An assembly BOM information automatic classification extraction method

Abstract

The application discloses an assembly BOM information automatic classification extraction method, and relates to the technical field of assembly, solves the problems of slow storage positioning and non-standard coding in the existing assembly BOM information extraction technology, and realizes full-process optimization from three aspects of data positioning, classification logic and transmission efficiency through integrated design of storage path digital coding, original coding standardization conversion, classified coding accurate mapping and uplink and downlink bandwidth dynamic optimal adjustment. Through uniform coding of non-digital characters, standard classification coding is formed, automatic, high-precision and high-stability classification of BOM information is realized, and errors, repeated operations and efficiency bottlenecks caused by manual classification are avoided. In the extraction link, the coding is directly matched and extracted based on the classification coding, quick retrieval according to the class is realized, the storage position is accurately reached, and invalid traversal and redundant data reading are significantly reduced.

Description

Technical Field

[0001] This invention relates to the field of assembly technology, specifically to an automated classification and extraction method for assembly BOM information. Background Technology

[0002] In digital design and intelligent manufacturing scenarios such as modern shipbuilding and high-end equipment assembly, assembly BOM information serves as the core data carrier connecting 3D design, process planning, production, material procurement, and cost control. Its extraction efficiency, classification accuracy, and data consistency directly determine the product development cycle and the quality of production collaboration.

[0003] As product structures become increasingly complex, a large number of multi-disciplinary, multi-level, and large-scale assemblies are being used, including ship hull sections, pipe trays, duct assemblies, marine equipment, and electrical outfitting. The number of 3D models is growing exponentially. Model files are stored in a scattered manner, with deep directory hierarchies and close cross-module relationships, which makes traditional BOM information extraction and classification methods face many technical bottlenecks.

[0004] Currently, the industry commonly uses manual retrieval and semi-automatic classification to process assembly BOM information. Operators must rely on experience to search the model storage path layer by layer, manually filter part information, and manually classify and assign categories. This is not only cumbersome and time-consuming, but also prone to problems such as path search errors, inconsistent classification standards, data omissions, and incorrect extractions, seriously affecting the accuracy and usability of BOM data. At the same time, existing automated extraction technologies do not perform unified digital encoding of assembly storage paths and lack a standardized location indexing mechanism. The system cannot quickly locate the target assembly and needs to repeatedly traverse the database and file directory, resulting in high retrieval redundancy, slow response, and difficulty in supporting the efficient extraction of large batches and multiple types of assemblies.

[0005] In the assembly coding and classification stages, existing systems typically use raw codes containing non-numeric characters such as letters and symbols. These codes are inconsistent, have poor readability, and are inefficient for machine recognition, hindering rapid matching and automatic classification. Consequently, BOM information classification relies on manual judgment, resulting in a lengthy and unstandardized process. Furthermore, during data extraction and network transmission, existing technologies generally employ fixed network bandwidth configurations, maintaining a constant ratio of uplink to downlink bandwidth for extraction nodes. This fails to dynamically adapt to changes in assembly data volume, model complexity, and network load.

