A bottleneck process scheduling method for a garment hanging system

Abstract

This invention discloses a bottleneck process scheduling method for a garment hanging system. After a workstation completes semi-finished product processing, garment hangers are dispatched. The hanging system records the delayed dispatch time of each workstation. If the cumulative delayed dispatch time of a certain workstation reaches three times the production line cycle time, a scheduling condition determination is initiated. The existence of a schedulable workstation is used as the scheduling condition; if it exists, the process proceeds to the next step. The cumulative delayed dispatch time is then reset to zero. After the cumulative delayed dispatch time is reset to zero, a scheduling priority determination is initiated. This invention features a simple process, timely resolution of bottleneck processes, high production efficiency, broad market prospects, and suitability for widespread application.

Description

Technical Field

[0001] This invention relates to a scheduling method, and more specifically, to a bottleneck process scheduling method for a garment hanging system, belonging to the field of garment manufacturing. Background Technology

[0002] Currently, an increasing number of garment manufacturing companies are adopting hanging systems to facilitate their digital and intelligent transformation and upgrading. Garment hanging systems offer advantages such as intelligent control and flexible transportation; however, most companies do not maximize these advantages in controlling production balance. For example, they cannot automatically identify and schedule bottleneck processes, thus hindering effective improvements in production efficiency.

[0003] A bottleneck process refers to a step in the entire production flow where the production capacity is less than the workload or cannot meet the production rhythm. In a traditional overhead conveyor system, when a bottleneck process occurs, hangers accumulate until the buffer zone at the station is full. The hangers will then circulate within the main track of the conveyor system but will not enter the next station until the worker completes the process and hangers leave. Alternatively, the process may rely on the experience of the shift leader to schedule the process. Both of these methods result in the bottleneck process not being resolved in a timely manner, which is detrimental to improving production efficiency. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a bottleneck process scheduling method for a garment hanging system, characterized by its ability to promptly resolve bottleneck processes and high production efficiency.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0006] This invention discloses a bottleneck process scheduling method for a garment hanging system, characterized in that the method includes:

[0007] Step 1: S of the garment hanging system k The positions are completed according to the prescribed a (a = 1, 2, 3, ..., b (S)) k The production process of semi-finished garments involves the garments leaving the station, and at the same time, the station position S is recorded. k The delayed departure time D(S) for completing the production process of the a-th semi-finished product k ) a The calculation formula is: D(s) k ) a =t(S k ) a -TT, k=1, 2, 3...m, a=1, 2, 3...b (S k );

[0008] b indicates the total number of orders for styles currently being produced on the garment hanging production line;

[0009] b(S k ) indicates position S k The number of semi-finished products that need to be completed;

[0010] t(S k ) a Indicates the location S of the suspended assembly line station. k The actual processing time consumed in processing the a-th semi-finished product, k = 1, 2, 3... m, a = 1, 2, 3... b (S) k );

[0011] D(S k ) a Indicates position S k The delay time of processing the a-th semi-finished product relative to the production line cycle time, k = 1, 2, 3...m, a = 1, 2, 3...b (S) k );

[0012] L(S k ) g Indicates position S k The cumulative outbound delay time before triggering the g-th scheduling, g = 1, 2, 3...b(S) k );

[0013] Step 2: If a < b (S) k ), and position S k The cumulative delay in exiting the station reached three times the assembly line cycle time, that is... Identify S k The stationary production process is a bottleneck process and requires production scheduling. Proceed to step 3 to determine scheduling conditions; otherwise, do not execute production scheduling and return to step 1 to continue semi-finished product processing. If a = b(S) k If the condition is met, proceed to step 6;

[0014] Step 3: Use the existence of a schedulable station as the scheduling condition. If a schedulable station exists, proceed to the next step 4 and record the cumulative number of semi-finished products completed by the hanging assembly line as a′. If no schedulable station exists, return to step 1 and continue processing semi-finished products. The method for determining a schedulable station is: 1) the three most recent delayed departure times D(S). k 1) The value is zero; 2) The equipment, cables, and personnel configured at the station are compatible with the station where the bottleneck process is located;

