All-hosting order two-in-one label intelligent generation method and system

Abstract

The invention provides an intelligent generation method and system for a two-in-one label of a full-trusteeship order, and relates to the technical field of logistics management, and the method comprises the steps: obtaining order information; determining multi-dimensional information data of a shop side according to the order information; designing a factory end template according to the order information; performing data synchronization on the multi-dimensional information data and factory end information data; inputting the synchronized data and the order information into a factory end template to generate a label prototype; according to a verification condition, verifying the tag prototype to obtain a verification result; judging whether the verification result passes or not; and generating a two-in-one label according to the verified label prototype. According to the invention, centralized configuration and one-time multiplexing of multi-dimensional information are realized, and the problem of dispersed input of pain points is solved; the requirements of multiple platforms are met through standardized and self-defined template design, and the template adaptation cost is reduced; and the two-in-one label is generated, so that the full-hosting order delivery efficiency is greatly improved, and the manpower and compliance cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of logistics management technology, and in particular to a method and system for intelligent generation of integrated labels for fully managed orders. Background Technology

[0002] With the rapid development of the fully managed cross-border e-commerce model, mainstream platforms such as Temu, Shein, TikTok, and AliExpress have imposed strict requirements on product packaging labels. Labels must include basic product information such as the manufacturer and batch number, as well as information on regional agents such as European agents, British agents, and Turkish agents, environmental compliance labels, and safety warnings. They must also comply with the size and format standards of international logistics regulations. Non-compliant labels have become a major cause of cross-border order returns and fines.

[0003] Currently, the creation of fully managed order labels for cross-border e-commerce mainly relies on manual information entry and template splicing. Sellers need to manually organize various information, use office software such as Word and Excel to create label templates, and modify and adjust them for each order before printing. Some platforms provide simple templates containing only basic product information, and a few third-party tools support label generation, but a complete closed loop of "information integration - template adaptation - intelligent printing" has not been formed.

[0004] However, existing technologies have many shortcomings. Data entry is cumbersome, requiring repeated manual input across platforms and markets, which is prone to errors. Furthermore, template adaptability is poor, and fixed formats cannot match the size and content requirements of different platforms. In addition, compliance guarantees are insufficient, lacking standardized verification mechanisms, making it easy for compliance information to be omitted or incorrect. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a fully managed order two-in-one label intelligent generation method, which can solve the problems of cumbersome information entry, repeated manual information entry across platforms and markets, and easy errors in the existing technology. At the same time, the template adaptability is poor, and the fixed format cannot match the size and content requirements of different platforms. Furthermore, compliance protection is insufficient, lacking a standardized verification mechanism, which easily leads to technical problems such as omissions or errors in compliance information.

[0006] A first aspect of this invention proposes a method for intelligently generating a combined tag for fully managed orders, comprising: S1: Get order information.

[0007] S2: Based on order information, determine multi-dimensional information data for the store.

[0008] S3: Design factory-side templates based on order information.

[0009] S4: Synchronize multi-dimensional information data with factory-side information data.

[0010] S5: Input the synchronized data and order information into the factory template to generate a label prototype.

[0011] S6: Verify the label prototype according to the verification conditions and obtain the verification result.

[0012] S7: Determine if the verification result passes. If yes, proceed to step S8. Otherwise, modify the multi-dimensional information data and return to step S1.

[0013] S8: Generate a combined tag based on the verified tag prototype.

[0014] A second aspect of this invention proposes a fully managed order two-in-one intelligent label generation system, comprising: a processor and a memory.

[0015] The memory stores a program or instruction that can run on a processor, and when the program or instruction is executed by the processor, it implements the steps of the fully managed order two-in-one label intelligent generation method as described in the first aspect.

[0016] A third aspect of the present invention provides a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the fully managed order two-in-one label intelligent generation method of the first aspect.

[0017] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: In this embodiment of the invention, by synchronizing multi-dimensional information data with factory-side information data, automatic and seamless integration between store-side configuration information and the factory-side printing system is achieved, eliminating the need for manual data transfer and reducing input errors from the source. Simultaneously, by designing factory-side templates, module layouts, position coordinates, font parameters, etc., can be freely adjusted to meet both standardization requirements and adapt to personalized scenarios. Through a verification mechanism, compliance information in the label prototype is automatically checked; if any item fails to meet the requirements, the first non-compliant item is returned, achieving automated and standardized compliance verification and avoiding omissions and errors from manual verification. Attached Figure Description

[0018] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0019] Figure 1 This is a flowchart illustrating a fully managed order two-in-one label intelligent generation method provided in an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of the structure of a fully managed order two-in-one intelligent label generation system provided in an embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions 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, not all embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] The following description, in conjunction with the accompanying drawings, details the intelligent generation method for the fully managed order two-in-one label provided by the present invention through specific embodiments and application scenarios.

