive calculation method, the product comprehensive structure tree is queried according to the hierarchical structure to obtain the second belonging information of the instantiated vehicle model. This second belonging information includes the vehicle series to which the instantiated vehicle model belongs. The first belonging information, the instantiated vehicle model, and the second belonging information of the part are output as the query results.

[0057] Furthermore, the aforementioned multi-layered nodes, from the root node to the leaf node, are, in order: vehicle series, basic vehicle model, instantiated mid-sized vehicle model, instantiated vehicle model, block, assembly, and part.

[0058] In a preferred embodiment, when the relationship between a block and the vehicle's functional configuration is expressed by a flag, the configuration expression of that block does not contain the aforementioned logical relationship.

[0059] Furthermore, when the relationship between a block and the overall vehicle function configuration is expressed using multiple flags, the configuration expression of the block includes AND, OR, and NOT relationships.

[0060] In a preferred embodiment, the method further includes:

[0061] Each node in the product's comprehensive structure tree is configured with a product data release time and a manufacturing data effective period. A production center is configured for each instantiated vehicle model. The product data release time is the release time of the corresponding node, the manufacturing data effective period is the application period of the corresponding node, and the production center is the application location of the corresponding node.

[0062] Upon receiving a part query command from an external source, the system queries the release status of the corresponding part and its parent node at or after that time, based on the query time specified in the command.

[0063] Upon receiving a part query command from an external source, the system queries the application status of the corresponding part and its parent node within that specified time period, based on the query time period specified in the command.

[0064] When a part query command is received from an external source, the application status of the corresponding part in that production center is queried based on the production center included in the part query command.

[0065] In a specific embodiment, in a real-world work scenario, a vehicle series will have several base models, a base model will have several instantiated neutral models, an instantiated neutral model will have several instantiated models, an instantiated model will have several blocks, and a block will have several assemblies and parts. The complete vehicle EBOM set table for vehicle series 1 is shown in Table 1 below (for simplicity, the vehicle series structure is simplified in this example, assuming that block 1 and its lower-level parts are released at the same time as block 2):

[0066]

[0067]

[0068] Table 1 shows the complete vehicle EBOM set for vehicle series 1. Table 2 shows the complete vehicle EBOM set for vehicle series 2.

[0069]

[0070] Table 2. Complete Vehicle EBOM Set for Vehicle Series 1

[0071] When a query command for a component is received, the query steps are as follows:

[0072] Step 1: Determine the target part code / Chinese name. Assume the target part code is A, and its corresponding Chinese name is Part 1.

[0073] Step 2: Set the product data regression calculation time point (product data release time). The time should be an 8-digit date, for example, 20230101.

[0074] Step 3: Find all target component codes / Chinese names that have been published at the set time point in the database.

[0075] Regression calculations from parts to modules (levels 7-5) are performed recursively according to a set time point, resolving all target part codes / Chinese names to their corresponding higher-level assemblies and modules based on the structural hierarchy. Regression calculations from modules to instantiated vehicle models (levels 5-4) are performed with configuration calculations at a set time point, resolving modules to their corresponding instantiated vehicle models. Regression calculations from instantiated vehicle models to vehicle series (levels 4-1) are performed recursively according to a set time point, resolving instantiated vehicle models to their corresponding higher-level instantiated neutral vehicle models, base vehicle models, and vehicle series based on the structural hierarchy, obtaining results as needed.

[0076] Regarding the configuration calculation from blocks to instantiated vehicle models, each instantiated vehicle model has a vehicle identifier definition. Each block of each instantiated vehicle model sets a configuration expression based on the vehicle identifier definition of that model. The block is then calculated to its corresponding instantiated vehicle model through the configuration expression. The vehicle identifier definition table for vehicle series 1 is shown in Table 3 below:

[0077]

[0078] Table 3 defines the vehicle markings for Model 1. Table 4 defines the vehicle markings for Model 2.

[0079]

[0080] Table 4. Vehicle Marking Definition Table for Series 2

[0081] In this context, "S" indicates that the configuration is standard, while "empty" indicates that this configuration is not available.

