An intelligent distribution system and method for a clothing production line

Abstract

This invention relates to the field of production line technology, specifically to an intelligent distribution system for garment production lines. The intelligent distribution system includes a buffer station for sorting garment information, a merging station for distributing the consolidated garments to workstations, and a maintenance station for monitoring workstations to ensure the distribution tasks are completed. The buffer station, used for consolidation and initial classification, includes an intelligent sorting module and a document merging module. This invention, through the cooperation of the buffer station and the merging station, can sort and classify different styles of garments, facilitating the processing of disorganized garment data, adapting to the distribution methods of the merging station, and combining garment data with production line conditions to formulate production plans. By integrating RFID technology, sensors, data analysis, and automated control, an intelligent hanging distribution system can be created to improve the efficiency and flexibility of garment production lines.

Description

Technical Field

[0001] This invention relates to the field of garment production line technology, and in particular to an intelligent distribution system and method for garment production line hanging systems. Background Technology

[0002] With the expansion and diversification of the apparel market, consumers are increasingly pursuing trends, fashion, and individuality in their clothing. Many apparel companies are following market demands by developing production trends towards greater variety, smaller batches, shorter production cycles, and higher quality. This presents significant challenges for apparel companies. The hanging system on the apparel production line enables the production of multiple varieties of apparel in small batches with short lead times, while single-piece flow can effectively control the production cycle. For each order with multiple processes, the system automatically collects data to calculate the SAM value of each process and intelligently allocates the stations in a single-process multi-station configuration through the main control software.

[0003] The current clothing styles are diverse and complex, making it difficult to accurately allocate them to the hanging production line. Data matching is challenging, which not only affects sorting speed and labor costs but also causes the production line to wait, wasting production resources. Furthermore, the production line's reliability is poor, data is not consistent, and malfunctions can easily interfere with each other, affecting the overall state. Troubleshooting is slow, and maintenance is difficult.

[0004] Therefore, an intelligent distribution system and method for hanging garments on a production line are proposed. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent allocation system and method for hanging garments on a production line, so as to solve the problems of poor data matching and difficulty in troubleshooting mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent distribution system for a garment production line, the intelligent distribution system including a buffer station for sorting garment information, a merging station for distributing the integrated garments to workstations, and a maintenance station for monitoring workstations to ensure the distribution tasks are completed. The buffer station is used for integration and preliminary classification. The buffer station includes an intelligent sorting module and a document merging module. The intelligent sorting module identifies different garment tasks through RFID tags and transmits the information to the electrically connected document merging module. The document merging module sorts and classifies different garments.

[0007] The merging station is used for accurate redistribution of garments. The merging station includes a data acquisition module, an intelligent allocation module, and an automatic execution module. The data acquisition module collects information from several garments and combines it with the production line to form the most reasonable processing plan. The data acquisition module combines the processing plan with the actual situation and transmits the information to the electrically connected intelligent allocation module. The automatic execution module selects the allocation tool based on the information generated by the intelligent allocation module and then executes the allocation to distribute the garments to several workstations.

[0008] The maintenance station monitors the status of each production stage. It includes a sensor monitoring module, a test module, and an alarm module. The sensor monitoring module monitors the entire production line and transmits the monitoring data to the electrically connected test module. The test module verifies the data from the sensor monitoring module and develops solutions. The alarm module notifies and reports faults based on the verification information from the test module.

[0009] Preferably, the intelligent sorting module also includes a feature extraction module, an optimization and correction module, and a monitoring and sorting module. The feature extraction module extracts key features of the garment by using data obtained from RFID tags through visual recognition or sensor detection. The optimization and correction module continuously optimizes the sorting process based on data records and performance reports. The monitoring and sorting module monitors the sorting process and works with the optimization and correction module to perform real-time corrections to correct misclassifications.

[0010] Preferably, the order merging module also includes a decision and classification module, a sorting operation module, and a data recording module. The decision and classification module uses computer algorithms or machine learning models to classify items based on extracted features. The sorting operation module allocates garments to the appropriate positions on the correct production line based on the classification results. The data recording module records all sorting operations and related data.

