Textile and clothing customization operation platform system based on C2M model with multi-party cooperation

Abstract

The present invention relates to the field of clothing customization operation technology. The present invention relates to a textile and clothing customization operation platform system based on a C2M model of multi-party cooperation. It includes an operation platform establishment unit, a participant classification unit, a dynamic form sending unit, a production monitoring unit and a clothing detection unit; the operation platform establishment unit is used to establish an operation platform and send it to participants of clothing customization multi-party transactions for registration and joining; the participant classification unit is used to classify the joined participants according to the operation type, and grant the participants authority in the operation platform according to the classification results; by establishing an operation platform, the problem of multiple subjects participating in the personalized customization transaction of clothing and textiles at the same time is solved, and each transaction participant realizes the collaborative operation and real-time communication of multiple transaction parties through the effective connection of the platform, and at the same time, the quality of the clothing is tested to avoid the outflow of inferior products and affect the sales reputation of the factory.

Description

Technical Field

[0001] The present invention relates to the technical field of clothing customization operation, and in particular to a textile and clothing customization operation platform system based on a C2M model of multi-party cooperation. Background Art

[0002] Generally, the clothing customization operation platform system based on the C2M model only solves a single, point-to-point management problem, that is, between customers and manufacturers (merchants) (C2M). When the factory production requires cooperation from multiple parties and cannot complete the production of clothing alone, for example, the raw materials required for the order exceed the factory inventory and need to be purchased from a third party, or the order involves other participants, the system cannot be completed automatically, and needs to be transferred to other systems or manual intervention. When the factory communicates with other participants, information time difference is caused. Due to the large volume of factory production orders, other participants need to produce in sequence, which makes it impossible to arrange in the first time and predict the completion time of clothing production, resulting in the production cycle of clothing may be greater than the user's time requirement. In view of this, a textile and clothing customization operation platform system based on the C2M model of multi-party cooperation is proposed. Summary of the invention

[0003] The purpose of the present invention is to provide a textile and clothing customization operation platform system based on the C2M model of multi-party cooperation to solve the problems raised in the above background technology.

[0004] To achieve the above purpose, a textile and clothing customization operation platform system based on the C2M model of multi-party cooperation is provided, including an operation platform establishment unit, a participant classification unit, a dynamic form sending unit, a production monitoring unit and a clothing testing unit;

[0005] The operation platform establishment unit is used to establish an operation platform and send it to participants of clothing customization multi-party transactions for registration and joining;

[0006] The participant classification unit is used to classify the joined participants according to the operation type, and grant permissions to the participants in the operation platform according to the classification results;

[0007] The dynamic form sending unit is used to enter the customer's order information into the operation platform, extract the demand according to the entered order information, generate a dynamic form according to the extracted demand information, and send the dynamic form to the operation platform for participants to view and produce;

[0008] The production monitoring unit is used to set the standard completion time according to the dynamic form generated by the dynamic form sending unit, monitor the production progress of the participants, predict the order completion time according to the monitoring results, compare the predicted completion time with the standard completion time, and send an expedited reminder signal to the participants if the predicted completion time in the comparison result is greater than the standard completion time;

[0009] The clothing detection unit is used to obtain clothing data uploaded by participants in the dynamic form, set production qualification standards according to the dynamic form information, and perform difference detection between the clothing data and the production qualification standards. If the detection result is qualified, the clothing produced by the participant is sent to the customer.

[0010] As a further improvement of the present technical solution, the operation platform establishment unit uses an open interface and a document-based database to record data to ensure that all original data is retained, while using unstructured data to be compatible with the platform docking requirements of all parties involved, thereby establishing an operation platform.

[0011] As a further improvement of the present technical solution, the operation platform establishment unit collects information of participants cooperating with the enterprise, and enables the participants to register accounts on the operation platform and upload information. At the same time, the operation platform uses image rules to extract key data required by the operation platform as input for resource matching and matchmaking algorithms.

