A method and system for processing customized clothing orders

Abstract

The present application provides a method and system for processing clothing customized orders, which relates to the field of computer technology. The method includes: obtaining the protocol data of the target order, the protocol data carrying the protocol countersignature instruction; when it is detected that the electronic agreement has been reached, the order data is generated based on the protocol data, and the protocol countersignature result is generated after the other countersignature terminals respond to the protocol countersignature instruction; when it is detected that the order data meets any order re-planning conditions, the adjustment countersignature instruction is initiated and sent to the countersignature terminal, and the order re-planning conditions include the demand abnormality conditions corresponding to the order demand data indicated by the order data and the demand change conditions corresponding to the protocol data; based on the adjustment countersignature result, the order data of the target order is regenerated, and production is carried out according to the updated order data, and the adjustment countersignature result is generated after the countersignature terminal responds to the adjustment countersignature instruction and countersigns. The present application improves production efficiency.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and system for processing clothing customization orders. Background Art

[0002] As consumers' demand for customized services increases, traditional order management models struggle to adapt to the complex and diverse nature of these needs. This is particularly evident in areas such as order confirmation, production planning, and supply chain collaboration, which often lead to low production efficiency, delayed delivery, and decreased customer satisfaction. Furthermore, customized orders involve the collaborative work of multiple departments and processes, including marketing, supply, production, quality control, and after-sales service. Each department has distinct operational requirements for orders, leading to significant information silos and hindering efficient communication.

[0003] Currently, existing approaches to apparel production involve an order management system and a countersignature agreement system, essentially two independent systems. The order management system is responsible for tasks like creating, sorting, and canceling production orders, while the countersignature agreement system handles tasks like remittances, pattern making, and finalization. This existing approach can meet most apparel production needs because most orders are large, with fixed sizes and types. Unless there are unexpected situations like order cancellations, the countersignature agreement system and the order management system don't interact significantly in terms of business logic. Therefore, even if these two systems operate independently, production efficiency remains relatively unaffected.

[0004] However, with the increasing number of customized clothing orders, which are typically small-batch, diversified production, the agreement signing system and order management system need to be modified simultaneously when customers request changes to size or style mid-production. The existing agreement signing system and order management system operate independently, which can lead to information asynchrony, resulting in production errors and significantly affecting production efficiency. Summary of the Invention

[0005] In order to solve the above-mentioned problems in the prior art, the present invention provides a method and system for processing customized clothing orders, which can improve production efficiency.

[0006] In a first aspect, the present application provides a method for processing a customized clothing order, for use in a processing device, comprising:

[0007] Acquire agreement data of the target order, wherein the agreement data carries an agreement countersigning instruction initiated from any countersigning terminal;

[0008] When it is detected that the electronic agreement corresponding to the target order has been reached as a result of the agreement countersigning, corresponding order data is generated based on the agreement data, wherein the agreement countersigning result is generated after countersigning by at least one other countersigning terminal in response to the agreement countersigning instruction;

[0009] When it is detected that the order data meets any one of the order re-planning conditions, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data;

[0010] Based on the obtained adjustment counter-signing result, the order data of the target order is regenerated, and production is performed according to the updated order data, wherein the adjustment counter-signing result is generated after the counter-signing terminal responds to the adjustment counter-signing instruction and counter-signs.

[0011] In one possible implementation, the agreement data includes interactive audio data and electronic agreement data for the electronic agreement, wherein the interactive audio data is used to record the voice communication process for the electronic agreement and / or the target order; and the method further includes:

[0012] When it is detected that the electronic agreement has not been reached as a result of the agreement countersigning, performing intention analysis on the interactive audio data of the target order;

[0013] When it is analyzed that the electronic agreement meets the preset conditions for the tendency to achieve the goal, the target order is added to the waiting queue;

[0014] Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data;

[0015] Clearing the target order corresponding to the agreement achievement intention degree lower than a preset low intention threshold in the waiting queue, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low-intent customer, so as to update customer source data, wherein the customer source data includes at least one customer and corresponding identification content;

[0016] The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct the customers corresponding to the orders in the return visit reminder queue to be reminded of the return visit.

[0017] In one possible implementation, determining the degree of agreement reaching intention based on the interactive audio data and the electronic agreement data includes:

[0018] Inputting the interactive audio data into a preset first feature extraction model to extract feature vectors from the interactive audio data, analyzing the feature vectors, and outputting speech feature data, wherein the speech feature data is used to indicate long-term dependencies in the interactive audio data;

[0019] Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data;

[0020] Calculating the speech feature data and the text feature data using a preset cross-attention model to determine a speech attention weight matrix and a text attention weight matrix;

[0021] Determining a corresponding speech attention weight feature based on the speech attention weight matrix, and determining a corresponding text attention weight feature based on the text attention weight matrix;

[0022] The speech attention weight feature and the text attention weight feature are spliced ​​to determine the intention to reach an agreement on the target order based on the splicing result.

[0023] In one possible implementation, the order data includes an order delivery date, clothing type, clothing quantity, and clothing size; when it is detected that the order data meets any one of the order re-planning conditions, a corresponding adjustment countersignature instruction is initiated and sent to the countersignature terminal, including:

[0024] quantifying the clothing type as at least one clothing material required for the target order, quantifying the clothing quantity and the clothing size as the material requirement of the target order, and constituting the material requirement data in the order requirement data with the clothing material and the material requirement;

[0025] querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material;

[0026] When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

[0027] In a possible implementation, the adjustment counter-signature instruction includes a material adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising:

[0028] When it is found that the material database does not have all the clothing materials, or the material demand of any of the clothing materials is lower than the material inventory, it is confirmed that the order data meets the demand abnormality condition, then a corresponding material adjustment countersignature instruction is generated and sent to the countersignature terminal, so that the countersignature terminal adjusts the agreement data in response to the material adjustment countersignature instruction and then countersigns;

[0029] When it is detected that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data, the order data is regenerated based on the adjusted agreement data.

