Garment production multi-stage dynamic plan intelligent production scheduling system
Through a multi-stage dynamic planning intelligent production scheduling system, the problem of insufficient flexibility and forward-looking in traditional clothing production scheduling methods is solved, the matching of equipment production capacity and personnel skills is achieved, the flexible adjustment of process flow and production progress is ensured, and the production cost is reduced.
Patent Information
- Application Number
- CN202510277205.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-10
- Publication Date
- 2025-07-25
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The traditional clothing production scheduling methods lack flexibility and foresight, resulting in idle or excessive tight production capacity, delays in delivery and increased production costs, especially in the face of emergencies such as seasonal order fluctuations, equipment failures and personnel changes.
A multi-stage dynamic planning intelligent production scheduling system is adopted, including real-time production scheduling modules of 15-360 days before delivery, 7-15 days before delivery and in production. Through data collection and model construction, equipment, personnel and materials are generated, and early warning and regenerated when mismatch is not met to ensure the matching of equipment production capacity, personnel skills, process flow and production progress.
It achieves the preliminary matching of equipment production capacity and personnel skills, ensures flexible adjustment of process flow and production progress, reduces idle capacity and delivery delays, and reduces production costs.
Smart Images
Figure CN120373698A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of clothing production, and particularly relates to an intelligent production scheduling system for multi-stage dynamic planning in clothing production. Background Art
[0002] Clothing production refers to the process of transforming a designed clothing style into an actual wearable clothing product through a series of processes and procedures, including multiple steps such as material preparation, cutting, sewing, and post-processing.
[0003] In the material preparation step, production scheduling for clothing production is required. However, traditional production scheduling methods are prone to problems such as idle production capacity or over-tension, delivery delays, and increased production costs due to lack of flexibility and foresight when facing seasonal order fluctuations, emergency order insertions, and unexpected situations during the production process including equipment failures and personnel changes.
[0004] In view of this, an intelligent production scheduling system for multi-stage dynamic planning in clothing production is designed to solve the above problems. Summary of the Invention
[0005] To solve the problems raised in the above background art, the present invention provides an intelligent production scheduling system for multi-stage dynamic planning in clothing production, which integrates two real-time pre-production stages and one real-time in-production stage, has flexibility and foresight, and solves the problems existing in the prior art.
[0006] To achieve the above object, the present invention provides the following technical solution: An intelligent production scheduling system for multi-stage dynamic planning in clothing production, comprising:
[0007] A pre-production first-stage plan scheduling module, which is started 15 - 360 days before production, collects market material intention data, market order intention data, and enterprise data, generates a first production schedule based on the market material intention data and market order intention data, including equipment production capacity and personnel technical level, compares it with the enterprise data, and gives an alarm and regenerates when the production scheduling does not match;
[0008] A pre-production second-stage plan scheduling module, which is started 7 - 15 days before production, collects market order data and enterprise data, generates a second production schedule based on the market order data, including equipment arrangement, personnel arrangement, material arrangement, and material distribution path arrangement for each process in the process flow, compares it with the enterprise data, and gives an alarm and regenerates when the production scheduling does not match;
[0009] An in-production stage plan scheduling module, which is started during production, collects market order data and enterprise data, generates a third production schedule based on the market order data, compares it with the enterprise data, and gives an alarm and regenerates when the production scheduling does not match until the clothing production is completed.
[0010] Further, the pre-production first-stage plan scheduling module includes:
[0011] The first data acquisition module collects market material intention data, including market material prices; collects market order intention data, including customer order prices, customer order scales, and customer order cycles; collects enterprise data, including equipment production capacity and personnel skill levels;
[0012] The model construction module constructs a customer order scale linear regression model based on the collected customer order prices and customer order scales; constructs a customer order cycle linear regression model based on the collected customer order scales and customer order cycles;
[0013] The first production schedule real-time generation module calculates the customer order price based on the collected market material prices. The customer order scale linear regression model predicts the customer order scale based on the customer order price. The customer order cycle linear regression model predicts the customer order cycle based on the customer order scale. Based on the predicted customer order scale and customer order cycle, a first production schedule is generated, including equipment production capacity and personnel skill levels;
[0014] The first inspection and warning module compares whether the equipment production capacity and personnel skill levels in the generated first production schedule match the collected equipment production capacity and personnel skill levels. If they match, no action is taken. If they do not match, warning information is generated, including insufficient equipment production capacity and insufficient personnel skill levels, and at the same time, the first production schedule is regenerated.
