Material assignment method, device and electronic equipment

Abstract

This application relates to the field of rail vehicle manufacturing technology, and provides a material assignment method, apparatus, and electronic device. The method includes: acquiring first engineering bill of materials data and first process list data for the current rail vehicle project; invoking a preset intelligent agent to automatically assign materials based on the first engineering bill of materials data and the first process list data, obtaining a first material assignment result, the first material assignment result including at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme; generating and displaying a material assignment view based on the first material assignment result; and determining a second material assignment result based on user interaction with the material assignment view. Based on this application's solution, material assignment for rail vehicle projects can be achieved efficiently and accurately.

Description

Technical Field

[0001] This invention relates to the field of rail vehicle manufacturing technology, and in particular to a material assignment method, apparatus, and electronic equipment. Background Technology

[0002] In the manufacturing process of rail vehicles, it is typically necessary to construct a Bill of Materials (PBOM) and a Bill of Procedure (BOP) structure based on the Engineering Bill of Materials (EBOM), and accurately allocate materials from the EBOM to the corresponding process nodes in the BOP. Currently, this material assignment mainly relies on manual operation by process engineers within a management system. Due to the complexity of material data and the diversity of process structures, manual assignment is difficult to automate efficiently. This manual operation mode is not only inefficient but also prone to assignment errors or omissions, which negatively impact subsequent process planning and manufacturing. Therefore, how to efficiently and accurately assign materials for rail vehicle projects has become a pressing technical problem to be solved. Summary of the Invention

[0003] This application provides a material assignment method, apparatus, and electronic device to solve the technical problem of how to efficiently and accurately implement material assignment for rail vehicle projects.

[0004] In a first aspect, embodiments of this application provide a material assignment method, including: Obtain the first engineering bill of materials data and the first process list data for the current rail vehicle project; The preset intelligent agent is invoked to automatically assign materials based on the first engineering bill of materials data and the first process list data, and the first material assignment result is obtained. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme in the at least one candidate material assignment scheme. Generate and display a material assignment view based on the first material assignment result; The second material assignment result is determined based on the user's interactive operations on the material assignment view.

[0005] In conjunction with the first aspect, in some possible implementations, obtaining the first engineering bill of materials data and the first process list data for the current rail vehicle project includes: Retrieve the bill of materials (BOM) data for the current rail vehicle project and display its hierarchical tree structure. The hierarchical tree structure contains multiple nodes, each corresponding to a material in the current rail vehicle project's BOM data. Based on the user's selection of the tree-like hierarchical structure, determine the first engineering bill of materials data to be assigned from the current engineering bill of materials data of the rail vehicle project; Based on the bill of materials data for the first project, obtain the bill of materials data for the first process of the current rail vehicle project.

[0006] Combining the first aspect and the above implementation methods, in some possible implementation methods, a preset intelligent agent is invoked to automatically assign materials based on the first engineering bill of materials data and the first process list data, thereby obtaining the first material assignment result, including: The preset intelligent agent is invoked to query the historical process knowledge base based on the material drawing number in the first project bill of materials data, and the query results are obtained. If the query results indicate that a first historical material assignment scheme corresponding to the material drawing number in the first engineering bill of materials data is found, the intelligent agent is invoked to determine the first candidate material assignment scheme and the corresponding first recommendation type tag based on the first historical material assignment scheme and the first process list data. If the query results indicate that no first historical material assignment scheme corresponding to the material drawing number in the first project bill of materials data is found, the intelligent agent is invoked to perform a similarity search in the historical process knowledge base based on the first project bill of materials data and the first process list data to obtain the similarity search results; the intelligent agent is invoked to determine the second candidate material assignment scheme and the corresponding second recommendation type tag based on the similarity search results; The intelligent agent determines the first material assignment result based on the first candidate material assignment scheme and the corresponding first recommendation type tag, and / or the second candidate material assignment scheme and the corresponding second recommendation type tag; Among them, the recommendation level represented by the first recommendation type label is higher than the recommendation level represented by the second recommendation type label.

[0007] Combining the first aspect and the above implementation methods, in some possible implementation methods, the intelligent agent is invoked to perform a similarity search in the historical process knowledge base based on the first engineering bill of materials data and the first process list data, and obtains the similarity search results, including: Multi-dimensional feature extraction is performed based on the first engineering bill of materials data to obtain the first material feature vector, and multi-dimensional feature extraction is performed based on the first process list data to obtain the first process step feature vector; The intelligent agent is invoked to perform vector similarity retrieval in the historical process knowledge base based on the first material feature vector and the first process step feature vector, and obtain the similarity value of each historical material assignment scheme in the historical process knowledge base. The intelligent agent is invoked to classify and determine the similarity values ​​of each historical material assignment scheme in the historical process knowledge base according to the preset similarity threshold, and the similarity retrieval results are obtained.

[0008] Combining the first aspect and the above implementation methods, in some possible implementation methods, the preset similarity threshold includes a first similarity threshold and a second similarity threshold, where the first similarity threshold is higher than the second similarity threshold; the intelligent agent is invoked to determine the second candidate material assignment scheme and the corresponding second recommendation type label based on the similarity retrieval results, including: If the similarity retrieval results indicate that a second historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the second historical material assignment scheme is greater than or equal to the first similarity threshold, the agent is invoked to extract the second historical material assignment scheme from the historical process knowledge base as the second candidate material assignment scheme, and a corresponding second recommendation type label is generated. If the similarity retrieval results indicate that there is a third historical material assignment scheme in the historical process knowledge base, and the similarity value of the third historical material assignment scheme is less than the first similarity threshold and greater than or equal to the second similarity threshold, the agent is invoked to extract the third historical material assignment scheme from the historical process knowledge base as the second candidate material assignment scheme, and the corresponding second recommendation type label is generated. Among them, the recommendation level of the second recommendation type tag corresponding to the second historical material assignment scheme is higher than the recommendation level of the second recommendation type tag corresponding to the third historical material assignment scheme.

[0009] In conjunction with the first aspect and the above implementation methods, in some possible implementation methods, the first material assignment result further includes at least one manual assignment flag, which is used to indicate that the corresponding material needs to be manually assigned; the method further includes: If the similarity search results indicate that a fourth historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the fourth historical material assignment scheme is less than the second similarity threshold, the agent is invoked to generate a manual assignment tag.

[0010] In combination with the first aspect and the above implementation methods, in some possible implementations, the method further includes: Obtain the second engineering bill of materials data and the second process list data of historical rail vehicle projects, as well as the material allocation plan of historical rail vehicle projects; Multi-dimensional feature extraction is performed based on the bill of materials data for the second project to obtain the feature vector of the second material, and multi-dimensional feature extraction is performed based on the bill of materials data for the second process to obtain the feature vector of the second process step. Based on the second material feature vector, the second process feature vector, and the material assignment scheme of historical rail vehicle projects, construct or update the historical process knowledge base.

[0011] Combining the first aspect and the above implementation methods, in some possible implementation methods, generating and displaying a material assignment view based on the first material assignment result includes: Based on the first material assignment result, a first subview and a second subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, and the second subview is used to indicate the assigned materials in the first material assignment result; Generate and display the material assignment view based on the first subview and the second subview; The second material assignment result is determined based on the user's interactive operations on the material assignment view, including: Based on the user's confirmation and / or adjustment operations on the assigned materials in the second subview of the material assignment view, determine the assigned correction results; Based on the already assigned correction results, determine the second material assignment result.

[0012] Combining the first aspect and the above implementation methods, in some possible implementation methods, generating and displaying a material assignment view based on the first material assignment result includes: Based on the first material assignment result, a first subview, a second subview, and a third subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, the second subview is used to indicate the assigned materials in the first material assignment result, and the third subview is used to indicate the unassigned materials in the first material assignment result. Generate and display the material assignment view based on the first subview, the second subview, and the third subview; The second material assignment result is determined based on the user's interactive operations on the material assignment view, including: Based on the user's confirmation and / or adjustment operations on the assigned materials in the second subview of the material assignment view, determine the assigned correction results; The manual assignment result is determined based on the user's manual assignment operation on the unassigned materials in the third subview of the material assignment view. Based on the already assigned correction results and the manual assignment results, determine the second material assignment result.

[0013] Combining the first aspect and the above implementation methods, in some possible implementation methods, the material assignment view includes a material surplus marker, which is dynamically adjusted according to the assigned quantity of the corresponding material.

[0014] Secondly, embodiments of this application provide a material dispatching device, comprising: The data acquisition module is used to acquire the first engineering material list data and the first process list data of the current rail vehicle project; The automatic assignment module is used to call a preset intelligent agent to perform automatic assignment processing based on the first engineering bill of materials data and the first process list data to obtain the first material assignment result. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme in the at least one candidate material assignment scheme. A generation and display module is used to generate and display a material assignment view based on the first material assignment result. The interactive determination module is used to determine the second material assignment result based on the user's interactive operation on the material assignment view.

[0015] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the program to implement the steps of the material assignment method of the first aspect.

[0016] The material assignment method, apparatus, and electronic device provided in this application first acquire the first engineering bill of materials data and the first process list data of the current rail vehicle project. Then, a preset intelligent agent is invoked to automatically assign materials based on the first engineering bill of materials data and the first process list data, resulting in a first material assignment result. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme. Next, a material assignment view is generated and displayed based on the first material assignment result. Finally, a second material assignment result is determined based on the user's interactive operation on the material assignment view. In this way, the preset intelligent agent is used to automatically assign materials to the first engineering bill of materials data and the first process list data to output a first material assignment result containing candidate material assignment schemes and recommendation type tags. The second material assignment result is determined by combining the material assignment view and the interactive operation, thereby combining automatic assignment processing with interactive operation to efficiently and accurately realize the material assignment corresponding to the rail vehicle project. Attached Figure Description

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

[0018] Figure 1 This is a flowchart illustrating the material assignment method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the overall process of material assignment provided in the embodiments of this application; Figure 3This is a schematic diagram of the tree-like hierarchical structure selection of the engineering bill of materials data provided in the embodiments of this application; Figure 4 This is a schematic diagram of a process bill of materials structure provided in an embodiment of this application; Figure 5 This is a schematic diagram of the interface layout and interaction logic of the material assignment view provided in the embodiments of this application; Figure 6 This is a schematic diagram of another interface layout and interaction logic of the material assignment view provided in the embodiments of this application; Figure 7 This is a schematic diagram showing the display status of the remaining quantity marker in the material assignment view provided in the embodiments of this application; Figure 8 This is a schematic diagram of the material dispatching device provided in the embodiments of this application; Figure 9 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] Explanation of some terms used in the embodiments of this application: Engineering Bill of Materials (EBOM); Process Bill of Materials (PBOM); Bill of Process (BOP); Bill of Materials (BOM); Large Language Model (LLM); Natural Language Processing (NLP).

[0021] In the production and manufacturing process of rail vehicles, it is usually necessary to build a process bill of materials and a process list structure based on the engineering bill of materials, and accurately allocate the materials in the engineering bill of materials to the corresponding process nodes in the process list.

[0022] For example, in some related technologies, the material assignment work mainly relies on the process engineer to perform manual operation in the management system. The process engineer needs to compare the materials in the engineering bill of materials with the process list structure one by one, and manually complete the material assignment based on personal experience, allocating the materials to the corresponding process nodes.

[0023] It is evident that the aforementioned technologies have shortcomings: due to the large number of materials in the engineering bill of materials and the diverse structure of the process list, the aforementioned material assignment method, which relies on manual operation, is difficult to achieve efficient automated matching, resulting in low processing efficiency of material assignment work; at the same time, material assignment based on personal experience is prone to errors in the material assignment results or omissions of materials, which in turn has an adverse impact on subsequent process planning and manufacturing.

[0024] Therefore, how to efficiently and accurately allocate materials for rail vehicle projects has become an urgent technical problem to be solved.

[0025] To address the aforementioned issues, the solution provided in this application mainly includes: firstly, acquiring the first engineering bill of materials data and the first process list data of the current rail vehicle project; then, invoking a preset intelligent agent to automatically assign materials based on the first engineering bill of materials data and the first process list data, obtaining a first material assignment result. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme. Next, generating and displaying a material assignment view based on the first material assignment result; finally, determining a second material assignment result based on the user's interactive operation on the material assignment view. Through the above method, the preset intelligent agent automatically assigns materials to the first engineering bill of materials data and the first process list data to output a first material assignment result containing candidate material assignment schemes and recommendation type tags, and combines the material assignment view with interactive operation to determine the second material assignment result, thereby combining automatic assignment processing with interactive operation to efficiently and accurately realize the material assignment corresponding to the rail vehicle project.