[0030] In a possible implementation, determining, based on the order data, the production scheduling data corresponding to when the production efficiency data in the garment production process reaches a preset high efficiency condition includes:

[0031] Determining correlation factors of the target order in the production process, wherein the correlation factors include the consumption of any garment material and the scheduling utilization rate of any processing equipment;

[0032] Building a production efficiency model for the target order based on the order data, wherein the production efficiency model is used to indicate production efficiency data of the target order under the influence of the correlation factors;

[0033] Building a scheduling model based on the production efficiency model of at least one target order currently to be processed;

[0034] The scheduling model is iteratively solved, and production scheduling data corresponding to when the production efficiency data of the target order meets the high-efficiency condition is screened out, wherein the high-efficiency condition includes at least one of minimizing production time and maximizing processing equipment utilization, and the production scheduling data is used to indicate the processing input quantity of any clothing material on any processing equipment.

[0035] In a possible implementation, constructing the production efficiency model of the target order based on the order data includes:

[0036] Obtaining a call rate, equipment processing efficiency data, and material processing efficiency data of the processing equipment, wherein the equipment processing efficiency data indicates the processing time required for the processing equipment to process a unit mass of a specified garment material, and the material processing efficiency data indicates the mass of any garment material processed per unit time;

[0037] Determining an equipment processing efficiency model for the target order based on any clothing material and equipment processing efficiency data of a processing equipment used to process the clothing material;

[0038] Determining a material processing efficiency model for the target order based on the call rate of the processing equipment, the material processing efficiency data, and the material requirement data of the target order;

[0039] Based on the equipment processing efficiency model and / or the material processing efficiency model, a production efficiency model of the target order is constructed.

[0040] In a possible implementation, the adjustment counter-signature instruction includes a demand adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising:

[0041] When it is determined that the production scheduling data meets the order requirement data, production is performed according to the production scheduling data, wherein the order requirement data includes time limit data related to the order delivery date, operation requirement data, and effect requirement data, the operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data;

[0042] When it is determined that the production scheduling data does not meet any of the order demand data, and it is confirmed that the order data meets the demand exception condition, a corresponding demand adjustment countersignature instruction is generated and then sent to the countersignature terminal, so that the countersignature terminal responds to the demand adjustment countersignature instruction, updates the agreement data, and then countersigns;

[0043] When it is detected that the demand adjustment counter-signing result sent by the counter-signing terminal is updated agreement data, the order data is regenerated based on the updated agreement data.

[0044] In a possible implementation, the adjustment counter-signature instruction includes a change adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising:

[0045] When a change is detected in the agreement data and it is confirmed that the order data meets the requirement change condition, a corresponding change adjustment countersignature instruction is generated and then sent to the countersignature terminal, so that the countersignature terminal responds to the change adjustment countersignature instruction and countersigns the changed agreement data;

[0046] When it is detected that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data, the order data is regenerated based on the changed agreement data.

[0047] In a second aspect, the present application provides a system for processing clothing customization orders, comprising: a processing device and at least one countersigning terminal;

[0048] The processing device is configured to obtain agreement data of a target order, wherein the agreement data carries an agreement countersigning instruction initiated from any countersigning terminal;

[0049] The countersignature terminal is used to respond to the agreement countersignature instruction to countersign and then generate an agreement countersignature result;

[0050] The processing device is configured to, upon detecting that the electronic agreement corresponding to the target order has been reached as a result of the agreement countersigning, generate corresponding order data based on the agreement data; and upon detecting that the order data satisfies any one of the order re-planning conditions, initiate a corresponding adjustment countersigning instruction and issue it to the countersigning terminal, wherein the order re-planning condition includes a demand anomaly condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data;

[0051] The countersignature terminal is used to respond to the adjustment countersignature instruction to perform countersignature and then generate an adjustment countersignature result;

[0052] The processing device is used to regenerate the order data of the target order based on the obtained adjustment and counter-signing results, and to perform production according to the updated order data.

[0053] The processing method and system of clothing customization orders provided by the embodiment of the present application countersigns the agreement data by responding to the agreement countersigning instruction, and the agreement countersigning result triggers the generation of order data based on the agreement data, and then when it is detected that the order data meets any order re-planning conditions, it initiates the adjustment countersigning instruction, thereby regenerating the order data of the target order based on the adjustment countersigning result, and producing according to the updated order data, so as to synchronize the data generated in the countersigning process to the order management, and realize the integration of order management and countersigning. In this way, it is different from the independent order management system and agreement countersigning system in the prior art, solves the problem of information asynchrony in the existing clothing production processing method, can be applied to the scenario of clothing customization orders, realizes adaptive synchronous scheduling, and can effectively improve production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A flowchart of a method for processing a customized clothing order provided in an embodiment of the present application;

[0055] Figure 2 A schematic diagram of the structure of a system for processing customized clothing orders provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0057] Figure 1 A flowchart of a method for processing a customized clothing order is provided in an embodiment of the present application. The method for processing a customized clothing order is used for a processing device, and the method includes steps S101 to S104.

[0058] S101. Acquire agreement data of a target order, where the agreement data carries an agreement countersigning instruction initiated from any countersigning terminal.

[0059] It should be noted that, unlike the independent order management systems and agreement countersigning systems in the prior art, the processing device can be an electronic device that can perform operations such as order processing and countersigning processes. The processing device integrates order management and countersigning, improves data synchronization in the clothing production process, and avoids production errors caused by data asynchrony.

[0060] A countersignature terminal can be a terminal device used by the client or the work execution party (such as agreement negotiators or production personnel). During the countersignature process, any countersignature terminal or processing device initiates a countersignature instruction, and the countersignature terminal associated with the instruction responds to the instruction and performs the countersignature.

[0061] In this application, the agreement data may be in text form, such as an electronic agreement, or in audio form. That is, the agreement data includes interactive audio data and electronic agreement data specific to the electronic agreement. Specifically, the interactive audio data and electronic agreement data may include the name of the clothing product ordered, the order quantity, the unit price of the clothing product, the total price of the clothing product, the order delivery date, the remittance address, the delivery method, and liability for breach of contract, etc. This application does not limit this.

[0062] S102. When it is detected that the agreement countersigning result is that the electronic agreement corresponding to the target order has been reached, corresponding order data is generated based on the agreement data, wherein the agreement countersigning result is generated after countersigning by at least one other countersigning terminal in response to the agreement countersigning instruction.