[0012] As a further improvement of the technical solution, the participant classification unit includes a type classification module and a permission allocation module;

[0013] The type classification module is used to establish operation types according to the steps required to complete the production and sales of clothing, including buyers, middlemen, manufacturers, suppliers, logistics providers, and financial service providers;

[0014] The authority allocation module is used to extract the information uploaded by the participants on the operation platform, obtain the operation services of the corresponding participants based on the information, classify the participant's operation services into the operation type established by the type classification module, and grant the participant the authority corresponding to the operation type in the operation platform.

[0015] As a further improvement of the present technical solution, the dynamic form sending unit enters the customer's order information into the operation platform, extracts the demand based on the entered order information, obtains the customer's quality requirements for customized clothing, and then manages it through a dynamic form, dynamically generates it according to the different quality requirements of each order customer, and obtains an exclusive dynamic form belonging to the customer.

[0016] As a further improvement of the technical solution, the dynamic form sending unit includes a participant matching module;

[0017] The participant matching module is used to perform similarity matching based on the quality requirements in the dynamic form and the participant's information, arrange a participant with the highest similarity to the quality requirements in each production link of the clothing, and display the dynamic form to the successfully matched participants, so that the participants can produce clothing according to the dynamic form information.

[0018] As a further improvement of the technical solution, the production monitoring unit includes a time setting module and a production monitoring module;

[0019] The time setting module is used to predict the time required for the garment to be produced and sent to the customer based on the dynamic form information, and set the predicted time as the standard completion time;

[0020] The production monitoring module is used to monitor the completion progress data of clothing production by all participants, and combine the completion progress data of all participants in the dynamic form to predict the completion time of the order, compare the predicted completion time with the standard completion time, and if the predicted completion time in the comparison result is greater than the standard completion time, send a reminder expedited signal to the participant to enable the participant to improve the clothing production efficiency, and if the predicted completion time in the comparison result is equal to or less than the standard completion time, continue monitoring.

[0021] As a further improvement of the technical solution, the clothing detection unit includes a qualified standard setting module and a difference detection module;

[0022] The module for setting the qualified standards is used to set the production qualified standards according to the customer's requirements for clothing in the dynamic form;

[0023] The difference detection module is used to detect the difference between the quality of the clothes produced by the participants and the production qualified standards. If the quality of the clothes meets the data requirements of the production qualified standards, the clothes are marked as qualified and shipped to the customers. If the quality of the clothes does not meet the data requirements of the production qualified standards, the clothes are marked as unqualified and feedback is given to the participants to enable them to re-produce.

[0024] As a further improvement of the present technical solution, the clothing inspection unit also includes a participant supervision module, which is used to supervise the inspection process of the clothing by the difference detection module. When the clothing is marked as unqualified, the participant who caused the quality problem is also marked. When the participant is marked more than three times in total, a reminder message is sent to the operation platform manager, prompting the manager to replace the participant.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] In the textile and clothing customization operation platform system based on the C2M model of multi-party cooperation, the problem of multiple subjects participating simultaneously in the personalized customization transactions of clothing and textiles is solved by establishing an operation platform. Through the effective connection of the platform, the transaction participants can realize the collaborative operation and real-time communication of multiple parties in the transaction. At the same time, the quality of clothing is tested to avoid the outflow of inferior products and affect the factory's sales reputation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is the overall structural principle diagram of the present invention.