[0015] Step 4: Determine if the number of schedulable stations is greater than 1. If so, determine the priority of the schedulable stations; otherwise, proceed to Step 5 to complete the scheduling. The method for determining the priority of schedulable stations is as follows: Iterate through all schedulable stations and select the station with the least amount of clothes hanger accumulation in the buffer. If the amount of clothes hanger accumulation is the same, then select the station with the least amount of clothes hanger accumulation. k The shortest position;

[0016] Step 5: Complete S k Station scheduling, and g = g + 1, b(S) k ) = b - 1, Transferred station b(S) k =b+1, return to step 1, and continue processing the semi-finished product;

[0017] Step 6: Position S k All semi-finished products have been processed.

[0018] Beneficial effects: The process is simple, bottleneck processes can be resolved in a timely manner, production efficiency is high, the market prospects are broad, and it is suitable for widespread use. Attached Figure Description

[0019] Figure 1 This is a simulation model diagram of an existing garment hanging production line.

[0020] Figure 2 This is a schematic diagram of the process of this invention.

[0021] Figure 3 This is a resource utilization diagram before and after scheduling in Example 1.

[0022] Figure 4 This is a graph showing the percentage of idle time before and after scheduling in Example 1. Detailed Implementation

[0023] The present invention will be further described below with reference to the accompanying drawings, but the present invention is not limited to the following embodiments.

[0024] In the existing technology, the garment hanging production line system (garment hanging system) is a high-tech automated equipment in the "rapid response production technology" of the garment industry. Its basic components are a main computer, a suspended object conveying system, and a workstation (workstation) containing a computer terminal.

[0025] The basic concept of a garment hanging system is to hang the cut pieces of each garment component on hangers, connecting various production workstations (stations) on the assembly line via a circular transport track. The hangers, carrying the fabric, automatically transfer the fabric between workstations according to a pre-set processing plan and intelligently adjust based on actual production conditions. The system delivers the fabric to each employee's workstation via the transport track, significantly reducing non-production time spent on handling, binding, and folding, and proactively identifying and resolving bottlenecks in the production process. Once a production worker completes a process, they simply press a control button, and the hanging system automatically transfers the hanger to the next processing station.

[0026] A basic hoisting system consists of: a main drive system, main rails, an inbound mechanism and branch rails, workstations (stations), an outbound mechanism, a pneumatic system, a control system, electronic components and software, as well as profile supports and storage racks. Each workstation (station) includes inbound and outbound release mechanisms, rack lifting mechanisms, and operating terminals. The core software components include a production information collection, processing, analysis, and intelligent scheduling system, and the drive software required for the entire hoisting system to operate.

[0027] Garment hanging assembly line systems utilize a unit production model for garment processing. The same process can be handled by multiple workstations, and a single workstation can handle different processes. From an overall structural perspective, garment hanging assembly line systems can be divided into two parts: the mechanical structure and the management and control system. The mechanical structure can be categorized by appearance into suspended and floor-mounted types; the management and control system can be categorized by control method into manual control, automatic computer control, and a combination of manual and computer control. The control system consists of four parts: an upper-station software management center, hardware control nodes, operating terminals, and the main track.

[0028] like Figure 1 As shown, a simulation of a garment hanging production line (garment hanging system) is presented.

[0029] Simulation Model Construction: The components of a garment hanging production line include semi-finished products, hangers, workstations (equipped with receiving and returning tracks, corresponding personnel, and sewing equipment), sensing devices, and conveying equipment. These components are abstracted into parts, containers, stations, flow control, and conveyors in simulation software.

[0030] Based on the production line layout, the production line was modeled using Plant Simulation software. The model included one material source (material distribution station), 24 stations (23 sewing stations and one quality inspection station, each equipped with a buffer to store semi-finished products), and one material termination point (representing garment warehousing). Each station had a start button; if actual production required fewer than 24 stations, the start buttons for some stations could be disabled to achieve flexible production station configuration. Based on the scheduling scheme of this application, the corresponding code could be designed using the Simtalk language.

