Embroidery process version generation system capable of automatically identifying personalized customization order

Abstract

The invention discloses an embroidery process version generation system capable of automatically identifying a personalized customization order, which comprises an order data import module, an intelligent identification and classification module, an information association and coding module, an automatic version generation module and a result export module, and relates to the technical field of order processing. According to the embroidery process version generation system capable of automatically identifying the personalized customization order, an intelligent identification and classification module adopts an automatic mobile window to combine with the identification logic of an embroidery process exclusive vocabulary library, the window can be self-adaptive to a line feed scene for segmentation and combination, and an identification path is optimized through character feature matching; according to the method, embroidery demand orders can be accurately screened from massive orders without manual intervention, so that the method adapts to personalized orders to improve the recognition efficiency, full-process automation is realized in the links of order importing, recognition and classification, information association, out-of-stock marking, version generation, result exporting and the like, and the accuracy and processing efficiency of embroidery process version generation are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of order processing technology, specifically to a system for automatically generating embroidery pattern templates for personalized custom orders. Background Technology

[0002] With the growth of personalized consumption demand, the number of personalized embroidery orders on cross-border e-commerce platforms has increased significantly. These orders are characterized by large order volumes, scattered personalized information, and the need to link express delivery information and inventory status. The process of creating embroidery patterns typically includes multiple steps such as order data extraction, process classification, information association, out-of-stock labeling, and software operation to generate patterns.

[0003] The reference patent is titled: Embroidery Simulation Method and System Based on 3D Modeling (Patent Publication No.: CN119939684A, Patent Publication Date: 2025-05-06), which includes: acquiring embroidery pattern files; constructing a 3D geometric model based on Three.js, and generating an independent embroidery thread model by parsing the stitch coordinates in the pattern file; parsing the embroidery pattern file to generate an embroidery pattern; constructing a fabric model, overlaying fabric materials, and restoring the fabric effect; simulating the natural state of wind blowing across the fabric to obtain the display effect of the pattern on the dynamically fluctuating fabric; and using a technology engine to render the embroidery result in real time in a virtual environment to complete the simulation.

[0004] Based on the description in the aforementioned documents, existing personalized customization orders are numerous and their personalized information is scattered. Relying on manual screening of embroidery orders is time-consuming and labor-intensive. Furthermore, order data, logistics label data, and the correspondence between order numbers and express tracking numbers are stored in a scattered manner without an automated mapping and association mechanism. When querying order details or logistics status, cross-platform and cross-file searches are required, resulting in poor information interoperability, a lack of unified coding rules, and a chaotic correspondence between orders and labels, making management difficult. Therefore, this invention provides an embroidery pattern generation system that automatically identifies personalized customization orders. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an embroidery pattern generation system that automatically identifies personalized custom orders. This system solves the problems of existing personalized custom orders being numerous and fragmented, requiring time-consuming and labor-intensive manual screening of embroidery orders, and having order data, logistics label data, and the correspondence between order numbers and tracking numbers stored in a scattered manner without an automated mapping and association mechanism. Furthermore, querying order details or logistics status requires cross-platform and cross-file searches, resulting in poor information interoperability, a lack of unified coding rules, chaotic correspondence between orders and labels, and significant management difficulties.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an embroidery pattern generation system for automatically identifying personalized custom orders, comprising:

[0007] The order data import module imports external data files of different formats from different platforms, removes files that do not meet the format requirements, and prompts the user.

[0008] The intelligent recognition and classification module extracts the imported data files and filters out the required embroidery orders through the intelligent recognition window;

[0009] The information association and coding module maps and associates the order data obtained by the intelligent identification and classification module with the corresponding order label data, and performs coding operations on the associated orders and labels. Then, it compares the required requirements in the order data with the current inventory status to confirm out-of-stock orders and marks the out-of-stock information on the out-of-stock orders and corresponding labels.

[0010] The automated template generation module generates a CSV file containing complete order information, logistics information, and inventory status. It saves the CSV file containing the information required for embroidered nameplate production to a specified location on the computer and executes the embroidery script to complete the nameplate production and save it to the specified location.

[0011] The results export module allows users to export automatically generated embroidery pattern files in Be and Dst formats after categorization.