[0023] Reference manual attached Figure 1 The diagram illustrates a flowchart of a fully managed order two-in-one label intelligent generation method provided by an embodiment of the present invention.

[0024] This invention provides a method for intelligently generating a combined tag for fully managed orders, which may include the following steps: S1: Get order information.

[0025] S2: Based on order information, determine multi-dimensional information data for the store.

[0026] In one possible implementation, S2 specifically includes sub-steps S201 to S203: S201: Bind the store to the fully managed store.

[0027] S202: Based on the order information, set the basic required information in the configuration pop-up window of the fully managed store that has been bound, and obtain the basic information dataset.

[0028] The information should be filled in according to the structured form categories: The required basic information includes: Manufacturer's name, address, and email address; European agent's name, address, email address, and postal code; Product safety warnings (to be filled in after confirming the packaging method with the factory); and optional product batch number and serial number.

[0029] The specific information for regional agents is as follows: If you open the Turkish and British markets, you need to supplement the Turkish agent (name, address, email, postal code, batch number, customer service link) and British agent (name, address, email) information. The system has built-in association rules: if the Turkish agent's batch number is not filled in, the European agent's batch number will be used automatically (no need to manually enter it again).

[0030] The environmental compliance matching information is as follows: Based on the product category and target market (such as Spain, Italy, Germany, etc.), select the corresponding environmental compliance logo (such as AMARILLORECICLA, VERDERECICLA, etc.), packaging type, consumable material + code, recyclability instructions and warnings from the system's preset options.

[0031] It should be noted that by setting basic required information based on order information, the core data needs of fully managed orders can be accurately targeted. By configuring a standardized data entry interface with pop-up windows, information errors caused by fragmented data entry can be avoided. At the same time, it provides accurate and unified basic data support for the subsequent integration of information such as regional agents and environmental compliance, and significantly reduces the frequency of repetitive manual operations.

[0032] S203: Combine basic information datasets, regional agent information, and environmental compliance information to obtain multi-dimensional information data.

[0033] Optionally, after clicking "Confirm", the system will store all category information in the store's database and automatically associate it with the corresponding order template. Subsequent orders will not need to be entered again; the configured information can be directly retrieved.

[0034] It should be noted that by systematically integrating basic product information, regional agency qualification information, and environmental compliance label information to form a structured and reusable multi-dimensional information dataset, we can avoid the confusion caused by the scattered storage of various types of information and provide a complete and unified data source for subsequent data synchronization and label content filling, thus ensuring the integrity and relevance of label information from the source.

[0035] In this embodiment of the invention, multi-dimensional data is collected in a targeted manner with order information as the core, accurately matching the scenario requirements of the corresponding fully managed order, ensuring that the data is strongly correlated with the order and without redundancy, providing a precise data source for subsequent template determination, data synchronization and other steps, and improving the continuity and reliability of the entire process data flow.

[0036] S3: Design factory-side templates based on order information.

[0037] In one possible implementation, S3 specifically includes sub-steps S301 to S304: S301: Select an order template based on the order information and output the template file corresponding to the order template.

[0038] In one possible implementation, the template file specifically includes: a standardized template file and a custom template file.

[0039] Specifically, the methods for defining custom template files include: Set the template name and label paper size parameters to obtain a blank custom template canvas.

[0040] Select the template content module based on multi-dimensional information data.

[0041] Input the template content module into the blank custom template canvas, and adjust the layout of the blank custom template canvas to obtain the custom template.

[0042] Save the custom template as a custom template file.

[0043] Specifically, it provides standardized templates adapted to mainstream platforms such as Temu, Shein, and TikTok, covering different sizes and content requirements, reducing template adaptation costs. The template library's categorization architecture is designed with platforms as the primary category (Temu, Shein, TikTok, AliExpress, etc.), and each platform category is further divided into secondary subcategories based on size and content requirements. Standardized template parameters are designed with each template having preset fixed core parameters, including tag size (length × width), content module layout area, font size, barcode format, and platform-mandated field positions. Parameter values ​​strictly match the official tag specifications of the corresponding platform. The template update mechanism includes a built-in platform rule synchronization interface to obtain real-time updates to tag policies across platforms (such as size adjustments and mandatory field additions / removals), automatically updating the corresponding templates in the template library while retaining historical versions for retrospective purposes.