[0063] In this application, any co-signing terminal initiates an agreement co-signing instruction. The processing device responds after receiving the agreement co-signing instruction and sends the agreement co-signing instruction to other co-signing terminals, so that the co-signing terminals perform multi-party co-signing based on the agreement data, and generate the corresponding agreement co-signing result and return it to the processing device. It should be noted that during the co-signing process, the co-signing terminal reviews whether the electronic agreement in the agreement data has been reached, and when multiple parties determine that the electronic agreement has been reached, it generates an agreement co-signing result indicating that the electronic agreement has been reached.

[0064] For example, the co-signing terminal A corresponding to the business personnel uploads the agreement data to the processing device and initiates the agreement co-signing instruction. Then the co-signing terminal where the customer is located and the co-signing terminal C corresponding to the process personnel need to review and co-sign the content of the electronic agreement. When both confirm that the electronic agreement has been reached, the agreement co-signing result indicating that the electronic agreement has been reached is fed back to the processing device, so that when the processing device recognizes that the electronic agreement has been reached, it triggers the generation of corresponding order data based on the agreement data.

[0065] Therefore, this application triggers the generation of order data through the agreement signing results, uses the signing results as the control factor of order management, realizes the mutual integration of signing and order management in data and processes, improves data consistency, and realizes adaptive synchronous scheduling.

[0066] In an optional embodiment, key order fields are extracted from the agreement data and then queried against a corresponding order template for those key order fields, thereby mapping the agreement data to the order template to form the order data. Thus, this embodiment generates orders that match the agreement requirements through keyword and template matching. The order data includes information such as order date, delivery date, garment type, garment quantity, and size, enabling rapid screening of order information that meets the agreement requirements and improving processing efficiency.

[0067] S103. When it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes the demand abnormality condition corresponding to the order demand data indicated by the order data and the demand change condition corresponding to the agreement data.

[0068] S104. Based on the obtained adjustment countersignature result, regenerate the order data of the target order, and perform production according to the updated order data, wherein the adjustment countersignature result is generated after the countersignature terminal responds to the adjustment countersignature instruction and countersigns.

[0069] In this application, order demand data may include material demand data related to order materials, time limit data related to order delivery dates, operational requirements data, and effect requirements data. The operational requirements data are used to indicate the operational requirements of the target order during the production process, and the effect requirements data include completion requirements data and quality requirements data. This application does not impose any restrictions on this. Demand abnormality conditions include abnormal conditions representing completion time exceeding the order delivery date, abnormal conditions representing operational failures that do not meet operational requirements data, and abnormal conditions representing effect failures that do not meet effect requirements data. Demand change conditions represent conditions under which agreement data (such as electronic agreements) are changed.

[0070] It should be noted that the order data is checked to see if it meets the order re-planning conditions, such as whether the order materials have reasonable inventory, whether the production scheduling data of the order can be delivered within the time limit, and whether the agreement data has changed. Then, when it is detected that at least one of the order re-planning conditions is met, an adjustment countersignature instruction is triggered and issued to the corresponding countersignature terminal, which then revises the agreement data, reviews, confirms, and countersigns the revised agreement data, and generates an adjustment countersignature result containing the confirmed revised agreement data.

[0071] Therefore, this application triggers the initiation of the counter-signing process when the order data meets any of the order re-planning conditions, and obtains the counter-signing results after multiple parties counter-sign. The order data is updated based on the counter-signing results, so that production is carried out based on the updated order data, ensuring that the production process can quickly adapt to changes, avoiding production errors caused by delays, and achieving timely response and adjustment. At the same time, production is carried out based on the updated order data, and the data generated in the counter-signing process is synchronously updated to the order management, realizing the integration of order management and counter-signing, and realizing the interdependence of various links in clothing production, thereby improving data response efficiency and thus improving production efficiency.

[0072] The processing method of clothing customization orders provided by the present application is to countersign the agreement data by responding to the agreement countersigning instruction, and the agreement countersigning result is triggered to generate order data based on the agreement data, and then when it is detected that the order data meets any order re-planning conditions, it initiates the adjustment countersigning instruction, thereby regenerating the order data of the target order based on the adjustment countersigning result, and producing according to the updated order data, so as to synchronize the data generated in the countersigning process to the order management, and realize the integration of order management and countersigning. In this way, different from the independent order management system and agreement countersigning system in the prior art, the problem of information asynchrony in the existing clothing production processing method is solved, and it can be applied to the scenario of clothing customization orders, realize adaptive synchronous scheduling, and effectively improve production efficiency.

[0073] In some embodiments, the agreement data includes interactive audio data and electronic agreement data for the electronic agreement, and the interactive audio data is used to record the voice communication process of the electronic agreement and / or the target order. Specifically, the method further includes:

[0074] When it is detected that the electronic agreement has not been reached as a result of the agreement countersigning, performing intention analysis on the interactive audio data of the target order;

[0075] When it is analyzed that the electronic agreement meets the preset conditions for the tendency to achieve the goal, the target order is added to the waiting queue;

[0076] Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data;

[0077] Clearing the target order corresponding to the agreement achievement intention degree lower than a preset low intention threshold in the waiting queue, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low-intent customer, so as to update customer source data, wherein the customer source data includes at least one customer and corresponding identification content;

[0078] The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct the customers corresponding to the orders in the return visit reminder queue to be reminded of the return visit.

[0079] In this embodiment, during the process of the countersigning terminal responding to the agreement countersigning instruction to countersign the agreement data with multiple parties, if the review confirms that the electronic agreement has not been reached, an agreement countersigning result is generated to indicate that the electronic agreement has not been reached. Subsequently, after receiving the agreement countersigning result, the processing device performs an intention analysis on the interactive audio data (such as a business negotiation recording) contained in the agreement data. Optionally, if the customer does not directly express a refusal during the communication process through voice recognition, it is considered that the electronic agreement meets the condition of the tendency to reach an agreement, and there is a possibility of reaching an agreement. Similarly, if the customer directly expresses the intention to refuse during the communication process, it is considered that the electronic agreement does not meet the condition of the tendency to reach an agreement.