[0012] Preferably, the different formats of external data files imported in the order data import module include:

[0013] Orders downloaded from the backend of the cross-border e-commerce platform are then exported as PDF files.

[0014] Output the external domain Label file exported from the logistics management platform, which is the corresponding logistics waybill data;

[0015] The out-of-stock order number table generated by the enterprise resource planning system is output in Excel or CSV format;

[0016] Create a table showing the relationship between order numbers and tracking numbers, and output it in Excel or CSV format.

[0017] Preferably, the operation of filtering out the required embroidery orders through the intelligent recognition window in the intelligent recognition and classification module is as follows:

[0018] Set the intelligent recognition window to F(a, b) a ), where a is the length of the intelligent recognition window, b a The number of characters under the corresponding window length 'a', and the intelligent recognition window is an automated moving window for content recognition operation;

[0019] First, extract the order-related documents by identifying the header identifiers of each document, and then perform content recognition operations based on the order documents;

[0020] Establish a vocabulary database about embroidery techniques, and match the extracted content with the vocabulary database during content recognition. If the extracted content is the same as the content in the vocabulary database, the current order is an order requiring embroidery techniques.

[0021] Preferably, the movement rules of the automated moving window are as follows:

[0022] The process begins by iterating through the contents of the order file, extracting the content from the window, removing symbols and spaces, and then matching it with the product information in the product database.

[0023] If a match is not found, the last character feature of the extracted content is determined to be the same as the first character feature of the word in the vocabulary. If they are the same, the automatic moving window moves a-1 and the extraction and matching are performed again. If no matching words are found after the matching, the intelligent recognition window moves a distance a and a new stage of recognition is started.

[0024] If a match fails and the characters do not have the same characteristics, the intelligent recognition window will move a distance 'a' and start a new stage of recognition. Based on the extracted customized information, it will intelligently match similar product information.

[0025] Furthermore, when the intelligent recognition window moves to a newline, it splits into two parts based on the last character feature of the current line. The remaining half of the intelligent recognition window is then used for recognition and extraction from the opening of the next line. When the two parts are on the same line, they are merged into a complete intelligent recognition window for recognition.

[0026] Preferably, the mapping and association operation in the information association and encoding module, which maps the order data obtained from the intelligent identification and classification module to the corresponding order's waybill data, is as follows:

[0027] Extract order data and import a table showing the relationship between order number and tracking number. The row headers of the relationship table correspond to the page number information of the PDF file containing the current order data, while the column headers of the relationship table correspond to the various data categories of the order data.

[0028] Furthermore, at the same time as confirming the order number, a tracking number is generated through the logistics management platform under the timestamp corresponding to the confirmed order number, and the order number and the tracking number are linked to achieve the mutual flow of order information and express delivery information;

[0029] Then, the information category required by the tracking number is matched with the category in the order information, and the order information is mapped to the corresponding information category on the waybill and populated. This means that when retrieving either the order number or the tracking number, both order information and express information can be displayed.

[0030] Preferably, the operation of encoding the associated order and waybill in the information association and encoding module is as follows:

[0031] As order data is sequentially stored in the database, corresponding PDF file page numbers are generated.

[0032] Extract page number information from the order data, and based on the tracking number associated with the current order number, generate a page number on the tracking number that is identical to the current order page number after the waybill information for the corresponding waybill number has been filled in.

[0033] Preferably, the operation in the information association and encoding module that compares the required specifications in the order data with the current inventory status to confirm out-of-stock orders is as follows:

[0034] Based on the order data, confirm the order inventory status to see if it can meet production needs;

[0035] Based on the required resource category content in the order data, confirm in the search bar of the inventory terminal to obtain the real-time available inventory quantity under the corresponding resource category;

[0036] It then compares the real-time available inventory quantity with the resource requirements of the order data to determine whether it is an out-of-stock order.

[0037] Preferably, the result of comparing the real-time available inventory quantity with the resource requirements of the order data is as follows:

[0038] Result 1: If the real-time available inventory quantity is greater than the resources in the order data, then the current order is not an out-of-stock order.

[0039] Result 2: If the real-time available inventory quantity is less than the resources in the order data, the current order is an out-of-stock order, and feedback needs to be provided after determining the specific circumstances of the resource shortage.