[0044] For example, when the order is placed on the Temu platform: if the ordered goods are standard products, select the 70x20mm system template. If the goods require additional special compliance information (such as multilingual warnings), select the 100x100mm custom template (such as the latest TEMU label template 20251126).

[0045] When the order is placed on the Shein platform: If the target market does not include Turkey, select the 70x20mm system template. If the target market includes Turkey (Turkish agent information must be included), select the 100x100mm custom template with box markings and Turkish agent information.

[0046] When the order is placed on TikTok: Choose from a variety of system templates in different sizes, such as 50x20mm (simplified information), 50x30mm (standard information), and 70x20mm (extended information), depending on the packaging size and information requirements.

[0047] When the order is placed on AliExpress: Select the corresponding template size according to the target market (such as Europe, the Middle East, etc.). For the European market, prioritize the 70x30mm template that includes the European agent module, and for the Middle Eastern market, select the 80x25mm template that includes Arabic warnings.

[0048] Specifically, the custom template design scheme supports drag-and-drop layout and parameter adjustment of modules such as basic information, agency information, and compliance identification, meeting the personalized labeling needs of different product categories.

[0049] The custom templates specifically include: module library components, regional agent module, compliance identification module, washing label module, and design assistance module.

[0050] The module library components specifically include: basic information module, regional agent module, compliance identification module, washing label module, and design assistance module.

[0051] Basic Information Module: Manufacturer Information Submodule, Batch Number Submodule, Serial Number Submodule, Product Name Submodule, Barcode Submodule.

[0052] Regional Agent Module: European Agent Sub-module, British Agent Sub-module, Turkish Agent Sub-module (each sub-module contains a complete field display of the corresponding agent).

[0053] Compliance Labeling Module: EU icon sub-module, UK icon module, environmental label module (including various market-specific environmental labels), and safety warning sub-module.

[0054] Wash label module: Material description submodule, Washing instructions submodule, Maintenance tips submodule.

[0055] Design support modules: vertical line submodule, rectangle border submodule, custom image upload submodule, and text box module.

[0056] Drag-and-drop functionality: Supports dragging modules to any position on the design canvas with the mouse, and displays the module's coordinates and size in real time.

[0057] Parameter adjustment component: Provides input boxes and adjustment sliders for configurable parameters such as module position coordinates (X, Y axis), width and height dimensions (W, H), font size (F), font color (C), alignment (A).

[0058] Save and reuse components: Supports custom template naming and categorized storage, and can be set as the default template for a specific product category.

[0059] Furthermore, the basic information module: all product tags are mandatory and are used to display core product data required by the platform, applicable to all fully managed orders.

[0060] EUEP Sub-module: Required for orders targeting the European Economic Area (EEA) to meet EUREP mandatory labeling requirements.

[0061] UK Sub-module: Required for orders targeting the UK market, used to meet UKREP's mandatory labeling requirements.

[0062] Turkey Sub-module: Required for orders targeting Turkey, used to meet TURREP mandatory labeling requirements.

[0063] Environmental Label Sub-module: This is mandatory for orders from markets such as the EU, Spain, and Italy that have mandatory environmental labeling requirements. Select the corresponding labeling sub-module based on the specific market.

[0064] Wash label module: Required for orders of clothing, home textiles and other textile categories, used to display washing and care information.

[0065] Design assistance module: for scenarios where you need to optimize the aesthetics of label layout, add brand logos, or customize warning borders.

[0066] It should be noted that by using order information as the core basis for targeted selection of the appropriate template, the system accurately matches the label size, format, and other requirements of the corresponding platform, and directly outputs a usable template file. This eliminates the tedious manual adjustment of the template, reduces the error rate of format adaptation, and lays an efficient and accurate foundation for the subsequent generation of label prototypes.

[0067] S302: Set the template file as the default template file.

[0068] It's important to note that setting the template file matching order requirements as the default allows subsequent fully managed orders of the same type to directly use it without repeated filtering and matching. This significantly improves template reuse efficiency and ensures consistency of tag templates for the same scenario, reducing the probability of human error in selection.

[0069] S303: Select a box mark template based on the default template file and box mark dimensions.