[0026] The material assignment method provided in the embodiments of this application will be described in detail below.

[0027] Please see Figure 1 , Figure 1 This is a flowchart illustrating a material assignment method provided in an embodiment of this application. Figure 1 As shown, the method in this application embodiment may include the following steps S101~S104: S101, Obtain the first engineering material list data and the first process list data of the current rail vehicle project; S102, invoke the preset intelligent agent to automatically assign materials according to the first engineering bill of materials data and the first process list data, and obtain the first material assignment result. The first material assignment result includes at least one candidate material assignment scheme and the recommendation type tag corresponding to each candidate material assignment scheme in the at least one candidate material assignment scheme. S103, Generate and display the material assignment view based on the first material assignment result; S104, determine the second material assignment result based on the user's interactive operation on the material assignment view.

[0028] Specifically, the first step is to obtain the first engineering bill of materials (BOM) data and the first process list data for the current rail vehicle project. The current rail vehicle project refers to a rail vehicle manufacturing project in the process planning stage that requires the conversion of design materials into process materials. The first engineering bill of materials (BOM) data for the current rail vehicle project refers to a dataset containing the hierarchical structure and attribute information of each material in the current rail vehicle project. The first process list data for the current rail vehicle project refers to a dataset containing the hierarchical structure and attribute information of each process node in the current rail vehicle project. It should be noted that the first engineering bill of materials (BOM) data for the current rail vehicle project can be the complete BOM data for the current rail vehicle project, or it can be a partial BOM data, such as the BOM data corresponding to the materials to be assigned selected by the user. Similarly, the first process list data for the current rail vehicle project can be the complete process list data for the current rail vehicle project, or it can be a partial process list data, such as the process list data associated with the selected materials to be assigned.

[0029] Regarding this step, some possible implementations include calling relevant data reading functions to read the initial data and using it as the first engineering bill of materials data and the first process list data for the current rail vehicle project. Alternatively, the relevant input information can be parsed to obtain the parsing results, which can then be used as the first engineering bill of materials data and the first process list data for the current rail vehicle project.

[0030] Furthermore, a pre-defined intelligent agent needs to be invoked to automatically assign materials based on the first engineering bill of materials data and the first process list data, thereby obtaining the first material assignment result. Here, the pre-defined intelligent agent refers to a computational program module capable of sensing environmental conditions, making autonomous decisions, and executing actions to achieve specific goals; the automatic assignment process refers to the process by which the pre-defined intelligent agent analyzes input data and outputs the correspondence between materials and process nodes. The first material assignment result includes at least one candidate material assignment scheme, and a recommendation type tag corresponding to each candidate material assignment scheme. A candidate material assignment scheme refers to a specific allocation strategy for distributing materials from the first engineering bill of materials data to specific process nodes in the first process list data; the recommendation type tag refers to identification information used to characterize the credibility or matching degree of the candidate material assignment scheme. It is understood that different candidate material assignment schemes may have different recommendation type tags because the historical data matching degree or algorithm confidence level on which different candidate material assignment schemes are generated varies. Candidate material assignment schemes with higher matching degrees or higher confidence levels will be assigned recommendation type tags indicating higher recommendation levels.

[0031] Regarding this step, in some possible implementations, the first engineering bill of materials data and the first process list data of the current rail vehicle project can be input into a preset intelligent agent. The preset intelligent agent performs relevant mathematical operations and outputs a first material allocation result containing at least one candidate material allocation scheme and a recommendation type tag corresponding to each candidate material allocation scheme. Alternatively, the preset intelligent agent can automatically allocate materials based on the first engineering bill of materials data and the first process list data of the current rail vehicle project, obtain relevant intermediate results, and generate a first material allocation result containing at least one candidate material allocation scheme and a recommendation type tag corresponding to each candidate material allocation scheme based on the relevant intermediate results.

[0032] Furthermore, a material assignment view needs to be generated and displayed based on the first material assignment result. The material assignment view refers to a graphical user interface used to visually display the first material assignment result and related material information. It should be noted that the material assignment view can be a single, integrated view that incorporates all assignment information, or it can be a composite view composed of multiple sub-views, such as a first sub-view displaying all materials, a second sub-view displaying assigned materials, and a third sub-view displaying unassigned materials. In addition, the material assignment view includes interactive areas. These interactive areas can be a portion of the display area of ​​the material assignment view, or some or all of the sub-views. Users can modify or confirm assignment information by performing actions within these interactive areas.

[0033] Regarding this step, in some possible implementations, the first material assignment result can be rendered to generate a material assignment view, which can then be displayed. Alternatively, a relevant view generation function can be called based on the first material assignment result to generate and display the material assignment view.

[0034] Furthermore, the second material assignment result needs to be determined based on the user's interactive operations on the material assignment view. Interactive operations refer to the user's actions of sending control commands to the material assignment view through input devices, such as confirming candidate material assignment schemes in the material assignment view, adjusting process nodes in candidate material assignment schemes, or manually allocating unassigned materials. The second material assignment result refers to the final material allocation scheme determined after the user's interactive operations.

[0035] It should be noted that the first material assignment result is an initial recommendation automatically generated by a preset intelligent agent, while the second material assignment result is the final confirmation result obtained after the first material assignment result has been corrected by user interaction. The accuracy or personalization of the second material assignment result is higher than that of the first material assignment result.

[0036] Regarding this step, in some possible implementations, user interaction with the material assignment view can be obtained, the first material assignment result can be updated based on the user's interaction with the material assignment view, and the updated first material assignment result can be used as the second material assignment result. Alternatively, in response to user interaction with the material assignment view, relevant state change processing can be performed on the first material assignment result, and the first material assignment result after relevant state change processing can be used as the second material assignment result.

[0037] Furthermore, it should be noted that the intelligent agent involved in this embodiment is an intelligent system built based on a large language model, capable of reasoning and decision-making in conjunction with an external knowledge base. At the architectural level, the pre-defined intelligent agent may include a perception module, a planning module, and an execution module. The perception module receives first engineering bill of materials data and first process list data; the planning module calls upon a historical process knowledge base for retrieval and similarity calculation to formulate candidate material assignment schemes; and the execution module outputs first material assignment results with recommendation type tags. During training, historical engineering bill of materials data, historical process list data, and manually confirmed historical material assignment schemes from historical rail vehicle projects can be used as training samples. The pre-defined intelligent agent can be optimized through supervised fine-tuning or reinforcement learning to enable it to accurately generate candidate material assignment schemes. Through the above architecture and training process, the pre-defined intelligent agent can transform the first engineering bill of materials data and the first process list data into first material assignment results with clear recommendation type tags, thereby supporting the generation of subsequent material assignment views and the determination of second material assignment results.

[0038] In this embodiment, the first engineering bill of materials (BOM) data and the first process list data of the current rail vehicle project are first obtained. Then, a preset intelligent agent is invoked to automatically assign materials based on the first engineering BOM data and the first process list data, resulting in a first material assignment result. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme. Next, a material assignment view is generated and displayed based on the first material assignment result. Finally, a second material assignment result is determined based on the user's interactive operation on the material assignment view. In this way, the preset intelligent agent is used to automatically assign materials based on the first engineering BOM data and the first process list data to output a first material assignment result containing candidate material assignment schemes and recommendation type tags. The second material assignment result is determined by combining the material assignment view with the interactive operation, thereby combining automatic assignment processing with interactive operation to efficiently and accurately realize the material assignment corresponding to the rail vehicle project.

[0039] In one embodiment, the step of "obtaining the first engineering material list data and the first process list data of the current rail vehicle project" can be further refined and may include the following steps: Retrieve the bill of materials (BOM) data for the current rail vehicle project and display its hierarchical tree structure. The hierarchical tree structure contains multiple nodes, each corresponding to a material in the current rail vehicle project's BOM data. Based on the user's selection of the tree-like hierarchical structure, determine the first engineering bill of materials data to be assigned from the current engineering bill of materials data of the rail vehicle project; Based on the bill of materials data for the first project, obtain the bill of materials data for the first process of the current rail vehicle project.

[0040] Specifically, considering that the bill of materials data for current rail vehicle projects typically contains a large amount of material data, directly processing all material data would consume a lot of computing resources and be inefficient. In addition, in the actual process planning process, different process engineers (a type of user) are often responsible for the material assignment work of different parts. This embodiment proposes a scheme to determine the first bill of materials data to be assigned based on the user's selected operation, so as to achieve data filtering and task allocation.

[0041] First, it is necessary to obtain the engineering bill of materials data for the current rail vehicle project; the engineering bill of materials data for the current rail vehicle project refers to the complete data set containing all material information generated during the design phase of the current rail vehicle project.

[0042] Regarding this step, some possible implementations include retrieving the engineering bill of materials (OBM) data for the current rail vehicle project from a database. Alternatively, it can involve receiving the BOM data for the current rail vehicle project from a relevant terminal.

[0043] Furthermore, the tree-like hierarchical structure of the engineering bill of materials (BOM) data for the current rail vehicle project is displayed. Here, the BOM data refers to the data used to describe the composition and attributes of materials; the tree-like hierarchical structure refers to the graphical structure used to represent the assembly or compositional relationships between materials. The tree-like hierarchical structure contains multiple nodes, each corresponding to a material in the current rail vehicle project's BOM data. For example, the top-level node in the tree-like hierarchical structure can correspond to the highest-level assembly material, lower-level nodes correspond to their child materials, and the connections or indentation relationships between nodes represent the parent-child inclusion relationships between materials.

[0044] Regarding this step, some possible implementations include using a graphical interface rendering component to generate and display a tree-like hierarchical structure based on the material hierarchy attributes in the current rail vehicle project's bill of materials data. Alternatively, a structured text file can be generated based on the current rail vehicle project's bill of materials data, and then parsed to display the tree-like hierarchical structure.

[0045] Furthermore, based on the user's selection operation on the tree-like hierarchical structure, it is necessary to determine the first engineering bill of materials (OBM) data to be assigned from the current engineering BOM data of the rail vehicle project. Here, the selection operation refers to the user's action of selecting a specific node in the tree-like hierarchical structure through an input device.

[0046] Regarding this step, in some possible implementations, in response to the user's click operation on the target node in the tree hierarchy, the material data corresponding to the target node and the material data corresponding to the lower-level nodes of the target node can be used as the first engineering bill of materials data to be assigned.

[0047] It is understood that a user's selection operation on the tree hierarchy can be a single selection of a single node, a multi-selection of multiple nodes, or a batch selection of nodes at a certain level. This application does not limit the specific form of the user's selection operation on the tree hierarchy.

[0048] Furthermore, it is necessary to obtain the first process list data for the current rail vehicle project based on the first engineering bill of materials data.

[0049] Regarding this step, in some possible implementations, one approach is to query the database for the process list data associated with the project identifier in the first engineering bill of materials data, and use this as the first process list data for the current rail vehicle project. Alternatively, one approach is to call the relevant system interface to obtain the matching process list data based on the material attribute information in the first engineering bill of materials data, and use this as the first process list data for the current rail vehicle project.

[0050] In this embodiment, by displaying the hierarchical tree structure of the current rail vehicle project's bill of materials data, the hierarchical relationship between materials is presented, allowing users to locate the area to be processed through selection operations, thereby determining the first bill of materials data to be assigned from the current rail vehicle project's bill of materials data. This method achieves data filtering, avoids the resource consumption caused by full data processing, and can obtain the corresponding first process list data based on the determined first bill of materials data, providing a data foundation for subsequent automatic assignment processing and improving the efficiency of material assignment.

[0051] In one embodiment, the step of "calling a preset intelligent agent to automatically assign materials based on the first engineering bill of materials data and the first process list data to obtain the first material assignment result" can be further refined and may include the following steps: The preset intelligent agent is invoked to query the historical process knowledge base based on the material drawing number in the first project bill of materials data, and the query results are obtained. If the query results indicate that a first historical material assignment scheme corresponding to the material drawing number in the first engineering bill of materials data is found, the intelligent agent is invoked to determine the first candidate material assignment scheme and the corresponding first recommendation type tag based on the first historical material assignment scheme and the first process list data. If the query results indicate that no first historical material assignment scheme corresponding to the material drawing number in the first project bill of materials data is found, the intelligent agent is invoked to perform a similarity search in the historical process knowledge base based on the first project bill of materials data and the first process list data to obtain the similarity search results; the intelligent agent is invoked to determine the second candidate material assignment scheme and the corresponding second recommendation type tag based on the similarity search results; The intelligent agent determines the first material assignment result based on the first candidate material assignment scheme and the corresponding first recommendation type tag, and / or the second candidate material assignment scheme and the corresponding second recommendation type tag; Among them, the recommendation level represented by the first recommendation type label is higher than the recommendation level represented by the second recommendation type label.