[0040] Preferably, the operation of the information association and encoding module in marking out-of-stock information on out-of-stock orders and corresponding shipping labels is as follows:

[0041] After identifying out-of-stock orders, the types and quantities of resources missing in the out-of-stock orders, as well as whether the resources have been procured, are extracted and a QR code is generated to display specific out-of-stock information.

[0042] Compare the order numbers in the CSV file with the out-of-stock order number table. If the order numbers match, add a red "Out of Stock" label to the header of the first page of the corresponding order PDF file. At the same time, add a QR code for out-of-stock information to the lower right corner of the logistics waybill data file, and scan the code to get the specific out-of-stock information.

[0043] Preferably, the operation of executing the embroidery script to complete the nameplate production in the automated template generation module is as follows:

[0044] Call the preset embroidery execution script and configure the CSV file path parameter in the execution program. Read the embroidery nameplate production information in the CSV file based on the configured path parameter.

[0045] Using embroidery processing software, the process simulates manual operation by following the set procedures to complete the creation of new embroidery files, importing customized parameters, setting embroidery size and stitch density, and previewing and verifying the effect.

[0046] After completing the nameplate production, save the files to the output path in both Be and Dst formats.

[0047] This invention provides a pattern generation system for embroidery techniques that automatically identifies personalized custom orders. Compared with existing technologies, it has the following advantages:

[0048] 1. This automatic embroidery pattern generation system for personalized custom orders utilizes an automated mobile window combined with an embroidery-specific vocabulary database for intelligent recognition and classification. The window can adapt to line breaks by segmenting and merging, and the recognition path is optimized through character feature matching. It can accurately filter embroidery-required orders from a massive number of orders without manual intervention, thereby adapting to personalized orders and improving recognition efficiency. The system automates the entire process, including order import, recognition and classification, information association, out-of-stock marking, pattern generation, and result export, effectively improving the accuracy and processing efficiency of embroidery pattern generation.

[0049] 2. This automatic identification system for generating embroidery patterns for personalized custom orders uses an information association and coding module to map order numbers and tracking numbers together with a page number coding mechanism. This enables two-way communication between order and logistics information. By extracting any tracking number, complete order and logistics data can be obtained simultaneously without cross-platform retrieval. The unified coding rules make the correspondence between orders and waybills clear and traceable, simplifying the order management process and improving the efficiency of information query and verification.

[0050] 3. This automatic identification system for personalized custom embroidery pattern generation can quickly determine out-of-stock orders by automatically comparing order resource requirements with real-time inventory status. The system generates a QR code label containing the out-of-stock category, quantity, and procurement status, and adds a red "Out of Stock" label to the header of the order PDF, making out-of-stock information visible and standardized. Relevant personnel can quickly obtain out-of-stock details by scanning the code, avoiding production and logistics disconnect caused by delayed out-of-stock information transmission, reducing the risk of misdelivery and delays, and improving supply chain response speed. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the embroidery pattern generation system of the present invention;

[0052] Figure 2 This is a flowchart of the format verification process of the present invention;

[0053] Figure 3 This is a flowchart of the intelligent recognition process for embroidery orders according to the present invention. Detailed Implementation

[0054] 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.

[0055] Please see Figures 1-3 This invention provides a technical solution: an embroidery pattern generation system for automatically identifying personalized custom orders, comprising:

[0056] The order data import module imports external data files of different formats from different platforms, removes files that do not meet the format requirements, and prompts the user.

[0057] The intelligent recognition and classification module extracts the imported data files and filters out the required embroidery orders through the intelligent recognition window;

[0058] The information association and coding module maps and associates the order data obtained by the intelligent identification and classification module with the corresponding order label data, and performs coding operations on the associated orders and labels. Then, it compares the required requirements in the order data with the current inventory status to confirm out-of-stock orders and marks the out-of-stock information on the out-of-stock orders and corresponding labels.

[0059] The automated template generation module generates a CSV file containing complete order information, logistics information, and inventory status. It saves the CSV file containing the information required for embroidered nameplate production to a specified location on the computer and executes the embroidery script to complete the nameplate production and save it to the specified location.

[0060] The results export module allows users to export automatically generated embroidery pattern files in Be and Dst formats after categorization.