[0006] In summary, existing assembly BOM information extraction technologies suffer from prominent problems such as slow storage and location, low classification efficiency, non-standard coding, and poor network bandwidth adaptability. These issues make it difficult to meet the actual needs of digital shipyards for automated, efficient, and accurate BOM information extraction, thus hindering the efficiency and intelligence level of data integration from 3D design to manufacturing. Therefore, there is an urgent need for a new automated classification and extraction method that can achieve path coding, coding standardization, automated classification, and adaptive bandwidth adjustment to address the aforementioned technical deficiencies. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides an automated classification and extraction method for assembly BOM information, which solves the prominent problems of slow storage and location and non-standard coding in existing assembly BOM information extraction technologies.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an automated classification and extraction method for assembly BOM information, comprising the following steps: Step 1: Determine the storage path of the assembly based on the storage location associated with each assembly, and assign different numerical codes to different levels and storage paths to confirm the retrieval code associated with each storage path. Based on the original code associated with the assembly, re-encode all characters except numbers in the original code to confirm the classification code of the corresponding assembly. The specific method is as follows: Lock the storage database associated with several assemblies, and assign codes to the storage locations at different levels within the storage database: Identify the storage folders associated with the first level of the storage database and assign codes according to the order of the corresponding storage folders. The assigned numerical codes are consistent with the order of the corresponding storage folders. After the storage folders associated with the first level are stored, the internal folders of different folders within the first level are coded again. The same coding method as the storage folders in the first level is used to confirm the numerical codes associated with different internal folders in turn. This process continues until the numerical codes associated with different folders at different levels in the storage database are confirmed. Based on the storage location of the corresponding assembly, identify the associated folders in sequence, identify the numerical codes associated with the corresponding folders, sort the identified numerical codes according to the order in which the folders are opened, and generate the extraction code for the corresponding assembly. Step 2: Based on the BOM information associated with different assemblies, identify the corresponding classification information of the assembly, determine the classification of the assembly according to the set classification method, and assign the associated classification code to the corresponding classification partition. The specific method is as follows: Based on the established classification method, confirm the classification information associated with different classification zones; From the BOM information associated with different assemblies, identify the assemblies that are consistent with the classification information, determine the classification code of the corresponding assemblies, and assign the corresponding classification code to the corresponding classification partition. Step 3: Based on the classification codes associated with different classification partitions, identify the assemblies associated with the classification codes, and then, based on the extraction codes associated with the assemblies, locate the storage path of the assemblies and directly extract the corresponding assemblies. The specific method is as follows: Based on the extraction instructions, the classification partition is directly locked, and then the classification code is selected from the different assemblies corresponding to different classification codes within the classification partition. Based on the assemblies associated with the classification codes, the extraction code of the corresponding assembly is determined. Based on the extraction code, the different storage folders associated with different levels in the storage database are identified in turn, and the storage location of the corresponding assembly is identified in turn, and the extraction and output are performed directly. During the extraction process, the uplink or downlink bandwidth of the extraction node is adjusted to achieve an optimal ratio, thereby improving the extraction speed of the assembly. Specifically: Record the average extraction rate V associated with the assembly extraction process before correction, and simultaneously record the uplink bandwidth and downlink bandwidth associated with the extraction nodes in the extraction process. Increase the uplink bandwidth by one unit and decrease the downlink bandwidth by one unit, with the unit being a preset unit. After the adjustment is completed, execute the extraction process for 3 seconds and confirm the average extraction rate V2 associated with the process within 3 seconds. Check whether V2 and the confirmed average extraction rate V satisfy the condition: V2 > V. If they satisfy the condition, continue to adjust the uplink and downlink bandwidths according to the adjustment method in the adjustment process until the average extraction rate no longer increases. If V2=V, then the current adjustment method remains unchanged, and no further adjustment is required; If V2 < V, then the uplink bandwidth is reduced by one unit and the downlink bandwidth is increased by one unit, and this adjustment is continued until the average extraction speed no longer increases.

[0009] Preferably, the different numerical codes are distinguished by setting a superscript character "-".

[0010] This invention provides an automated classification and extraction method for assembly BOM information. Compared with existing technologies, it has the following advantages: Through an integrated design that digitally encodes storage paths, standardizes and converts existing codes, accurately maps classification codes, and dynamically optimizes uplink and downlink bandwidth, the entire process is optimized from three levels: data location, classification logic, and transmission efficiency. By uniformly assigning codes to non-numeric characters, a standardized classification code is formed, enabling automated, high-precision, and highly stable classification of BOM information, avoiding errors, repetitive operations, and efficiency bottlenecks caused by manual classification. In the extraction stage, the extraction code is directly matched based on the classification code, achieving rapid retrieval by category and precise access to the storage location, significantly reducing invalid traversal and redundant data reading. Meanwhile, by adaptively adjusting the uplink and downlink bandwidth of the extraction node in reverse, the optimal bandwidth ratio is dynamically found, which improves the data transmission and reading speed without increasing the hardware load, thus solving problems such as slow extraction of large assemblies, low network resource utilization, and easy lag and timeout. Attached Figure Description