[0052] Specifically, considering the uniqueness of material drawing numbers, if a material drawing number has appeared in a historical project, its corresponding process route and process node have high reference value; if a material drawing number has not appeared, it is necessary to combine other attribute characteristics of the material to perform fuzzy matching to find similar process solutions. This embodiment proposes a hierarchical recommendation strategy that combines precise matching based on material drawing numbers with fuzzy matching based on feature similarity to improve the accuracy and coverage of automatic assignment.

[0053] First, a pre-defined intelligent agent needs to be invoked to query the historical process knowledge base based on the material drawing numbers in the first project's bill of materials data, and obtain the query results. Here, the material drawing number in the first project's bill of materials data refers to the coding information used to uniquely identify the materials in the first project's bill of materials data; the historical process knowledge base refers to a database that stores engineering bill of materials data, process list data, and corresponding material allocation schemes for historical rail vehicle projects; and the query results refer to indication information used to indicate whether there is historical record information in the historical process knowledge base that matches the material drawing number in the first project's bill of materials data.

[0054] Regarding this step, in some possible implementations, the query function of a preset intelligent agent can be invoked, using the material drawing number in the first engineering bill of materials data as the query key value, and performing an index search in the historical process knowledge base. If a historical record containing the material drawing number is found, a query result is generated to indicate that the corresponding first historical material assignment scheme has been found; if no historical record containing the material drawing number is found, a query result is generated to indicate that the corresponding first historical material assignment scheme has not been found.

[0055] Furthermore, if the query results indicate the presence of a first historical material allocation scheme corresponding to the material drawing number in the first engineering bill of materials data, the intelligent agent needs to be invoked to determine the first candidate material allocation scheme and its corresponding first recommendation type tag based on the first historical material allocation scheme and the first process list data. Here, the first historical material allocation scheme refers to the process route and operation node information of historical materials with the same material drawing number as those in the first engineering bill of materials data, stored in the historical process knowledge base, which were assigned in historical rail vehicle projects; the first candidate material allocation scheme refers to the allocation strategy determined based on the first historical material allocation scheme, which assigns materials from the first engineering bill of materials data to specific operation nodes in the first process list data; and the first recommendation type tag refers to the identification information used to characterize the first candidate material allocation scheme as having the highest credibility or highest matching degree.

[0056] Regarding this step, in some possible implementations, the mapping processing function of the intelligent agent can be invoked to extract the process node information in the first historical material assignment scheme, and to find the corresponding process node in the current first process list data. If the corresponding process node is found, the materials in the first engineering material list data are associated with the found process node to generate the first candidate material assignment scheme, and the scheme is assigned a first recommendation type label representing the highest recommendation level.

[0057] Furthermore, if the query results indicate that no first historical material assignment scheme corresponding to the material drawing number in the first engineering bill of materials data was found, the intelligent agent needs to be invoked to perform a similarity search in the historical process knowledge base based on the first engineering bill of materials data and the first process list data to obtain the similarity search results. The intelligent agent is then invoked to determine the second candidate material assignment scheme and its corresponding second recommendation type tag based on the similarity search results. Here, similarity search refers to the process of searching for historical material assignment schemes with similar characteristics in the historical process knowledge base based on the material attribute characteristics in the first engineering bill of materials data and the process attribute characteristics in the first process list data; similarity search results refer to the data set used to characterize the similarity between each historical material assignment scheme in the historical process knowledge base and the currently assigned material and process; the second candidate material assignment scheme refers to the allocation strategy determined based on the similarity search results, which assigns materials from the first engineering bill of materials data to specific process nodes in the first process list data; and the second recommendation type tag refers to the identification information used to characterize whether the second candidate material assignment scheme has medium or low confidence or matching degree.

[0058] Regarding this step, in some possible implementations, the feature extraction function of the intelligent agent can be invoked to extract features from the first engineering bill of materials data to obtain material feature vectors, and to extract features from the first process list data to obtain process step feature vectors. Then, the similarity values ​​between the material feature vectors and process step feature vectors and the feature vectors corresponding to each historical material assignment scheme in the historical process knowledge base are calculated. Historical material assignment schemes with similarity values ​​exceeding a preset threshold are taken as similarity retrieval results. A second candidate material assignment scheme is generated based on the similarity retrieval results, and a corresponding second recommendation type label is generated based on the numerical range of the similarity value.

[0059] Furthermore, it is necessary to invoke the intelligent agent to determine the first material assignment result based on the first candidate material assignment scheme and the corresponding first recommendation type tag, and / or the second candidate material assignment scheme and the corresponding second recommendation type tag.

[0060] Regarding this step, in some possible implementations, the agent can be invoked to directly use the first candidate material allocation scheme and its corresponding first recommendation type tag as the first material allocation result when the query result indicates that a first historical material allocation scheme has been found. Alternatively, the agent can be invoked to use the second candidate material allocation scheme and its corresponding second recommendation type tag as the first material allocation result when the query result indicates that no first historical material allocation scheme has been found but the similarity retrieval result indicates that a historical scheme with a similarity higher than a preset threshold has been found. Alternatively, the agent can be invoked to merge the first candidate material allocation scheme and its corresponding first recommendation type tag with the second candidate material allocation scheme and its corresponding second recommendation type tag when the first engineering bill of materials contains multiple materials, and some materials have found a first historical material allocation scheme while others have not found a first historical material allocation scheme but have similarity retrieval results, to obtain a first material allocation result containing multiple recommendation type tags.

[0061] The recommendation level represented by the first recommendation type label is higher than that represented by the second recommendation type label. The recommendation level refers to a hierarchical indicator used to characterize the credibility, priority, or probability of adoption of candidate material assignment schemes.

[0062] It should be noted that the recommendation level of the second recommendation type marker may differ for different second candidate material assignment schemes. Specifically, when the similarity search results indicate a high similarity between historical material assignment schemes, the corresponding second recommendation type marker has a higher recommendation level; conversely, when the similarity search results indicate a low similarity between historical material assignment schemes, the corresponding second recommendation type marker has a lower recommendation level. This is because higher similarity indicates that historical materials and current materials are closer in attribute characteristics, and the reliability of their assignment schemes is correspondingly higher. This embodiment mainly focuses on the hierarchical relationship where the recommendation level of the first recommendation type marker is higher than that of the second recommendation type marker, and does not limit the specific level division method between the second recommendation type markers corresponding to different second candidate material assignment schemes.

[0063] In this embodiment, a preset intelligent agent is invoked to first query the historical process knowledge base based on the material drawing number in the first engineering bill of materials data. When a first historical material assignment scheme is found, a first candidate material assignment scheme with a high recommendation level is generated, ensuring the accuracy of assignment in the precise matching scenario. When no scheme is found, a second candidate material assignment scheme is generated using similarity retrieval, expanding the coverage of automatic assignment. By distinguishing between the first recommendation type tag and the second recommendation type tag, a confidence reference is provided for the user's interactive operation of the material assignment view, thereby improving the overall efficiency of material assignment while ensuring the accuracy of the material assignment results.

[0064] In one embodiment, the step of "calling the intelligent agent to perform a similarity search in the historical process knowledge base based on the first engineering bill of materials data and the first process list data, and obtaining the similarity search results" can be further refined and may include the following steps: Multi-dimensional feature extraction is performed based on the first engineering bill of materials data to obtain the first material feature vector, and multi-dimensional feature extraction is performed based on the first process list data to obtain the first process step feature vector; The intelligent agent is invoked to perform vector similarity retrieval in the historical process knowledge base based on the first material feature vector and the first process step feature vector, and obtain the similarity value of each historical material assignment scheme in the historical process knowledge base. The intelligent agent is invoked to classify and determine the similarity values ​​of each historical material assignment scheme in the historical process knowledge base according to the preset similarity threshold, and the similarity retrieval results are obtained.

[0065] Specifically, considering that material data and process data contain multi-dimensional attribute information, it is difficult to accurately reflect the compatibility between materials and processes by relying solely on single-dimensional matching. Furthermore, the contribution of features of different dimensions to the matching results varies. This embodiment proposes to convert unstructured or semi-structured data into vector representations and achieve accurate similarity retrieval by combining vector similarity calculation with threshold grading.

[0066] First, multi-dimensional feature extraction is performed based on the first engineering bill of materials data to obtain the first material feature vector. Then, multi-dimensional feature extraction is performed based on the first process list data to obtain the first process step feature vector. The first material feature vector refers to the numerical vector representing the material in the first engineering bill of materials data within the multi-dimensional feature space; the first process step feature vector refers to the numerical vector representing the step in the first process list data within the multi-dimensional feature space.

[0067] Regarding this step, in some possible implementations, a preset feature extraction model can be invoked to encode the material name, specifications, and material attributes in the first engineering bill of materials data, and the result of the encoding process can be used as the first material feature vector; at the same time, the process name, processing type, and required tooling attributes in the first process list data can be encoded, and the result of the encoding process can be used as the first process feature vector.

[0068] Furthermore, the intelligent agent needs to perform vector similarity retrieval in the historical process knowledge base based on the first material feature vector and the first process step feature vector to obtain the similarity values ​​of each historical material assignment scheme in the historical process knowledge base. Here, vector similarity retrieval refers to the calculation process of distance or similarity between vectors; each historical material assignment scheme in the historical process knowledge base refers to the historical material assignment schemes stored in the historical process knowledge base, which can be all historical material assignment schemes in the historical process knowledge base, or a subset of historical material assignment schemes selected according to preset conditions; the similarity value of each historical material assignment scheme refers to the numerical value representing the degree of similarity between the combined vector composed of the first material feature vector and the first process step feature vector and the feature vector corresponding to each historical material assignment scheme in the historical process knowledge base.

[0069] Regarding this step, in some possible implementations, the intelligent agent's computing module can be invoked to calculate the cosine similarity or Euclidean distance between the combined vector formed by the first material feature vector and the first process step feature vector and the feature vector corresponding to each historical material assignment scheme in the historical process knowledge base. The calculated cosine similarity value or the normalized distance value is then used as the similarity value of each historical material assignment scheme in the historical process knowledge base.

[0070] Furthermore, it is necessary to invoke an intelligent agent to classify and determine the similarity values ​​of each historical material assignment scheme in the historical process knowledge base according to a preset similarity threshold, thereby obtaining similarity retrieval results. Here, the preset similarity threshold refers to the critical value used to determine whether the degree of similarity meets the recommendation requirements. The preset similarity threshold can be a fixed value or a range of values ​​containing multiple different levels. Classification and determination refer to the process of determining the recommendation level of the corresponding historical material assignment scheme or whether to include it in the similarity retrieval results based on the comparison result between the similarity value and the preset similarity threshold.

[0071] Regarding this step, in some possible implementations, an agent can be invoked to compare the similarity values ​​of each historical material assignment scheme in the historical process knowledge base with a preset similarity threshold, and include historical material assignment schemes with similarity values ​​greater than or equal to the preset similarity threshold in the similarity retrieval results. Alternatively, if the preset similarity threshold includes multiple level thresholds, the agent can be invoked to assign corresponding level labels to the corresponding historical material assignment schemes based on the threshold range in which the similarity values ​​fall, and use the historical material assignment schemes with level labels as similarity retrieval results.

[0072] In this embodiment, multi-dimensional feature extraction is performed based on the first engineering bill of materials data and the first process list data to obtain the first material feature vector and the first process step feature vector, thereby realizing the quantitative representation of data features; by calling the intelligent agent to perform vector similarity retrieval, the similarity value of each historical material assignment scheme in the historical process knowledge base is calculated, thereby realizing the matching of historical schemes; by performing hierarchical judgment based on the preset similarity threshold, the validity of the similarity retrieval results is ensured, thereby improving the accuracy of similarity retrieval.

[0073] In one embodiment, the preset similarity threshold includes a first similarity threshold and a second similarity threshold, wherein the first similarity threshold is higher than the second similarity threshold. Further refining the above step "calling the intelligent agent to determine the second candidate material assignment scheme and the corresponding second recommendation type tag based on the similarity retrieval results" can include the following steps: If the similarity retrieval results indicate that a second historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the second historical material assignment scheme is greater than or equal to the first similarity threshold, the agent is invoked to extract the second historical material assignment scheme from the historical process knowledge base as the second candidate material assignment scheme, and a corresponding second recommendation type label is generated. If the similarity retrieval results indicate that there is a third historical material assignment scheme in the historical process knowledge base, and the similarity value of the third historical material assignment scheme is less than the first similarity threshold and greater than or equal to the second similarity threshold, the agent is invoked to extract the third historical material assignment scheme from the historical process knowledge base as the second candidate material assignment scheme, and the corresponding second recommendation type label is generated. Among them, the recommendation level of the second recommendation type tag corresponding to the second historical material assignment scheme is higher than the recommendation level of the second recommendation type tag corresponding to the third historical material assignment scheme.