[0028] The meaning of each number in the figure is:

[0029] 10. Operation platform establishment unit; 20. Participant classification unit; 30. Dynamic form sending unit; 40. Production monitoring unit; 50. Clothing testing unit. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0031] Example 1

[0032] See also Figure 1 As shown, the purpose of this embodiment is to provide a textile and clothing customization operation platform system based on the C2M model of multi-party cooperation, including an operation platform establishment unit 10, a participant classification unit 20, a dynamic form sending unit 30, a production monitoring unit 40 and a clothing detection unit 50;

[0033] The operation platform establishment unit 10 is used to establish an operation platform;

[0034] The operation platform establishment unit 10 uses an open interface and a document-based database to record data, ensuring that all original data is retained, and uses unstructured data to be compatible with the platform docking requirements of all parties involved, thereby establishing an operation platform. The steps are as follows:

[0035] Determine the document database: Select a suitable document database system, such as MongoDB, CouchDB, etc., and install and configure it;

[0036] Design data model: Design a suitable data model according to business needs. Determine the data fields and data relationships that need to be recorded, and create corresponding database collections or tables;

[0037] Create interfaces: connect the operation platform with the platforms of all participants through open interfaces. The interfaces can be implemented using Web services, APIs or other communication protocols;

[0038] Define data recording interface: define the data recording interface for each participant platform, including the URL for receiving data, request method, data format, etc. Ensure that the interface connection meets the requirements for data integrity and accuracy;

[0039] Receiving and processing data: Establishing corresponding data receiving and processing logic on the operation platform, receiving data from each participant’s platform, and verifying, processing and storing the data;

[0040] Use document-based databases to record data: Based on the received data, use appropriate library functions or APIs to record the data into a document-based database. Ensure the integrity and consistency of each data record;

[0041] Processing unstructured data: Appropriate technologies and tools can be used to process and transform unstructured data, such as using natural language processing technology to analyze text and extract key information;

[0042] Data backup and archiving: Perform data backup and archiving regularly to ensure that all original data is retained. You can use database backup tools or cloud backup services.

[0043] And send it to the participants of the clothing customization multi-party transaction to register and join;

[0044] The operation platform establishment unit 10 collects information about participants cooperating with the enterprise, and enables the participants to register accounts on the operation platform and upload information. At the same time, the operation platform uses image rules to extract key data required by the operation platform as input for resource matching and matching algorithms. For a certain order, it is necessary to split it into many sub-orders to inquire with raw material suppliers and factories to understand their supply capacity and production line plans. In the past, this part of the work was done manually, and only a small number of raw material suppliers and factories could be connected. The algorithm will simulate the manual arrangement of resources and match the best arrangement based on the user's preferences for time priority, price priority, etc. The steps are as follows:

[0045] Establish the participant information collection process: determine the participant information that needs to be collected, such as basic personal information, company information, project requirements, skills and expertise, etc. Design the corresponding form or interface for participants to fill in and submit information;

[0046] Function of creating participant registration account: the function of creating a registration account on the operation platform, including user name, password, email address and other information. Ensure the security and manageability of the account;

[0047] Provide the function of uploading documents: After the participants register their accounts, the function of uploading documents is provided, allowing the participants to upload necessary documents such as identity cards, corporate documents, project requirements documents, etc. to the operation platform;

[0048] Design image rules and key data extraction logic: Design image rules and key data extraction logic according to the needs of resource matching and matching algorithms. These rules and logic can be manually defined or automatically processed using natural language processing and machine learning technologies;

[0049] Extract key data: Extract necessary key data from the materials submitted by the participants according to the mapping rules and key data extraction logic. This data can be the participant's skill tags, project requirement descriptions, industry, etc.

[0050] Storing and managing data: storing the extracted key data in a database or other data storage system and ensuring the security and privacy management of the data;

[0051] Perform resource matching and matching algorithms: Use the extracted key data as input to the resource matching and matching algorithms to perform resource matching and matching operations. Use algorithms to screen and match the most suitable participants and companies for cooperation.