[0011] Preferably, the data acquisition module also includes a style analysis module, a time analysis module, and a processing plan formulation module. The style analysis module analyzes and confirms the style of the garment based on the process database. The time analysis module formulates a standard time based on normal speed and correct methods, taking into account various relevant factors. The processing plan formulation module combines each independent process with the best production sequence and method.

[0012] Preferably, the intelligent allocation module also includes an automated allocation algorithm module, an optimized path planning module, and a dynamic adjustment module. The automated allocation algorithm module determines which hanging garments to allocate to the workstations, the optimized path planning module intelligently plans the path for the hanging garments, and the dynamic adjustment module can dynamically adjust the allocation strategy.

[0013] Preferably, the automatic execution module also includes a hanging selection module and a path selection module. The hanging selection module selects different types of hanging, and the path selection module selects a conveyor belt or track to move on the production line.

[0014] Preferably, the sensor monitoring module also includes a position monitoring module, a load monitoring module, and an inventory monitoring module. The position monitoring module monitors the position of the hanging garments in real time, the load monitoring module monitors the load of the production line in real time and provides feedback, and the inventory monitoring module monitors the material inventory status.

[0015] Preferably, the test module also includes an existing data analysis module, a test objective confirmation module, and a test method formulation module. The existing data analysis module records and analyzes existing data, the test objective confirmation module verifies whether each step in the production process is performed in accordance with the prescribed standards and specifications and identifies the problems that need to be solved, and the test method formulation module formulates various test methods.

[0016] Preferably, the alarm module also includes a display alarm module, an audio alarm module, and an internet remote alarm module. The display alarm module displays information about the fault, the audio alarm module emits a loud audible alarm, and the internet remote alarm module remotely monitors the device status and receives fault alarms via the internet.

[0017] A method for using an intelligent distribution system and method for hanging garments on a production line includes the following steps:

[0018] S1. Different styles of clothing with RFID tags are sent to the buffer station. The buffer station identifies the RFID tags of the clothing, extracts the key information of the clothing, sorts and classifies the clothing information and continuously corrects and optimizes it. Finally, the data is recorded and the clothing is sent to the merging station. The performance and efficiency of the sorting process are tracked and reported.

[0019] S2. The merging station combines the data recorded by garment identification with the actual situation of the garment production line to formulate a production plan. Then, based on the development of automated allocation algorithms and optimized path planning, it can automatically decide to allocate the hanging garments to the corresponding workstations based on real-time demand and the situation on the production line. Finally, it selects different forms of hanging and paths.

[0020] S3. Faults caused by the normal operation of the workstation are detected by various sensors in the maintenance station, mainly for accurate monitoring of clothing location, workstation load, and material inventory;

[0021] S4. The maintenance station will re-verify the monitoring results, then investigate the verification results, attempt to resolve the problem automatically, and if the problem cannot be resolved, provide reminders in various ways. The investigation results will also be provided for reference in the form of codes, etc.

[0022] The beneficial effects of this invention are:

[0023] This invention, through the cooperation of a buffer station and a merging station, can sort and classify different styles of clothing, facilitating the processing of messy clothing data and adapting to the distribution method of the merging station. It can also combine clothing data with the situation on the production line to formulate production plans. By combining RFID technology, sensors, data analysis, and automated control, an intelligent hanging distribution system can be created to improve the efficiency and flexibility of the clothing production line, reduce manual operation, reduce production time, and improve the overall efficiency of the production line. The system can select workstations, hanging methods, and paths in real time according to the plan.

[0024] 2. This invention, through the design of a maintenance station in conjunction with a merging station, accurately monitors information such as garment location, workstation load, and material inventory. When a fault occurs, it is detected and reported in a timely manner for dynamic adjustment, rapid optimization to avoid conflicts and reduce the impact on other workstations. After automatic verification and troubleshooting, faults can be automatically attempted for repair and recorded for future reference. If the problem cannot be resolved, multiple methods are used to remind and seek assistance. Furthermore, the troubleshooting results are provided to maintenance personnel in the form of codes, etc., to facilitate quick problem identification and save time in problem-solving. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is an overall external flowchart of an intelligent distribution system and method for hanging garment production lines according to an embodiment of the present invention;

[0027] Figure 2 This is an overall internal flowchart of an intelligent distribution system and method for hanging garment production lines according to an embodiment of the present invention;

[0028] Figure 3 This is a flowchart of a buffer station in an intelligent distribution system and method for hanging garment production lines, according to an embodiment of the present invention.

