Warp knitting industry order management method and device, electronic equipment and storage medium
Through modern information technology and intelligent algorithms, the order management process of the warp knitting industry is optimized, and the problems of long production cycle, inaccurate planning and insufficient information support in traditional methods are solved, and more efficient order delivery and resource management are achieved.
Patent Information
- Application Number
- CN202411649818.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-19
- Publication Date
- 2025-03-11
AI Technical Summary
The traditional warp knitting industry has problems such as long production cycle, inaccurate planning, and insufficient information support, resulting in tight lead times, frequent adjustments in production plans and difficulty in sharing information.
Modern information technology and intelligent algorithms are adopted to realize the steps of order parameter analysis, production capacity assessment, production plan formulation, production resource allocation, production process monitoring and quality inspection, and form a comprehensive order management process.
Through information sharing and decision-making optimization, we can improve order delivery speed and work efficiency, reduce inventory and waste, which is suitable for the management needs of small and medium-sized warp knitting enterprises.
Smart Images
Figure CN119599355A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the field of production planning and management, and in particular to a method device, electronic equipment and storage medium for order management in the warp knitting industry. Background Art
[0002] Warp knitting is a technique that interweaves yarns or fibers in a specific way. The warp knitting industry has a wide variety of products, including various textile fabrics, textile products and textile crafts. The main problems faced by traditional order management methods in the warp knitting industry are:
[0003] 1) Long production cycle and tight delivery time. The production process of warp knitted products is relatively complicated and requires multiple processes and techniques, resulting in a long production cycle. Customers have strict requirements on delivery time, especially when market demand is strong, the tightness of delivery time will be further aggravated.
[0004] 2) Inaccurate planning and frequent adjustments during execution. Due to the uncertainty of market demand, fluctuations in raw material supply, and limited production capacity, the production schedule is often uncertain and difficult to be accurate. In the actual production process, due to various reasons, such as equipment failure, personnel changes, raw material shortages, etc., the production schedule may need to be adjusted frequently, resulting in a disconnect between planning and execution.
[0005] 3) Lack of information support. Various departments in the warp knitting industry often have information islands, which leads to the inability to share and coordinate information such as production plans, material requirements plans, and sales orders in a timely manner. The traditional manual scheduling method is inefficient and difficult to cope with complex order scheduling needs.
[0006] In view of the above problems, a method of order management in the warp knitting industry is needed to comprehensively optimize the traditional order management in the warp knitting industry. Summary of the invention
[0007] In order to utilize modern information technology and intelligent algorithms to achieve information sharing and decision optimization, thereby promoting the development of enterprises in the warp knitting industry in a more efficient and intelligent direction, the first purpose of the present invention is to provide a method for order management in the warp knitting industry, comprising the following steps:
[0008] S1. Receive an order and analyze order parameters; the order includes a replenishment order and a sales order, and the order parameters include product specifications, delivery date, price information, customer requirements, and order priority;
[0009] S2. Based on the results of order analysis, evaluate the production capacity of the enterprise and prepare corresponding production resources;
[0010] S3. Formulate a production schedule for the order, which includes production time, production line, production workers, production batch, production quantity, and production sequence;
[0011] S4. According to the production schedule, production tasks are assigned to specific production lines and workers, and responsibilities and task completion time are clearly defined;
[0012] S5. During the production process, monitor the production progress and quality and make deviation adjustments in a timely manner;
[0013] S6. After production is completed, the finished products are inspected for quality and sent to the warehouse for storage and management;
[0014] S7. Arrange the delivery time and logistics method according to the customer's delivery date requirements.
[0015] Preferably, step S1 includes the following sub-steps:
[0016] S11. Receive sales orders from customers or internal replenishment orders through various channels;
[0017] S12. Check the received order information to ensure the accuracy and completeness of the order and confirm the validity of the order;
[0018] S13. Perform an initial analysis on the order, including demand analysis, cost estimation, risk assessment, and initial priority sorting.