[0080] Furthermore, the orders corresponding to the electronic agreements that meet the conditions for the tendency to reach an agreement are added to the waiting queue to further judge the customer's willingness and enthusiasm. Specifically, the electronic agreement data and the interactive audio data are subjected to feature analysis to determine the intention to reach an agreement. The intention to reach an agreement can be a customer's score for the intention to reach an agreement, such as 0-100. Then, by setting a threshold, electronic agreements with an intention to reach an agreement below a low intention threshold are deemed invalid agreements and cleaned up. Feedback is given to relevant business personnel in the form of an agreement termination (such as an agreement termination instruction) to update the customer source data (marked as a low-intention customer). In addition, the remaining agreements in the waiting queue are sorted from large to small according to the intention to reach an agreement, and the corresponding return visit reminder queue and return visit reminder instruction are generated to achieve regular push of customer return visit reminders in the sorted order to promote the reaching of an agreement.

[0081] Therefore, this embodiment detects that the result of the agreement signing is that the electronic agreement has not been reached, then performs intention analysis on orders with a tendency to reach the agreement, eliminates orders with a low intention to reach the agreement, and reminds customers to return visit based on the level of intention to reach the agreement, thereby realizing potential data mining and intention mining and improving data utilization.

[0082] In some embodiments, determining the degree of agreement reaching intention based on the interactive audio data and the electronic agreement data includes:

[0083] Inputting the interactive audio data into a preset first feature extraction model to extract feature vectors from the interactive audio data, analyzing the feature vectors, and outputting speech feature data, wherein the speech feature data is used to indicate long-term dependencies in the interactive audio data;

[0084] Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data;

[0085] Calculating the speech feature data and the text feature data using a preset cross-attention model to determine a speech attention weight matrix and a text attention weight matrix;

[0086] Determining a corresponding speech attention weight feature based on the speech attention weight matrix, and determining a corresponding text attention weight feature based on the text attention weight matrix;

[0087] The speech attention weight feature and the text attention weight feature are spliced ​​to determine the intention to reach an agreement on the target order based on the splicing result.

[0088] In this embodiment, the first feature extraction model includes a convolutional neural network and a recurrent neural network, arranged sequentially. Specifically, the convolutional neural network extracts features from the interactive audio data to obtain feature vectors, which are then analyzed again by the recurrent neural network to obtain speech feature data. Therefore, this embodiment uses the first feature extraction model to extract features from the interactive audio data, improving data extraction accuracy.

[0089] Exemplarily, the operation of the convolutional neural network is determined by the following formula:

[0090]

[0091] in, is the eigenvector, Represents the operation of convolutional neural network, Represents a sequence of interactive audio data sampled at a unit step size.

[0092] The operation of the recurrent neural network is determined by the following formula:

[0093]

[0094] in, is the speech feature data, Represents the operation of a recurrent neural network.

[0095] In this embodiment, the second feature extraction model includes a Bert model and a recurrent neural network, which are sequentially arranged. Specifically, the Bert model calculates embedded values ​​for the electronic agreement data to obtain a text vector, which is then analyzed using the recurrent neural network to obtain text feature data. Therefore, this embodiment uses the second feature extraction model to extract features from the electronic agreement data, improving data extraction accuracy.

[0096] Furthermore, this embodiment calculates the speech feature data and text feature data using a cross-attention model (which is built on the cross-attention mechanism) to obtain a speech attention weight matrix and a text attention weight matrix. Subsequently, through a statistical pooling layer, speech attention weight features and text attention weight features are obtained, where the attention weight features include the mean and standard deviation features of the attention weight. Furthermore, the speech attention weight features and text attention weight features are concatenated in the channel dimension, and then the concatenation result is processed in combination with multiple fully connected layers to obtain the customer's intention score for reaching an agreement, that is, the degree of intention to reach an agreement.

[0097] Therefore, this embodiment performs feature extraction on interactive audio data through the first feature extraction model, performs feature extraction on electronic agreement data through the second feature extraction model, and determines the voice attention weight feature and the text attention weight feature, so as to obtain the intention degree of agreement reaching, achieve the accuracy of feature extraction, accurately reflect the intention of the agreement data, and improve the accuracy of intention analysis.

[0098] In some embodiments, the order data includes order delivery date, clothing type, clothing quantity, and clothing size; when it is detected that the order data meets any one of the order re-planning conditions, a corresponding adjustment countersignature instruction is initiated and sent to the countersignature terminal, including:

[0099] quantifying the clothing type as at least one clothing material required for the target order, quantifying the clothing quantity and the clothing size as the material requirement of the target order, and constituting the material requirement data in the order requirement data with the clothing material and the material requirement;

[0100] querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material;

[0101] When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

[0102] In this embodiment, the material requirement data includes at least one garment material in the target order and the required quantity for each garment material. Subsequently, a material database is queried based on the material requirement data. If the database contains all garment materials and the required quantity for each garment material exceeds the material inventory, it indicates that there is sufficient inventory to process the target order. Accordingly, corresponding production scheduling data is generated based on the order data.

[0103] Therefore, this embodiment determines whether the order data meets the material demand data to confirm whether the order re-planning conditions are met, thereby eliminating delays caused by material shortages in the initial stage, achieving timely response and adjustment, reducing production losses, and improving production efficiency.

[0104] Based on the above embodiment, in some embodiments, the adjustment counter-signature instruction includes a material adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising:

[0105] When it is found that the material database does not have all the clothing materials, or the material demand of any of the clothing materials is lower than the material inventory, it is confirmed that the order data meets the demand abnormality condition, then a corresponding material adjustment countersignature instruction is generated and sent to the countersignature terminal, so that the countersignature terminal adjusts the agreement data in response to the material adjustment countersignature instruction and then countersigns;

[0106] When it is detected that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data, the order data is regenerated based on the adjusted agreement data.

[0107] In this embodiment, when it is found that the material database does not have all the clothing materials, or the material demand of any clothing material is lower than the material inventory, it indicates that the material inventory of the target order is in short supply. Then, it is confirmed that the order data meets the order re-planning conditions (i.e., the demand abnormality conditions corresponding to the material demand data), and a material adjustment countersignature instruction is triggered.