[0015] Furthermore, the pre-production second-stage plan scheduling module includes:
[0016] The second data acquisition module collects market order data, including customer order process requirements, customer order scales, and customer order cycles; collects enterprise data, including equipment scale, personnel skill levels, material scale, and site scale;
[0017] The second production schedule real-time generation module generates a process flow based on the collected customer order process requirements, and generates a second production schedule based on the collected customer order scale and customer order cycle, including equipment arrangements, personnel arrangements, material arrangements, and material distribution path arrangements for each process in the process flow;
[0018] The second inspection and warning module compares whether the generated second production schedule matches the collected equipment scale, personnel skill levels, material scale, and site scale. If they match, no action is taken. If they do not match, warning information is generated, including insufficient equipment scale, insufficient personnel skill levels, insufficient materials, and the site does not support material distribution, and at the same time, the second production schedule is regenerated.
[0019] Furthermore, the in-production stage plan scheduling module includes:
[0020] The third data collection module collects market order data, including customer order price, customer order scale, and customer order cycle; it also collects enterprise data, including production progress.
[0021] The third production scheduling plan real-time generation module optimizes the production scheduling plan based on the comparison of the collected customer order price, customer order scale, and customer order cycle, and preferentially schedules orders with high profit and urgency. It generates a daily production capacity plan for the orders based on the customer order scale and customer order cycle.
[0022] The third inspection and warning module compares the daily production capacity plan of the generated orders with the collected production progress. If they match, it takes no action; if they do not match, it generates warning information, including a lag in production progress, and simultaneously regenerates the third production scheduling plan.
[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0024] The present invention conducts the first real-time production scheduling 15 - 360 days before production to ensure the matching of equipment production capacity and personnel skill levels. It conducts the second real-time production scheduling 7 - 15 days before production to ensure the matching of equipment arrangement, personnel arrangement, material arrangement, and material distribution path arrangement in each process of the technological process. At the same time, it conducts the third real-time production scheduling during production to ensure the matching of production progress. It integrates two real-time pre-productions and one real-time in-production, featuring flexibility and foresight, and solves the problems existing in the prior art. Description of the Drawings
[0025] Figure 1 It is the overall system framework diagram of the present invention;
[0026] Figure 2 It is the module framework diagram of the pre-production first-stage plan scheduling module of the present invention;
[0027] Figure 3 It is the module framework diagram of the pre-production second-stage plan scheduling module of the present invention;
[0028] Figure 4 It is the module framework diagram of the in-production stage plan scheduling module of the present invention;
[0029] In the figure: 1. Pre-production first-stage plan scheduling module; 2. Pre-production second-stage plan scheduling module; 3. In-production stage plan scheduling module;
[0030] 101. First data collection module; 102. Model construction module; 103. First production scheduling plan real-time generation module; 104. First inspection and warning module;
[0031] 201. Second data collection module; 202. Second production scheduling plan real-time generation module; 203. Second inspection and warning module;
[0032] 301. Third data acquisition module; 302. Third real-time production scheduling plan generation module; 303. Third inspection and warning module. Detailed implementation manners
[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.