[0019] Preferably, step S2 includes the following sub-steps:
[0020] S21. Evaluate the production capacity of existing production equipment based on historical production data, equipment maintenance records and equipment performance parameters;
[0021] S22. Assess the skill level, productivity and availability of existing employees, as well as labor shortages or surpluses;
[0022] S23. Check the quantity and quality of raw materials and auxiliary materials in stock to ensure that they can meet order requirements;
[0023] S24. Prepare corresponding production process documents and technical standards according to order requirements.
[0024] Preferably, step S3 includes the following sub-steps:
[0025] S31. Decompose the order into specific production processes according to product type, quantity, delivery date and other requirements, and clarify the goals, requirements and completion time of each production process; the processes include yarn preparation, warping, weaving, dyeing, shaping and cloth dropping;
[0026] S32. Allocate production resources to corresponding production tasks according to the requirements of the production process and the allocation principle and allocation algorithm;
[0027] S33. Determine the execution order of the production tasks according to the production scheduling factors of the production tasks; the production scheduling factors include priority, delivery date, and availability of production resources.
[0028] Preferably, the allocation principles include:
[0029] 1) Prioritize the use of in-product resources;
[0030] 2) Give priority to using work-in-progress resources with a longer inventory time;
[0031] 3) Give priority to using the most matching in-process resources;
[0032] The allocation algorithm is a genetic algorithm, and the steps include:
[0033] 1) Define the problem as maximizing production efficiency, minimizing costs, or optimizing equipment utilization;
[0034] 2) Using binary coding to represent a resource allocation scheme, each gene bit represents the allocation of a resource in a specific process;
[0035] 3) Randomly generate a set of initial solutions that meet the constraints as the population;
[0036] 4) Design a fitness function to evaluate the quality of each individual;
[0037] 5) Select excellent individuals for reproduction according to the fitness function value;
[0038] 6) Repeat the genetic operation until the preset number of iterations is reached or the fitness function value no longer increases significantly.
[0039] Preferably, step S5 includes the following sub-steps:
[0040] S51. Monitor the operating status and production progress of production equipment through sensors and cameras, and upload the monitoring data to the back-end control system;
[0041] S52, implementing progress monitoring through a mobile phone APP or mini program, wherein the progress monitoring includes cloth drop monitoring, cloth patchwork monitoring, and cloth head monitoring;
[0042] S53. Analyze real-time monitoring and progress monitoring data to identify abnormal situations and potential risks in the production process; establish an early warning system to automatically issue an early warning signal when the monitoring data reaches the preset threshold or trigger condition, reminding relevant personnel to take timely measures to make adjustments;
[0043] S54. Use visualization technology to display real-time monitoring data and analysis results in a visual form;
[0044] S55. Adjust production plans based on real-time monitoring data and early warning signals.
[0045] The second object of the present invention is to provide a device for order management in the warp knitting industry, comprising:
[0046] 1) Order receiving module: used to receive orders and analyze order parameters;
[0047] 2) Production capacity assessment module: used to assess the production capacity of the enterprise and prepare corresponding production resources based on the results of order analysis;
[0048] 3) Production scheduling module: used to formulate production scheduling for orders;
[0049] 4) Production scheduling and task allocation module: According to the production schedule, production tasks are allocated to specific production lines or workers, and responsibilities and task completion time are clearly defined;
[0050] 5) Production process monitoring and adjustment module: used to monitor production progress and quality during the production process and make deviation adjustments in a timely manner;
[0051] 6) Finished product inspection and warehousing module: used to inspect the quality of finished products after production is completed and send the finished products to the warehouse for storage and management;
[0052] 7) Shipping and delivery module: used to arrange the shipping time and logistics method according to the customer's delivery date requirements.
[0053] A third object of the present invention is to provide an electronic device, comprising:
[0054] Memory for storing computer programs;
[0055] The processor is used to execute the program stored in the memory to implement the steps of the method for order management in the warp knitting industry described in any one of the above items.
[0056] A fourth object of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for order management in the warp knitting industry described in any one of the above items are implemented.
[0057] The present invention has the following beneficial effects:
[0058] 1) Suitable for enterprises in the warp knitting industry, especially small and medium-sized enterprises, to manage orders and production.
[0059] 2) It can make full use of the products to rationally arrange production and improve the order delivery speed.