[0052] The participant classification unit 20 is used to classify the joined participants according to the operation type, and grant the participants permissions in the operation platform according to the classification results;

[0053] The participant classification unit 20 includes a type classification module and a permission allocation module;

[0054] The type classification module is used to establish operation types according to the steps required to complete the production and sales of clothing, including buyers, middlemen, manufacturers, suppliers, logistics providers, and financial service providers;

[0055] The authority allocation module is used to extract the data uploaded by the participants on the operation platform, obtain the operation services of the corresponding participants based on the data, classify the participant's operation services into the operation type established by the type classification module, and grant the participant the authority corresponding to the operation type in the operation platform. The steps are as follows:

[0056] Design the information collection process for participants: Design the corresponding information collection process for each participant type. Determine the information that needs to be collected, such as personal / company name, contact information, business scope, qualification certificate, etc.;

[0057] Create an operation platform registration account and data upload function: create a registration account for participants on the operation platform, provide data upload function, and allow participants to upload necessary data files to ensure the security and manageability of the account;

[0058] Extracting participant information: Based on the key data required for each participant type, use appropriate techniques and tools to extract necessary information from the materials submitted by the participants. Technologies such as natural language processing and image recognition can be used for automated processing;

[0059] Allocate operational services and classify operational types: According to the participant's profile information, assign corresponding operational services to them and classify them into corresponding operational types. Determine specific operational services based on the participant's business model and the role they are based on;

[0060] Set permissions and access control: Set corresponding permissions and access control for participants in each operation type. Ensure that only participants with relevant permissions can perform corresponding operations and access relevant resources;

[0061] Provide operation type permissions within the operation platform: Set corresponding operation type permissions for each participant on the operation platform to ensure that participants can only operate and access within the operation type to which they belong.

[0062] The dynamic form sending unit 30 is used to input the customer's order information into the operation platform, extract the demand according to the input order information, and generate a dynamic form according to the extracted demand information;

[0063] The dynamic form sending unit 30 enters the customer's order information into the operation platform, extracts the demand according to the entered order information, obtains the customer's quality requirements for clothing customization, and then manages it through a dynamic form, dynamically generates according to the different quality requirements of each order customer, and obtains a dynamic form exclusive to the customer. The steps are as follows:

[0064] Enter order information: On the order management page of the operation platform, fill in and enter the customer's order information, including order number, customer name, contact information, order date, etc.;

[0065] Demand extraction: Extract the customer's quality requirements for clothing customization based on the entered order information. This may include requirements for fabric texture, tailoring style, detail processing, clothing function, etc.;

[0066] Dynamic form design: Design dynamic forms to manage customer demand details according to different quality requirements. You can use the form design function of the operation platform to create dynamic form templates that meet different needs;

[0067] Dynamic form generation: Dynamically generate the corresponding dynamic form according to the quality requirements of the customer's order. Dynamically fill in the form fields and options according to the customer's requirements for fabrics, tailoring, details, functions, etc.;

[0068] Provide customers with exclusive dynamic forms: Provide customers with the generated exclusive dynamic forms, usually by sending the form link to customers via email or the message notification system of the operation platform;

[0069] Customers fill in dynamic forms: Customers click on the dynamic form link provided to enter the form page and fill in the corresponding demand details. Customers can choose appropriate options or fill in relevant instructions based on their quality requirements;

[0070] Dynamic form management: The operation platform can save the dynamic form data filled in by customers and associate it with order information. This makes it convenient for enterprises to customize according to customer needs and provide customers with clothing customization services that meet their quality requirements.

[0071] The dynamic form is sent to the operation platform for participants to view and produce;

[0072] The dynamic form sending unit 30 includes a participant matching module;

[0073] The participant matching module is used to perform similarity matching based on the quality requirements in the dynamic form and the participant's information. A participant with the highest similarity to the quality requirements is arranged in each production link of the clothing, and the dynamic form is displayed to the successfully matched participants, so that the participants can produce clothing according to the dynamic form information. The steps are as follows:

[0074] Extract quality requirements in dynamic forms: Extract fields and options related to quality requirements based on the dynamic form information filled in by customers;