[0031] Simulation Parameter Settings: To better simulate the actual production process, simulation parameters need to be set to control various behaviors and events in the simulation model. Based on their nature, parameters are divided into constant parameters and variable parameters. Constant parameters are those that remain unchanged throughout the simulation, such as order quantity, working time, and track speed. Setting variable parameters can more realistically simulate disturbances that occur in actual production and can also better test the robustness of the scheduling scheme. Common variables include actual worker processing time, worker absences, and equipment failures; these are usually random occurrences, and their distribution can be described using the random distribution in statistics.

[0032] The actual processing time of workers is usually affected by their skill level, mood, and various accidental factors, fluctuating around the standard working hours, and can be represented by a triangular distribution. During processing, a learning effect occurs, meaning that as the cumulative output per unit increases, the unit production cost or time gradually decreases, which can usually be fitted as a power function. For the time intervals of random events such as equipment failure and worker absence, an exponential distribution can be used to describe them. The exponential distribution is well-suited for describing the time intervals of random events; its probability density function exhibits an exponentially decreasing trend, and the probability of the event gradually increases with time. Table 1 shows the constant and variable parameters set in this simulation model.

[0033] Table 1 Constant Parameters and Variable Parameters

[0034] Tab.1 Constant parameters and variable parameters

[0035]

[0036]

[0037] In order to make the parameter settings in the distribution function and power function as close as possible to reality and effective, the following two methods are used to set the parameters: (1) Using historical data for fitting, using the fitting function built into the simulation software, and setting the parameters according to the fitting results, including the production line cycle time (process value), the actual processing time of the worker (process value), equipment failure and worker absence; (2) Referring to the expert experience value to set the parameters, including the actual processing time of the worker (initial value).

[0038] This invention utilizes a garment hanging system to quickly resolve bottleneck processes and significantly improve production efficiency. For example... Figure 1-4 The illustration shows a specific embodiment of a bottleneck process scheduling method for a garment hanging system. This embodiment of a bottleneck process scheduling method for a garment hanging system includes: bottleneck process determination, scheduling condition determination, and scheduling priority determination.

[0039] This invention discloses a bottleneck process scheduling method for a garment hanging system, characterized in that the method includes:

[0040] Step 1: S of the garment hanging system k Once the specified production process for the a-th (a = 1, 2, 3, ..., b(Sk))th garment semi-finished product is completed at station S, the garment semi-finished product leaves the station, and station S is recorded. k The delayed departure time D(S) for completing the production process of the a-th semi-finished product k ) a The calculation formula is: D(S) k ) a =t(S k ) a -TT, k=1, 2, 3...m, a=1, 2, 3...b (S k );

[0041] b indicates the total number of orders for styles currently being produced on the garment hanging production line;

[0042] b(S k ) indicates position S k The number of semi-finished products that need to be completed;

[0043] t(S k ) a Indicates the location S of the suspended assembly line station. k The actual processing time consumed in processing the a-th semi-finished product, k = 1, 2, 3... m, a = 1, 2, 3... b (S) k );

[0044] D(S k ) a Indicates position S k The delay time of processing the a-th semi-finished product relative to the production line cycle time, k = 1, 2, 3...m, a = 1, 2, 3...b (S) k );

[0045] L(S k ) g Indicates position S k The cumulative outbound delay time before triggering the g-th scheduling, g = 1, 2, 3...b(S) k );

[0046] Step 2: If a < b (S) k ), and position S k The cumulative delay in exiting the station reached three times the assembly line cycle time, that is... Identify S kThe stationary production process is a bottleneck process and requires production scheduling. Proceed to step 3 to determine scheduling conditions; otherwise, do not execute production scheduling and return to step 1 to continue semi-finished product processing. If a = b(S) k If the condition is met, proceed to step 6;

[0047] Step 3: Use the existence of a schedulable station as the scheduling condition. If a schedulable station exists, proceed to the next step 4 and record the cumulative number of semi-finished products completed by the hanging assembly line as a′. If no schedulable station exists, return to step 1 and continue processing semi-finished products. The method for determining a schedulable station is: 1) the three most recent delayed departure times D(S). k 1) The value is zero; 2) The equipment, cables, and personnel configured at the station are compatible with the station where the bottleneck process is located;

[0048] Step 4: Determine if the number of schedulable stations is greater than 1. If so, determine the priority of the schedulable stations; otherwise, proceed to Step 5 to complete the scheduling. The method for determining the priority of schedulable stations is as follows: Iterate through all schedulable stations and select the station with the least amount of clothes hanger accumulation in the buffer. If the amount of clothes hanger accumulation is the same, then select the station with the least amount of clothes hanger accumulation. k The shortest position;

[0049] Step 5: Complete S k Station scheduling, and g = g + 1, b(S) k ) = b - 1, Transferred station b(S) k =b+1, return to step 1, and continue processing the semi-finished product;

[0050] Step 6: Position S k All semi-finished products have been processed.