[0061] The intelligent recognition and classification module employs an automated mobile window combined with the recognition logic of a vocabulary database specific to embroidery techniques. The window can adapt to line breaks by segmenting and merging, and the recognition path is optimized through character feature matching. It can accurately filter embroidery demand orders from massive orders without manual intervention, thereby adapting to personalized orders and improving recognition efficiency. The entire process of order import, recognition and classification, information association, out-of-stock marking, pattern generation, and result export is fully automated, effectively improving the accuracy and processing efficiency of embroidery pattern generation.

[0062] In this embodiment of the invention, the different formats of external data files imported into the order data import module include:

[0063] Orders downloaded from the backend of the cross-border e-commerce platform are then exported as PDF files.

[0064] Output the external domain Label file exported from the logistics management platform, which is the corresponding logistics waybill data;

[0065] The out-of-stock order number table generated by the enterprise resource planning system is output in Excel or CSV format;

[0066] Create a table showing the relationship between order numbers and tracking numbers, and output it in Excel or CSV format.

[0067] The order data import module supports the unified import of multiple data formats, including PDF orders from cross-border e-commerce platforms, logistics label files, and Excel / CSV files from ERP systems. It automatically removes files that do not meet the format requirements and provides real-time prompts to users. This eliminates the need for manual data matching between different platforms, significantly reducing the manual cost of data import, minimizing format compatibility errors, and laying a reliable data foundation for subsequent processes.

[0068] Cross-border e-commerce platforms (such as Amazon, Etsy, etc.) download pending orders in their backends and generate standard PDF order files using the platform's built-in export function. Logistics management platforms (such as SF International, DHL) export external domain label files (in .PDF format), which include the tracking number prefix and waybill template fields. ERP systems (Enterprise Resource Planning systems) generate a table of out-of-stock order numbers and export it in Excel format (.xlsx). The table column names include "Out-of-Stock Order Number", "Resource Category", "Out-of-Stock Quantity", "Whether Purchased", "Purchase Order Number", and "Estimated Arrival Time".

[0069] In this embodiment of the invention, the operation of filtering out the required embroidery orders through the intelligent recognition window in the intelligent recognition and classification module is as follows:

[0070] Set the intelligent recognition window to F(a, b) a ), where a is the length of the intelligent recognition window, b a The number of characters under the corresponding window length 'a', and the intelligent recognition window is an automated moving window for content recognition operation;

[0071] First, extract the order-related documents by identifying the header identifiers of each document, and then perform content recognition operations based on the order documents;

[0072] Establish a vocabulary database about embroidery techniques, and match the extracted content with the vocabulary database during content recognition. If the extracted content is the same as the content in the vocabulary database, the current order is an order requiring embroidery techniques.

[0073] The vocabulary database for embroidery techniques contains 50+ core terms, divided into basic terms (such as "embroidery", "embroidery flower", "embroidery label", "embroidery lettering", "embroidery nameplate", "embroidery pattern"), material terms (such as "embroidery thread", "cotton embroidery", "silk thread embroidery"), and technique terms (such as "flat embroidery", "appliqué embroidery", "openwork embroidery", "3D embroidery"). The vocabulary database allows users to add, delete, or modify terms through the "vocabulary management" function in the system backend, and modifications are synchronized to the recognition engine in real time.

[0074] In this embodiment of the invention, the movement rules for the automated movable window are as follows:

[0075] The process begins by iterating through the contents of the order file, extracting the content from the window, removing symbols and spaces, and then matching it with the product information in the product database.

[0076] If a match is not found, the last character feature of the extracted content is determined to be the same as the first character feature of the word in the vocabulary. If they are the same, the automatic moving window moves a-1 and the extraction and matching are performed again. If no matching words are found after the matching, the intelligent recognition window moves a distance a and a new stage of recognition is started.

[0077] If a match fails and the characters do not have the same characteristics, the intelligent recognition window will move a distance 'a' and start a new stage of recognition. Based on the extracted customized information, it will intelligently match similar product information.

[0078] Furthermore, when the intelligent recognition window moves to a newline, it splits into two parts based on the last character feature of the current line. The remaining half of the intelligent recognition window is then used for recognition and extraction from the opening of the next line. When the two parts are on the same line, they are merged into a complete intelligent recognition window for recognition.