[0108] In response to the material adjustment countersignature instruction, the countersignature terminal can adjust the material requirement data in the agreement data, review and countersign the adjusted agreement data, and return the material adjustment countersignature result to the processing device. Subsequently, based on the material adjustment countersignature result including the adjusted agreement data, the order data is regenerated, and the material requirement data indicated by the updated order data is determined, so that the material inventory status can be queried in the material database.

[0109] Therefore, this embodiment queries the material shortage of the target order in the material database to confirm that the material demand data corresponding to the order data meets the demand abnormality conditions, and then sends a material adjustment countersignature instruction, and regenerates the order data based on the adjusted agreement data contained in the material adjustment countersignature result, thereby realizing synchronous scheduling, avoiding data inconsistency, and improving processing efficiency and generation efficiency.

[0110] In some embodiments, determining, based on the order data, the production scheduling data corresponding to when the production efficiency data in the garment production process reaches a preset high efficiency condition includes:

[0111] Determining correlation factors of the target order in the production process, wherein the correlation factors include the consumption of any garment material and the scheduling utilization rate of any processing equipment;

[0112] Building a production efficiency model for the target order based on the order data, wherein the production efficiency model is used to indicate production efficiency data of the target order under the influence of the correlation factors;

[0113] Building a scheduling model based on the production efficiency model of at least one target order currently to be processed;

[0114] The scheduling model is iteratively solved, and production scheduling data corresponding to when the production efficiency data of the target order meets the high-efficiency condition is screened out, wherein the high-efficiency condition includes at least one of minimizing production time and maximizing processing equipment utilization, and the production scheduling data is used to indicate the processing input quantity of any clothing material on any processing equipment.

[0115] In this embodiment, the correlation factors represent parameters in the production process, such as the consumption of a certain material or the scheduling utilization rate of processing equipment. Based on the order data, a production efficiency model of the target order under the influence of the correlation factors is determined. The production efficiency model can include production efficiency and cost functions under the correlation factors. Then, based on the current multiple target orders to be processed and the corresponding production efficiency models, a scheduling model is determined. It should be noted that the scheduling model is used to achieve collaborative planning of the current multiple target orders to be processed, aiming to improve the overall processing efficiency while taking into account the improvement of individual production efficiency.

[0116] Furthermore, existing optimization algorithms, such as ant colony algorithms, can be used to iteratively solve the scheduling model, obtaining production scheduling data for multiple pending target orders. Specifically, this data includes the allocation of processing information, such as the processing quantity of the i-th material on the j-th processing equipment. Specifically, during the scheduling model solution, high-efficiency conditions, such as minimizing production time and maximizing processing equipment utilization, are set to select the production scheduling data that meets these high-efficiency conditions.

[0117] Therefore, this embodiment constructs a production efficiency model for target orders and a scheduling model for collaborative production of multiple target orders by determining correlation factors, thereby improving the rationality and efficiency of production scheduling and improving equipment utilization.

[0118] In some embodiments, constructing the production efficiency model of the target order based on the order data includes:

[0119] Obtaining a call rate, equipment processing efficiency data, and material processing efficiency data of the processing equipment, wherein the equipment processing efficiency data indicates the processing time required for the processing equipment to process a unit mass of a specified garment material, and the material processing efficiency data indicates the mass of any garment material processed per unit time;

[0120] Determining an equipment processing efficiency model for the target order based on any clothing material and equipment processing efficiency data of a processing equipment used to process the clothing material;

[0121] Determining a material processing efficiency model for the target order based on the call rate of the processing equipment, the material processing efficiency data, and the material requirement data of the target order;

[0122] Based on the equipment processing efficiency model and / or the material processing efficiency model, a production efficiency model of the target order is constructed.

[0123] In this embodiment, the production efficiency model is determined by the following formula:

[0124]

[0125] in, represents the production efficiency model of the kth order, M represents the number of associated factors, Represents the model function of the k-th order under the M-th associated factor.

[0126] Optionally, by constructing an equipment processing efficiency model as the model function, the production efficiency model is represented as an equipment processing efficiency model under the influence of multiple related factors. The model function can be determined by the following formula:

[0127]

[0128] in, Represents clothing material M, represents the equipment processing efficiency model, It represents the equipment processing efficiency data, that is, it indicates the processing time required for the i-th processing equipment to process a unit mass of the specified clothing material M, and n is the number of processing equipment.

[0129] Optionally, by constructing a material processing efficiency model as the model function, the production efficiency model is represented as a material processing efficiency model under the influence of multiple related factors. The model function can be determined by the following formula:

[0130]

[0131] in, represents the material processing efficiency model, represents the call rate of the Mth processing equipment, Represents material processing efficiency data, which is used to indicate the quality of processing the j-th type of clothing material per unit time. represents the material demand of the jth type of clothing material, and z represents the number of types of clothing materials.

[0132] Optionally, a fusion model is generated by using the material processing efficiency model and the equipment processing efficiency model. Based on the fusion model as the model function, the production efficiency model is represented as a fusion model under the influence of multiple correlation factors.

[0133] Therefore, this embodiment constructs a production efficiency model by constructing a material processing efficiency model and an equipment processing efficiency model, thereby improving the accuracy of the model and facilitating improving the efficiency of production scheduling.

[0134] In some embodiments, the adjustment counter-signature instruction includes a demand adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising:

[0135] When it is determined that the production scheduling data meets the order requirement data, production is performed according to the production scheduling data, wherein the order requirement data includes time limit data related to the order delivery date, operation requirement data, and effect requirement data, the operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data;

[0136] When it is determined that the production scheduling data does not meet any of the order demand data, and it is confirmed that the order data meets the demand exception condition, a corresponding demand adjustment countersignature instruction is generated and then sent to the countersignature terminal, so that the countersignature terminal responds to the demand adjustment countersignature instruction, updates the agreement data, and then countersigns;

[0137] When it is detected that the demand adjustment counter-signing result sent by the counter-signing terminal is updated agreement data, the order data is regenerated based on the updated agreement data.