[0075] Similarity matching based on participant information: The dynamic form information filled in by the customer is matched with the participant information. Similarity algorithms such as cosine similarity and Jaccard similarity can be used to calculate the matching degree of quality requirements;

[0076] Select the participant with the highest similarity: Based on the similarity matching results, select the participant with the highest similarity to the quality requirements. You can sort and select the highest participant based on the calculated similarity value;

[0077] Arrange participants in various production links: Assign the successfully matched participants to various production links of clothing, such as fabric procurement, tailoring, detail processing, etc. Ensure that each link has a participant who is most similar to the quality requirements;

[0078] Display successfully matched participants: Display the information of successfully matched participants to customers. The name, qualifications, evaluation and other relevant information of the participants can be displayed on the operation platform to increase customers' understanding and selection of participants;

[0079] Participants produce garments according to the dynamic form information: Participants produce garments according to the quality requirements in the dynamic form. According to the assigned production links and quality requirements, ensure that the produced garments meet the customer's requirements.

[0080] The production monitoring unit 40 is used to set the standard completion time according to the dynamic form generated by the dynamic form sending unit 30, monitor the production progress of the participants, predict the order completion time according to the monitoring results, compare the predicted completion time with the standard completion time, and send an expedited reminder signal to the participants if the predicted completion time in the comparison result is greater than the standard completion time;

[0081] The production monitoring unit 40 includes a time setting module and a production monitoring module;

[0082] The time setting module is used to predict the time required for the garment to be produced and sent to the customer based on the dynamic form information, and set the predicted time as the standard completion time; the steps are as follows:

[0083] Collect historical data: Collect relevant data on past clothing production and distribution, including order completion time, production time, logistics delivery time, etc.;

[0084] Analyze historical data: Use regression analysis to analyze the collected historical data and explore the impact of different factors on clothing production and delivery time;

[0085] Build a predictive model: Based on the analysis results and historical data, build a predictive model to predict the time required for clothing to be produced and shipped to customers. You can use machine learning algorithms to build the model;

[0086] Input dynamic form information: The dynamic form information filled in by the customer is used as the input of the model, including quality requirements, clothing specifications and other information;

[0087] Make time predictions: Use the prediction model to predict the production and delivery time of clothing. Based on the dynamic form information as input, the model will output the estimated completion time;

[0088] Set standard completion time: Set the predicted completion time as the standard completion time. This time will be used as the time target for the entire production process.

[0089] The production monitoring module is used to monitor the completion progress data of clothing production by all participants, and combine the completion progress data of all participants in the dynamic form to predict the completion time of the order, and compare the predicted completion time with the completion standard time. If the predicted completion time in the comparison result is greater than the completion standard time, a reminder expedited signal is sent to the participant to improve the clothing production efficiency. If the predicted completion time in the comparison result is equal to or less than the completion standard time, the monitoring is continued. The steps are as follows:

[0090] Monitor the completion progress data of all parties involved: Establish a monitoring system on the operation platform to collect the completion progress data of clothing production by all parties involved, including the progress of each production link, the time consumed, etc.;

[0091] Combine the completion progress data of participants: Combine the completion progress data of all participants in the dynamic form to calculate the overall completion progress and required time;

[0092] Predicting order completion time: Based on the participants’ completion progress data and historical data, a prediction model is used to predict the order completion time. The prediction can use a regression model, a time series model, or other prediction algorithms.

[0093] Compare the predicted completion time with the standard completion time: Compare the predicted order completion time with the standard completion time;

[0094] Sending expedited signal reminders: If the predicted completion time is longer than the standard completion time, an expedited signal reminder will be sent to the participants to encourage them to improve their productivity;

[0095] Continue monitoring: If the predicted completion time is equal to or less than the completion standard time, continue to monitor the progress of the participants to ensure that the order is completed on time. The expression is as follows:

[0096] Compare the predicted completion time with the standard completion time:

[0097] When the predicted completion time is greater than the standard completion time, an expedited signal is sent to remind participants to speed up production;

[0098] If the predicted completion time is less than or equal to the standard completion time, continue monitoring;

[0099] The clothing detection unit 50 is used to obtain the clothing data uploaded by the participant in the dynamic form, set the production qualification standard according to the dynamic form information, and perform difference detection between the clothing data and the production qualification standard. If the detection result is qualified, the clothing produced by the participant is sent to the customer.