[0082] The block configuration expression table is shown in Table 5 below:

[0083] Serial Number Car series Code / Name Configuration Expression 1 Car Series 1 Module 1 Logo 1 AND Logo 2 2 Car Series 1 Block 2 Logo 1 3 Car Series 2 Block 2 Mark 5 OR Mark 7 N Model N Block N ……

[0084] Table 5 Block Configuration Expression Table

[0085] Flag 1 is the flag code corresponding to the basic configuration, indicating that the vehicle series to which the block belongs is vehicle series 1. Flag 2 is the description flag code or color flag code. In the configuration calculation example from the block to the instantiated vehicle model above, the calculation result of block 1 is "instantaneous vehicle model 1" and "instantaneous vehicle model 3" for vehicle series 1. The calculation result of block 2 is "instantaneous vehicle model 2" for vehicle series 1, "instantaneous vehicle model 4" for vehicle series 2, "instantaneous vehicle model 5" for vehicle series 2, and "instantaneous vehicle model 6".

[0086] In the above example, if the target component code "A" is regressed to the vehicle series, the result is "Vehicle Series 1". If the target component code "A" is regressed to the base vehicle model, the result is "Base Vehicle Model 1" and "Base Vehicle Model 2". If the target component's Chinese name "Part 1" is regressed to the vehicle series, the result is "Vehicle Series 1" and "Vehicle Series 2".

[0087] When the EBOM structure of a vehicle model changes, the regression calculation results for the target component will also change. Assuming component "A" is removed from block 1, if the target component code "A" is regressed to the vehicle series, the result will be "empty". If the target component code "A" is regressed to the base vehicle model, the result will also be "empty". If the Chinese name of the target component "Part 1" is regressed to the vehicle series, the result will be "Vehicle Series 1" or "Vehicle Series 2".

[0088] The complete vehicle MBOM set table for vehicle series 1 is shown in Table 6 below (for the sake of simplicity, the vehicle series structure is simplified in this example. It is assumed that the manufacturing data of block 1 and its lower-level parts take effect at the same time as block 2, the manufacturing data of instantiated models 1, 2, and 3 take effect at the same time, and the manufacturing data of instantiated models 4, 5, and 6 take effect at the same time):

[0089]

[0090] Table 6 shows the complete vehicle MBOM set for vehicle series 1, and Table 7 shows the complete vehicle MBOM set for vehicle series 2.

[0091]

[0092]

[0093] Table 7. Complete Vehicle MBOM Set for Model Series 2

[0094] The regression calculation method for manufacturing data at specific time points under given conditions includes the following steps:

[0095] Step 1: Determine the target part code / Chinese name. Assume the target part code is "A" and the corresponding Chinese name is "Part 1".

[0096] Step 2: Set the production center and time point (the effective time of the manufacturing data) for the manufacturing data regression calculation. Set the production center to "DFPV" and the time point to "20220801". (Note: If no production center condition is set, the regression calculation result will be the usage of this part on all vehicle models across all production centers at the set time point.)

[0097] Step 3: Locate all target component codes / Chinese names that are effective at the set time points in the database. For the component-to-block level (levels 7-5), regression calculation is performed recursively according to the set time points, resolving all target component codes / Chinese names level by level to the higher-level assembly and block according to the structural hierarchy. For the block-to-instantiated vehicle level (levels 5-4), regression calculation is performed according to the set production center and time points, resolving the blocks to the instantiated vehicle level. For the instantiated vehicle level (levels 4-1), regression calculation is performed recursively according to the set time points (comparing to product data release time), resolving the instantiated vehicle level by level to the higher-level instantiated neutral vehicle, base vehicle, and vehicle series according to the structural hierarchy, obtaining results as needed.

[0098] The configuration calculation method and examples for transforming blocks into instantiated vehicle models are the same as those for product data regression calculation.

[0099] In the above example, if the target component code "A" is regressed to the vehicle series, the result is "empty"; if the target component code "A" is regressed to the base vehicle model, the result is "empty"; if the target component's Chinese name "Part 1" is regressed to the vehicle series, the result is "Vehicle Series 2".

[0100] When the MBOM structure of a certain vehicle model changes, the regression calculation results of the target parts will change accordingly. Suppose that part "C" is removed from block 2. In this case, if the Chinese name of the target part "part 1" is regressed to the vehicle series, the solution result will be "empty".

[0101] The regression calculation method for manufacturing data over a given time period under specified conditions includes the following steps:

[0102] Step 1: Determine the target part code / Chinese name. Assume the target part code is "A" and the corresponding Chinese name is "Part 1".