[0060] The method for warp knitting industry order management of the present invention can reasonably arrange production scheduling, improve work efficiency, and reduce inventory and waste. BRIEF DESCRIPTION OF THE DRAWINGS
[0061] Figure 1 This is a step diagram of a method for order management in the warp knitting industry according to an embodiment of the present invention;
[0062] Figure 2 This is an example of a warping process sheet of a method for order management in the warp knitting industry according to an embodiment of the present invention;
[0063] Figure 3 This is an example of a weaving sheet of a method for order management in the warp knitting industry according to an embodiment of the present invention;
[0064] Figure 4 This is an example of cloth drop registration in a method for order management in the warp knitting industry according to an embodiment of the present invention;
[0065] Figure 5 This is an example of patchwork registration in a method for order management in the warp knitting industry according to an embodiment of the present invention;
[0066] Figure 6 This is an example of warp knitting industry order management method according to an embodiment of the present invention. DETAILED DESCRIPTION
[0067] In order to further understand the present invention, preferred embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the present invention.
[0068] The embodiment of the present invention provides a method for order management in the warp knitting industry, such as Figure 1 As shown, the following steps are included:
[0069] S1. Receive the order and analyze the order parameters.
[0070] The warp knitting industry has many types of products, including general products such as denim, and special products such as customized textile products. The orders received by enterprises in the warp knitting industry include replenishment orders and sales orders. A certain amount of inventory is required for general products. When the inventory level is lower than the safety stock or the demand is expected to increase, the enterprise needs to issue a replenishment order to ensure the stability of inventory. A sales order refers to a sales agreement signed between an enterprise and a customer, reflecting the customer's demand for specific goods. A sales order usually contains key elements such as customer information, product details, price, and delivery date.
[0071] Enterprises need to receive orders from internal or external customers, usually through email, phone, online platform or other channels. After receiving the order, the enterprise needs to conduct a preliminary analysis of the order, including key information such as order quantity, product type, specification requirements, delivery date, etc. This information will be used for subsequent production planning.
[0072] Step S1 includes the following sub-steps:
[0073] S11. Order received.
[0074] Enterprises receive sales orders from customers or internal replenishment orders through various channels, including telephone, email, online platforms, etc. Order parameters are important information that describes order characteristics. In the warp knitting industry, order parameters include:
[0075] Order quantity: indicates the quantity of products that customers need to purchase or the company needs to produce.
[0076] Product specifications: Describe the product's size, material, color, and other details.
[0077] Delivery date: The date of receipt expected by the customer, which is also an important basis for the company to formulate production plans and arrange shipments.
[0078] Price information: including unit price, total price and payment method, etc.
[0079] Customer requirements: Customers’ special needs or customized requirements for products, such as packaging methods, labeling requirements, etc.
[0080] Order priority: Indicates the importance or urgency of an order, which helps companies arrange production sequence and resource allocation reasonably.
[0081] S12. Order review.
[0082] Warp knitting companies need to carefully check the order information they receive to ensure its accuracy and completeness. This includes checking whether the product name, specifications, quantity, price, delivery date, etc. are consistent with customer needs. Warp knitting companies also need to confirm the validity of the order, including checking whether the customer is eligible to purchase and whether the order complies with the company's sales policy.
[0083] S13. Initial analysis of orders.
[0084] The initial analysis of the order includes:
[0085] 1) Demand analysis: Companies need to further analyze customer needs to understand their specific requirements and expectations for products. This helps companies develop production plans that better meet customer needs and improve customer satisfaction.
[0086] 2) Cost estimation: Estimate the cost and profit of the order based on the order quantity, product specifications and price information.
[0087] 3) Risk assessment: Companies also need to assess the risks that may be encountered during order execution, including raw material supply issues, production equipment failures, etc., and formulate corresponding response measures to ensure the smooth execution of orders.
[0088] 4) Initial priority sorting: Orders are initially sorted based on factors such as order priority and delivery date to determine production sequence and resource allocation.