[0070] It should be noted that the default label template corresponding to the order is used as a reference, and the appropriate box mark template is selected accurately in combination with the box mark size to ensure the format coordination between the two-in-one label and the box mark, avoid printing errors caused by size mismatch, provide highly matched template support for subsequent integrated printing, and improve the consistency of the entire process.

[0071] S304: Combine order information, default template file and box label template to determine the factory template.

[0072] It should be noted that by integrating three core elements—order information, the default template for the two-in-one label, and the box mark template—the determined factory-side template can accurately match the full-process requirements of the fully managed order, ensuring that the label and box mark formats are consistent and the content is compatible. This avoids printing errors caused by fragmented templates and lays a unified template foundation for subsequent data filling and integrated printing.

[0073] In this embodiment of the invention, order information is used as the core to coordinate the design of factory-side templates, integrate two-in-one label templates and box mark templates, realize unified planning and precise adaptation of templates, avoid format conflicts between different templates, and lay a solid standardized foundation for subsequent label generation and integrated printing.

[0074] S4: Synchronize multi-dimensional information data with factory-side information data.

[0075] In one possible implementation, S4 specifically includes sub-steps S401 to S405: S401: Generate data change logs based on multi-dimensional information data from the store using database triggers.

[0076] Specifically, the data change log includes: operation type, data ID, change content, and timestamp.

[0077] It should be noted that the automatic generation of data change logs is achieved by relying on database triggers without manual intervention. It can completely record key information such as operation type, data ID, and change content, which facilitates the traceability and verification of the entire data flow and provides accurate and reliable data source support for subsequent synchronization.

[0078] S402: Encapsulate the data change log as a JSON format message.

[0079] JSON format messages refer to messages encapsulated using JavaScript Object Notation, a lightweight data exchange format, and are one of the mainstream carriers for cross-system and cross-platform data transmission.

[0080] It should be noted that encapsulating data change logs into JSON format messages can ensure the integrity and standardization of the data structure, adapt to cross-system transmission requirements, facilitate quick parsing and verification on the factory side, reduce the risk of data distortion during transmission in the RabbitMQ message queue, and improve synchronization efficiency.

[0081] S403: Push JSON format messages to the factory via RabbitMQ message queue, and verify the JSON format messages and factory information data to obtain the verification result.

[0082] RabbitMQ message queue is an open-source message middleware developed based on the Advanced Message Queuing Protocol (AMQP). Its core function is to enable asynchronous, reliable, and decoupled data communication between different systems, modules, or devices.

[0083] Specifically, after the store completes the information configuration and clicks "Confirm", the database trigger is activated and a data change log is generated (including operation type, data ID, change content, and timestamp).

[0084] It should be noted that RabbitMQ message queues enable efficient and reliable cross-platform data transmission while simultaneously performing data verification. This allows for timely identification of issues related to information integrity and format compliance, preventing invalid data transfer and ensuring the consistency and accuracy of data between the store and factory ends during the transmission process.

[0085] S404: Determine whether the verification result meets the requirements for data integrity and format compliance. If yes, send a synchronization success receipt to the store and update the information data on the factory side. Otherwise, send a synchronization failure receipt and an error reason receipt to the store and proceed to step S405.

[0086] It should be noted that by automatically determining the integrity and format of data, accurate feedback of synchronization results is achieved. When successful, the factory-side data is updated in a timely manner to ensure consistency between the two ends. When failure occurs, the error reason is pushed to facilitate quick location and repair, which greatly improves the reliability of data synchronization and the efficiency of problem handling.

[0087] Specifically, data reception and verification are handled by the factory-side system listening to the message queue. After receiving a message, the data verification module verifies the data integrity (verification of non-empty fields for required fields) and the format compliance (such as email format and address format verification).

[0088] S405: Repeat steps S401 to S405 until the preset number of times is reached, trigger a manual alarm, and return to step S1.

[0089] Specifically, if the verification fails, a "synchronization failed + error reason" receipt is returned. The store-side system triggers a retry mechanism, automatically retrying 3 times at intervals of 3 seconds, 5 seconds, and 10 seconds. If it still fails, a manual alarm is triggered.

[0090] Optionally, data consistency is ensured using an optimistic locking mechanism, which controls concurrent synchronization conflicts through data ID and timestamp version number. The version number is calculated as follows: Version Number (V) = Base Version Number (V0) + Number of Changes (N), where V0 is the initial version number (default 1.0), and N is the cumulative number of data changes (automatically incremented by 1 with each change). When the version number of a message received by the factory is lower than the locally stored version number, the message is automatically discarded to prevent old data from overwriting new data.