[0074] Specifically, considering that it is difficult to distinguish the reference value of historical solutions with different matching degrees for current materials by judging similarity using only a single threshold, this embodiment proposes a scheme to set dual thresholds to classify similarity retrieval results, thereby balancing the coverage and accuracy of recommendation results.

[0075] The preset similarity thresholds include a first similarity threshold and a second similarity threshold, with the first similarity threshold being higher than the second similarity threshold. Specifically, the first similarity threshold is used to define highly similar historical schemes, and the second similarity threshold is used to define partially similar historical schemes. By setting different threshold ranges, historical material assignment schemes in the historical process knowledge base can be divided into different recommendation priorities. For example, the first similarity threshold can be set to 80%, and the second similarity threshold can be set to 50%. In this case, historical schemes with a similarity value greater than or equal to 80% are considered highly similar, and historical schemes with a similarity value between 50% and 80% are considered partially similar. It should be noted that the above values ​​are only illustrative examples, and the specific values ​​of the preset similarity thresholds are not limited in this application embodiment. The preset similarity thresholds can be dynamically adjusted or customized according to the data quality, the number of historical samples, or the user's requirements for recommendation accuracy in the actual scenario.

[0076] First, if the similarity retrieval results indicate the existence of a second historical material assignment scheme in the historical process knowledge base, and the similarity value of the second historical material assignment scheme is greater than or equal to the first similarity threshold, the agent is invoked to extract the second historical material assignment scheme from the historical process knowledge base as a second candidate material assignment scheme, and a corresponding second recommendation type tag is generated. Here, the second historical material assignment scheme refers to a historical material assignment scheme stored in the historical process knowledge base that highly matches the material characteristics in the first engineering bill of materials data and the process characteristics in the first process list data; the second recommendation type tag corresponding to the second candidate material assignment scheme refers to identification information used to characterize that the scheme has high credibility or high matching degree, such as a "medium recommendation" or "highly similar recommendation" tag.

[0077] Regarding this step, in some possible implementations, an agent can be invoked to traverse the similarity retrieval results, identify historical material assignment schemes with similarity values ​​greater than or equal to the first similarity threshold as second historical material assignment schemes, and read the process node mapping relationship contained in the second historical material assignment scheme from the historical process knowledge base. This process node mapping relationship is then applied to the current first process list data to generate a second candidate material assignment scheme. At the same time, a second recommendation type tag representing a higher recommendation level is generated and associated with the second candidate material assignment scheme and stored.

[0078] Furthermore, if the similarity retrieval results indicate the existence of a third historical material assignment scheme in the historical process knowledge base, and the similarity value of the third historical material assignment scheme is less than the first similarity threshold but greater than or equal to the second similarity threshold, then the agent is invoked to extract the third historical material assignment scheme from the historical process knowledge base as the second candidate material assignment scheme, and a corresponding second recommendation type tag is generated. Here, the third historical material assignment scheme refers to a historical material assignment scheme stored in the historical process knowledge base that partially matches the material in the first engineering bill of materials data and the process feature in the first process list data; the second recommendation type tag corresponding to the third historical material assignment scheme refers to identification information used to characterize that the scheme has moderate credibility or a partial matching degree, such as a "weak recommendation" or "partially similar recommendation" tag.

[0079] Regarding this step, in some possible implementations, an agent can be invoked to traverse the similarity retrieval results, identify historical material assignment schemes with similarity values ​​less than the first similarity threshold and greater than or equal to the second similarity threshold as the third historical material assignment scheme, and read the process node mapping relationship contained in the third historical material assignment scheme from the historical process knowledge base. This process node mapping relationship is then applied to the current first process list data to generate the second candidate material assignment scheme. At the same time, a second recommendation type tag representing a lower recommendation level is generated and associated with the second candidate material assignment scheme and stored.

[0080] The recommendation level of the second recommendation type tag corresponding to the second historical material assignment scheme is higher than that of the second recommendation type tag corresponding to the third historical material assignment scheme. Specifically, since the similarity value of the second historical material assignment scheme is higher, it indicates that its characteristics overlap with the current material to be assigned is higher. Therefore, its corresponding recommendation scheme has higher reference value and should be given a higher recommendation level to prompt users to pay priority. For example, the second recommendation type tag corresponding to the second historical material assignment scheme can be displayed in highlighted green in the user interface or placed at the top of the recommendation list, while the second recommendation type tag corresponding to the third historical material assignment scheme can be displayed in ordinary yellow or placed at the bottom of the recommendation list. It should be noted that the specific forms of recommendation level are not limited to color differentiation, sorting priority differentiation, label text differentiation, or icon style differentiation, and this application embodiment does not limit this.

[0081] In this embodiment, by setting a preset similarity threshold, including a first similarity threshold and a second similarity threshold, the similarity values ​​of each historical material assignment scheme in the historical process knowledge base are divided into intervals. This allows for the differentiation between second and third historical material assignment schemes with different matching degrees. By assigning a higher recommendation level to the second historical material assignment scheme with a higher similarity value, the priority of high-matching schemes in the second material assignment results is ensured. This expands the coverage of automatic assignment while improving the discriminativeness and assignment accuracy of the second candidate material assignment schemes.

[0082] In one embodiment, the first material assignment result further includes at least one manual assignment flag, which indicates that the corresponding material needs to be manually assigned. The material assignment method of this application embodiment may further include the following steps: If the similarity search results indicate that a fourth historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the fourth historical material assignment scheme is less than the second similarity threshold, the agent is invoked to generate a manual assignment tag.

[0083] Specifically, considering that when the similarity value of historical material assignment schemes in the historical process knowledge base is too low, the historical material assignment scheme has low reference value for the current material, and directly adopting the scheme may lead to assignment errors, this embodiment proposes a scheme to filter low similarity schemes and generate manual assignment marks to prompt human intervention.

[0084] The first material assignment result also includes at least one manual assignment marker. A manual assignment marker refers to identification information used to indicate that the corresponding material cannot be automatically matched with a historical solution that meets the similarity requirements by the intelligent agent, and therefore needs to be manually assigned by the user. For example, the manual assignment marker can be a specific field attached to the material attributes, a specific icon displayed next to the material node, or a label used to filter materials. It should be noted that this application embodiment does not limit the specific data format and display style of the manual assignment marker, as long as it serves to prompt the user to perform manual assignment.

[0085] First, the similarity search results indicate the existence of a fourth historical material assignment scheme in the historical process knowledge base. If the similarity value of the fourth historical material assignment scheme is less than the second similarity threshold, the agent is invoked to generate a manual assignment tag. The fourth historical material assignment scheme refers to a historical material assignment scheme stored in the historical process knowledge base that has a low degree of matching with the material features in the first engineering bill of materials data and the process feature features in the first process list data.

[0086] Regarding this step, in some possible implementations, an intelligent agent can be invoked to monitor the similarity retrieval results. When a fourth historical material assignment scheme is identified in the historical process knowledge base and its similarity value is less than a second similarity threshold, a manual assignment tag is generated to indicate that the material requires manual handling, and this manual assignment tag is output as part of the first material assignment result. Alternatively, when the intelligent agent determines that the similarity value of the fourth historical material assignment scheme is less than the second similarity threshold, it does not extract the fourth historical material assignment scheme as a recommended scheme, but instead directly generates a manual assignment tag and associates it with the corresponding material identifier to form a first material assignment result containing the manual assignment tag.

[0087] It should be noted that the first material assignment result involved in this embodiment includes at least one candidate material assignment scheme, a recommendation type tag corresponding to each candidate material assignment scheme, and at least one manual assignment tag. In this case, the material assignment view generated and displayed based on the first material assignment result will contain material information with manual assignment tags. This material information is usually displayed in the unassigned view or the pending area. By displaying materials with manual assignment tags in the material assignment view, a list of materials that cannot be automatically assigned can be shown to the user, assisting the user in locating pending objects, and supporting the user to manually assign materials with manual assignment tags through interactive operations, thereby achieving a seamless connection between automatic assignment and manual assignment.

[0088] In this embodiment, by generating a manual assignment marker when the similarity value of the fourth historical material assignment scheme is less than the second similarity threshold, materials corresponding to historical material assignment schemes with insufficient matching in the historical process knowledge base can be identified and marked. By incorporating the manual assignment marker into the first material assignment result, the classification and management of materials that cannot be automatically matched is realized, avoiding interference from low similarity schemes on the assignment results, and providing clear prompts for manual intervention in the material assignment view. This allows users to complete the assignment of remaining materials through interactive operations, ensuring the integrity of the material assignment process.

[0089] In one embodiment, the material assignment method of this application may further include the following steps: Obtain the second engineering bill of materials data and the second process list data of historical rail vehicle projects, as well as the material allocation plan of historical rail vehicle projects; Multi-dimensional feature extraction is performed based on the bill of materials data for the second project to obtain the feature vector of the second material, and multi-dimensional feature extraction is performed based on the bill of materials data for the second process to obtain the feature vector of the second process step. Based on the second material feature vector, the second process feature vector, and the material assignment scheme of historical rail vehicle projects, construct or update the historical process knowledge base.

[0090] Specifically, considering that the richness of the historical process knowledge base directly affects the accuracy and coverage of the intelligent agent's automatic assignment, this embodiment proposes a scheme to construct or update the historical process knowledge base in order to expand the information content of the historical process knowledge base and improve the assignment capability of the intelligent agent. By converting the data of historical rail vehicle projects into structured feature vectors and storing them, data support can be provided for subsequent automatic assignment processing.

[0091] First, it is necessary to obtain the second engineering bill of materials (BOM) data and the second process list data of historical rail vehicle projects, as well as the material allocation schemes for these projects. Historical rail vehicle projects refer to rail vehicle manufacturing projects for which material allocation has been completed and relevant data has been stored. The second engineering BOM data refers to the engineering BOM data generated during the design phase of the historical rail vehicle project, containing material information. The second process list data refers to the process list data generated during the process planning phase of the historical rail vehicle project, containing process node information. The material allocation scheme for historical rail vehicle projects refers to the allocation strategy, confirmed manually or recorded by the system, that distributes materials from the engineering BOM data of the historical rail vehicle project to specific process nodes in the process list data. It should be noted that the second bill of materials (BOM) data for historical rail vehicle projects can be the complete BOM data for the historical rail vehicle projects, or it can be a partial BOM data for the historical rail vehicle projects, such as BOM data generated within a specific time period or BOM data for a specific model series; correspondingly, the second process list data for historical rail vehicle projects can be the complete process list data for the historical rail vehicle projects, or it can be a partial process list data for the historical rail vehicle projects, such as process list data associated with the selected BOM data. This application does not limit the specific scope of the second BOM data and the second process list data for historical rail vehicle projects in its embodiments.

[0092] Regarding this step, some possible implementations include retrieving the second engineering bill of materials data, the second process list data, and the material allocation scheme for historical rail vehicle projects from a database. Alternatively, it can receive the second engineering bill of materials data, the second process list data, and the material allocation scheme for historical rail vehicle projects from relevant terminals.

[0093] Furthermore, it is necessary to perform multi-dimensional feature extraction based on the second engineering bill of materials data to obtain the second material feature vector, and to perform multi-dimensional feature extraction based on the second process list data to obtain the second process step feature vector. Here, multi-dimensional feature extraction refers to the process of extracting feature information from multiple dimensions of data and converting it into numerical representations; the second material feature vector refers to the numerical vector used to represent the materials in the second engineering bill of materials data in the multi-dimensional feature space; and the second process step feature vector refers to the numerical vector used to represent the processes in the second process list data in the multi-dimensional feature space.

[0094] Regarding this step, in some possible implementations, a preset feature extraction model can be invoked to encode the material name, specifications, and material attributes in the second engineering bill of materials data, and the result of the encoding process can be used as the second material feature vector; at the same time, the process name, processing type, and required tooling attributes in the second process list data can be encoded, and the result of the encoding process can be used as the second process process feature vector.

[0095] Furthermore, it is necessary to construct or update the historical process knowledge base based on the second material feature vector, the second process feature vector, and the material assignment scheme of historical rail vehicle projects.

[0096] Regarding this step, in some possible implementations, in the absence of a historical process knowledge base, an initial database can be established as the historical process knowledge base based on the correspondence between the second material feature vector, the second process step feature vector, and the material allocation scheme of historical rail vehicle projects. Alternatively, if a historical process knowledge base already exists, the correspondence between the second material feature vector, the second process step feature vector, and the material allocation scheme of historical rail vehicle projects can be added to the historical process knowledge base to update its data volume.