[0089] In the step of order reception and analysis, through meticulous order reception, review, analysis and confirmation, the enterprise can ensure the accuracy and effectiveness of the order, thus providing a basis for subsequent production planning and resource allocation.
[0090] S2. Production capacity assessment and resource preparation
[0091] According to order requirements, enterprises need to evaluate their own production capacity, including the number of machines and equipment, the skill level of workers, the inventory of raw materials, etc. After evaluating production capacity, enterprises need to prepare corresponding production resources, such as purchasing raw materials, deploying machines and equipment and workers, etc.
[0092] Step S2 includes the following sub-steps:
[0093] S21. Equipment capacity assessment: Conduct capacity assessment on existing production equipment, and understand the production capacity, operating efficiency, available time and other information of each equipment through historical production data, equipment maintenance records and equipment performance parameters.
[0094] S22. Human Resources Assessment: Assess the skill level, productivity, and availability of existing employees. This includes considering employee scheduling, training programs, and possible labor shortages or surpluses.
[0095] S23. Raw materials and auxiliary materials evaluation: Check the quantity and quality of raw materials and auxiliary materials in stock to ensure that they can meet order requirements. At the same time, it is also necessary to consider the procurement cycle of raw materials and the stability of suppliers.
[0096] S24, Technical Preparation: Prepare the corresponding production process documents and technical standards according to the order requirements. This includes ensuring that all employees understand and are familiar with the new production requirements and technical standards.
[0097] S3. Develop production schedule.
[0098] Based on order demand and production capacity assessment, enterprises need to make detailed production plans. This includes determining the specific time of production, the allocation of production lines or workers, production batches and quantities, etc. When making production plans, the management system assists enterprises in considering how to optimize the production process to improve production efficiency and reduce costs. This includes adjusting the production sequence, optimizing the production process, etc.
[0099] Step S3: Formulate a production schedule including the following sub-steps:
[0100] S31. Decomposition of production tasks.
[0101] Decompose the total task in the warp knitting order into specific production processes according to product type, quantity, delivery date and other requirements, and clarify the goals, requirements and completion time of each production process. The production task decomposition completes the following work content:
[0102] 1) Basic data preparation. Collect and organize basic data such as the company's factory workshop production line and other organizational structure information, equipment information, product information, material information, etc. These data are the basis for formulating production plans.
[0103] 2) Processing configuration. Configure the required process parameters for warp knitting products, including process routes, work flow documents for each process, and material information required for each assembly process. This step ensures that each production process has clear operating guidelines and quality standards. For example, the generated warping process configuration information can be filled in as follows: Figure 2 The table shown.
[0104] 3) Order information analysis. Analyze order information in detail, including order quantity, product specifications, delivery date, etc. Based on the order information and combined with the product's process configuration, conduct subsequent process decomposition.
[0105] 4) Decomposition of production processes. Decompose the order into specific production processes. For the warp knitting industry, common processes include yarn preparation, warping, weaving, dyeing, shaping, and cloth dropping. Each process should clearly mark the required resources, including equipment, personnel, materials, etc., as well as key information such as processing time, quality standards and priorities. For example, the decomposed weaving process production order is as follows: Figure 3 shown.
[0106] S32. Allocation of production resources. According to the requirements of production tasks, production resources, including equipment, personnel, raw materials, etc., are allocated to corresponding production tasks.
[0107] The following optimization principles are considered in production resource allocation:
[0108] 1) Give priority to the use of in-process resources. For example, in-process products that have completed warping and whose specifications and quality requirements meet the requirements of the decomposed process should be used as in-process resources. This is conducive to balancing the workload in the off-season and peak season, and is also conducive to the rapid delivery of orders.
[0109] 2) Give priority to the use of work-in-progress resources with a longer inventory time. Due to deviations in sales forecasts and the requirement for production continuity, some work-in-progress resources may have a longer inventory time. At this time, by adjusting the priority, give priority to the use of work-in-progress resources with a longer inventory time.
[0110] 3) Give priority to using the most matching in-process resources. Each roll of fabric produced by the warp knitting industry has a number of meters of fabric dropped. The maximum matching principle is met when the number of meters of fabric dropped minus the number of meters required by the order is the smallest.