[0091] It should be noted that setting up an automatic retry mechanism can repeatedly execute the process to attempt repair after data synchronization failure. The preset number of attempts avoids infinite loops, and triggering manual alerts can promptly notify and handle difficult issues. Returning to the initial steps ensures a closed loop for the entire process, significantly reducing the risk of process stagnation caused by data synchronization failure.

[0092] In this embodiment of the invention, an automated data synchronization link is built based on database triggers and RabbitMQ message queues. Data integrity and standardization are ensured through multiple rounds of verification. Retry mechanism and manual alarm are used to avoid process stagnation, so as to achieve accurate data consistency between the store and the factory and greatly reduce the cost of manual intervention.

[0093] S5: Input the synchronized data and order information into the factory template to generate a label prototype.

[0094] In this embodiment of the invention, synchronized and consistent multi-dimensional data and order information are accurately input into the adapted factory template to automatically generate standardized label prototypes. This eliminates the tedious manual filling of content, avoids information errors and omissions, and provides a unified and standardized verification carrier for subsequent compliance checks, greatly improving the efficiency and accuracy of label generation.

[0095] S6: Verify the label prototype according to the verification conditions and obtain the verification result.

[0096] Specifically, the verification conditions include: basic integrity verification conditions, format compliance verification conditions, platform-specific verification conditions, and compliance judgment verification. By verifying integrity and format compliance, the risk of returns and fines due to non-compliant labels can be avoided in advance.

[0097] The criteria for determining whether a label is compliant are as follows: A "basic verification rule base + platform-specific rule base" is established. A multi-dimensional combination of conditions is used for judgment. If all conditions are met, the label is deemed compliant; if any condition is not met, the label is deemed non-compliant and a specific error is returned. Specific verification conditions include: The basic integrity verification conditions (applicable to all platforms) specifically include: The manufacturer's name, address, and email address are not empty.

[0098] The regional agent information for the target market is not empty (for the European market, the European agent information is complete; for the UK market, the UK agent information is complete; and for the Turkish market, the Turkish agent information is complete).

[0099] Environmental compliance labels are aligned with the target market (no omissions, no incorrect selections).

[0100] Product batch number / serial number (required if required by the platform) must not be empty.

[0101] The specific format conformity verification conditions include: The label size conforms to the requirements of the platform to which the order belongs (e.g., Temu order size ∈ {70x20mm, 100x100mm}).

[0102] The email address format conforms to the regular expression rule: ^[a-zA-Z0-9_-]+@[a-zA-Z0-9_-]+(.[a-zA-Z0-9_-]+)+$.

[0103] The regional agent's postcode format conforms to the rules of the target market (e.g., EU postcodes are 5 digits, and UK postcodes are a combination of letters and numbers).

[0104] The barcode format must conform to the platform requirements (e.g., Temu requires EAN-13 format, Shein requires Code128 format).

[0105] Platform-specific verification conditions (customized according to the platform): Temu platform special feature: Security warnings include mandatory expressions such as "Keep away from fire", and labels contain no unnecessary advertising information.

[0106] Shein Platform Special Item: Soil information and box marking information are consistent; environmental protection label is located in the lower right corner of the label.

[0107] TikTok platform specific requirements: font size ≥ 10pt, serial number and order number association and matching.

[0108] The compliance determination formula specifically includes: The compliance determination result (R) = C1∧C2∧C3∧C4∧C5∧C6∧C7∧C8∧corresponding platform-specific conditions. Where: ∧ represents a logical "AND". R = compliant when all conditions are "true" (satisfied). R = non-compliant when any condition is "false" (not satisfied), and returns the first non-compliant condition number and its explanation (e.g., "UK market UK agent address not filled in").

[0109] In this embodiment of the invention, a comprehensive compliance verification of the label prototype is carried out based on preset verification conditions. This can accurately identify potential problems such as missing information and inconsistent formats, and avoid the risk of returns and penalties caused by non-compliant labels in advance, thus building a reliable quality defense line for the subsequent generation of two-in-one labels.

[0110] S7: Determine if the verification result passes. If yes, proceed to step S8. Otherwise, modify the multi-dimensional information data and return to step S1.