[0100] The clothing detection unit 50 includes a qualified standard setting module and a difference detection module;

[0101] The module for setting qualified standards is used to set production qualified standards according to the customer's requirements for clothing in the dynamic form;

[0102] The difference detection module is used to detect the difference between the quality of the clothing produced by the participants and the production qualification standards. If the clothing quality meets the data requirements of the production qualification standards, the clothing is marked as qualified and shipped to the customer. If the clothing quality does not meet the data requirements of the production qualification standards, the clothing is marked as unqualified and feedback is given to the participants to make them re-produce. The steps are as follows;

[0103] Determine production qualification standards based on customer requirements for clothing, including requirements for fabric quality, cutting accuracy, sewing technology, etc.;

[0104] Conduct quality inspection on the clothing produced by the participants and collect relevant quality data. The quality characteristic data of the clothing can be obtained by visual inspection, physical testing, etc.;

[0105] Detect differences between the clothing quality data produced by participants and the production qualification standards. Statistical methods and rule engines can be used for judgment and evaluation;

[0106] If the quality of the garment meets the data requirements of the production qualification standard, the garment is marked as qualified, and the subsequent delivery process is carried out to deliver the garment to the customer;

[0107] If the quality of the garment does not meet the data requirements of the production qualification standards, the garment will be marked as unqualified, feedback will be provided to the participant, and he will be required to re-produce it.

[0108] Since in the clothing customization process, once the clothing has quality problems and needs to be re-produced, the time consumed will exceed the time required by the customer, causing unhappy shopping for the customer and leading to customer loss, the clothing detection unit 50 also includes a participant supervision module, which is used to supervise the detection process of the clothing by the difference detection module. When the clothing is marked as unqualified, the participant who caused the quality problem is also marked. When the participant is marked more than three times in total, a reminder message is sent to the operation platform manager to prompt the manager to replace the participant. The steps are as follows:

[0109] Establishing a participant supervision module: Establishing a participant supervision module in the operation platform to supervise the detection process of clothing by the difference detection module;

[0110] Set rules for participant marking: determine the rules and standards for participants to be marked as causing quality problems, such as marking the corresponding participants when clothing is marked as unqualified;

[0111] Marking of quality issues: When the difference detection module marks the garment as unqualified, the participants who caused the quality issue are also marked;

[0112] Cumulative marking monitoring: monitor the number of times participants are marked as having quality issues, and record the number of times each participant is marked;

[0113] Reminder message sending: When the number of markings of a participant exceeds three times, a reminder message will be sent to the operation platform manager, prompting the manager to replace the participant or take other necessary measures.