[0111] Production resource allocation can use intelligent scheduling algorithms, such as genetic algorithms, simulated annealing algorithms, etc., combined with the real-time status of production resources and the requirements of production tasks to achieve automatic allocation and optimization of production resources. These algorithms can take into account multiple factors, such as equipment capacity, personnel skill level, raw material supply, etc., to ensure the rational allocation and efficient use of production resources.
[0112] For example, using a genetic algorithm, the optimal allocation can be achieved through the following steps:
[0113] 1) Problem definition. Set the goal to maximize production efficiency, minimize costs, or maximize equipment utilization. Set variables to: the allocation of resources such as equipment, personnel, and materials. Set constraints to: process requirements, equipment capabilities, personnel skills, etc.
[0114] 2) Genetic algorithm coding. Use binary coding or real number coding to represent each individual, that is, a resource (equipment, personnel, materials) allocation plan. Each gene bit represents the allocation of a resource in a specific process.
[0115] 3) Initial population generation. A set of initial solutions that meet the constraints are randomly generated as the population. The population size should be appropriately selected according to the scale and complexity of the problem.
[0116] 4) Fitness function. Design a fitness function to evaluate the pros and cons of each individual. The fitness function should reflect the value of the objective function and take into account the satisfaction of the constraints. The fitness function can consider the weighted sum of multiple factors, including production efficiency, cost, equipment utilization, personnel skill matching, raw material supply, etc.
[0117] 5) Genetic operation. Select excellent individuals for reproduction according to the fitness function value. Roulette selection, tournament selection and other methods can be used. Crossover operation can simulate the gene recombination process to generate new solutions. Mutation operation can simulate the gene mutation process, which helps to jump out of the local optimal solution.
[0118] 6) Iteration and termination conditions: Repeat the genetic operation until the preset number of iterations is reached or the fitness function value no longer increases significantly.
[0119] Through the above steps, genetic algorithms can be applied to the resource allocation problems of yarn preparation, warping, weaving, dyeing, shaping, and cloth dropping in warp knitting enterprises.
[0120] S33. Production sequence arrangement.
[0121] The execution order of production tasks is determined based on factors such as production task priority, delivery date, and availability of production resources. Scheduling tools and techniques, such as Gantt charts and critical path methods, can be used to intuitively display the execution order and time schedule of production tasks. At the same time, the production sequence can be dynamically adjusted in combination with real-time production data and changes in market demand to ensure the flexibility and adaptability of the production plan.
[0122] S4. Production scheduling and task allocation.
[0123] According to the production plan, the enterprise needs to arrange production scheduling, that is, determine the specific time and sequence of each production link. Assign production tasks to specific production lines or workers, and clarify their responsibilities and task completion time.
[0124] Establish an electronic production plan approval and release process, use cloud computing and mobile technology to achieve rapid approval and real-time release of production plans, and improve the execution efficiency of production plans. Establish an electronic task allocation and execution system, such as mobile applications or online platforms, so that production departments or teams can receive, view and execute production tasks in real time.
[0125] S5. Production process monitoring and adjustment
[0126] During the production process, the company needs to monitor the production progress and quality in real time to ensure that the production process is carried out according to plan. If any problems or deviations are found in the production process, the company needs to make timely adjustments to ensure the smooth implementation of the production plan.
[0127] Production process monitoring includes real-time monitoring and progress monitoring. Step S5 includes the following sub-steps:
[0128] S51. Real-time monitoring of the production process.
[0129] By installing sensors, cameras and other equipment at the production site, key indicators such as the operating status of production equipment, production progress, and product quality can be monitored in real time. Using wireless or wired communication technology, real-time monitoring data can be uploaded to the background control system to achieve centralized data management and analysis.
[0130] S52. Production process progress monitoring.
[0131] In the embodiment of the present invention, the production process progress monitoring makes full use of mobile communication technology and implements progress monitoring through a mobile phone APP or a small program. The progress monitoring of a warp knitting enterprise includes cloth drop monitoring, cloth patchwork monitoring, and cloth head monitoring.