[0111] In this embodiment of the invention, a closed-loop processing of the label prototype verification result is achieved. If the result passes, the label generation process is advanced; if it fails, the data is modified and the process is restarted. This prevents non-compliant labels from flowing into subsequent stages, ensuring the compliance and accuracy of the final label from the process level, and significantly reducing the risk of penalties for cross-border order returns.

[0112] S8: Generate a combined tag based on the verified tag prototype.

[0113] In this embodiment of the invention, a two-in-one label is generated based on a label prototype that has passed compliance verification. This ensures that the label fully complies with the regulatory requirements of the cross-border platform and the target market. It integrates multi-dimensional core information without the need for separate production and can be directly connected to the printing process, which greatly improves the efficiency of label delivery for fully managed orders and avoids compliance risks from the end.

[0114] In one possible implementation, after S8, the following is also included: S9: Select a shipping label template based on the order information.

[0115] S10: Combine the two-in-one label and box mark template to obtain an integrated printable document.

[0116] Specifically, through data association mapping technology, a four-dimensional mapping relationship is established based on the order number as the unique association key, consisting of "store-side configuration information - order information - label template - box label template".

[0117] Using an HTML / CSS+PDF rendering engine (such as iTextPDF), the label module and box mark module are combined into the same print file.

[0118] Redis is used to manage print task queues and supports load balancing across multiple printers.

[0119] For example, in the data association stage: the factory enters the "Managed Scan-to-Ship" page, scans the order QR code or enters the order number, and the system queries the four-dimensional mapping relationship through the order number to obtain the corresponding store configuration information (manufacturer, agent, compliance information, etc.), default label template, and default box label template.

[0120] The template synthesis stage specifically includes: label generation, box mark generation, and integrated synthesis.

[0121] Label generation: Based on the label template layout, the configuration information is filled into the corresponding modules, and a PDF file of product label (including compliance mark) is generated through the PDF rendering engine.

[0122] Carton label generation: Based on the carton label template (provided by the platform, with sizes such as 70x70mm and 100x100mm), fill in the order number, recipient information, key information of regional agents, quantity of goods, etc., and generate a carton label PDF file.

[0123] Integrated merging: Combines label PDF and box mark PDF into a single print file according to the preset format of "label on top, box mark on bottom" or "left and right layout" (supports A4 paper pagination printing or label paper continuous printing).

[0124] The print scheduling phase specifically includes: the system adds the merged print file to the Redis print task queue, with the queue priority rule being: order urgency (urgent orders priority = 1, regular orders priority = 2).

[0125] The print driver module retrieves print jobs from the queue in priority order and sends print commands through CUPS print service (Linux system) or Windows print API (Windows system) according to the preset printer configuration (such as HP30138B5AD3AC).

[0126] The printer completes the synchronous printing of the label and box mark, the system updates the order printing status to "printed", and records the printing time and printer number.

[0127] Number of printed pages (P) = CEIL(Order quantity (Q) / Label capacity per page (N)) + 1 (Box label is fixed at 1 page). Where: CEIL is the floor function, and N is the maximum number of labels a label template can print on the selected paper size (e.g., if 10 labels can be printed per page on 70x20mm label paper, then N = 10). Example: Order quantity Q = 25, N = 10, then P = CEIL(25 / 10) + 1 = 3 + 1 = 4 pages (3 labels + 1 box label).

[0128] In this embodiment of the invention, a suitable box mark template is accurately matched based on the order information, and the compliant two-in-one label is integrated with the box mark template to generate an integrated print file. There is no need to produce and print them separately, which ensures that the label and box mark information are consistent, greatly improves the production efficiency of packaging materials for cross-border orders, and avoids the risk of format mismatch.

[0129] The fully managed order two-in-one label intelligent generation method provided in this application embodiment can be executed by a fully managed order two-in-one label intelligent generation device. This application embodiment uses the fully managed order two-in-one label intelligent generation device executing the fully managed order two-in-one label intelligent generation method as an example to illustrate the fully managed order two-in-one label intelligent generation device provided in this application embodiment.

[0130] Reference manual attached Figure 2 The diagram shows a structural schematic of a fully managed order two-in-one intelligent label generation system provided by an embodiment of the present invention.

[0131] This invention provides a fully managed order two-in-one label intelligent generation system 20, including: a processor 201 and a memory 202; The memory 202 stores programs or instructions that can run on the processor 201. When the program or instructions are executed by the processor 201, they implement the steps of the above-described fully managed order two-in-one label intelligent generation method and achieve the same technical effect. To avoid repetition, the present invention will not elaborate further.