[0029] Figure 4 This is a flowchart of a merging station for an intelligent distribution system and method for hanging garment production lines, according to an embodiment of the present invention.

[0030] Figure 5 This is an optimized flowchart of the dynamic adjustment module of an intelligent allocation system and method for garment production line hanging according to an embodiment of the present invention;

[0031] Figure 6 This is a flowchart of a maintenance station for an intelligent distribution system and method for garment production line hanging, as described in an embodiment of the present invention.

[0032] The diagram is labeled as follows: 1. Buffer Station; 101. Intelligent Sorting Module; 1011. Feature Extraction Module; 1012. Optimization and Correction Module; 1013. Monitoring Sorting Module; 102. Order Merging Module; 1021. Decision and Classification Module; 1022. Sorting Operation Module; 1023. Data Recording Module; 2. Merging Station; 201. Data Acquisition Module; 2011. Style Analysis Module; 2012. Working Hour Analysis Module; 2013. Processing Plan Formulation Module; 202. Intelligent Allocation Module; 2021. Automated Allocation Algorithm Module; 2022. Optimized Path Planning Module; 2023. 1. Dynamic adjustment module; 203. Automatic execution module; 2031. Hanging selection module; 2032. Path selection module; 3. Maintenance station; 301. Sensor monitoring module; 3011. Position monitoring module; 3012. Load monitoring module; 3013. Inventory monitoring module; 302. Test module; 3021. Existing data analysis module; 3022. Test purpose confirmation module; 3023. Test method formulation module; 303. Alarm module; 3031. Display alarm module; 3032. Sound alarm module; 3033. Internet remote alarm module; 4. Clothing; 5. Workstation. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0034] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0035] Please see Figures 1 to 6This invention provides a technical solution: an intelligent allocation system for a garment production line. The intelligent allocation system includes a buffer station 1 for sorting garment information (4), a merging station 2 for allocating the integrated garments (4) to workstations (5), and a maintenance station 3 for monitoring workstations (5) to ensure allocation tasks. The buffer station 1 is used for integration and preliminary classification. It includes an intelligent sorting module 101 and a document merging module 102. The intelligent sorting module 101 identifies different garments (4) using RFID tags and transmits the information to the electrically connected document merging module 102. The document merging module 102 sorts and classifies different garments (4), allowing for sorting and classifying different styles of garments, facilitating data processing of disorganized garments, and adapting to the allocation method of the merging station. The merging station 2 is used for accurate redistribution of garments (4). It includes a data acquisition module 201, an intelligent allocation module 202, and an automatic execution module 203. The data acquisition module 201 collects information from several garments (4) and combines it with the production line to form the most reasonable processing plan. The data acquisition module 201 is used to combine the processing plan... The system analyzes the actual situation and transmits the information to the electrically connected intelligent distribution module 202. The automatic execution module 203 selects the distribution tool based on the information generated by the intelligent distribution module 202 and executes the distribution, distributing garments 4 to several workstations 5 and maintenance stations 3. The maintenance station 3 monitors the status of each production stage. The maintenance station 3 includes a sensor monitoring module 301, a test module 302, and an alarm module 303. The sensor monitoring module 301 monitors the entire production line and transmits the monitoring data to the electrically connected test module 302. The test module 302 verifies the data from the sensor monitoring module 301 and formulates solutions. The alarm module 303 notifies and reports faults based on the verification information from the test module 302, records faults, and seeks external assistance. By combining RFID technology, sensors, data analysis, and automated control, an intelligent hanging distribution system can be created to improve the efficiency and flexibility of the garment production line, reduce manual operation, reduce production time, and improve the overall efficiency of the production line. The system can select workstations, hanging methods, and paths in real time according to the plan.