[0132] 1) Cloth drop monitoring, such as Figure 4 As shown in the figure, it refers to the process of registering and monitoring the quantity (length or weight) of each piece of cloth after the woven fabric is cut off from the loom (i.e., the cloth is dropped). The loom operator scans the machine QR code through the mobile terminal and fills in the cloth drop information, which will be transmitted to the background progress monitoring. After the cloth drop is registered, the cloth roll number and QR code are generated for subsequent tracking and statistics.
[0133] 2) Patchwork monitoring, such as Figure 5 As shown, it refers to the process of registering and monitoring the patchwork process when the fabrics need to be spliced together due to some reasons, such as insufficient fabric length, during the production process. Patchwork registration can also be completed by using a mobile terminal to scan the machine QR code and fill in the patchwork information.
[0134] 3) Pan head monitoring, such as Figure 6 As shown, it refers to the process of registering and monitoring the yarn heads (i.e. yarn reels) of the loom during the warp knitting production process, which includes information such as the type, specification, quantity and usage status of the yarn, which helps to ensure the supply and management of the yarn, and can also provide reference information for quality, progress control and finished product inspection in the production process.
[0135] S53. Data analysis and early warning. Analyze real-time monitoring and progress monitoring data to identify abnormal situations and potential risks in the production process. Establish an early warning system. When the monitoring data reaches the preset threshold or trigger condition, it will automatically send out an early warning signal to remind relevant personnel to take timely measures to make adjustments.
[0136] S54. Visual display. Visualization technology is used to display real-time monitoring data and analysis results in the form of charts, dashboards, etc., so that relevant personnel can quickly understand the production situation. Through mobile applications or online platforms, real-time sharing and remote monitoring of production data can be achieved to improve management efficiency and response speed.
[0137] S55. Production adjustment. According to real-time monitoring data and early warning signals, the production plan can be flexibly adjusted to ensure the timely completion of production tasks. The optimization algorithm can be used again to optimize the configuration and utilization of production resources and improve production efficiency.
[0138] Through the above production process monitoring and adjustment steps, we can make full use of mobile terminal registration, background centralized processing and display to ensure that the order management of warp knitting enterprises meets expectations.
[0139] S6. Finished product inspection and warehousing. After production is completed, the company needs to conduct quality inspection on the finished products to ensure that the products meet customer requirements and standards. After passing the inspection, online operations and confirmation are completed through mobile or fixed terminals. Finished products that pass the inspection will be sent to the warehouse for storage and management, waiting for subsequent shipment and delivery.
[0140] S7. Shipping and delivery. According to the customer's delivery date requirements, the company needs to arrange the appropriate shipping time and logistics method. After the goods arrive at the customer's hands, the company needs to confirm the delivery with the customer to ensure that the goods are intact and meet the customer's expectations. Checkpoints are set for each operation inspection to optimize the process and ensure the execution order through the order management system.
[0141] In summary, the order management method of the warp knitting industry includes several main steps, including order reception and analysis, production capacity assessment and resource preparation, production plan formulation, production scheduling and task allocation, production process monitoring and adjustment, finished product inspection and warehousing, and shipment and delivery. These steps are interrelated and together constitute the entire process of order management in the warp knitting industry.
[0142] The above embodiments are only used to help understand the method and core idea of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.
Claims
1. A method for order management in the warp knitting industry, characterized in that: The following steps are involved: S1. Receive an order and analyze order parameters; the order includes a replenishment order and a sales order, and the order parameters include product specifications, delivery date, price information, customer requirements, and order priority; S2. Based on the results of order analysis, evaluate the production capacity of the enterprise and prepare corresponding production resources; S3. Formulate a production schedule for the order, which includes production time, production line, production workers, production batch, production quantity, and production sequence; S4. According to the production schedule, production tasks are assigned to specific production lines and production workers, and responsibilities and task completion time are clearly defined; S5. During the production process, monitor the production progress and quality and make deviation adjustments in a timely manner; S6. After production is completed, the finished products are inspected for quality and sent to the warehouse for storage and management; S7. Arrange the delivery time and logistics method according to the customer's delivery date requirements.