[0132] It should be understood that the processor 201 in this embodiment of the invention may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0133] It should also be understood that the memory 202 in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DR RAM).

[0134] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0135] It should be understood that, in various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0136] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0137] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0138] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0139] The units described as separate components may or may not be physically separate. 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0140] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0141] If the aforementioned functions are 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 invention, essentially, 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 described in the various embodiments of this invention. 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.

[0142] This invention provides a readable storage medium comprising: storing a program or instructions on the readable storage medium, wherein when the program or instructions are executed by a processor, the program or instructions implement the steps of the above-described fully managed order two-in-one label intelligent generation method and achieve the same technical effect. To avoid repetition, this invention will not elaborate further.

[0143] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention 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; and these 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 the present invention. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligently generating a combined tag for fully managed orders, characterized in that, include: S1: Obtain order information; S2: Based on the order information, determine the multi-dimensional information data for the store; S3: Design the factory-side template based on the order information; S4: Synchronize the multi-dimensional information data with the factory-side information data; S5: Input the synchronized data and the order information into the factory template to generate a label prototype; S6: Verify the label prototype according to the verification conditions to obtain the verification result; S7: Determine whether the verification result passes; if yes, proceed to step S8; otherwise, modify the multi-dimensional information data and return to step S1. S8: Generate a combined tag based on the verified tag prototype.

2. The intelligent generation method for a combined tag for fully managed orders according to claim 1, characterized in that, S2 specifically includes: S201: Bind the aforementioned store terminal to the fully managed store; S202: Based on the order information, set the basic required information in the configuration pop-up interface of the fully managed store that has been bound, and obtain the basic information dataset; S203: Combine the aforementioned basic information dataset, regional agent information, and environmental compliance information to obtain multi-dimensional information data.

3. The intelligent generation method for a combined tag for fully managed orders according to claim 1, characterized in that, S3 specifically includes: S301: Based on the order information, select an order template and output the template file corresponding to the order template; S302: Set the template file as the default template file; S303: Select a box mark template based on the default template file and box mark dimensions; S304: Determine the factory-side template by combining the order information, the default template file, and the box label template.

4. The intelligent generation method for a combined tag for fully managed orders according to claim 3, characterized in that, The template files specifically include: standardized template files and custom template files.

5. The intelligent generation method for a combined tag for fully managed orders according to claim 4, characterized in that, The definition methods for the custom template file specifically include: Set the template name and label paper size parameters to obtain a blank custom template canvas; Based on the multi-dimensional information data, select the template content module; The template content module is input into the blank custom template canvas, and the layout of the blank custom template canvas is adjusted to obtain a custom template; Save the custom template as a custom template file.

6. The intelligent generation method for a combined tag for fully managed orders according to claim 1, characterized in that, S4 specifically includes: S401: Generate a data change log based on the multi-dimensional information data from the store using a database trigger; S402: Encapsulate the data change log into a JSON format message; S403: Push the JSON format message to the factory through the RabbitMQ message queue, and verify the JSON format message and the factory information data to obtain the verification result; S404: Determine whether the verification result meets the requirements of data integrity and format standardization; if yes, send a synchronization success receipt to the store and update the information data on the factory side; otherwise, send a synchronization failure receipt and an error reason receipt to the store and proceed to step S405. S405: Repeat steps S401 to S405 until the preset number of times is reached, trigger a manual alarm, and return to step S1.

7. The intelligent generation method for a combined tag for fully managed orders according to claim 6, characterized in that, The data change log specifically includes: operation type, data ID, change content, and timestamp.

8. The intelligent generation method for a combined tag for fully managed orders according to claim 1, characterized in that, The verification conditions specifically include: basic integrity verification conditions, format standardization verification conditions, platform-specific verification conditions, and compliance judgment verification.

9. The intelligent generation method for a combined tag for fully managed orders according to claim 1, characterized in that, Following S8, it also includes: S9: Select a shipping label template based on the order information; S10: Combine the two-in-one label with the box label template to obtain an integrated printable document.

10. A fully managed order two-in-one intelligent label generation system, characterized in that, include: Processor and memory; The memory stores programs or instructions that can run on the processor, which, when executed by the processor, implement the steps of the fully managed order two-in-one label intelligent generation method as described in any one of claims 1 to 9.

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