[0097] It should be noted that the material allocation schemes for historical rail vehicle projects are not equivalent to the historical material allocation schemes in the historical process knowledge base. Specifically, the historical material allocation schemes in the historical process knowledge base refer to the collection of all material allocation schemes stored in the historical process knowledge base, which includes the material allocation scheme for at least one historical rail vehicle project; while the material allocation schemes for historical rail vehicle projects only refer to the material allocation schemes for the specific historical rail vehicle project currently used to construct or update the historical process knowledge base. During the construction or updating of the historical process knowledge base, the material allocation schemes for historical rail vehicle projects are added to the historical process knowledge base as initial or incremental data, becoming part of the historical material allocation schemes in the historical process knowledge base.

[0098] In this embodiment, by acquiring the second engineering bill of materials data and the second process list data of historical rail vehicle projects, as well as the material allocation schemes of historical rail vehicle projects, and performing multi-dimensional feature extraction to obtain the second material feature vector and the second process feature vector, a historical process knowledge base is constructed or updated, achieving structured storage and accumulation of historical data. This method enriches the data volume of the historical process knowledge base, enabling the intelligent agent to perform accurate matching or similarity calculation based on the second material feature vector and the second process feature vector, thereby providing a searchable data foundation for subsequent automatic allocation processing and improving the recommendation accuracy of material allocation schemes.

[0099] In one embodiment, the steps of "generating and displaying a material assignment view based on the first material assignment result" and "determining a second material assignment result based on the user's interactive operation on the material assignment view" can be further refined and may include the following steps: Based on the first material assignment result, a first subview and a second subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, and the second subview is used to indicate the assigned materials in the first material assignment result; Generate and display the material assignment view based on the first subview and the second subview; Based on the user's confirmation and / or adjustment operations on the assigned materials in the second subview of the material assignment view, determine the assigned correction results; Based on the already assigned correction results, determine the second material assignment result.

[0100] Specifically, this embodiment proposes a scheme to construct subviews containing different information dimensions to assist users in making hierarchical decisions.

[0101] First, based on the first material assignment result, a first sub-view and a second sub-view need to be generated. The first sub-view is a graphical interface component that displays the overall picture of the materials to be assigned in the current rail vehicle project; the second sub-view is a graphical interface component that displays the materials and their corresponding assignment information after automatic assignment processing by a preset intelligent agent. Specifically, the first sub-view indicates all materials in the first project bill of materials data, and the second sub-view indicates the assigned materials in the first material assignment result. All materials refer to the collection of all material nodes and their attribute information contained in the first project bill of materials data; assigned materials refer to materials with candidate material assignment schemes in the first material assignment result.

[0102] Regarding this step, in some possible implementations, a graphics rendering engine can be invoked to render and generate a first subview based on the tree-like hierarchical structure of the first engineering bill of materials data. At the same time, the first material assignment results can be traversed to extract material data containing candidate material assignment schemes and render and generate a second subview.

[0103] Furthermore, a material assignment view needs to be generated and displayed based on the first subview and the second subview.

[0104] Regarding this step, in some possible implementations, the first subview and the second subview can be combined in a split-screen manner to generate and display a material assignment view. Alternatively, the first subview and the second subview can be combined in a tab-switching manner to generate and display a material assignment view.

[0105] Furthermore, the assigned correction result needs to be determined based on the user's confirmation and / or adjustment operations on the assigned materials in the second sub-view of the material assignment view. Here, a confirmation operation refers to the user's interaction of acknowledging and submitting the assigned materials and their candidate material assignment schemes displayed in the second sub-view via an input device; an adjustment operation refers to the user's interaction of modifying the candidate material assignment schemes for the assigned materials displayed in the second sub-view via an input device; and the assigned correction result refers to the updated material assignment related data based on the confirmation or adjustment operations.

[0106] Regarding this step, in some possible implementations, in response to the user's click confirmation command on the target assigned material in the second sub-view, the status of the candidate material assignment scheme corresponding to the target assigned material can be updated to "confirmed," and the updated data can be used as the assignment correction result. Alternatively, in response to the user's modification command on the process node of the target assigned material in the second sub-view, the process node association in the candidate material assignment scheme corresponding to the target assigned material can be updated, and the updated association can be used as the assignment correction result. Alternatively, in response to the user's confirmation operation on some assigned materials and adjustment operation on another part of the assigned materials in the second sub-view, the status or association of the corresponding materials can be updated respectively, and all updated data can be summarized as the assignment correction result.

[0107] Furthermore, the second material assignment result needs to be determined based on the already assigned correction result.

[0108] Regarding this step, in some possible implementations, the assignment information corresponding to each material in the already assigned correction result can be encapsulated to generate a second material assignment result that conforms to a preset data format.

[0109] Understandably, the first material assignment result includes initial recommended data generated by a pre-defined intelligent agent, the assigned correction result includes intermediate data after interactive correction by the user based on the first material assignment result, and the second material assignment result is the data finally determined based on the assigned correction result and used to guide subsequent production and manufacturing.

[0110] In this embodiment, by generating a first sub-view indicating all materials in the first engineering bill of materials data and a second sub-view indicating assigned materials, a categorized and visual display of material data is achieved, facilitating user identification of review targets. By determining the assigned correction result based on the user's confirmation and / or adjustment operations on the assigned materials in the second sub-view, and accordingly determining the second material assignment result, manual verification and correction of the first material assignment result is achieved. This method, while utilizing a pre-defined intelligent agent to achieve automatic assignment processing to improve efficiency, eliminates potential deviations in candidate material assignment schemes through interactive operations, thereby ensuring the accuracy of the second material assignment result.

[0111] In one embodiment, the steps of "generating and displaying a material assignment view based on the first material assignment result" and "determining a second material assignment result based on the user's interactive operation on the material assignment view" can be further refined and may include the following steps: Based on the first material assignment result, a first subview, a second subview, and a third subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, the second subview is used to indicate the assigned materials in the first material assignment result, and the third subview is used to indicate the unassigned materials in the first material assignment result. Generate and display the material assignment view based on the first subview, the second subview, and the third subview; Based on the user's confirmation and / or adjustment operations on the assigned materials in the second subview of the material assignment view, determine the assigned correction results; The manual assignment result is determined based on the user's manual assignment operation on the unassigned materials in the third subview of the material assignment view. Based on the already assigned correction results and the manual assignment results, determine the second material assignment result.

[0112] Specifically, considering that there may be materials that have not been automatically assigned in the first material assignment result, and that users need to manually intervene in these materials, this embodiment proposes a scheme to construct a view containing unassigned materials to assist users in completing the assignment of the remaining materials.

[0113] First, based on the first material assignment result, a first subview, a second subview, and a third subview need to be generated. The third subview is a graphical interface component used to display materials in the current rail vehicle project that have not been automatically assigned and their related information. Specifically, the first subview indicates all materials in the first project bill of materials data, the second subview indicates assigned materials in the first material assignment result, and the third subview indicates unassigned materials in the first material assignment result. All materials refer to the collection of all material nodes and their attribute information contained in the first project bill of materials data; assigned materials refer to materials in the first material assignment result that have candidate material assignment schemes; unassigned materials refer to materials in the first material assignment result that do not have candidate material assignment schemes or are marked as requiring manual assignment.

[0114] Regarding this step, in some possible implementations, a graphics rendering component can be invoked to render and generate a first subview based on the first engineering bill of materials data; the first material assignment results can be traversed to identify materials with candidate material assignment schemes and render and generate a second subview; materials without candidate material assignment schemes can be identified and render and generate a third subview.

[0115] Furthermore, a material assignment view needs to be generated and displayed based on the first subview, the second subview, and the third subview.

[0116] Regarding this step, in some possible implementations, the first, second, and third subviews can be combined and displayed as a multi-window side-by-side to generate a material assignment view. Alternatively, the first, second, and third subviews can be combined and displayed as a tabbed interface to generate a material assignment view.

[0117] Furthermore, the assigned correction result needs to be determined based on the user's confirmation and / or adjustment operations on the assigned materials in the second sub-view of the material assignment view. Here, a confirmation operation refers to the user's interaction with the assigned materials and their candidate material assignment schemes displayed in the second sub-view via an input device; an adjustment operation refers to the user's interaction with the user to modify the candidate material assignment schemes for the assigned materials displayed in the second sub-view via an input device; and the assigned correction result refers to the updated material assignment related data based on the confirmation or adjustment operations.

[0118] Regarding this step, in some possible implementations, in response to the user's confirmation instruction for the target assigned material in the second sub-view, the candidate material assignment scheme corresponding to the target assigned material can be retained, and the retained data can be used as the assigned correction result. Alternatively, in response to the user's adjustment instruction for the target assigned material in the second sub-view, the candidate material assignment scheme corresponding to the target assigned material can be modified, and the modified data can be used as the assigned correction result. Alternatively, in response to the user's confirmation operation for some assigned materials and adjustment operation for another part of the assigned materials in the second sub-view, the corresponding candidate material assignment schemes can be retained or modified respectively, and the processed data can be summarized as the assigned correction result.

[0119] Furthermore, the manual assignment result needs to be determined based on the user's manual assignment operation on the unassigned materials in the third sub-view of the material assignment view. The manual assignment operation refers to the interactive behavior of the user establishing a relationship between the unassigned materials in the third sub-view and the process nodes in the first process list data through an input device. The manual assignment result refers to the association data between materials and process nodes generated based on the manual assignment operation.

[0120] Regarding this step, in some possible implementations, the association between the unassigned material and the target process node can be established in response to the user dragging and dropping the target unassigned material from the third subview to the target process node in the first process list data, and this association can be used as the result of manual assignment. Alternatively, the association between the unassigned material and the target process node can be established in response to the user's right-click menu selection of the unassigned material in the third subview, selecting the target process node from the pop-up process list, and this association can be used as the result of manual assignment.

[0121] Furthermore, the second material assignment result needs to be determined based on the already assigned correction result and the manual assignment result.

[0122] Regarding this step, in some possible implementations, the assigned correction results and the manual assignment results can be fused together to generate a second material assignment result that includes the final assignment status of all materials.

[0123] Understandably, the first material assignment result includes initial recommendation data generated by a preset intelligent agent, the assigned correction result includes data after interactive correction of the assigned materials in the first material assignment result, the manual assignment result includes data after manual allocation of the unassigned materials in the first material assignment result, and the second material assignment result is the final material assignment data obtained by integrating the assigned correction result and the manual assignment result.

[0124] In this embodiment, by generating a third sub-view to indicate unassigned materials, a centralized display of materials that cannot be automatically matched in the first material assignment result is achieved. By determining the manual assignment result based on the user's manual assignment operation on the unassigned materials in the third sub-view, and combining this with the already assigned correction result, the second material assignment result is determined, thus achieving data fusion between automatic and manual assignment. This method improves assignment efficiency by utilizing a pre-set intelligent agent while compensating for the deficiency of automatic assignment processing in covering all materials, ensuring the completeness of the second material assignment result.

[0125] In one embodiment, the material assignment view includes a material balance marker, which is dynamically adjusted according to the assigned quantity of the corresponding material.

[0126] Specifically, the material balance mark refers to the identification information used to represent the remaining unassigned quantity of material in the current assignment task; the material corresponding to the balance mark refers to the material node displayed in the material assignment view that is associated with the balance mark; the balance mark with the assigned quantity of the corresponding material means that there is a functional relationship or mapping relationship between the value or status displayed by the balance mark and the quantity of the corresponding material that has been assigned; dynamic adjustment means that as the assignment operation proceeds, the display content or style of the balance mark is updated in real time or periodically.

[0127] More specifically, in the process of determining the second material assignment result based on the user's interactive operations on the material assignment view, the materials displayed in the material assignment view have a preset total demand quantity. When the user performs an interactive operation, the system determines the assignment quantity corresponding to this operation based on the type of interactive operation. The system calculates the difference between the total demand quantity of materials and the already assigned quantity in real time, and displays this difference as the current value of the margin marker in the material assignment view.

[0128] Regarding this process, in some possible implementations, user interaction with the target material in the material assignment view can be monitored; in response to the interaction, the assigned quantity of the target material can be updated; based on the total demand quantity of the target material and the updated assigned quantity, the current remaining quantity of the target material can be calculated; and the current remaining quantity can be updated as the value of the remaining quantity marker to the display area in the material assignment view corresponding to the target material.

[0129] Furthermore, the material assignment view can adjust the display style of materials based on changes in the balance marker value. For example, when the balance marker is zero, it indicates that the material has been fully assigned, and the material assignment view can mark the material in the first display state; when the balance marker is not zero, it indicates that the material has not been fully assigned, and the material assignment view can mark the material in the second display state. Through this dynamic adjustment, users can know the material assignment progress, thus helping them locate materials that have not been assigned and continue performing interactive operations.