[0036] like Figure 1 and Figure 2 as well as Figure 3The intelligent sorting module 101 also includes a feature extraction module 1011, an optimization and correction module 1012, and a monitoring and sorting module 1013. The feature extraction module 1011 extracts key features of the garment from data obtained from RFID tags through visual recognition or sensor detection, processing the image into digital data or converting sensor data into identifiable information. The optimization and correction module 1012 continuously optimizes based on data records and performance reports to improve sorting efficiency and accuracy. The monitoring and sorting module 1013 monitors the sorting process and works with the optimization and correction module 1012 to perform real-time corrections to rectify misclassification or other problems. The order merging module 102 also includes a decision and classification module 1021, a sorting operation module 1022, and a data processing module. The recording module 1023 and the decision-making and classification module 1021 use computer algorithms or machine learning models to classify items based on extracted features. The sorting operation module 1022 allocates the garments to the appropriate positions on the correct production line based on the classification results, which is accomplished by robotic arms, pneumatic devices, or conveyor lines. The data recording module 1023 records all sorting operations and related data to track and report the performance and efficiency of the sorting process. Garments of different styles with RFID tags are sent to the buffer station. The buffer station identifies the RFID tags of the garments, extracts key information of the garments, sorts and classifies the garment information, and continuously corrects and optimizes to reduce errors and omissions. Finally, the data is recorded and the garments are sent to the merging station to track and report the performance and efficiency of the sorting process.

[0037] like Figure 1 and Figure 4 as well as Figure 5As shown, the data acquisition module 201 also includes a style analysis module 2011, a time analysis module 2012, and a processing plan formulation module 2013. The style analysis module 2011 analyzes and confirms the style of garment 4 based on the process database. The process requirements and technical indicators of the style are a technical basis for guiding the production workshop and the quality control department. It is the technical foundation and guarantee for the industrialization and standardization of garment production. The time analysis module 2012 formulates a standard time based on normal speed and correct methods, taking into account various relevant factors. It also simplifies auxiliary actions, improves the main operations, and formulates a reasonable time based on normal speed, correct methods, and various relevant factors. To make production planning more precise and process pricing more reasonable, the processing scheme formulation module 2013 combines independent processes in the best production sequence and method, and rationally arranges the processes of each component in the production workshop. The composition of the process flow is the basis for the assembly line, aiming to minimize the process route, processing time, and costs during production. The intelligent allocation module 202 also includes an automated allocation algorithm module 2021, an optimized path planning module 2022, and a dynamic adjustment module 2023. The automated allocation algorithm module 2021 considers the current production demand, workstation status, and RFID tag information to determine which workstation to allocate the hanging garments to. The optimized path planning module 2022 intelligently plans the path of the hanging garments based on the garment flow on the production line to ensure the shortest movement distance and the best production efficiency. The dynamic adjustment module 2023 can dynamically adjust the allocation strategy to cope with the production line. Changes in the process, such as the addition of urgent orders or a malfunction at a workstation, can often effectively solve complex problems. However, it is important to properly define sub-problems and state transition equations, as well as to manage the solutions to sub-problems effectively. The automatic execution module 203 also includes a hanging selection module 2031 and a path selection module 2032. The hanging selection module 2031 selects different forms of hanging, including single-pole hanging, double-pole hanging, chain hanging, etc., which are suitable for different types of garments and production processes. The path selection module 2032 selects a conveyor belt or track to move on the production line. The conveyor belt and track can be designed as straight, curved, or complex paths to adapt to different production needs. The merging station combines the data recorded by garment identification with the actual situation of the garment production line to formulate a production plan. Then, based on the development of automated allocation algorithms and optimized path planning, it can automatically decide to allocate the hanging garments to the corresponding workstations based on real-time demand and the situation on the production line. Finally, it selects different forms of hanging and paths.