[0011] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] First Embodiment Please see Figure 1 This application provides an automated classification and extraction method for assembly BOM information, including the following steps: Step 1: Determine the storage path of the assembly based on the storage location associated with different assemblies, and assign different numerical codes to different levels and storage paths. Confirm the extraction codes associated with different storage paths. Based on the original codes associated with the assemblies, re-encode the characters other than numbers in the original codes to confirm the classification codes of the corresponding assemblies. Specifically, within the corresponding software system, different assembly model parts have different storage locations. In order to quickly locate the storage location during the subsequent model extraction process, a storage path quantization method is used to quantify the storage locations at different levels of the assembly storage database, lock the corresponding code of the corresponding assembly storage location, and thus quickly extract the model in the subsequent extraction process. Furthermore, when classifying, it is necessary to determine the category to which the corresponding assembly belongs based on the different classification information in the BOM information. However, the process of identifying the category information takes too long. If an encoding recognition method is used, effective classification can be performed quickly. Step 2: Based on the BOM information associated with different assemblies, identify the classification information associated with the corresponding assembly, determine the category to which the corresponding assembly belongs according to the set classification method, and assign the associated classification code to the corresponding category partition. Step 3: Based on the classification codes associated with different classification partitions, identify the assemblies associated with the classification codes, and then based on the extraction codes associated with the assemblies, lock the storage path of the assemblies, directly extract the corresponding assemblies, and improve the extraction speed of the assemblies by adjusting the uplink or downlink bandwidth of the extraction nodes to achieve the optimal ratio.

[0014] Second Embodiment In a further implementation of this embodiment, the specific implementation includes: Step 1, the specific method for confirming the extraction codes of different storage paths is as follows: S11. Lock the storage database associated with several assemblies, and assign codes to the storage locations at different levels within the storage database: Identify the storage folders associated with the first level of the storage database and assign codes according to the order of the corresponding storage folders (here only the creation time is used for sorting). The assigned numerical code is consistent with the sorting position of the corresponding storage folder (if the sorting is 16, then the associated numerical code is 16. For example, if there are several different folders in the C drive, then each folder has a different numerical code). After the storage folders associated with the first level are stored, the internal folders of different folders within the first level are coded again. The same coding method as the storage folders in the first level is used to confirm the numerical codes associated with different internal folders in turn. This process continues until the numerical codes associated with different folders at different levels in the storage database are confirmed. S12. Based on the storage location of the corresponding assembly, identify the associated folders sequentially, and determine the numerical codes associated with each folder. Sort the identified numerical codes according to the order in which the folders are opened, and distinguish different numerical codes using a superscript character "-". Generate the extraction code for the corresponding assembly. For example: If the database contains three folders A, B, and C, corresponding to numerical codes 1, 2, and 3 respectively; folder A contains three folders A1, A2, and A3, corresponding to numerical codes 1, 2, and 3 respectively; and folders A11, A12, A13, and A14, corresponding to numerical codes 1, 2, 3, and 4 respectively, and an assembly is stored in folder A14, then the extraction code associated with the corresponding assembly is: 1. - 1 - 4- It is marked with a superscript character "-" above it for effective distinction; Step one also includes the specific method for confirming the classification codes of different assemblies, as follows: A11. Extract the assembly code associated with the corresponding assembly (this is a preset code, generally a code formed by the model, time and other relevant information of the assembly, which is generated by the system itself). Identify special characters that do not belong to the numerical code from the assembly code, and confirm the numerical code corresponding to different special characters according to the preset special character comparison table. The feature character comparison table is a preset table, which is set in advance by the operator according to the existence of special characters. A12. Keep the sorting position of the numerical codes corresponding to different feature characters unchanged, and generate the classification code of the corresponding assembly; Specifically, since each assembly is associated with a different assembly code, the identified numerical codes are not entirely the same, and the total codes after reordering are also different. The reason for removing important characters here is to facilitate the subsequent actual classification process.