[0130] In this embodiment, by setting a reserve marker in the material assignment view that dynamically adjusts with the assigned quantity, real-time visual monitoring of the material assignment progress is achieved. During the user's interactive operation to determine the second material assignment result, the reserve marker can provide feedback on the remaining quantity of materials to be assigned, assisting the user in determining whether the assignment task has been completed. This avoids omissions or over-assignments during the material assignment process, thereby improving the accuracy and efficiency of the material assignment work.

[0131] In one embodiment, please refer to Figure 2 , Figure 2 This is a schematic diagram of the overall process of material assignment provided in the embodiments of this application.

[0132] Specifically, firstly, historical rail vehicle project data is acquired, and multi-dimensional feature extraction is performed on this data to construct a historical process knowledge base. Next, the first engineering bill of materials (BOM) data and the first process list data for the current rail vehicle project are acquired and input into a pre-defined agent. The pre-defined agent first queries the historical process knowledge base based on the material drawing number in the first engineering BOM data to obtain the query results. If the query results indicate that a first historical material assignment scheme corresponding to the material drawing number is found, the pre-defined agent is invoked to determine a first candidate material assignment scheme and its corresponding first recommendation type tag based on the first historical material assignment scheme and the first process list data. If the query results indicate that no first historical material assignment scheme corresponding to the material drawing number is found, the pre-defined agent is invoked to perform a similarity retrieval. During the similarity retrieval process, the pre-defined agent performs multi-dimensional feature extraction based on the first engineering BOM data and the first process list data to obtain a first material feature vector and a first process feature vector, and then performs a vector similarity retrieval in the historical process knowledge base based on these first material feature vectors and first process feature vectors to obtain a similarity value X. Subsequently, a pre-defined agent performs threshold-based classification on the similarity value X according to a pre-defined similarity threshold. If the similarity value X is greater than or equal to the first similarity threshold, a second candidate material assignment scheme and its corresponding second recommendation type label are determined, with the second recommendation type label representing a higher recommendation level. If the similarity value X is less than the first similarity threshold but greater than or equal to the second similarity threshold, a second candidate material assignment scheme and its corresponding second recommendation type label are determined, with the second recommendation type label representing a lower recommendation level. If the similarity value X is less than the second similarity threshold, a pre-defined agent is invoked to generate a manual assignment label. The aforementioned first candidate material assignment scheme and first recommendation type label, second candidate material assignment scheme and second recommendation type label, and manual assignment label are combined to form the first material assignment result. A material assignment view is generated and displayed based on the first material assignment result. This view includes a first subview, a second subview, and a third subview. The first subview indicates all materials in the first project bill of materials data. The second subview indicates the assigned materials in the first material assignment result. The third subview indicates the unassigned materials in the first material assignment result, and materials corresponding to manually assigned materials are displayed in the third subview. Furthermore, the material assignment view includes a surplus marker, which dynamically adjusts according to the assigned quantity of the corresponding material. Users perform interactive operations on the material assignment view. These operations include confirming or adjusting the assigned materials in the second subview, and manually assigning the unassigned materials in the third subview. Finally, the second material assignment result is determined based on these interactive operations.

[0133] This embodiment illustrates the process from building a knowledge base from historical data, inputting current project data, using a pre-defined intelligent agent for hierarchical judgment based on image number query and similarity retrieval, to generating and visualizing the first material assignment result, and finally determining the second material assignment result through interactive operation.

[0134] In one embodiment, please refer to Figure 3 , Figure 3 This is a schematic diagram illustrating the selection of the tree-like hierarchical structure of the bill of materials data provided in the embodiments of this application.

[0135] Specifically, Figure 3 This interface displays the hierarchical tree structure of the current rail vehicle project's Bill of Materials (BOM) data. This interface allows users to select items within the tree structure to determine the first BOM data to be assigned. The interface includes a title display area, a node selection status indicator area, a tree structure display area, and operation button areas. The title display area identifies the type of BOM data currently displayed, i.e., an EBOM structure; the node selection status indicator area displays the number of currently selected nodes, such as zero nodes; and the tree structure display area shows the hierarchical relationships between materials in the current rail vehicle project's BOM data in a tree-like format.

[0136] In the tree-like hierarchical display area, each material is presented as a node, with the indentation relationship between nodes representing the parent-child containment relationship. The top-level parent node corresponds to the bogie assembly, with material code 4000100604, version number 01, and required quantity of 1. The drawing number information for this material is SFE62TC01-500-00000, and the node sequence number is zero. This parent node contains seven lower-level child nodes, corresponding to the wheelset system assembly, braking system assembly, suspension system assembly, traction system assembly, bogie frame assembly, connection and fastener system, and sealing and protection system, respectively. The materials code for the wheelset system assembly is 4000100605, version number 01, required quantity 2, drawing number SFE62TC01-510-00000, and node number 1; the material code for the braking system assembly is 4000100659, version number 01, required quantity 1, drawing number SFE62TC01-520-00000, and node number 2; the material code for the suspension system assembly is 4000100710, version number 01, required quantity 1, drawing number SFE62TC01-530-00000, and node number 3; the material code for the traction system assembly is 4000100737, version number 01, required quantity... The following components are listed: 1. The part number is SFE62TC01-540-00000, and the node number is four; 2. The part number for the bogie frame assembly is 4000100784, version number 01, and quantity required is 1; the part number for the drawing is SFE62TC01-550-00000, and the node number is five; 3. The part number for the connection and fastener system is 4000100827, version number 01, and quantity required is 1; the drawing number for the drawing is SFE62TC01-560-00000, and the node number is six; 4. The part number for the sealing and protection system is 4000100847, version number 01, and quantity required is 1; the drawing number for the drawing is SFE62TC01-570-00000, and the node number is seven. Additionally, checkbox controls next to each node are used to receive user selections.

[0137] The operation button area includes an OK button and a Close button. The OK button responds to the user's selection of a target node in the tree-like hierarchy, confirming the material data corresponding to the selected node and its subordinate nodes as the first engineering bill of materials data to be assigned, and triggering the subsequent process of obtaining the first process list data. The Close button cancels the current selection and exits the interface. Through this interface, process engineers can select specific nodes according to the division of process tasks, thereby processing only the material data that needs to be assigned and avoiding duplication of work among different process engineers.

[0138] In this embodiment, the parent-child relationship between materials at each level in the engineering bill of materials data of the current rail vehicle project is visualized through a tree-like hierarchical graphical display. This allows process engineers to quickly locate and determine the range of materials to be assigned through node selection operations, providing a data foundation for subsequent automatic assignment processing by intelligent agents. At the same time, by displaying the number of selected nodes, real-time feedback on the selection status is achieved, improving the accuracy and efficiency of data filtering.

[0139] In one embodiment, please refer to Figure 4 , Figure 4 This is a schematic diagram of a process bill of materials structure provided in an embodiment of this application.

[0140] Specifically, the title display area is used to identify the data type currently being displayed, namely the PBOM structure (Process Bill of Materials structure); the process structure display area is used to display the process route nodes, operation nodes, and candidate material assignment schemes assigned to the corresponding operation nodes in the first process list data in a tree-like manner.

[0141] In the process structure display area, each node is arranged in a hierarchical indentation manner, with the upper-level node being the parent node and the lower-level indented node being the child node, which is used to represent the parent-child containment relationship of the process assembly.

[0142] For example, under the suspension system assembly branch, the process route node "Suspension System Assembly" is displayed, with code P000100011, version number 01, and required quantity 1. This node includes the lower-level sub-node "Optimized Axle Box Vibration Damper Assembly," with code P000100013, version number 01, and required quantity 1. This sub-node further includes the process node "Valve System Assembly," with process code OP10011003, version number 01, and required quantity 1. Under this process node, the first candidate material assignment scheme is displayed, corresponding to the seat material, with material code 4000200112, version number 03, required quantity 6, drawing number SFE91TC01-543-20112, and node sequence number 1. This candidate material assignment scheme is associated with a first recommendation type marker, characterized by a strong recommendation identifier, and displays an assignment quantity of 6.

[0143] Under the primary suspension assembly branch, the process route node primary suspension assembly is displayed, with its code P000100031, version number 01, and required quantity of 1. This node contains multiple lower-level process nodes: Spring steel wire heat treatment process, process code OP10024001, version number 01, associated with the second candidate material assignment scheme, corresponding to spring steel wire material, material code 4000100713, version number 01, required quantity 1, drawing number SFE62TC01-531-11001, node number 1, assigned quantity 1; Spring forming processing process, process code OP10024002, version number 01, associated with the second candidate material assignment scheme, corresponding to spring steel wire material, material code 4000100713, version number 01, required quantity 1, drawing number SFE62TC01-531-11001, node number 1, assigned quantity 1; Axle box spring assembly process, process code OP10024006, version number 01, associated with two lower-level process nodes. Two candidate material assignment schemes are provided, corresponding to spring steel wire and spring seat materials respectively. The spring seat material is coded 4000100714, version number 01, required quantity 2, drawing number SFE62TC01-531-11002, node number 2, and assigned quantity 2. The spring seat processing procedure is coded OP10024003, version number 01, associated with the second candidate material assignment scheme, corresponding to the spring seat material, and assigned quantity 1. The spring seat assembly procedure is coded OP10024004, version number 01, associated with two second candidate material assignment schemes, corresponding to spring seat materials and spring pad materials respectively. The spring pad material is coded 4000100715, version number 01, required quantity 2, drawing number SFE62TC01-531-11003, node number 3, and assigned quantity 2. Each of the above-mentioned second candidate material assignment schemes is associated with a second recommendation type marker, which is characterized by a medium recommendation identifier.

[0144] In this embodiment, the first material assignment result is displayed through a tree-like hierarchical structure, which realizes the visualization of the mapping relationship between candidate material assignment schemes and process nodes in the process list data. This allows process engineers to intuitively identify the specific process location to which each material is automatically assigned and its recommendation credibility. At the same time, by distinguishing the display styles of the first recommendation type marker and the second recommendation type marker, process engineers are provided with assignment schemes with different confidence levels for reference, which facilitates the subsequent determination of the second material assignment result based on the user's interactive operation on the material assignment view.

[0145] In one embodiment, please refer to Figure 5 , Figure 5 This is a schematic diagram of the interface layout and interaction logic of the material assignment view provided in the embodiments of this application.

[0146] Specifically, Figure 5 The interface layout of the material assignment view generated based on the first material assignment result is shown. This interface includes a view switching area, a status filtering area, and a sub-view content area. The view switching area provides view switching options, with switchable views including an EBOM view (corresponding to the first sub-view), an assigned view (corresponding to the second sub-view), and an unassigned view (corresponding to the third sub-view). Selecting different view switching options controls the display of different sub-view contents in the left-hand display area. The status filtering area provides status filtering labels, including all assigned labels, partial assigned labels, and unassigned labels, used to classify and filter materials in the first material assignment result by status.

[0147] The second sub-view displays the assigned materials in the first project's bill of materials data, presenting the parent-child relationships between materials in a tree-like hierarchical structure. The top layer displays the bogie assembly, with material code 4000100604, version number 01, required quantity 1, drawing number SFE62TC01-500-00000, and node number 0. The lower layer contains the wheelset system assembly, with code 4000100605, version number 01, required quantity 2, drawing number SFE62TC01-510-00000, and node number 1. Below the wheelset system assembly are the wheels, with code 4000100004, version number 01, required quantity 2, drawing number SFE45TC01-511-10001, and node number 1. Below the wheels are the hubs and rims. The system includes three sub-materials: rims, wheel rims, and wheel hubs. The wheel hub's code is 4000100005, version number 01, required quantity 1, drawing number SFE45TC01-511-11001, node number 1, and remaining quantity marker 3. The wheel rim's code is 4000100006, version number 01, required quantity 1, drawing number SFE45TC01-511-11002, node number 2, and remaining quantity marker 3. The wheel hub's code is 4000100007, version number 01, required quantity 1, drawing number SFE45TC01-511-11003, node number 3, and remaining quantity marker 3. Each material node displays a process route identifier and is associated with a cad.dwg format computer-aided design drawing file, along with viewing options, to display the design drawing information for that material. Both the wheel hub and wheel rim are associated with the process node "wheel hub and wheel rim assembly", with process code OP100001, version number 01, and associated quantity 1. The complete path is "wheelset system assembly", with path code P000100002, version number 01, and required quantity 1. The wheel rim is associated with the process node "wheel rim installation", with process code OP100002, version number 01, and associated quantity 1. The complete path is also "wheelset system assembly".