2. A method for order management in warp knitting industry according to claim 1, characterized in that: The step S1 comprises the following sub-steps: S11. Receive sales orders from customers or internal replenishment orders through various channels; S12. Check the received order information to ensure the accuracy and completeness of the order and confirm the validity of the order; S13. Perform an initial analysis on the order, including demand analysis, cost estimation, risk assessment, and initial priority sorting.
3. The method for order management in warp knitting industry according to claim 1, characterized in that: The step S2 comprises the following sub-steps: S21. Evaluate the production capacity of existing production equipment based on historical production data, equipment maintenance records and equipment performance parameters; S22. Assess the skill level, productivity and availability of existing employees, as well as labor shortages or surpluses; S23. Check the quantity and quality of raw materials and auxiliary materials in stock to ensure that they can meet order requirements; S24. Prepare corresponding production process documents and technical standards according to order requirements.
4. The method for order management in the warp knitting industry according to claim 1, characterized in that: The step S3 comprises the following sub-steps: S31. Decompose the order into specific production processes according to product type, quantity, delivery date and other requirements, and clarify the goals, requirements and completion time of each production process; the processes include yarn preparation, warping, weaving, dyeing, shaping and cloth dropping; S32. Allocate production resources to corresponding production tasks according to the requirements of the production process and the allocation principle and allocation algorithm; S33. Determine the execution order of the production tasks according to the production scheduling factors of the production tasks; the production scheduling factors include priority, delivery date, and availability of production resources.
5. A method for order management in warp knitting industry according to claim 4, characterized in that: The allocation principles include: 1) giving priority to the use of in-product resources; 2) Give priority to using work-in-progress resources with a longer inventory time; 3) Give priority to using the most matching in-process resources; The allocation algorithm is a genetic algorithm, and the steps include: 1) Define the problem as maximizing production efficiency, minimizing costs, or optimizing equipment utilization; 2) Using binary coding to represent a resource allocation scheme, each gene bit represents the allocation of a resource in a specific process; 3) Randomly generate a set of initial solutions that meet the constraints as the population; 4) Design a fitness function to evaluate the quality of each individual; 5) Select excellent individuals for reproduction according to the fitness function value; 6) Repeat the genetic operation until the preset number of iterations is reached or the fitness function value no longer increases significantly.
6. A method for order management in the warp knitting industry according to any one of claims 1 to 5, characterized in that: The step S5 comprises the following sub-steps: S51. Monitor the operating status and production progress of production equipment through sensors and cameras, and upload the monitoring data to the back-end control system; S52, implementing progress monitoring through a mobile phone APP or mini program, wherein the progress monitoring includes cloth drop monitoring, cloth patchwork monitoring, and cloth head monitoring; S53. Analyze real-time monitoring and progress monitoring data to identify abnormal situations and potential risks in the production process; establish an early warning system to automatically issue an early warning signal when the monitoring data reaches the preset threshold or trigger condition, reminding relevant personnel to take timely measures to make adjustments; S54. Use visualization technology to display real-time monitoring data and analysis results in a visual form; S55. Adjust production plans based on real-time monitoring data and early warning signals.
7. A device for order management in the warp knitting industry, characterized in that: Includes the following modules: 1) Order receiving module: used to receive orders and analyze order parameters; 2) Production capacity assessment module: used to assess the production capacity of the enterprise and prepare corresponding production resources based on the results of order analysis; 3) Production scheduling module: used to formulate production scheduling for orders; 4) Production scheduling and task allocation module: According to the production schedule, production tasks are allocated to specific production lines or workers, and responsibilities and task completion time are clearly defined; 5) Production process monitoring and adjustment module: used to monitor production progress and quality during the production process and make deviation adjustments in a timely manner; 6) Finished product inspection and warehousing module: used to inspect the quality of finished products after production is completed and send the finished products to the warehouse for storage and management; 7) Shipping and delivery module: used to arrange shipping time and logistics method according to customer's delivery date requirements.
8. An electronic device comprising: Memory for storing computer programs; A processor is used to execute the program stored in the memory to implement the method steps described in any one of claims 1-6.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps described in any one of claims 1 to 6 are implemented.