[0034] Refer to the attached Figure 1 , the present invention provides the following technical solutions: A multi-stage dynamic plan intelligent production scheduling system for clothing production, including:
[0035] The first-stage pre-production plan scheduling module 1 is started 15 - 360 days before production, collects market material intention data, market order intention data, and enterprise data, generates a first production scheduling plan based on the market material intention data and market order intention data, including equipment production capacity and personnel technical level, compares with the enterprise data, and issues a warning and regenerates when the production scheduling does not match;
[0036] The second-stage pre-production plan scheduling module 2 is started 7 - 15 days before production, collects market order data and enterprise data, generates a second production scheduling plan based on the market order data, including equipment arrangement, personnel arrangement, material arrangement, and material distribution path arrangement for each process in the process flow, compares with the enterprise data, and issues a warning and regenerates when the production scheduling does not match;
[0037] The in-production stage plan scheduling module 3 is started during production, collects market order data and enterprise data, generates a third production scheduling plan based on the market order data, compares with the enterprise data, and issues a warning and regenerates when the production scheduling does not match until the clothing production is completed.
[0038] Refer to the attached Figure 2 , specifically, the first-stage pre-production plan scheduling module 1 includes:
[0039] The first data acquisition module 101 collects market material intention data, including market material prices; collects market order intention data, including customer order prices, customer order scales, and customer order cycles; collects enterprise data, including equipment production capacity and personnel skill levels;
[0040] The market material intention data collected by the first data acquisition module 101 is the price data updated in real time by material suppliers;
[0041] The market order intention data and enterprise data collected by the first data acquisition module 101 are historical data entered in advance;
[0042] The model construction module 102 constructs a linear regression model for the customer order volume based on the collected customer order price and customer order volume; constructs a linear regression model for the customer order cycle based on the collected customer order volume and customer order cycle;
[0043] The first production plan real-time generation module 103 calculates the customer order price based on the collected market material price. The customer order volume linear regression model predicts the customer order volume based on the customer order price, and the customer order cycle linear regression model predicts the customer order cycle based on the customer order volume. Based on the predicted customer order volume and customer order cycle, a first production plan is generated, including equipment production capacity and personnel skill level;
[0044] The first inspection and warning module 104 compares whether the equipment production capacity and personnel skill level in the generated first production plan match the collected equipment production capacity and personnel skill level. If they match, it does not act. If they do not match, warning information is generated, including insufficient equipment production capacity and insufficient personnel skill level, and at the same time, the first production plan is regenerated.
[0045] Refer to the appendix Figure 3 Specifically, the pre-production second-stage plan scheduling module 2 includes:
[0046] The second data collection module 201 collects market order data, including customer order process requirements, customer order volume, and customer order cycle; collects enterprise data, including equipment scale, personnel skill level, material scale, and site scale;
[0047] The market order data and enterprise data collected by the second data collection module 201 are pre-entered real-time data;
[0048] The second production plan real-time generation module 202 generates a process flow based on the collected customer order process requirements, and generates a second production plan based on the collected customer order volume and customer order cycle, including equipment arrangement, personnel arrangement, material arrangement, and material distribution path arrangement for each process in the process flow;
[0049] The second inspection and warning module 203 compares whether the generated second production plan matches the collected equipment scale, personnel skill level, material scale, and site scale. If they match, it does not act. If they do not match, warning information is generated, including insufficient equipment scale, insufficient personnel skill level, insufficient materials, and the site does not support material distribution, and at the same time, the second production plan is regenerated.
[0050] Refer to the appendix Figure 4 Specifically, the in-production stage plan scheduling module 3 includes:
[0051] The third data collection module 301 collects market order data, including customer order price, customer order size, and customer order cycle; it collects enterprise data, including production progress;
[0052] The market order data and enterprise data collected by the third data collection module 301 are pre-entered real-time data;
[0053] The third production scheduling plan real-time generation module 302 optimizes the production scheduling plan based on the comparison among the collected customer order price, customer order size, and customer order cycle, and preferentially schedules orders with high profit and urgency. It generates a daily production capacity plan for the orders based on the customer order size and customer order cycle;
[0054] The third inspection and warning module 303 compares the daily production capacity plan of the generated orders with the collected production progress. If they match, it takes no action; if they do not match, it generates warning information, including production progress lag, and at the same time regenerates the third production scheduling plan.