[0138] In this embodiment, the production scheduling data is checked to see if it meets the order requirements, such as, but not limited to, whether it can be delivered within the time limit, whether it meets production operation requirements, and whether it meets performance requirements. Subsequently, if it is detected that the production scheduling data meets the order requirements, it indicates that the production scheduling process and results meet the order requirements, and production is then carried out according to the production scheduling data.

[0139] Therefore, this embodiment plans the production scheduling data of the order and checks whether the production scheduling data meets the order demand data, thereby achieving timely response and adjustment, reducing production losses, and improving production efficiency.

[0140] Optionally, when it is detected that the production scheduling data does not meet the order demand data, such as overtime delivery, substandard production process, and results that do not meet requirements, the order data is confirmed to meet the order re-planning conditions (i.e., the demand abnormality conditions corresponding to the order demand data), and a demand adjustment countersignature instruction is triggered.

[0141] In response to this demand adjustment countersignature instruction, the countersignature terminal can adjust the delivery date, product performance, and other aspects of the agreement data. It then reviews and countersigns the updated agreement data and returns the demand adjustment countersignature result to the processing device. Subsequently, based on the demand adjustment countersignature result, which includes the updated agreement data, the order data is regenerated. Once the updated order data is confirmed to meet the material demand data, the production scheduling data is regenerated to reallocate the processing status.

[0142] Optionally, when it is detected that the production scheduling data does not meet the order demand data, the target order can be added to a waiting queue to perform an intention analysis on the agreement data.

[0143] Therefore, this embodiment uses the production scheduling data to confirm that the order demand data corresponding to the order data meets the demand abnormality condition, and then sends a demand adjustment countersignature instruction, and regenerates the order data and production scheduling data based on the updated protocol data contained in the demand adjustment countersignature result to achieve synchronous scheduling, avoid data inconsistency, and improve processing efficiency and generation efficiency.

[0144] In some embodiments, the adjustment counter-signature instruction includes a change adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising:

[0145] When a change is detected in the agreement data and it is confirmed that the order data meets the requirement change condition, a corresponding change adjustment countersignature instruction is generated and then sent to the countersignature terminal, so that the countersignature terminal responds to the change adjustment countersignature instruction and countersigns the changed agreement data;

[0146] When it is detected that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data, the order data is regenerated based on the changed agreement data.

[0147] In this embodiment, if a change in the agreement data (i.e., a change in user requirements) is detected during any process, and the order data is confirmed to meet the requirements change conditions, a change adjustment countersignature instruction is generated. The countersignature terminal then responds to this change adjustment countersignature instruction, reviews and countersigns the updated agreement data (i.e., the changes in the agreement data), and returns the change adjustment countersignature result to the processing device. Subsequently, based on the change adjustment countersignature result, which includes the changed agreement data, the order data is regenerated. The updated order data and production scheduling data are then combined to reassign the processing status.

[0148] Therefore, this embodiment detects changes in the protocol data to confirm that the order data meets the demand change conditions, and then sends a change adjustment countersignature instruction, and regenerates the order data and production scheduling data based on the changed protocol data contained in the change adjustment countersignature result, to achieve synchronous scheduling, avoid data inconsistency, improve processing efficiency and generation efficiency, and ensure that production efficiency continues to remain optimal.

[0149] Optionally, a delivery countersignature is initiated after production is completed, so that the countersignature equipment conducts multi-party review and countersignature on the delivery countersignature to complete the entire production and delivery process of the order.

[0150] Figure 2 This is a structural diagram of a system for processing clothing customization orders provided in an embodiment of the present application. The clothing customization order processing system 200 includes: a processing device 201 and at least one countersigning terminal 202;

[0151] The processing device 201 is configured to obtain the agreement data of the target order, wherein the agreement data carries the agreement countersigning instruction initiated by any countersigning terminal;

[0152] The countersigning terminal 202 is used to respond to the agreement countersigning instruction to countersign and then generate an agreement countersigning result;

[0153] The processing device 201 is configured to, upon detecting that the electronic agreement corresponding to the target order has been reached as a result of the agreement countersigning, generate corresponding order data based on the agreement data; and upon detecting that the order data satisfies any one of the order re-planning conditions, initiate a corresponding adjustment countersigning instruction and issue it to the countersigning terminal, wherein the order re-planning condition includes a demand exception condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data;

[0154] The countersigning terminal 202 is used to countersign in response to the adjustment countersigning instruction and then generate an adjustment countersigning result;

[0155] The processing device 201 is used to regenerate the order data of the target order based on the obtained adjustment countersignature result, and perform production according to the updated order data.

[0156] In some embodiments, the agreement data includes interactive audio data and electronic agreement data for the electronic agreement, wherein the interactive audio data is used to record the voice communication process of the electronic agreement and / or the target order;

[0157] The processing device is further configured to perform intention analysis on the interactive audio data of the target order when detecting that the agreement countersigning result is that the electronic agreement has not been reached;

[0158] When it is analyzed that the electronic agreement meets the preset conditions for the tendency to achieve the goal, the target order is added to the waiting queue;

[0159] Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data;

[0160] Clearing the target order corresponding to the agreement achievement intention degree lower than a preset low intention threshold in the waiting queue, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low-intent customer, so as to update customer source data, wherein the customer source data includes at least one customer and corresponding identification content;

[0161] The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct the customers corresponding to the orders in the return visit reminder queue to be reminded of the return visit.

[0162] In some embodiments, the processing device is further configured to input the interactive audio data into a preset first feature extraction model to extract feature vectors from the interactive audio data, analyze the feature vectors, and output speech feature data, wherein the speech feature data is used to indicate long-term dependencies in the interactive audio data;

[0163] Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data;

[0164] Calculating the speech feature data and the text feature data using a preset cross-attention model to determine a speech attention weight matrix and a text attention weight matrix;

[0165] Determining a corresponding speech attention weight feature based on the speech attention weight matrix, and determining a corresponding text attention weight feature based on the text attention weight matrix;

[0166] The speech attention weight feature and the text attention weight feature are spliced ​​to determine the intention to reach an agreement on the target order based on the splicing result.