[0051] The determination of the bottleneck process in this invention is specifically as follows:

[0052] To achieve automatic scheduling of bottleneck processes, it is first necessary to set the judgment rules for bottleneck processes and use them as the trigger signal for rescheduling. To better monitor production efficiency, this invention sets the production line cycle time TT for the garment hanging system. Since each station's buffer zone contains a certain amount of semi-finished products, the production line is not strictly a "single-piece flow" but rather a "small-batch flow," allowing workers to complete the production of semi-finished products at their own pace. When the worker's actual production time t(S) k ) a When the production cycle time exceeds the set time, the number of hangers leaving the station becomes less than the number of hangers entering the station over time, causing hangers to gradually accumulate in the buffer zone, thus forming a bottleneck process. The purpose of bottleneck process scheduling is to relocate hangers about to enter the station to stations with excess capacity when there is a tendency for hangers to accumulate in the buffer zone, without over-scheduling. The bottleneck process determination rules are set as follows:

[0053] When the a-th semi-finished product is completed, the actual processing time at the station is t(S). k ) a If the assembly line cycle time is TT, then the delayed departure time is D(S). k ) a :

[0054] D(S k ) a =t(S k ) a -TT, k=1, 2, 3...m, a=1, 2, 3...b (S k (1)

[0055] If the cumulative D(S) k If the pipeline cycle time TT reaches n times, then scheduling is triggered (when t(S)). k ) a If the quantity is less than TT, it is considered a negative cumulative total. Based on interviews with production experts, n is typically 3, meaning that for every 3 units slower than the entire production line, 1 unit is rescheduled. This multiplier can be fine-tuned based on the complexity of the style and process. For example, for a standard style, at a certain station t(S k )1=180s,t(S k )2=210s,t(S k )3=220s, TT=200s, then the cumulative D(S) k The time interval is (-20) + 10 + 20 = 10 seconds, which is less than 3 times the production line cycle time TT. Therefore, it is considered a non-bottleneck process and scheduling is not triggered. If the time interval at a certain station is t(S) k )1=300s,t(S k )2=310s,t(S k )3=315s,t(S k )4=400s,t(S k )5=305s, TT=200s, then the cumulative D(S) k The timeout is 100+110+115+200+105=630s, which is 3 times the production line cycle time TT. It is determined to be a non-bottleneck process and the scheduling is triggered.

[0056] After the scheduling is triggered, the cumulative D(S) k ) clear to zero; if the cumulative D(S) k If the flow rate reaches three times the production line cycle time again, scheduling will be triggered once more.

[0057] The specific scheduling conditions for the bottleneck process in this invention are as follows:

[0058] The hangers that are about to enter the bottleneck process will be reassigned to a station where there have been no delays in the last three semi-finished product production processes. However, not all stations with excess capacity are suitable for reassignment; compatibility with equipment, materials, and personnel skills must also be ensured.

[0059] 1) Equipment compatibility. Since a station can only accommodate a maximum of two different types of equipment, if the equipment type of the station after scheduling does not include the equipment type required for the scheduled process, then the equipment compatibility requirement is not met.

[0060] 2) Thread compatibility. Due to differences in style or process design, garment production may require different types of sewing threads. To avoid the extra time caused by changing threads, in addition to ensuring equipment compatibility, the sewing threads required by the equipment must also be the same.

[0061] 3) Personnel Skill Compatibility. Workers with different skill levels vary in the difficulty of the work processes they can complete, the quality of their work, and their work efficiency. This paper categorizes personnel skill levels into three levels—A, B, and C—based on the difficulty of the work processes they can complete, from highest to lowest. Skill levels are only compatible downwards; for example, an A-level worker can complete a C-level worker's work, but the reverse is not true. Companies can set their own personnel rating standards based on their specific circumstances.