[0148] The right side is the view area corresponding to the PBOM structure, used to provide auxiliary information. Specifically, it displays the relationship between candidate material assignment schemes and process nodes in the first process list data in the form of a process hierarchy structure. For example, it shows the process node "Integrated Frame Stress Relief Maintenance", with process code OP10020002, version number 01, and required quantity 1; the process route node "Suspension System Assembly", with code P000100011, version number 01, and required quantity 1; its lower level includes "Optimized Axle Box Vibration Damper Assembly", with code P000100013, version number 01, and required quantity 1; and the lower level of this node includes the valve system assembly process, with process code OP1001. 1003, version number 01, required quantity 1, this process is associated with the first candidate material assignment scheme, corresponding to the seat material, code 4000200112, version number 03, required quantity 6, drawing number SFE91TC01-543-20112, node number 1, assigned quantity 6, and associated with the first recommended type tag; it also includes a first-stage suspension assembly, code P000100031, version number 01, required quantity 1, its lower level includes The heat treatment process for spring steel wire, with process code OP10024001 and version number 01, is associated with the second candidate material assignment scheme. The corresponding spring steel wire material has code 4000100713, version number 01, and a required quantity of 1. The drawing number is SFE62TC01-531-11001, the node number is 1, the assigned quantity is 1, and it is associated with the second recommended type tag. The spring forming process, with process code OP10024002 and version number 0, is also associated with the second recommended type tag. 1. Similarly, the second candidate material assignment scheme for the spring steel wire material mentioned above is associated with the axle box spring assembly process, with process code OP10024006 and version number 01. It is associated with two second candidate material assignment schemes, corresponding to spring steel wire material and spring seat material respectively. The spring seat material has the code 4000100714, version number 01, required quantity of 2, drawing number information SFE62TC01-531-11002, node number 2, and assigned quantity of 2.

[0149] Users can filter materials with different assignment statuses using status filter tabs, and switch to different sub-views using view switching options to view all materials, assigned materials, and unassigned materials. In the second sub-view, users can perform confirmation or adjustment operations on assigned materials to determine the assigned correction result, and then determine the second material assignment result based on this correction result. The remaining quantity marker dynamically adjusts with the assigned quantity of the corresponding material, indicating the remaining quantity of the material to be assigned.

[0150] In this embodiment, by displaying sub-views in different areas, the synchronous visualization of various types of materials in the first engineering bill of materials data is achieved, allowing users to compare and view the original hierarchical structure of materials and their process associations after automatic assignment on the same interface. By providing status filtering labels and view switching options, users can quickly locate target materials according to different needs. By displaying margin markers, process route association information, and recommended type markers for candidate material assignment schemes, complete information is provided for users to perform confirmation or adjustment operations, thereby supporting users to efficiently and accurately determine the assigned correction results and then determine the second material assignment results.

[0151] In one embodiment, please refer to Figure 6 , Figure 6 This is a schematic diagram of another interface layout and interaction logic of the material assignment view provided in the embodiments of this application.

[0152] Specifically, Figure 6 This diagram illustrates another interface state of the material assignment view generated based on the first material assignment result. This interface includes a view switching area, a status filtering area, and a subview content area. The subview content area currently displays the unassigned view (corresponding to the third subview); the status filtering area contains all assignment labels, partial assignment labels, and unassigned labels, used to filter the material assignment status.

[0153] The Unassigned View is used to display unassigned materials in the first material assignment result, presenting the parent-child containment relationship between the materials in a tree-like hierarchical structure. The top layer displays the bogie assembly, with material code 4000100604, version number 01, required quantity 1, drawing number SFE62TC01-500-00000, and node number 0. Below this is the wheelset system assembly, with material code 4000100605, version number 01, required quantity 2, drawing number SFE62TC01-510-00000, and node number 1. Below the wheelset system assembly is the wheel, with material code 4000100004, version number 01, required quantity 2, drawing number SFE45TC01-511-10001, and node number 1. Below the wheel is five unassigned sub-materials: hub, rim, wheel clamp, rim flange, and spoke. Among them, the wheel hub is coded 4000100005, version number 01, required quantity 1, drawing number SFE45TC01-511-11001, node number 1, and the remaining quantity is marked as 3; the wheel rim is coded 4000100006, version number 01, required quantity 1, drawing number SFE45TC01-511-11002, node number 2, and the remaining quantity is marked as 3; the wheel clamp is coded 4000100007, version number 01, required quantity 1, drawing number information... The material node SFE45TC01-511-11003 has a node number of 3 and a remaining quantity marker of 3. The rim has a code of 4000100008, a version number of 01, a required quantity of 1, and a drawing number of SFE45TC01-511-11004, with a node number of 4 and a remaining quantity marker of 4. The spoke has a code of 4000100009, a version number of 01, a required quantity of 8, and a drawing number of SFE45TC01-511-11005, with a node number of 5 and a remaining quantity marker of 24. All material nodes display a process route identifier and are associated with a cad.dwg format computer-aided design drawing file and viewing options to display the design drawing information for that material.

[0154] The right side is the view area corresponding to the PBOM structure, used to display the relationship between candidate material assignment schemes and process nodes in the first process list data. Specifically, it displays the process route nodes, process nodes, and candidate material assignment schemes assigned to the corresponding process nodes in the first process list data in a process hierarchy structure. For example, it shows the stress relief treatment and maintenance of the integrated framework of the process node, with process code OP10020002, version number 01, and required quantity 1; the process route node suspension system assembly, with code P000100011, version number 01, and required quantity 1; its lower layer includes optimized axle box vibration damper assembly, with code P000100013, version number 01, and required quantity 1; the lower layer of this node includes valve system assembly process, with process code OP10011003, version number 01, and required quantity 1; under this process, it is associated with the first candidate material assignment scheme, corresponding to the seat material, with code 4000200112, version number 03, and required quantity 6, drawing number information SFE91TC01-543-20112, node sequence number 1, assignment quantity 6, and associated with the first recommended type tag; It also includes a suspension assembly, coded P000100031, version number 01, and required quantity 1. Its lower layer includes a spring steel wire heat treatment process, coded OP10024001, version number 01, associated with the second candidate material assignment scheme, corresponding to spring steel wire material, coded 4000100713, version number 01, required quantity 1, drawing number SFE62TC01-531-11001, node number 1, assigned quantity 1, and associated with the second recommended type marker; a spring forming processing process, coded OP10024002, version number 01, also associated with the second candidate material assignment scheme for the aforementioned spring steel wire material; and an axle box spring assembly process, coded OP10024006, version number 01, associated with the second candidate material assignment scheme, corresponding to spring steel wire material.

[0155] In this embodiment, by displaying sub-views in different regions, the unassigned materials and process hierarchy in the first material assignment result are presented in a synchronized and visual manner, allowing users to compare and view the materials to be processed and the target process nodes on the same interface. By providing status filter labels and view switching options, users can quickly locate unassigned materials. By displaying manual assignment markers and remaining quantity markers, users can clearly identify the materials to be processed and their remaining assignment quantities. By supporting drag-and-drop or selection operations to establish the association between materials and process nodes, manual allocation of unassigned materials is realized, thereby making up for the coverage blind spots of automatic assignment processing and ensuring the integrity of the second material assignment result determined based on the already assigned correction result and the manual assignment result.

[0156] In one embodiment, for easier understanding of this application's content regarding the material assignment view including material reserve markers and the dynamic adjustment of these reserve markers according to the assigned quantity of the corresponding material, please refer to [link to relevant documentation]. Figure 7 , Figure 7 This is a schematic diagram showing the display status of the remaining quantity marker in the material assignment view provided in the embodiments of this application.

[0157] Specifically, Figure 7 This diagram illustrates the hierarchical structure of a portion of the Bill of Materials (BOM) data for the first project within the Material Assignment View. This display area can be a partial view of the first, second, or third sub-view, used to show the remaining quantity markers of materials and their associated information. The diagram illustrates the compositional relationship between the parent material, "Wheel," and its lower-level child materials. The parent material, "Wheel," has a material code of 4000100004, version number 01, required quantity of 2, drawing number SFE45TC01-511-10001, and node number 1. This parent material contains five lower-level child materials: hub, rim, wheel clamp, rim flange, and spoke. Among them, the material code for the wheel hub is 4000100005, version number is 01, required quantity is 1, drawing number is SFE45TC01-511-11001, node number is 1, and the associated surplus mark is 3; the material code for the wheel rim is 4000100006, version number is 01, required quantity is 1, drawing number is SFE45TC01-511-11002, node number is 2, and the associated surplus mark is 3; the material code for the wheel clamp is 4000100007, version number is 01, required quantity is 1, and drawing number is... For example, the material code for the wheel rim is SFE45TC01-511-11003, with node number 3 and associated margin marker displaying 3; the material code for the wheel rim is 4000100008, version number 01, required quantity 1, drawing number SFE45TC01-511-11004, node number 4, and associated margin marker displaying 4; the material code for the wheel spoke is 4000100009, version number 01, required quantity 8, drawing number SFE45TC01-511-11005, node number 5, and associated margin marker displaying 24. All of the above material entries include process route identifiers and are associated with cad.dwg format computer-aided design drawing files and viewing options.

[0158] The remaining quantity marker represents the remaining quantity of the corresponding material to be assigned in the current task. Its value is determined by the difference between the total demand for the material and the quantity already assigned. During user interaction with the material assignment view, the system monitors the assigned quantity in real time and dynamically updates the assigned quantity of the corresponding material. The remaining quantity marker value is then recalculated based on the difference between the updated assigned quantity and the total demand. When the remaining quantity marker value is zero, it indicates that the material has been fully assigned, and the system marks it as fully assigned in the material assignment view. When the remaining quantity marker value is not zero, it indicates that the material is in an incompletely assigned state. Through the dynamic display of this remaining quantity marker, process engineers can monitor the assignment progress of each material in real time, helping them to identify any omissions or over-assignments, thereby ensuring the accuracy and completeness of the second material assignment results determined based on the interaction.

[0159] In this embodiment, by displaying a dynamically adjusted margin marker in the material assignment view, real-time quantitative feedback on the material assignment progress is achieved. By associating the margin marker with the hierarchical structure information, process route identifiers, and design drawings of each material, comprehensive data reference is provided for users to perform confirmation, adjustment, or manual assignment operations. The change in the margin marker value distinguishes between the fully assigned and incompletely assigned states of materials, effectively assisting users in identifying materials to be processed, improving the efficiency and accuracy of material assignment work, and avoiding omissions caused by manual verification.

[0160] The following will combine Figure 8 The material assignment device 800 provided in this application embodiment will be described in detail. The material assignment device 800 and the material assignment method described above can be referred to in correspondence. Specifically, the material assignment device 800 may include a data acquisition module 810, an automatic assignment module 820, a generation and display module 830, and an interactive confirmation module 840, as detailed below: Data acquisition module 810 is used to acquire the first engineering material list data and the first process list data of the current rail vehicle project; The automatic assignment module 820 is used to call a preset intelligent agent to perform automatic assignment processing based on the first engineering bill of materials data and the first process list data to obtain the first material assignment result. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme in the at least one candidate material assignment scheme. A generation and display module 830 is used to generate and display a material assignment view based on the first material assignment result. The interactive determination module 840 is used to determine the second material assignment result based on the user's interactive operation on the material assignment view.

[0161] Optionally, in some embodiments, the data acquisition module 810 can be used to: Retrieve the bill of materials (BOM) data for the current rail vehicle project and display its hierarchical tree structure. The hierarchical tree structure contains multiple nodes, each corresponding to a material in the current rail vehicle project's BOM data. Based on the user's selection of the tree-like hierarchical structure, determine the first engineering bill of materials data to be assigned from the current engineering bill of materials data of the rail vehicle project; Based on the bill of materials data for the first project, obtain the bill of materials data for the first process of the current rail vehicle project.

[0162] Optionally, in some embodiments, the automatic assignment module 820 can be used to: The preset intelligent agent is invoked to query the historical process knowledge base based on the material drawing number in the first project bill of materials data, and the query results are obtained. If the query results indicate that a first historical material assignment scheme corresponding to the material drawing number in the first engineering bill of materials data is found, the intelligent agent is invoked to determine the first candidate material assignment scheme and the corresponding first recommendation type tag based on the first historical material assignment scheme and the first process list data. If the query results indicate that no first historical material assignment scheme corresponding to the material drawing number in the first project bill of materials data is found, the intelligent agent is invoked to perform a similarity search in the historical process knowledge base based on the first project bill of materials data and the first process list data to obtain the similarity search results; the intelligent agent is invoked to determine the second candidate material assignment scheme and the corresponding second recommendation type tag based on the similarity search results; The intelligent agent determines the first material assignment result based on the first candidate material assignment scheme and the corresponding first recommendation type tag, and / or the second candidate material assignment scheme and the corresponding second recommendation type tag; Among them, the recommendation level represented by the first recommendation type label is higher than the recommendation level represented by the second recommendation type label.