[0114] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A textile and clothing customization operation platform system based on the C2M model of multi-party cooperation, characterized by: It includes an operation platform establishment unit (10), a participant classification unit (20), a dynamic form sending unit (30), a production monitoring unit (40) and a clothing detection unit (50); The operation platform establishment unit (10) is used to establish an operation platform and send it to participants of clothing customization multi-party transactions for registration and joining; The participant classification unit (20) is used to classify the participants according to the operation type, and grant the participants permissions in the operation platform according to the classification results; The dynamic form sending unit (30) is used to input the customer's order information into the operation platform, extract the demand according to the input order information, generate a dynamic form according to the extracted demand information, and send the dynamic form to the operation platform for participants to view and produce; The production monitoring unit (40) is used to set the standard completion time according to the dynamic form generated by the dynamic form sending unit (30), monitor the production progress of the participants, predict the order completion time according to the monitoring results, compare the predicted completion time with the standard completion time, and send an expedited reminder signal to the participants if the predicted completion time in the comparison result is greater than the standard completion time; The clothing detection unit (50) is used to obtain clothing data uploaded by the participant in the dynamic form, set production qualification standards according to the dynamic form information, and perform difference detection between the clothing data and the production qualification standards. If the detection result is qualified, the clothing produced by the participant is sent to the customer; The operation platform establishment unit (10) collects information of participants cooperating with the enterprise and enables the participants to register accounts on the operation platform and upload information. At the same time, the operation platform uses image rules to extract key data required by the operation platform as input for resource matching and matchmaking algorithms; The participant classification unit (20) comprises a type classification module and a permission allocation module; The type classification module is used to establish operation types according to the steps required to complete the production and sales of clothing, and the operation types include buyers, middlemen, manufacturers, suppliers, logistics providers and financial service providers; The authority allocation module is used to extract the data uploaded by the participant on the operation platform, obtain the operation service of the corresponding participant according to the data, classify the participant into the operation type established by the type classification module according to the operation service of the participant, and grant the participant the authority belonging to the operation type in the operation platform; The production monitoring unit (40) comprises a time setting module and a production monitoring module; The time setting module is used to predict the time required for the garment to be produced and sent to the customer based on the dynamic form information, and set the predicted time as the standard completion time; the steps are as follows: Collect historical data: Collect relevant data on past clothing production and distribution, including order completion time, production time, and logistics delivery time; Analyze historical data: Use regression analysis to analyze the collected historical data and explore the impact of different factors on clothing production and delivery time; Build a forecasting model: Based on the analysis results and historical data, build a forecasting model to predict the time required for garment production to be completed and sent to customers; Input dynamic form information: The dynamic form information filled in by the customer is used as the input of the prediction model, including quality requirements and clothing specifications; Make time predictions: Use prediction models to predict the production and delivery time of clothing; Based on the dynamic form information as input, the prediction model outputs the estimated completion time; Set standard completion time: Set the predicted completion time as the standard completion time; this standard completion time will be used as the time target for the entire production process; The production monitoring module is used to monitor the completion progress data of clothing production by all participants, and combine the completion progress data of all participants in the dynamic form to predict the completion time of the order, compare the predicted completion time with the completion standard time, and if the predicted completion time in the comparison result is greater than the completion standard time, send a reminder expedited signal to the participant to improve the clothing production efficiency of the participant, and if the predicted completion time in the comparison result is equal to or less than the completion standard time, continue monitoring; the steps are as follows: Monitor the completion progress data of all parties involved: Establish a monitoring system on the operation platform to collect the completion progress data of clothing production from all parties involved, including the progress of each production link and the time consumed; Combine the completion progress data of participants: Combine the completion progress data of all participants in the dynamic form to calculate the overall completion progress and required time; Predicting order completion time: Based on the participants’ completion progress data and historical data, use a prediction model to predict the order completion time. The prediction uses a regression model or a time series model. Compare the predicted completion time with the standard completion time: Compare the predicted order completion time with the standard completion time; Sending expedited signal reminders: If the predicted completion time is longer than the standard completion time, an expedited signal reminder will be sent to the participants to encourage them to improve their productivity; Continue monitoring: If the predicted completion time is equal to or less than the completion