[0055] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.
Claims
1. An intelligent scheduling system for multi-stage dynamic planning in clothing production, characterized in that, Including: The pre-production first-stage production scheduling module (1) is started 15 - 360 days before production, collects market material intention data, market order intention data and enterprise data, generates the first production schedule based on the market material intention data and the market order intention data, including equipment production capacity and personnel technical level, compares with the enterprise data, and issues a warning for regeneration when the production scheduling does not match; The pre-production second-stage production scheduling module (2) is started 7 - 15 days before production, collects market order data and enterprise data, generates the second production schedule based on the market order data, including equipment arrangement, personnel arrangement, material arrangement and material distribution path arrangement for each process in the process flow, compares with the enterprise data, and issues a warning for regeneration when the production scheduling does not match; The in-production stage production scheduling module (3) is started during production, collects market order data and enterprise data, generates the third production schedule based on the market order data, compares with the enterprise data, and issues a warning for regeneration when the production scheduling does not match until the clothing production is completed.
2. The intelligent scheduling system for multi-stage dynamic planning of clothing production according to claim 1, wherein: The pre-production first-stage production scheduling module (1) includes: The first data collection module (101) collects market material intention data, including market material prices; collects market order intention data, including customer order prices, customer order scales and customer order cycles; collects enterprise data, including equipment production capacity and personnel skill levels; The model construction module (102) constructs a customer order scale linear regression model based on the collected customer order prices and customer order scales; constructs a customer order cycle linear regression model based on the collected customer order scales and customer order cycles; The first production schedule real-time generation module (103) calculates the customer order price based on the collected market material prices, the customer order scale linear regression model predicts the customer order scale based on the customer order price, the customer order cycle linear regression model predicts the customer order cycle based on the customer order scale, and generates the first production schedule based on the predicted customer order scale and customer order cycle, including equipment production capacity and personnel skill levels; The first inspection and warning module (104) compares whether the equipment production capacity and personnel skill levels in the generated first production schedule match the collected equipment production capacity and personnel skill levels. If they match, it does not take any action. If they do not match, it generates warning information, including insufficient equipment production capacity and insufficient personnel skill levels, and at the same time regenerates the first production schedule.
3. The intelligent scheduling system for multi-stage dynamic planning of garment production according to claim 2, wherein: The pre-production second-stage production scheduling module (2) includes: The second data collection module (201) collects market order data, including customer order process requirements, customer order scales and customer order cycles; collects enterprise data, including equipment scale, personnel skill levels, material scale and site scale; The second production schedule real-time generation module (202) generates the process flow based on the collected customer order process requirements, and generates the second production schedule based on the collected customer order scales and customer order cycles, including equipment arrangement, personnel arrangement, material arrangement and material distribution path arrangement for each process in the process flow; The second patrol warning module (203) compares whether the generated second production plan matches the collected equipment scale, personnel skill level, material scale, and site scale. If it matches, it does not take any action. If it does not match, it generates warning information, including insufficient equipment scale, insufficient personnel skill level, insufficient materials, and the site not supporting material distribution, and at the same time regenerates the second production plan.
4. An intelligent scheduling system for multi-stage dynamic planning of garment production according to claim 3, characterized in that: The in-production stage plan scheduling module (3) includes: The third data collection module (301) collects market order data, including customer order price, customer order scale, and customer order cycle; and collects enterprise data, including production progress. The third real-time production plan generation module (302) optimizes the production plan and preferentially schedules orders with high profit and urgency based on the comparison of the collected customer order price, customer order scale, and customer order cycle, and generates the daily production capacity plan for the orders based on the customer order scale and customer order cycle. The third patrol warning module (303) compares the daily production capacity plan of the generated orders with the collected production progress. If it matches, it does not take any action. If it does not match, it generates warning information, including lagging production progress, and at the same time regenerates the third production plan.