[0103] Step 2: Set the production center and time period (the effective date of the manufacturing data) for the manufacturing data regression calculation. Set the production center to "DFPV" and the time period to "20210501-20220320". (Note: If no production center condition is set, the regression calculation result will be the usage of the part across all vehicle models in all production centers within the set time period.)

[0104] Step 3: Locate all target component codes / Chinese names that are effective within the set time period in the database. For the component-to-block level (levels 7-5), regression calculation is performed recursively according to the set time period, resolving all target component codes / Chinese names to the next higher-level block based on the structural hierarchy. For the block-to-instantiated vehicle level (levels 5-4), regression calculation is performed according to the set production center and time period, resolving the block to the instantiated vehicle. For the instantiated vehicle level (levels 4-1), regression calculation is performed recursively according to the set time period (comparing to product data release time), resolving the instantiated vehicle to the vehicle series based on the structural hierarchy.

[0105] Regarding the configuration calculation method and example from the block to the instantiated vehicle model, it is the same as (1) product data regression calculation method.

[0106] In the above example, if the target component code "A" is regressed to the vehicle series, the result is "empty"; if the target component's Chinese name "Part 1" is regressed to the vehicle series, the result is "Vehicle Series 2".

[0107] When the MBOM structure of a certain vehicle model changes, the regression calculation results of the target parts will change accordingly. Suppose that part "C" is removed from block 2. In this case, if the Chinese name of the target part "part 1" is regressed to the vehicle series, the solution result will be "empty".

[0108] In summary, this invention can accurately calculate the assembly, block, instantiated vehicle model, instantiated neutral vehicle model, base vehicle model, and vehicle series to which the target component belongs at a set time point (product data release time), supporting designers in quickly selecting design solutions and identifying special parts.

[0109] This invention can accurately calculate the assembly, block, instantiated vehicle model, instantiated neutral vehicle model, base vehicle model, and vehicle series to which the target component belongs at a set production center and time point (manufacturing data effective time), supporting data engineers to quickly and accurately control and analyze the impact of design changes.

[0110] This invention can accurately calculate the usage of target components in various vehicle models at a set production center and time period (manufacturing data effective time), providing fast, accurate, and intuitive data support for the source analysis and handling of on-site problems in the implementation and control of vehicle design changes.

[0111] This invention also provides an embodiment of a precise regression management system for vehicle parts, such as... Figure 2 As shown, it includes a preprocessing module 1 and a query module 2, with the preprocessing module 1 connected to the query module 2.

[0112] Preprocessing module 1 is used to construct the comprehensive product structure tree of the whole vehicle. It configures a whole vehicle identifier definition for each instantiated model in the comprehensive product structure tree. The whole vehicle identifier definition includes all functional configurations of the model. Each functional configuration has an identifier code. Based on the identifier code, a configuration expression is configured for each block in the comprehensive product structure tree. The configuration expression is used to represent the logical relationship between the block and the whole vehicle functional configuration.

[0113] When query module 2 receives a part query command sent from an external source, it uses a recursive calculation method to query the product comprehensive structure tree according to the hierarchical structure to obtain the first belonging information of the part. The first belonging information includes the block to which the part belongs. It uses the configuration expression to solve the instantiated vehicle model to which the block belongs. It then uses a recursive calculation method to query the product comprehensive structure tree according to the hierarchical structure to obtain the second belonging information of the instantiated vehicle model. The second belonging information includes the vehicle series to which the instantiated vehicle model belongs. The first belonging information, the instantiated vehicle model, and the second belonging information of the part are output as the query result.

[0114] The management system in this embodiment is applicable to the management methods described above.

[0115] This application is not limited to the above-described embodiments. For those skilled in the art, several improvements and modifications can be made without departing from the principles of this application, and these improvements and modifications are also considered to be within the scope of protection of this application.