[0015] Step 2, the specific method for determining the category to which the corresponding assembly belongs is as follows: Based on the established classification method, confirm the classification information associated with different classification zones; From the BOM information associated with different assemblies, identify the assemblies that are consistent with the classification information, determine the classification code of the corresponding assemblies, and assign the corresponding classification code to the corresponding classification partition. Specifically, the BOM information of an assembly covers various information about the corresponding assembly. For example, if the classification method is set as main components (large components) and sub-components (small through-hole components), then the classification of the corresponding assembly can be determined based on the relevant information in the BOM information, and the corresponding classification code can be classified accordingly. If the corresponding assemblies are re-partitioned, this classification method is time-consuming and laborious due to the large size of the assemblies. Using classification coding for partitioning can quickly identify the associated corresponding assemblies, and then quickly retrieve them based on the storage path associated with the corresponding assembly.

[0016] Step 3: Extract the corresponding assembly: Based on the extraction instructions, the classification partition is directly locked, and then the classification code is selected from the different assemblies corresponding to different classification codes within the classification partition. Based on the assemblies associated with the classification codes, the extraction code of the corresponding assembly is determined. Based on the extraction code, the different storage folders associated with different levels in the storage database are identified in turn, and the storage location of the corresponding assembly is identified in turn, and the extraction and output are performed directly.

[0017] Third Embodiment In specific implementation, this embodiment is a further embodiment of embodiment two, mainly focusing on how to improve the extraction rate during the extraction process of the assembly; Step three also includes: the specific method for correcting the uplink or downlink bandwidth of the extraction node is as follows: Record the average extraction rate V associated with the assembly extraction process before correction, and simultaneously record the uplink bandwidth and downlink bandwidth associated with the extraction nodes in the extraction process (when debugging, the uplink bandwidth and downlink bandwidth need to be reversed. If the uplink bandwidth is increased, then the downlink bandwidth is decreased. If they are increased simultaneously, it will seriously increase the operating burden of the enhancement node, causing its extraction rate to slow down). Increase the uplink bandwidth by one unit and decrease the downlink bandwidth by one unit. The unit is a preset unit, which is 5M / s in this case. After the adjustment is completed, execute the extraction process for 3 seconds and confirm the average extraction rate V2 associated with the 3-second period. Check whether V2 and the confirmed average extraction rate V satisfy: V2 > V. If they satisfy, continue to adjust the uplink and downlink bandwidth according to the adjustment method in the adjustment process until the average extraction rate no longer increases. If V2 = V, keep the current adjustment method unchanged and no further adjustment is required. If V2 < V, decrease the uplink bandwidth by one unit and increase the downlink bandwidth by one unit, and continue to adjust according to this method until the average extraction rate no longer increases. Specifically, by adjusting the processing method accordingly, the extraction rate of the assembly during the extraction process can be effectively changed, thereby effectively reducing the extraction time of the corresponding assembly during the extraction process, thus ensuring the overall extraction effect.

[0018] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0019] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for automated classification and extraction of assembly BOM information, characterized in that, Includes the following steps: Step 1: Determine the storage path of the assembly based on the storage location associated with different assemblies, and assign different numerical codes to different levels and storage paths to confirm the extraction codes associated with different storage paths. Based on the original codes associated with the assemblies, re-encode the characters other than numbers in the original codes to confirm the classification codes of the corresponding assemblies. Step 2: Based on the BOM information associated with different assemblies, identify the classification information associated with the corresponding assembly, determine the category to which the corresponding assembly belongs according to the set classification method, and assign the associated classification code to the corresponding category partition. Step 3: Based on the classification codes associated with different classification partitions, identify the assemblies associated with the classification codes, and then, based on the extraction codes associated with the assemblies, lock the storage path of the assemblies and directly extract the corresponding assemblies.