[0167] In some embodiments, the order data includes order delivery date, clothing type, clothing quantity, and clothing size;

[0168] The processing device is further configured to quantify the clothing type into at least one clothing material required for the target order, quantify the clothing quantity and the clothing size into the material requirement of the target order, and form the material requirement data in the order requirement data from the clothing material and the material requirement;

[0169] querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material;

[0170] When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

[0171] In some embodiments, the adjustment countersignature instruction includes a material adjustment countersignature instruction;

[0172] The processing device is configured to, when it is found that the material database does not fully contain the clothing materials, or the material demand of any of the clothing materials is lower than the material inventory, confirm that the order data meets the demand abnormality condition, generate a corresponding material adjustment countersignature instruction, and then send it to the countersignature terminal;

[0173] The countersignature terminal is configured to respond to the material adjustment countersignature instruction, adjust the agreement data, and then countersign to generate a material adjustment countersignature result;

[0174] The processing device is used to regenerate the order data based on the adjusted agreement data when detecting that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data.

[0175] In some embodiments, the processing device is used to determine correlation factors of the target order in the production process, wherein the correlation factors include the consumption of any clothing material and the scheduling utilization rate of any processing equipment;

[0176] Building a production efficiency model for the target order based on the order data, wherein the production efficiency model is used to indicate production efficiency data of the target order under the influence of the correlation factors;

[0177] Building a scheduling model based on the production efficiency model of at least one target order currently to be processed;

[0178] The scheduling model is iteratively solved, and production scheduling data corresponding to when the production efficiency data of the target order meets the high-efficiency condition is screened out, wherein the high-efficiency condition includes at least one of minimizing production time and maximizing processing equipment utilization, and the production scheduling data is used to indicate the processing input quantity of any clothing material on any processing equipment.

[0179] In some embodiments, the processing device is used to obtain the call rate of the processing equipment, equipment processing efficiency data, and material processing efficiency data, wherein the equipment processing efficiency data is used to indicate the processing time required for the processing equipment to process a unit mass of a specified garment material, and the material processing efficiency data is used to indicate the mass of any garment material processed per unit time;

[0180] Determining an equipment processing efficiency model for the target order based on any clothing material and equipment processing efficiency data of a processing equipment used to process the clothing material;

[0181] Determining a material processing efficiency model for the target order based on the call rate of the processing equipment, the material processing efficiency data, and the material requirement data of the target order;

[0182] Based on the equipment processing efficiency model and / or the material processing efficiency model, a production efficiency model of the target order is constructed.

[0183] In some embodiments, the adjustment countersignature instruction includes a demand adjustment countersignature instruction;

[0184] The processing device is configured to, upon determining that the production scheduling data meets the order demand data, perform production according to the production scheduling data, wherein the order demand data includes time limit data, operation requirement data, and effect requirement data related to the order delivery date, the operation requirement data being used to indicate the operation requirements of the target order during the production process, and the effect requirement data including completion requirement data and quality requirement data; upon determining that the production scheduling data does not meet any of the order demand data, confirming that the order data meets the demand abnormality condition, generate a corresponding demand adjustment countersignature instruction, and then send the instruction to the countersignature terminal;

[0185] The countersigning terminal is configured to adjust the countersigning instruction in response to the demand, and countersign the updated agreement data;

[0186] The processing device is configured to regenerate the order data based on the updated agreement data when detecting that the demand adjustment counter-signing result sent by the counter-signing terminal is the updated agreement data.

[0187] In some embodiments, the adjusting countersignature instruction includes changing the adjusting countersignature instruction;

[0188] The processing device is configured to, upon detecting a change in the agreement data, confirm that the order data meets the requirement change condition, generate a corresponding change adjustment countersignature instruction, and then send the instruction to the countersignature terminal;

[0189] The countersigning terminal is configured to countersign the changed agreement data in response to the change adjustment countersigning instruction;

[0190] The processing device is used to regenerate the order data based on the changed agreement data when detecting that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data.

[0191] The system of the embodiment of the present application can execute the method provided by the embodiment of the present application, and the implementation principle is similar. The actions performed by each device in the system of each embodiment of the present application correspond to the steps in the method of each embodiment of the present application. For the detailed functional description of each device of the system, please refer to the description in the corresponding method shown in the previous text, and will not be repeated here.

[0192] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for processing clothing customization orders, characterized in that: For processing equipment, including: Acquire agreement data of the target order, wherein the agreement data carries an agreement countersigning instruction initiated from any countersigning terminal; When it is detected that the electronic agreement corresponding to the target order has been reached as a result of the agreement countersigning, corresponding order data is generated based on the agreement data, wherein the agreement countersigning result is generated after countersigning by at least one other countersigning terminal in response to the agreement countersigning instruction; When it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data, including: based on the order data, determining the production scheduling data corresponding to when the production efficiency data in the clothing production process reaches a preset high-efficiency condition; wherein, determining the associated factors of the target order in the production process, the associated factors include the consumption of any clothing material and the scheduling utilization rate of any processing equipment; based on the order data, constructing a production efficiency model of the target order, the production efficiency model is used to indicate the production efficiency data of the target order under the influence of the associated factors; constructing a scheduling model based on the production efficiency model of at least one target order currently to be processed; iteratively solving the scheduling model, and screening out the corresponding production efficiency data when the production efficiency data of the target order reaches the high-efficiency condition. Production scheduling data, wherein the high-efficiency condition includes at least one of minimizing production time and maximizing processing equipment utilization, and the production scheduling data is used to indicate the processing input quantity of any garment material on any processing equipment; wherein the production efficiency model is constructed by the following steps, including: obtaining the call rate, equipment processing efficiency data, and material processing efficiency data of the processing equipment, the equipment processing efficiency data indicating the processing time required for the processing equipment to process a specified garment material per unit mass, and the material processing efficiency data indicating the mass of any garment material processed per unit time; determining the equipment processing efficiency model of the target order based on the equipment processing efficiency data of any garment material and the processing equipment used to process the garment material; determining the material processing efficiency model of the target order based on the call rate, material processing efficiency data, and material requirement data of the processing equipment; and constructing a production efficiency model for the target order based on the equipment processing efficiency model and / or the material processing efficiency model; Based on the obtained adjustment counter-signing result, the order data of the target order is regenerated, and production is performed according to the updated order data, wherein the adjustment counter-signing result is generated after the counter-signing terminal responds to the adjustment counter-signing instruction and counter-signs.