Claims

1. A method for precise regression management of vehicle parts, characterized by, The method comprises the following steps: constructing a product comprehensive structure tree of a whole vehicle; configuring a whole vehicle sign definition for each instantiated vehicle model in the product comprehensive structure tree, the whole vehicle sign definition comprising all functional configurations of the vehicle model, each functional configuration having a sign code, the sign code comprising a basic sign code, a description sign code, and a color sign code; and configuring a configuration expression for each group in the product comprehensive structure tree by using the sign code, the configuration expression being used to represent a logical relationship between the group and the functional configuration of the whole vehicle; when receiving a part query instruction sent by an external device, obtaining first belonging information of the part by recursively querying the product comprehensive structure tree according to a hierarchical structure, the first belonging information comprising a group to which the part belongs, calculating an instantiated vehicle model to which the group belongs by using the configuration expression, and obtaining second belonging information of the instantiated vehicle model by recursively querying the product comprehensive structure tree according to the hierarchical structure, the second belonging information comprising a vehicle series to which the instantiated vehicle model belongs; outputting the first belonging information of the part, the instantiated vehicle model, and the second belonging information as a query result; the method further comprises the following steps: configuring a product data release time and a manufacturing data effective time period for each node in the product comprehensive structure tree, the product data release time being a release time of the corresponding node, and the manufacturing data effective time period being an application time period of the corresponding node; the method further comprises the following steps: when receiving a part query instruction sent by an external device, querying a release condition of the corresponding part and an upper node to which the part belongs at a time point not later than the time point according to the query time point contained in the part query instruction; and when receiving a part query instruction sent by an external device, querying an application condition of the corresponding part and an upper node to which the part belongs in a time period according to the query time period contained in the part query instruction.

2. The method of claim 1, wherein, The product comprehensive structure tree comprises a vehicle series, a basic vehicle model, an instantiated medium-sized vehicle model, an instantiated vehicle model, a group, an assembly, and a part from a root node to a leaf node.

3. The method of claim 1, wherein, In the whole vehicle sign definition, a functional configuration possessed by a corresponding instantiated vehicle model is marked as S, and a functional configuration not possessed by the corresponding instantiated vehicle model is marked as empty.

4. The method of claim 1, wherein, When a relationship between a group and a functional configuration of a whole vehicle is expressed by one sign code, the configuration expression of the group does not contain the logical relationship.

5. The method of claim 1, wherein, When a relationship between a group and a functional configuration of a whole vehicle is expressed by multiple sign codes, the configuration expression of the group contains an and relationship, an or relationship, and a not relationship.

6. The method of claim 1, wherein, The method further comprises the following steps: configuring a production center for an instantiated vehicle model node in the product comprehensive structure tree, the production center being an application location of the corresponding node.

7. The method of claim 6, wherein the method further comprises: The method further comprises the following steps: when receiving a part query instruction sent by an external device, querying an application condition of the corresponding part in a production center according to the production center contained in the part query instruction.

8. An accurate return management system for vehicle parts, characterized by, The method comprises the following steps: The preprocessing module is configured to build a product comprehensive structure tree of the whole vehicle, and is further configured to configure a whole vehicle sign definition for each instantiated vehicle model in the product comprehensive structure tree, the whole vehicle sign definition including all functional configurations of the vehicle model, each functional configuration having a sign code, the sign code including a basic sign code, a description sign code, and a color sign code, and is further configured to configure a configuration expression for each group in the product comprehensive structure tree according to the sign code, the configuration expression being used to represent a logical relationship between the group and the functional configuration of the whole vehicle. The query module is configured to, when receiving a part query instruction sent from outside, obtain first belonging information of the part by hierarchically querying the product comprehensive structure tree by using a recursive calculation method, the first belonging information including a group to which the part belongs, solve an instantiated vehicle model to which the group belongs by using the configuration expression, and obtain second belonging information of the instantiated vehicle model by hierarchically querying the product comprehensive structure tree by using the recursive calculation method, the second belonging information including a vehicle series to which the instantiated vehicle model belongs. The query module is further configured to output the first belonging information of the part, the instantiated vehicle model, and the second belonging information as a query result. Each node in the product comprehensive structure tree is configured with a product data release time and a manufacturing data effective time period, the product data release time being a release time of the corresponding node, and the manufacturing data effective time period being an application time period of the corresponding node. When receiving a part query instruction sent from outside, the query module is configured to query a release condition of the corresponding part and an upper node to which the part belongs at a time point no later than the time point included in the part query instruction; and When receiving a part query instruction sent from outside, the query module is configured to query an application condition of the corresponding part and an upper node to which the part belongs in a time period included in the part query instruction.

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