[0163] Optionally, in some embodiments, the automatic assignment module 820 can be used to: Multi-dimensional feature extraction is performed based on the first engineering bill of materials data to obtain the first material feature vector, and multi-dimensional feature extraction is performed based on the first process list data to obtain the first process step feature vector; The intelligent agent is invoked to perform vector similarity retrieval in the historical process knowledge base based on the first material feature vector and the first process step feature vector, and obtain the similarity value of each historical material assignment scheme in the historical process knowledge base. The intelligent agent is invoked to classify and determine the similarity values ​​of each historical material assignment scheme in the historical process knowledge base according to the preset similarity threshold, and the similarity retrieval results are obtained.

[0164] Optionally, in some embodiments, the preset similarity threshold includes a first similarity threshold and a second similarity threshold, wherein the first similarity threshold is higher than the second similarity threshold; the automatic assignment module 820 can be used for: If the similarity retrieval results indicate that a second historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the second historical material assignment scheme is greater than or equal to the first similarity threshold, the agent is invoked to extract the second historical material assignment scheme from the historical process knowledge base as the second candidate material assignment scheme, and a corresponding second recommendation type label is generated. If the similarity retrieval results indicate that there is a third historical material assignment scheme in the historical process knowledge base, and the similarity value of the third historical material assignment scheme is less than the first similarity threshold and greater than or equal to the second similarity threshold, the agent is invoked to extract the third historical material assignment scheme from the historical process knowledge base as the second candidate material assignment scheme, and the corresponding second recommendation type label is generated. Among them, the recommendation level of the second recommendation type tag corresponding to the second historical material assignment scheme is higher than the recommendation level of the second recommendation type tag corresponding to the third historical material assignment scheme.

[0165] Optionally, in some embodiments, the first material assignment result further includes at least one manual assignment marker, which is used to indicate that the corresponding material needs to be manually assigned; the material assignment device 800 can be used for: If the similarity search results indicate that a fourth historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the fourth historical material assignment scheme is less than the second similarity threshold, the agent is invoked to generate a manual assignment tag.

[0166] Optionally, in some embodiments, the material dispatching device 800 can be used for: Obtain the second engineering bill of materials data and the second process list data of historical rail vehicle projects, as well as the material allocation plan of historical rail vehicle projects; Multi-dimensional feature extraction is performed based on the bill of materials data for the second project to obtain the feature vector of the second material, and multi-dimensional feature extraction is performed based on the bill of materials data for the second process to obtain the feature vector of the second process step. Based on the second material feature vector, the second process feature vector, and the material assignment scheme of historical rail vehicle projects, construct or update the historical process knowledge base.

[0167] Optionally, in some embodiments, the display generation module 830 can be used to: Based on the first material assignment result, a first subview and a second subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, and the second subview is used to indicate the assigned materials in the first material assignment result; Generate and display the material assignment view based on the first subview and the second subview; Optionally, in some embodiments, the interaction determination module 840 may be used to: Based on the user's confirmation and / or adjustment operations on the assigned materials in the second subview of the material assignment view, determine the assigned correction results; Based on the already assigned correction results, determine the second material assignment result.

[0168] Optionally, in some embodiments, the display generation module 830 can be used to: Based on the first material assignment result, a first subview, a second subview, and a third subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, the second subview is used to indicate the assigned materials in the first material assignment result, and the third subview is used to indicate the unassigned materials in the first material assignment result. Generate and display the material assignment view based on the first subview, the second subview, and the third subview; Optionally, in some embodiments, the interaction determination module 840 may be used to: Based on the user's confirmation and / or adjustment operations on the assigned materials in the second subview of the material assignment view, determine the assigned correction results; The manual assignment result is determined based on the user's manual assignment operation on the unassigned materials in the third subview of the material assignment view. Based on the already assigned correction results and the manual assignment results, determine the second material assignment result.

[0169] Optionally, in some embodiments, the material assignment view includes a material balance marker, which is dynamically adjusted according to the assigned quantity of the corresponding material.

[0170] The effects achievable in this embodiment can be found in the relevant embodiments of the above material assignment method, which will not be repeated here.

[0171] Figure 9 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 9As shown, the electronic device may include: a processor 1301, a communication interface 1302, a memory 1303, and a communication bus 1304, wherein the processor 1301, the communication interface 1302, and the memory 1303 communicate with each other via the communication bus 1304. The processor 1301 can call a computer program in the memory 1303 to execute steps of a material assignment method, such as: Obtain the first engineering bill of materials data and the first process list data for the current rail vehicle project; The preset intelligent agent is invoked to automatically assign materials based on the first engineering bill of materials data and the first process list data, and the first material assignment result is obtained. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme in the at least one candidate material assignment scheme. Generate and display a material assignment view based on the first material assignment result; The second material assignment result is determined based on the user's interactive operations on the material assignment view.

[0172] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0173] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0174] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0175] All actions involving the acquisition of signal information or data in this application were carried out in compliance with the relevant data protection laws and policies of the country where the application is located, and with the authorization granted by the owner of the relevant device. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method of assigning material, characterized by, include: Obtain the first engineering bill of materials data and the first process list data for the current rail vehicle project; The preset intelligent agent is invoked to automatically assign materials based on the first engineering bill of materials data and the first process list data, and a first material assignment result is obtained. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme in the at least one candidate material assignment scheme. Generate and display a material assignment view based on the first material assignment result; The second material assignment result is determined based on the user's interactive operations on the material assignment view.

2. The method of claim 1, wherein, The acquisition of the first engineering material list data and the first process list data of the current rail vehicle project includes: Obtain the bill of materials (BOM) data for the current rail vehicle project and display the tree-like hierarchical structure of the BOM data for the current rail vehicle project; wherein the tree-like hierarchical structure contains multiple nodes, and the nodes correspond to the materials in the BOM data for the current rail vehicle project; Based on the user's selection operation of the tree-like hierarchical structure, the first engineering bill of materials data to be assigned is determined from the engineering bill of materials data of the current rail vehicle project; Based on the first engineering bill of materials data, obtain the first process list data for the current rail vehicle project.

3. The method of claim 1, wherein, The invocation of a preset intelligent agent automatically assigns materials based on the first engineering bill of materials data and the first process list data to obtain the first material assignment result, including: The preset intelligent agent is invoked to query the historical process knowledge base based on the material drawing number in the first engineering bill of materials data, and the query results are obtained. If the query result indicates that a first historical material assignment scheme corresponding to the material drawing number in the first engineering bill of materials data is found, the intelligent agent is invoked to determine the first candidate material assignment scheme and the corresponding first recommendation type tag based on the first historical material assignment scheme and the first process list data. If the query result indicates that no first historical material assignment scheme corresponding to the material drawing number in the first engineering bill of materials data is found, the intelligent agent is invoked to perform a similarity search in the historical process knowledge base based on the first engineering bill of materials data and the first process list data to obtain a similarity search result; the intelligent agent is then invoked to determine a second candidate material assignment scheme and a corresponding second recommendation type tag based on the similarity search result. The intelligent agent is invoked to determine the first material assignment result based on the first candidate material assignment scheme and the corresponding first recommendation type tag, and / or the second candidate material assignment scheme and the corresponding second recommendation type tag; The recommendation level represented by the first recommendation type marker is higher than the recommendation level represented by the second recommendation type marker.

4. The method of claim 3, wherein, The process involves invoking the intelligent agent to perform a similarity search in the historical process knowledge base based on the first engineering bill of materials data and the first process list data, and obtaining similarity search results, including: Multi-dimensional feature extraction is performed based on the first engineering bill of materials data to obtain the first material feature vector, and multi-dimensional feature extraction is performed based on the first process list data to obtain the first process step feature vector. The intelligent agent is invoked to perform vector similarity retrieval in the historical process knowledge base based on the first material feature vector and the first process step feature vector, so as to obtain the similarity value of each historical material assignment scheme in the historical process knowledge base; The intelligent agent is invoked to classify and determine the similarity values ​​of each historical material assignment scheme in the historical process knowledge base according to a preset similarity threshold, and the similarity retrieval results are obtained.

5. The method of claim 4, wherein, The preset similarity threshold includes a first similarity threshold and a second similarity threshold, wherein the first similarity threshold is higher than the second similarity threshold; the step of invoking the intelligent agent to determine the second candidate material assignment scheme and the corresponding second recommendation type label based on the similarity retrieval result includes: If the similarity retrieval result indicates that a second historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the second historical material assignment scheme is greater than or equal to the first similarity threshold, the agent is invoked to extract the second historical material assignment scheme from the historical process knowledge base as a second candidate material assignment scheme, and a corresponding second recommendation type tag is generated. If the similarity retrieval result indicates that a third historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the third historical material assignment scheme is less than the first similarity threshold and greater than or equal to the second similarity threshold, the agent is invoked to extract the third historical material assignment scheme from the historical process knowledge base as a second candidate material assignment scheme, and a corresponding second recommendation type tag is generated. The recommendation level of the second recommendation type marker corresponding to the second historical material assignment scheme is higher than the recommendation level of the second recommendation type marker corresponding to the third historical material assignment scheme.

6. The method of claim 5, wherein, The first material assignment result further includes at least one manual assignment marker, which indicates that the corresponding material needs to be manually assigned; the method further includes: If the similarity retrieval result indicates that a fourth historical material assignment scheme exists in the historical process knowledge base, and the similarity value of the fourth historical material assignment scheme is less than the second similarity threshold, the agent is invoked to generate a manual assignment tag.

7. The method of claim 3, wherein, The method further includes: Obtain the second engineering bill of materials data and the second process list data of the historical rail vehicle project, as well as the material allocation scheme of the historical rail vehicle project; Multi-dimensional feature extraction is performed based on the second engineering bill of materials data to obtain the second material feature vector, and multi-dimensional feature extraction is performed based on the second process list data to obtain the second process step feature vector; Based on the second material feature vector, the second process feature vector, and the material assignment scheme of the historical rail vehicle project, construct or update the historical process knowledge base.

8. The method of claim 1, wherein, The step of generating and displaying a material assignment view based on the first material assignment result includes: Based on the first material assignment result, a first subview and a second subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, and the second subview is used to indicate the assigned materials in the first material assignment result; Generate and display a material assignment view based on the first subview and the second subview; The step of determining the second material assignment result based on the user's interactive operation on the material assignment view includes: Based on the user's confirmation and / or adjustment operations on the assigned materials in the second sub-view of the material assignment view, the assigned correction result is determined; Based on the already assigned correction results, the second material assignment result is determined.

9. The method of claim 1, wherein, The step of generating and displaying a material assignment view based on the first material assignment result includes: Based on the first material assignment result, a first subview, a second subview, and a third subview are generated; wherein, the first subview is used to indicate all materials in the first engineering bill of materials data, the second subview is used to indicate the assigned materials in the first material assignment result, and the third subview is used to indicate the unassigned materials in the first material assignment result. Generate and display a material assignment view based on the first subview, the second subview, and the third subview; The step of determining the second material assignment result based on the user's interactive operation on the material assignment view includes: Based on the user's confirmation and / or adjustment operations on the assigned materials in the second sub-view of the material assignment view, the assigned correction result is determined; The manual assignment result is determined based on the user's manual assignment operation on the unassigned materials in the third subview of the material assignment view. The second material assignment result is determined based on the already assigned correction result and the manually assigned result.

10. The method according to any one of claims 1 to 9, characterized in that, The material assignment view includes a material balance marker, which is dynamically adjusted according to the assigned quantity of the corresponding material.

11. A material assignment apparatus, characterized by, include: The data acquisition module is used to acquire the first engineering material list data and the first process list data of the current rail vehicle project; An automatic assignment module is used to call a preset intelligent agent to perform automatic assignment processing based on the first engineering bill of materials data and the first process list data to obtain a first material assignment result. The first material assignment result includes at least one candidate material assignment scheme and a recommendation type tag corresponding to each candidate material assignment scheme in the at least one candidate material assignment scheme. A generation and display module is used to generate and display a material assignment view based on the first material assignment result. The interactive determination module is used to determine the second material assignment result based on the user's interactive operation on the material assignment view.

12. An electronic device comprising a processor and a memory having a computer program stored therein, characterized in that When the processor executes the computer program, it implements the steps of the material assignment method according to any one of claims 1 to 10.

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