[0079] In this embodiment of the invention, the mapping and association operation in the information association and encoding module, which maps and associates the order data obtained from the intelligent identification and classification module with the corresponding order's waybill data, is as follows:

[0080] Extract order data and import a table showing the relationship between order number and tracking number. The row headers of the relationship table correspond to the page number information of the PDF file containing the current order data, while the column headers of the relationship table correspond to the various data categories of the order data.

[0081] Furthermore, at the same time as confirming the order number, a tracking number is generated through the logistics management platform under the timestamp corresponding to the confirmed order number, and the order number and the tracking number are linked to achieve the mutual flow of order information and express delivery information;

[0082] Then, the information category required by the tracking number is matched with the category in the order information, and the order information is mapped to the corresponding information category on the waybill and populated. This means that when retrieving either the order number or the tracking number, both order information and express information can be displayed.

[0083] By mapping order numbers and tracking numbers through the information association and coding module, combined with the page number coding mechanism, two-way communication between order information and logistics information can be achieved. Extracting any tracking number can simultaneously obtain complete order and logistics data without cross-platform retrieval. The unified coding rules make the correspondence between orders and waybills clear and traceable, simplifying the order management process and improving the efficiency of information query and verification.

[0084] In this embodiment of the invention, the operation of encoding the associated order and waybill in the information association and encoding module is as follows:

[0085] As order data is sequentially stored in the database, corresponding PDF file page numbers are generated.

[0086] Extract page number information from the order data, and based on the tracking number associated with the current order number, generate a page number on the tracking number that is identical to the current order page number after the waybill information for the corresponding waybill number has been filled in.

[0087] The order data is sequentially stored in the MySQL database according to the import order. The system automatically assigns a unique PDF page number to each order (starting from 1 and incrementing, e.g., the page number of the 1st order is 1, the 2nd is 2, and so on). The page number corresponds one-to-one with the order number. The system extracts the page number information of the order, associates the corresponding electronic shipping label through the express order number, and adds a page number identifier in the lower right corner of the shipping label to ensure the physical association between the order and the shipping label, facilitating offline verification by users.

[0088] In the embodiment of the present invention, the operation of the information association and coding module to identify out-of-stock orders by comparing the required requirements in the order data with the current inventory status is as follows:

[0089] According to the order data, confirm the order inventory situation and whether it can meet the production requirements;

[0090] According to the content of the required resource category in the order data, confirm in the search bar of the inventory terminal to obtain the real-time available inventory quantity under the corresponding resource category;

[0091] And compare the real-time available inventory quantity with the required resource quantity in the order data to determine whether it is an out-of-stock order.

[0092] The system extracts the unprocessed embroidery orders from the cross-border e-commerce platform order data, analyzes the corresponding product information (such as "red cotton embroidery thread", "white canvas fabric", "metal nameplate base") and resource usage of the orders. The system uses the inventory terminal API interface to input the resource category keyword in the search bar of the inventory terminal to obtain the real-time available inventory quantity of the corresponding resource (the inventory data is synchronized every 5 minutes to ensure real-time). Let the required resource quantity of the order be Q and the real-time available inventory quantity be S; if S > Q, it is determined as a "non-out-of-stock order" and the inventory status is marked as "sufficient", if S < Q, it is determined as an "out-of-stock order", the inventory status is marked as "out of stock", and the out-of-stock details (resource category, out-of-stock quantity, current inventory quantity) are extracted.

[0093] In the embodiment of the present invention, the result of comparing the real-time available inventory quantity with the required resource quantity in the order data is:

[0094] Result 1: If the real-time available inventory quantity is greater than the resources in the order data, the current order is not an out-of-stock order;

[0095] Result 2: If the real-time available inventory quantity is less than the resources in the order data, the current order is an out-of-stock order, and it is necessary to feedback by determining the specific situation of the resource out-of-stock.

[0096] In the embodiment of the present invention, the operation of the information association and coding module to mark out-of-stock information on the out-of-stock order and the corresponding shipping label is as follows:

[0097] After identifying out-of-stock orders, the types and quantities of resources missing in the out-of-stock orders, as well as whether the resources have been procured, are extracted and a QR code is generated to display specific out-of-stock information.

[0098] Compare the order numbers in the CSV file with the out-of-stock order number table. If the order numbers match, add a red "Out of Stock" label to the header of the first page of the corresponding order PDF file. At the same time, add a QR code for out-of-stock information to the lower right corner of the logistics waybill data file, and scan the code to get the specific out-of-stock information.