2. The method for automated classification and extraction of assembly BOM information according to claim 1, characterized in that, In step one, the specific method for extracting codes from different storage paths is as follows: Lock the storage database associated with several assemblies, and assign codes to the storage locations at different levels within the storage database: Identify the storage folders associated with the first level of the storage database and assign codes according to the order of the corresponding storage folders. The assigned numerical codes are consistent with the order of the corresponding storage folders. After the storage folders associated with the first level are stored, the internal folders of different folders within the first level are coded again. The same coding method as the storage folders in the first level is used to confirm the numerical codes associated with different internal folders in turn. This process continues until the numerical codes associated with different folders at different levels in the storage database are confirmed. Based on the storage location of the corresponding assembly, identify the associated folders in sequence, identify the numerical codes associated with the corresponding folders, sort the identified numerical codes according to the order in which the folders are opened, and generate the extraction code for the corresponding assembly.

3. The method for automated classification and extraction of assembly BOM information according to claim 2, characterized in that, The different numeric codes are distinguished by setting a superscript character "-".

4. The method for automated classification and extraction of assembly BOM information according to claim 1, characterized in that, In step one, the specific method for confirming the classification codes of different assemblies is as follows: Extract the assembly code associated with the corresponding assembly, identify special characters that do not belong to the numeric code from the assembly code, and confirm the numeric code corresponding to different special characters according to the preset special character comparison table, where the feature character comparison table is a preset table; By keeping the sorting order of the numerical codes corresponding to different feature characters unchanged, the classification codes of the corresponding assemblies are generated.

5. The method for automated classification and extraction of assembly BOM information according to claim 1, characterized in that, In step two, the specific method for determining the category to which the corresponding assembly belongs is as follows: Based on the established classification method, confirm the classification information associated with different classification zones; From the BOM information associated with different assemblies, identify the assemblies that are consistent with the classification information, determine the classification code of the corresponding assemblies, and assign the corresponding classification code to the corresponding classification partition.

6. The method for automated classification and extraction of assembly BOM information according to claim 1, characterized in that, In step three, the specific method for extracting the corresponding assembly is as follows: Based on the extraction instructions, the classification partition is directly locked, and then the classification code is selected from the different assemblies corresponding to different classification codes within the classification partition. Based on the assemblies associated with the classification codes, the extraction code of the corresponding assembly is determined. Based on the extraction code, the different storage folders associated with different levels in the storage database are identified in turn, and the storage location of the corresponding assembly is identified in turn, and the extraction and output are performed directly.

7. The method for automated classification and extraction of assembly BOM information according to claim 1, characterized in that, Step three also includes: during the extraction process, adjusting the uplink or downlink bandwidth of the extraction node to achieve an optimal ratio, thereby improving the speed of the assembly during the extraction process.

8. The method for automated classification and extraction of assembly BOM information according to claim 7, characterized in that, In step three, the specific method for correcting the uplink or downlink bandwidth of the extraction node is as follows: Record the average extraction rate V associated with the assembly extraction process before correction, and synchronously record the uplink bandwidth and downlink bandwidth associated with the extraction nodes in the extraction process. Increase the uplink bandwidth by one unit and decrease the downlink bandwidth by one unit, with the unit being a preset unit. After the adjustment is completed, execute the extraction process for 3 seconds and confirm the average extraction rate V2 associated with it during the 3 seconds. Check whether V2 and the confirmed average extraction rate V satisfy: V2 > V. If they satisfy, continue to adjust the uplink and downlink bandwidths according to the adjustment method in the adjustment process until the average extraction rate no longer increases.

9. The method for automated classification and extraction of assembly BOM information according to claim 1, characterized in that, If V2=V, then the current adjustment method remains unchanged, and no further adjustment is required.

10. The method for automated classification and extraction of assembly BOM information according to claim 8, characterized in that, If V2 < V, then the uplink bandwidth is reduced by one unit and the downlink bandwidth is increased by one unit, and this adjustment is continued until the average extraction speed no longer increases.

Images