standard time, continue to monitor the progress of the participants to ensure that the order is completed on time; the expression is as follows: Compare the predicted completion time with the standard completion time: When the predicted completion time is greater than the standard completion time, an expedited signal is sent to remind participants to speed up production; If the predicted completion time is less than or equal to the standard completion time, continue monitoring; The operation platform establishment unit (10) records data using a document-based database through an open interface to ensure that all original data is retained, and uses unstructured data to be compatible with the platform docking requirements of all parties involved, thereby establishing an operation platform; the steps are as follows: Determine the document-based database: Select a document-based database system, and install and configure it; Design data model: Design data model according to business needs; determine the data fields and data relationships that need to be recorded, and create corresponding database collections or tables; Create interfaces: connect the operation platform with the platforms of all participants through open interfaces; Define data recording interface: define the data recording interface for each participant platform, including the URL for receiving data, request method, and data format; ensure that the interface connection meets the requirements for data integrity and accuracy; Receiving and processing data: Establishing corresponding data receiving and processing logic on the operation platform, receiving data from each participant’s platform, and verifying, processing and storing the data; Use document-based databases to record data: Based on the received data, use library functions or APIs to record the data into a document-based database; ensure the integrity and consistency of each data record; Processing unstructured data: For unstructured data, natural language processing technology is used to analyze the text and extract key information; Data backup and archiving: Data backup and archiving are performed regularly to ensure that all original data is retained; Use a database backup tool or cloud backup service; And send it to the participants of the clothing customization multi-party transaction to register and join; The dynamic form sending unit (30) enters the customer's order information into the operation platform, extracts the demand according to the entered order information, obtains the customer's quality demand for clothing customization, and then manages it through a dynamic form, dynamically generates according to the different quality demands of each order customer, and obtains a dynamic form exclusive to the customer; The dynamic form sending unit (30) comprises a participant matching module; The participant matching module is used to perform similarity matching based on the quality requirements in the dynamic form and the data of the participants, arrange a participant with the highest similarity to the quality requirements in each production link of the clothing, and display the dynamic form to the successfully matched participants, so that the participants can produce the clothing according to the dynamic form information; The clothing detection unit (50) comprises a qualification standard setting module and a difference detection module; The module for setting the qualified standards is used to set the production qualified standards according to the customer's requirements for clothing in the dynamic form; The difference detection module is used to detect the difference between the quality of the clothes produced by the participants and the production qualified standards. If the quality of the clothes meets the data requirements of the production qualified standards, the clothes are marked as qualified and shipped to the customers. If the quality of the clothes does not meet the data requirements of the production qualified standards, the clothes are marked as unqualified and feedback is given to the participants to make them re-produce. The steps are as follows; Determine production qualification standards based on customer requirements for clothing, including fabric quality, cutting accuracy, and sewing process requirements; Conduct quality inspection on the garments produced by the participants and collect relevant quality data; obtain the quality data of the garments through visual inspection or physical testing; Detect differences between the clothing quality data produced by participants and the production qualification standards; use statistical methods and rule engines to make judgments and evaluations; If the quality of the garment meets the data requirements of the production qualification standard, the garment is marked as qualified, and the subsequent delivery process is carried out to deliver the garment to the customer; If the quality of the garment does not meet the data requirements of the production qualification standard, the garment will be marked as unqualified, and feedback will be provided to the participant, requiring them to re-produce; The clothing inspection unit (50) further comprises a participant supervision module, the participant supervision module being used to supervise the inspection process of the clothing by the difference detection module. When the clothing is marked as unqualified, the participant causing the quality problem is also marked. When the participant is marked more than three times in total, a reminder message is sent to the operation platform manager, prompting the manager to replace the participant. The steps are as follows: Establishing a participant supervision module: Establishing a participant supervision module in the operation platform to supervise the detection process of clothing by the difference detection module; Setting rules for participant marking: determining the rules and criteria for participants to be marked as causing quality problems, wherein when a garment is marked as unqualified, the corresponding participant is marked; Marking of quality issues: When the difference detection module marks the garment as unqualified, the participant who caused the quality issue is also marked. Cumulative marking monitoring: Monitor the number of times a participant is marked as causing quality issues, and record the number of times each participant is marked; Reminder message sending: When the number of markings of a participant exceeds three times, a reminder message will be sent to the operation platform manager to prompt the manager to replace the participant.

Images