[0099] The system generates a unique QR code for out-of-stock orders. The QR code contains the following information fields: order number, resource category, out-of-stock quantity, current inventory, whether it has been purchased (yes / no), purchase order number (if purchased), and estimated arrival time (if purchased). The system uses the QR code encoding standard to ensure a high success rate for scanning. The system compares the order number in the CSV file with the out-of-stock order number table exported from the ERP system. If the order numbers match, a red "out-of-stock" label is added to the header of the first page of the corresponding order PDF file.

[0100] By automatically comparing order resource requirements with real-time inventory status, the system can quickly identify out-of-stock orders, generate QR code labels containing out-of-stock category, quantity, and procurement status, and add a red "Out of Stock" label to the header of the order PDF, realizing the visualization and standardized marking of out-of-stock information. Relevant personnel can quickly obtain out-of-stock details by scanning the code, avoiding production and logistics disconnect caused by the lag in the transmission of out-of-stock information, reducing the risk of misdelivery and delays, and improving the supply chain response speed.

[0101] In this embodiment of the invention, the operation of executing the embroidery script to complete the nameplate production in the automated pattern generation module is as follows:

[0102] Call the preset embroidery execution script and configure the CSV file path parameter in the execution program. Read the embroidery nameplate production information in the CSV file based on the configured path parameter.

[0103] Using embroidery processing software, the process simulates manual operation by following the set procedures to complete the creation of new embroidery files, importing customized parameters, setting embroidery size and stitch density, and previewing and verifying the effect.

[0104] After the nameplate is completed, save the files to the output path in Be format and Dst format respectively. Be format and Dst format are international standard embroidery template file formats, which support the storage of stitch coordinates and color information.

[0105] The system integrates complete information from embroidery orders (order number, customer requirements, embroidery pattern parameters, logistics information, and inventory status) to generate a CSV file. Fields include: order number, pattern name, pattern coordinates (X / Y axis coordinates, in mm), embroidery size (length × width, in mm), stitch density (stitches / 10mm), embroidery thread color code (Pantone color code), label number, inventory status, and whether it is out of stock. The embroidery processing software must support API interface calls, be able to receive parameters such as pattern coordinates and stitch density from external scripts, and be compatible with the ISO standard embroidery file format.

[0106] Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0107] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0108] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An embroidery pattern generation system for automatically recognizing personalized custom orders, characterized in that: include: The order data import module imports external data files of different formats from different platforms, removes files that do not meet the format requirements, and prompts the user. The intelligent recognition and classification module extracts the imported data files and filters out the required embroidery orders through the intelligent recognition window; The information association and coding module maps and associates the order data obtained by the intelligent identification and classification module with the corresponding order label data, and performs coding operations on the associated orders and labels. Then, it compares the required requirements in the order data with the current inventory status to confirm out-of-stock orders and marks the out-of-stock information on the out-of-stock orders and corresponding labels. The automated template generation module generates a CSV file containing complete order information, logistics information, and inventory status. It saves the CSV file containing the information required for embroidered nameplate production to a specified location on the computer and executes the embroidery script to complete the nameplate production and save it to the specified location. The results export module allows users to export automatically generated embroidery pattern files in Be and Dst formats after categorization.

2. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 1, characterized in that: The external data files imported in the order data import module include those in different formats: Orders downloaded from the backend of the cross-border e-commerce platform are then exported as PDF files. Output the external domain Label file exported from the logistics management platform, which is the corresponding logistics waybill data; The out-of-stock order number table generated by the enterprise resource planning system is output in Excel or CSV format; Create a table showing the relationship between order numbers and tracking numbers, and output it in Excel or CSV format.

3. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 1, characterized in that: The intelligent recognition and classification module performs the following operation to filter out the required embroidery orders through the intelligent recognition window: Set the intelligent recognition window to F(a, b) a ), where a is the length of the intelligent recognition window, b a The number of characters under the corresponding window length 'a', and the intelligent recognition window is an automated moving window for content recognition operation; First, extract the order-related documents by identifying the header identifiers of each document, and then perform content recognition operations based on the order documents; Establish a vocabulary database about embroidery techniques, and match the extracted content with the vocabulary database during content recognition. If the extracted content is the same as the content in the vocabulary database, the current order is an order requiring embroidery techniques.

4. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 3, characterized in that: The movement rules for the automated movable window are as follows: The process begins by iterating through the contents of the order file, extracting the content from the window, removing symbols and spaces, and then matching it with the product information in the product database. If a match is not found, the last character feature of the extracted content is determined to be the same as the first character feature of the word in the vocabulary. If they are the same, the automatic moving window moves a-1 and the extraction and matching are performed again. If no matching words are found after the matching, the intelligent recognition window moves a distance a and a new stage of recognition is started. If a match fails and the characters do not have the same characteristics, the intelligent recognition window will move a distance 'a' and start a new stage of recognition. Based on the extracted customized information, it will intelligently match similar product information. Furthermore, when the intelligent recognition window moves to a newline, it splits into two parts based on the last character feature of the current line. The remaining half of the intelligent recognition window is then used for recognition and extraction from the opening of the next line. When the two parts are on the same line, they are merged into a complete intelligent recognition window for recognition.

5. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 2, characterized in that: The mapping and association operation in the information association and encoding module, which maps and associates the order data obtained from the intelligent identification and classification module with the corresponding order's waybill data, is as follows: Extract order data and import a table showing the relationship between order number and tracking number. The row headers of the relationship table correspond to the page number information of the PDF file containing the current order data, while the column headers of the relationship table correspond to the various data categories of the order data. Furthermore, at the same time as confirming the order number, a tracking number is generated through the logistics management platform under the timestamp corresponding to the confirmed order number, and the order number and the tracking number are linked to achieve the mutual flow of order information and express delivery information; Then, the information category required by the tracking number is matched with the category in the order information, and the order information is mapped to the corresponding information category on the waybill and populated. This means that when retrieving either the order number or the tracking number, both order information and express information can be displayed.

6. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 5, characterized in that: The information association and encoding module performs the following operation to encode the associated orders and waybills: As order data is sequentially stored in the database, corresponding PDF file page numbers are generated. Extract page number information from the order data, and based on the tracking number associated with the current order number, generate a page number on the tracking number that is identical to the current order page number after the waybill information for the corresponding waybill number has been filled in.

7. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 2, characterized in that: The operation of identifying out-of-stock orders in the information association and encoding module by comparing the required data in the order data with the current inventory status is as follows: Based on the order data, confirm the order inventory status to see if it can meet production needs; Based on the required resource category content in the order data, confirm in the search bar of the inventory terminal to obtain the real-time available inventory quantity under the corresponding resource category; It then compares the real-time available inventory quantity with the resource requirements of the order data to determine whether it is an out-of-stock order.

8. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 7, characterized in that: The result of comparing the resource requirements based on real-time available inventory and order data is as follows: Result 1: If the real-time available inventory quantity is greater than the resources in the order data, then the current order is not an out-of-stock order. Result 2: If the real-time available inventory quantity is less than the resources in the order data, the current order is an out-of-stock order, and feedback needs to be provided after determining the specific circumstances of the resource shortage.

9. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 7, characterized in that: The information association and encoding module marks out-of-stock information on out-of-stock orders and corresponding shipping labels as follows: After identifying out-of-stock orders, the types and quantities of resources missing in the out-of-stock orders, as well as whether the resources have been procured, are extracted and a QR code is generated to display specific out-of-stock information. Compare the order numbers in the CSV file with the out-of-stock order number table. If the order numbers match, add a red "Out of Stock" label to the header of the first page of the corresponding order PDF file. At the same time, add a QR code for out-of-stock information to the lower right corner of the logistics waybill data file, and scan the code to get the specific out-of-stock information.

10. The embroidery pattern generation system for automatically identifying personalized custom orders according to claim 1, characterized in that: The operation of executing the embroidery script to complete the nameplate production in the automated template generation module is as follows: Call the preset embroidery execution script and configure the CSV file path parameter in the execution program. Read the embroidery nameplate production information in the CSV file based on the configured path parameter. Using embroidery processing software, the process simulates manual operation by following the set procedures to complete the creation of new embroidery files, importing customized parameters, setting embroidery size and stitch density, and previewing and verifying the effect. After completing the nameplate production, save the files to the output path in both Be and Dst formats.

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