[0062] When preparing for delivery, identify the criteria for materials and skills required to facilitate the scheduling process, as shown in Table 2.

[0063] Table 1. Assembly Line Equipment and Wire Setup Table

[0064]

[0065] The scheduling priority of the bottleneck process in this invention is specifically as follows:

[0066] If multiple stations meet the scheduling criteria, they will be scheduled according to the following priority:

[0067] (1) The position with the least amount of clothes hangers piled up in the buffer zone is given priority;

[0068] (2) If the stacking volume is the same, the station with the shortest average actual processing time tm shall be given priority.

[0069] Example 1: Production Example Analysis Using the Technical Solution of this Application

[0070] 1.1 Shirt hanging assembly line arrangement

[0071] Using a standard shirt as the experimental subject, with an order quantity of 500 pieces and a worker's working time of 8 hours / day, the "Man-Machine Process Table" is shown in Table 3. Among them, stations 2 and 3, stations 13 and 14, and stations 16 and 17 are parallel stations, each processing the same process.

[0072] Table 1. Shirt Manufacturing Process Table

[0073] Tab.1 Worker,machine,process table of shirt

[0074]

[0075]

[0076]

[0077] 1.2 Verification of the Shirt Hanging Production Line Model

[0078] Before running the established model in simulation, it needs to be validated. Validation methods include compiler verification and comparison of simulation results with real-world conditions. To ensure the model's feasibility, the compiler process in Plant Simulation software was used to verify the model, and the animation effects during simulation were observed. The results showed that the established model could accurately execute each program line. To ensure the model accurately reflects the real production process, the order was implemented in actual production, using the same assembly line scheduling scheme as in Table 3. A comparison was made between the simulated maximum completion time and the actual maximum completion time. Excluding worker training time, before adopting the scheduling scheme, the simulated maximum completion time was 3 days, 5 hours, and 31 minutes, while the actual maximum completion time was 3 days, 6 hours, and 20 minutes. This indicates that although the simulation results have some deviations, they are basically consistent with the actual situation.

[0079] 1.3 Simulation of Shirt Sewing Production Line Operation

[0080] Based on Table 3, "Shirt Machine Operation Table," and the existing simulation model presented in this paper, the operational results include maximum completion time, variance of stacking volume, and resource utilization rate. A comparative analysis is conducted to examine the differences in operational results before and after implementing the scheduling scheme.

[0081] 1.4 Maximum completion time

[0082] Maximum completion time refers to the longest time required to complete an order, which is determined by the processing time required for each process and the transportation time of semi-finished products. Table 4 shows the maximum completion time displayed by the event controller before and after the implementation of the scheduling scheme.

[0083] Table 2 Maximum Completion Time Before and After Scheduling

[0084] Tab.2 Scheduling before and after completion time

[0085]

[0086] Table 4 shows that after implementing the scheduling plan, the maximum completion time was reduced by 1 hour and 39 minutes. Based on production efficiency...

[13] The calculation formula is as follows:

[0087] Production efficiency = (Standard total working hours / Actual total working hours) * 100%

[0088] It can be seen that under the premise of fixed order input and the same production resources, the standard total working hours remain unchanged, while the actual total input working hours after scheduling are reduced. This indicates that the scheme achieves process control of production, enabling the hangers to circulate quickly on the production line, avoiding accumulation and congestion, reducing waiting time in the production process, and thus improving production efficiency and overall production capacity.

[0089] 1.5 Variance of Stacking Amount

[0090] Stacking variance refers to the variance of the stacking of hangers within the buffer zones of each station, reflecting the balance of the production line. The calculation formula is as follows:

[0091] D=∑(C n -C) 2 / N

[0092] In the formula: D is the variance of the accumulation amount; C n C represents the amount of clothes hangers piled up at each station; C represents the average amount of clothes hangers piled up; N represents the number of stations.

[0093] Table 5 shows the variance of the accumulation amount at different times before and after the implementation of the scheduling plan.