[0038] In further proposals, such as Figure 1 and Figure 2 as well as Figure 6As shown, the sensor monitoring module 301 also includes a position monitoring module 3011, a load monitoring module 3012, and an inventory monitoring module 3013. The position monitoring module 3011 monitors the position of the hanging garments in real time; the load monitoring module 3012 monitors the load of the production line in real time and provides feedback; the inventory monitoring module 3013 monitors the material inventory. The test module 302 also includes an existing data analysis module 3021, a test purpose confirmation module 3022, and a test method formulation module 3023. The existing data analysis module 3021 records and analyzes existing data and takes corrective measures when necessary. The test purpose confirmation module 3022 verifies whether each step in the production process is performed according to the prescribed standards and specifications and identifies the problems that need to be solved. The test method formulation module 3023 formulates various test methods, including physical tests, chemical tests, electronic tests, mechanical tests, etc., depending on the production process and the type of garment being manufactured. The alarm module 303 also includes... The system includes a display alarm module 3031, a sound alarm module 3032, and an internet remote alarm module 3033. The existing data analysis module 3021 displays fault information, such as error codes or fault descriptions. The sound alarm module 3032 emits a loud sound to attract attention when a fault occurs. The internet remote alarm module 3033 has remote monitoring capabilities, allowing it to remotely monitor equipment status and receive fault alarms via the internet. It accurately monitors information such as garment location, workstation load, and material inventory. When a fault occurs, it promptly detects and reports it, then dynamically adjusts and optimizes the system to avoid conflicts and reduce impact on other workstations. After automatic verification and troubleshooting, the system automatically attempts to repair and records the fault for future reference. If the problem cannot be resolved, it uses various methods to alert and seek assistance. The troubleshooting results are provided to maintenance personnel in the form of codes, facilitating quick problem identification and saving time.

[0039] A method for using an intelligent distribution system and method for hanging garments on a production line includes the following steps:

[0040] S1. Different styles of clothing with RFID tags are sent to the buffer station. The buffer station identifies the RFID tags of the clothing, extracts the key information of the clothing, sorts and classifies the clothing information and continuously corrects and optimizes it. Finally, the data is recorded and the clothing is sent to the merging station. The performance and efficiency of the sorting process are tracked and reported.

[0041] S2. The merging station combines the data recorded by garment identification with the actual situation of the garment production line to formulate a production plan. Then, based on the development of automated allocation algorithms and optimized path planning, it can automatically decide to allocate the hanging garments to the corresponding workstations based on real-time demand and the situation on the production line. Finally, it selects different forms of hanging and paths.

[0042] S3. Faults caused by the normal operation of the workstation are detected by various sensors in the maintenance station, mainly for accurate monitoring of clothing location, workstation load, and material inventory;

[0043] S4. The maintenance station will re-verify the monitoring results, then investigate the verification results, attempt to resolve the problem automatically, and if the problem cannot be resolved, provide reminders in various ways. The investigation results will also be provided for reference in the form of codes, etc.

[0044] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples; within the framework of the invention, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in the details for the sake of brevity.

[0045] This invention is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An intelligent distribution system for a garment production line, the intelligent distribution system comprising a buffer station (1) for sorting garment (4) information, a merging station (2) for distributing the integrated garments (4) to workstations (5), and a maintenance station (3) for monitoring workstations (5) to ensure the distribution task, characterized in that: A buffer station (1) is used for integration and preliminary classification. The buffer station (1) includes an intelligent sorting module (101) and a document merging module (102). The intelligent sorting module (101) identifies different garments (4) using RFID tags and transmits the information to the electrically connected document merging module (102). The document merging module (102) sorts and classifies different garments (4). The merging station (2) is used to accurately redistribute the garments (4). The merging station (2) includes a data acquisition module (201), an intelligent allocation module (202), and an automatic execution module (203). The data acquisition module (201) collects information from several garments (4) and combines it with the production line to form the most reasonable processing plan. The data acquisition module (201) is used to combine the processing plan with the actual situation and transmit the information to the electrically connected intelligent allocation module (202). The automatic execution module (203) selects the allocation tool according to the information generated by the intelligent allocation module (202) and then executes it to allocate the garments (4) to several workstations (5). Maintenance station (3) monitors the status of each production stage. The maintenance station (3) includes a sensor monitoring module (301), a test module (302), and an alarm module (303). The sensor monitoring module (301) monitors the entire production line and transmits the monitoring data to the electrically connected test module (302). The test module (302) verifies the data from the sensor monitoring module (301) and formulates solutions. The alarm module (303) notifies and reports faults based on the verification information from the test module (302). The intelligent sorting module (101) also includes a feature extraction module (1011), an optimization and correction module (1012), and a monitoring and sorting module (1013). The feature extraction module (1011) extracts key features of clothing by obtaining data from RFID tags through visual recognition or sensor detection. The optimization and correction module (1012) continuously optimizes based on data records and performance reports. The monitoring and sorting module (1013) monitors the sorting process and works with the optimization and correction module (1012) to perform real-time correction to correct misclassification. The order merging module (102) further includes a decision and classification module (1021), a sorting operation module (1022), and a data recording module (1023). The decision and classification module (1021) uses computer algorithms or machine learning models to classify items based on extracted features. The sorting operation module (1022) allocates clothing to the appropriate position on the correct production line based on the classification results. The data recording module (1023) records all sorting operations and related data. The data acquisition module (201) also includes a style analysis module (2011), a time analysis module (2012), and a processing plan formulation module (2013). The style analysis module (2011) analyzes and confirms the style of the garment (4) based on the process database. The time analysis module (2012) formulates a standard time based on normal speed and correct methods, taking into account various relevant factors. The processing plan formulation module (2013) combines each independent process with the best production sequence and method. The intelligent allocation module (202) also includes an automated allocation algorithm module (2021), an optimized path planning module (2022), and a dynamic adjustment module (2023). The automated allocation algorithm module (2021) determines to allocate the hanging garments to the workstation (5). The optimized path planning module (2022) intelligently plans the path of the hanging garments. The dynamic adjustment module (2023) can dynamically adjust the allocation strategy.