2. The method for processing clothing customization orders according to claim 1, characterized in that: The agreement data includes interactive audio data and electronic agreement data for the electronic agreement, wherein the interactive audio data is used to record the voice communication process for the electronic agreement and / or the target order; The method further comprises: When it is detected that the electronic agreement has not been reached as a result of the agreement countersigning, performing intention analysis on the interactive audio data of the target order; When it is analyzed that the electronic agreement meets the preset conditions for the tendency to achieve the goal, the target order is added to the waiting queue; Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data; Clearing the target order corresponding to the agreement achievement intention degree lower than a preset low intention threshold in the waiting queue, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low-intent customer, so as to update customer source data, wherein the customer source data includes at least one customer and corresponding identification content; The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct the customers corresponding to the orders in the return visit reminder queue to be reminded of the return visit.

3. The method for processing clothing customization orders according to claim 2, characterized in that: The determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data includes: Inputting the interactive audio data into a preset first feature extraction model to extract feature vectors from the interactive audio data, analyzing the feature vectors, and outputting speech feature data, wherein the speech feature data is used to indicate long-term dependencies in the interactive audio data; Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data; Calculating the speech feature data and the text feature data using a preset cross-attention model to determine a speech attention weight matrix and a text attention weight matrix; Determining a corresponding speech attention weight feature based on the speech attention weight matrix, and determining a corresponding text attention weight feature based on the text attention weight matrix; The speech attention weight feature and the text attention weight feature are spliced ​​to determine the intention to reach an agreement on the target order based on the splicing result.

4. The method for processing clothing customization orders according to claim 3, characterized in that: The order data includes the order delivery date, clothing type, clothing quantity, and clothing size; when it is detected that the order data meets any order re-planning conditions, a corresponding adjustment countersignature instruction is initiated and sent to the countersignature terminal, including: quantifying the clothing type as at least one clothing material required for the target order, quantifying the clothing quantity and the clothing size as the material requirement of the target order, and constituting the material requirement data in the order requirement data with the clothing material and the material requirement; querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material; When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

5. The method for processing clothing customization orders according to claim 4, characterized in that: The adjustment counter-signature instruction includes a material adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When it is found that the material database does not have all the clothing materials, or the material demand of any of the clothing materials is lower than the material inventory, it is confirmed that the order data meets the demand abnormality condition, then a corresponding material adjustment countersignature instruction is generated and sent to the countersignature terminal, so that the countersignature terminal adjusts the agreement data in response to the material adjustment countersignature instruction and then countersigns; When it is detected that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data, the order data is regenerated based on the adjusted agreement data.

6. The method for processing clothing customization orders according to claim 5, characterized in that: The adjustment countersignature instruction includes a demand adjustment countersignature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment countersignature instruction is initiated and sent to the countersignature terminal, further comprising: When it is determined that the production scheduling data meets the order requirement data, production is performed according to the production scheduling data, wherein the order requirement data includes time limit data related to the order delivery date, operation requirement data, and effect requirement data, the operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data; When it is determined that the production scheduling data does not meet any of the order demand data, and it is confirmed that the order data meets the demand exception condition, a corresponding demand adjustment countersignature instruction is generated and then sent to the countersignature terminal, so that the countersignature terminal responds to the demand adjustment countersignature instruction, updates the agreement data, and then countersigns; When it is detected that the demand adjustment counter-signing result sent by the counter-signing terminal is updated agreement data, the order data is regenerated based on the updated agreement data.

7. The method for processing clothing customization orders according to claim 1, characterized in that: The adjustment counter-signature instruction includes a change adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, the corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When a change is detected in the agreement data and it is confirmed that the order data meets the requirement change condition, a corresponding change adjustment countersignature instruction is generated and then sent to the countersignature terminal, so that the countersignature terminal responds to the change adjustment countersignature instruction and countersigns the changed agreement data; When it is detected that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data, the order data is regenerated based on the changed agreement data.

8. A system for processing customized clothing orders, characterized in that: include: processing equipment and at least one countersigning terminal; The processing device is configured to obtain agreement data of a target order, wherein the agreement data carries an agreement countersigning instruction initiated from any countersigning terminal; The countersignature terminal is used to respond to the agreement countersignature instruction to countersign and then generate an agreement countersignature result; The processing device is configured to generate corresponding order data based on the agreement data when detecting that the agreement countersigning result indicates that the electronic agreement corresponding to the target order has been reached; When it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data, including: based on the order data, determining the production scheduling data corresponding to when the production efficiency data in the clothing production process reaches a preset high-efficiency condition; wherein, determining the associated factors of the target order in the production process, the associated factors include the consumption of any clothing material and the scheduling utilization rate of any processing equipment; based on the order data, constructing a production efficiency model of the target order, the production efficiency model is used to indicate the production efficiency data of the target order under the influence of the associated factors; constructing a scheduling model based on the production efficiency model of at least one target order currently to be processed; iteratively solving the scheduling model, and screening out the corresponding production efficiency data when the production efficiency data of the target order reaches the high-efficiency condition. Production scheduling data, wherein the high-efficiency condition includes at least one of minimizing production time and maximizing processing equipment utilization, and the production scheduling data is used to indicate the processing input quantity of any garment material on any processing equipment; wherein the production efficiency model is constructed by the following steps, including: obtaining the call rate, equipment processing efficiency data, and material processing efficiency data of the processing equipment, the equipment processing efficiency data indicating the processing time required for the processing equipment to process a specified garment material per unit mass, and the material processing efficiency data indicating the mass of any garment material processed per unit time; determining the equipment processing efficiency model of the target order based on the equipment processing efficiency data of any garment material and the processing equipment used to process the garment material; determining the material processing efficiency model of the target order based on the call rate, material processing efficiency data, and material requirement data of the processing equipment; and constructing a production efficiency model for the target order based on the equipment processing efficiency model and / or the material processing efficiency model; The countersignature terminal is used to respond to the adjustment countersignature instruction to perform countersignature and then generate an adjustment countersignature result; The processing device is used to regenerate the order data of the target order based on the obtained adjustment and counter-signing results, and to perform production according to the updated order data.

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