[0094] Table 3. Variance of Accumulation Amount Before and After Scheduling

[0095] Tab.3 Scheduling before and after accumulation variance

[0096]

[0097] As shown in Table 5, after implementing the scheduling scheme, the variance of the accumulation amount at different times decreased, indicating that the balance of the production line was improved.

[0098] 1.6 Resource Utilization Rate

[0099] Resource utilization rate refers to the degree to which resources used in the production process are fully utilized, and is usually expressed as a percentage.

[0100] Define B(t) as the resource "busy state" function, as shown in the following formula:

[0101]

[0102] Therefore, the resource utilization rate is the area under curve B(t) divided by the production cycle:

[0103]

[0104] In the formula: U is the resource utilization rate; T is the maximum completion time.

[0105] Depend on Figure 3 , 4 It can be seen that after implementing the scheduling plan, the resource utilization rate of each station increased, with the average resource utilization rate rising from 61.2% to 64.8%, and the idle time ratio of each station decreased. This indicates that after implementing the scheduling plan, the bottleneck process was effectively transferred, reducing the waste and idleness of production resources, and the production process became more stable and efficient.

[0106] In conclusion:

[0107] (1) To address the issue that bottleneck processes cannot be automatically identified and scheduled in garment hanging production lines, an event-driven bottleneck process scheduling scheme was designed. Through analysis of a shirt example, the maximum completion time, variance of stacking volume, and resource utilization rate of the production line were all optimized after scheduling, indicating that the scheduling scheme can effectively improve the production efficiency and production line balance of hanging production lines.

[0108] (2) A simulation model of a garment sewing production line was constructed using Plant Simulation software. To make the model more closely resemble actual production conditions, this application analyzed the possible disturbance factors in production and matched the distribution function according to their characteristics, providing a design idea for the simulation modeling of garment production lines.

[0109] (3) Because Plant Simulation software has extremely high versatility, it can be used to predict bottleneck processes and verify production balance for different styles before actual production, avoid risks in advance, and further improve production efficiency.

[0110] Finally, it should be noted that the present invention is not limited to the above embodiments, and many variations are possible. All variations that can be directly derived or conceived by those skilled in the art from the disclosure of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A bottleneck process scheduling method for a garment hanging system, characterized in that... The method includes: Step 1: Garment Hanging System The designated position has been completed. The production process of semi-finished garments; the semi-finished garments leave the station, and the station location is recorded simultaneously. Processing the first Delayed exit time of semi-finished products relative to the assembly line cycle time The calculation formula is: ; Indicates position The number of semi-finished products that need to be completed; Indicates the location of the suspended assembly line station. In processing the first The actual processing time consumed by a semi-finished product; Indicates the cycle time of the assembly line; Step 2: If And the position In triggering the The cumulative delay time before the next dispatch Reaching three times the production line cycle time, that is Identify If the stationary production process is a bottleneck process, production scheduling is required. Proceed to step 3 to determine scheduling conditions; otherwise, production scheduling is not executed, and return to step 1 to continue semi-finished product processing. Then proceed to step 6; Indicates position In triggering the The cumulative delayed departure time before the next dispatch; Step 3: Determine the scheduling condition based on the existence of a schedulable station. If a schedulable station exists, proceed to the next step, Step 4, and record the cumulative number of semi-finished parts completed by the hanging assembly line at this point. If no schedulable station is found, return to step 1 and continue processing the semi-finished product. The method for determining a schedulable station is the three most recent delays in departure time. The value is zero, and the equipment, cables, and personnel configured at the station are compatible with the station where the bottleneck process is located; Step 4: Determine if the number of schedulable stations is greater than 1. If so, perform schedulable station priority determination; otherwise, proceed to Step 5 to complete the scheduling. The method for determining the priority of schedulable stations is as follows: traverse all schedulable stations and select the station with the least amount of clothes hanger accumulation in the buffer zone; if the amount of clothes hanger accumulation is the same, select the station with the shortest average actual processing time. Step 5: Complete Station scheduling, and Adjusted station position =b+1, return to step 1, and continue processing the semi-finished product; Step 6: Positioning All semi-finished products have been processed.

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