2. The smart dispensing system for a garment production line according to claim 1, wherein, The automatic execution module (203) also includes a hanging selection module (2031) and a path selection module (2032). The hanging selection module (2031) selects different forms of hanging, and the path selection module (2032) selects a conveyor belt or track to move on the production line.

3. The smart dispensing system for a garment production line according to claim 1, wherein, The sensor monitoring module (301) also includes a position monitoring module (3011), a load monitoring module (3012), and an inventory monitoring module (3013). The position monitoring module (3011) monitors the position of the hanging garments in real time. The load monitoring module (3012) monitors the load of the production line in real time and provides feedback. The inventory monitoring module (3013) monitors the inventory of materials.

4. The smart dispensing system for a garment production line according to claim 1, wherein, The test module (302) also includes an existing data analysis module (3021), a test objective confirmation module (3022), and a test method formulation module (3023). The existing data analysis module (3021) records and analyzes existing data. The test objective confirmation module (3022) verifies whether each step in the production process is performed in accordance with the prescribed standards and specifications and identifies the problems that need to be solved. The test method formulation module (3023) formulates various test methods.

5. The smart dispensing system for a garment production line according to claim 1, wherein, The alarm module (303) also includes a display alarm module (3031), an audio alarm module (3032), and an internet remote alarm module (3033). The display alarm module (3031) displays information about the fault, the audio alarm module (3032) emits a loud audio alarm, and the internet remote alarm module (3033) remotely monitors the device status and receives fault alarms via the internet.

6. A method of using an intelligent dispensing system suitable for use in a garment production line hanger according to any one of claims 1 to 5, characterised in that: Includes the following steps; S1. Different styles of clothing with RFID tags are sent to the buffer station. The buffer station identifies the RFID tags of the clothing, extracts the key information of the clothing, sorts and classifies the clothing information and continuously corrects and optimizes it. Finally, the data is recorded and the clothing is sent to the merging station. The performance and efficiency of the sorting process are tracked and reported. S2. The merging station combines the data recorded by garment identification with the actual situation of the garment production line to formulate a production plan. Then, based on the development of automated allocation algorithms and optimized path planning, it can automatically decide to allocate the hanging garments to the corresponding workstations based on real-time demand and the situation on the production line. Finally, it selects different forms of hanging and paths. S3. Faults caused by the normal operation of the workstation are detected by various sensors in the maintenance station, enabling precise monitoring of garment location, workstation load, and material inventory; S4. The maintenance station will re-verify the monitoring results, then investigate the verification results, attempt to resolve the problem automatically, and if the problem cannot be resolved, issue reminders in multiple ways. The investigation results will also be provided for reference in the form of codes.

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