Polyester fiber dyeing method

Abstract

The invention relates to a polyester fiber dyeing method which comprises the following steps: acquiring order information in real time, and generating a dyeing demand; based on the dyeing demand, matching and determining a dyeing scheme through a preset scheme matching model; determining a dyeing intelligent control item based on the order information and the dyeing scheme, and performing matching to generate an intelligent regulation and control scheme; generating a scheduling instruction according to the dyeing scheme, and sending the scheduling instruction to a worker to convey the raw materials to dyeing equipment; sending the equipment parameter information to the dyeing equipment for parameter setting; and generating a dyeing process instruction according to the dyeing scheme, controlling the dyeing equipment to dye the polyester fibers according to the dyeing process flow, performing data acquisition on the dyeing monitoring items in the dyeing process, and generating a regulation and control instruction in real time according to the dyeing regulation and control flow to regulate the parameters of the dyeing equipment so as to prepare the polyester fibers required by the order. According to the method, enterprise resource allocation can be optimized, and the effect of facilitating improvement of polyester dyeing efficiency and dyeing quality is achieved.

Description

Technical Field

[0001] The present application relates to the field of polyester dyeing, and in particular to a polyester fiber dyeing method. Background Art

[0002] Polyester is the simplest of the three major synthetic fibers and is relatively cheap. In addition, it is strong and durable, elastic, not easy to deform, corrosion-resistant, insulating, crisp, easy to wash and dry quickly, so it is loved by people. Polyester is a synthetic fiber among textile fibers. In the production and processing of polyester fibers, after the polyester fibers are prepared, they are usually dyed according to market needs.

[0003] Existing polyester dyeing methods mainly include hot melt dyeing, high temperature and high pressure dyeing, carrier dyeing and disperse dye dyeing. Polyester fibers for different dyeing requirements often need to go through complicated preparations to conduct research and development verification to determine the polyester dyeing scheme, which often requires a lot of manpower and material resources, and is prone to uneven dyeing, poor color fastness, insufficient dyeing depth and other problems due to insufficient dyeing schemes. And with the development of science and technology, during the dyeing process, various sensors are installed to monitor dyeing parameters in real time, such as dye liquor temperature, pH value, dye concentration, fabric humidity, etc., to achieve intelligent control of the dyeing process, which can further improve the dyeing quality. However, different control items are based on the differences in their control methods, and the manpower and material resources they consume are often different. Therefore, how to balance the difficulty of intelligent control for different dyeing orders to ensure the cost of the enterprise is also a problem to be solved. Summary of the invention

[0004] In order to solve the above problems, the present application provides a polyester fiber dyeing method.

[0005] In a first aspect, the present application provides a polyester fiber dyeing method, which adopts the following technical solution:

[0006] A polyester fiber dyeing method comprises the following steps:

[0007] Acquire order information in real time and generate dyeing requirements; the order information includes polyester finished product information, purchase unit information, purchase quantity information and order level information; the dyeing requirements include polyester raw material information, dyeing color requirements and dyeing performance requirements;

[0008] Based on dyeing requirements, a dyeing scheme is determined by matching a preset scheme matching model; the scheme matching model is a machine learning model obtained by iterative training of historical dyeing data; the dyeing scheme includes at least one raw material, at least one dyeing equipment, equipment parameter information and dyeing process flow information;

[0009] Determine the dyeing intelligent control items based on the order information and the dyeing scheme, and match and generate an intelligent control scheme; the intelligent control scheme report includes at least one dyeing monitoring item and dyeing control process information;

[0010] Generate scheduling instructions according to the dyeing plan and send them to the staff to transport the raw materials to the dyeing equipment;

[0011] Send the equipment parameter information to the dyeing equipment for parameter setting;

[0012] Generate dyeing process instructions according to the dyeing plan, control the dyeing equipment to dye the polyester fiber according to the dyeing process flow, collect data on dyeing monitoring items during the dyeing process, and generate control instructions in real time according to the dyeing control process to adjust the dyeing equipment parameters to produce the polyester fiber required for the order.

[0013] Preferably, the dyeing performance requirements include one or more of color fastness, color accuracy, uniformity and degree of fiber damage, the color fastness including rubbing fastness, washing fastness, sunlight fastness and sublimation fastness; the color accuracy includes color brightness, color hue, color saturation and color depth.

[0014] Preferably, the step of determining the dyeing scheme based on the dyeing requirement by matching a preset scheme matching model specifically comprises the following steps:

[0015] Based on the dyeing requirement, at least one backup solution that meets the dyeing requirement is determined by matching a preset solution matching model;

[0016] Calculate the scheme score of each alternative scheme by using a preset scheme score calculation formula;

[0017] The alternative plans are sorted based on their scores, and the alternative plan with the highest score is selected as the target plan.

[0018] Preferably, the scheme scoring calculation formula is specifically:

[0019]

[0020] Among them, X 1 is the preset cost scoring coefficient, A is the preset unit base cost, and A i is the unit product cost of the ith alternative; X 2 is the preset cost scoring coefficient, B is the preset dyeing benchmark time per unit product, and B i is the dyeing time of the unit product of the ith alternative; 3 is the preset environmental protection factor, C i is the dyeing environmental protection score of the ith alternative, C is the preset dyeing environmental protection benchmark score; X4 is the preset dyeing performance coefficient, n is the total number of performance requirements in the dyeing performance requirements, D ik is the performance value of the kth performance requirement item of the ith alternative solution, E k is the demand value of the kth performance requirement item in the dyeing performance requirement;

[0021] m is the total number of environmental protection indicators of the ith alternative plan, w ij is the pre-set weight of the jth environmental indicator of the ith backup plan, s ij The j-th environmental indicator score of the ith alternative plan.

[0022] Preferably, the step of determining the dyeing intelligent control items based on the order information and the dyeing scheme, and matching and generating the intelligent control scheme specifically comprises the following steps:

[0023] Outputting control items that can be controlled in the dyeing scheme and their adjustment difficulty levels through a preset control analysis model according to the dyeing scheme; the control analysis model is a neural network model obtained by iterative training through historical dyeing control data;

[0024] Select control items based on order information matching to generate dyeing intelligent control items;

[0025] Based on the intelligent control items, an intelligent control plan is generated by matching the pre-set control analysis model.

[0026] Preferably, the method of generating dyeing intelligent control items by selecting control items based on order information matching specifically includes the following steps:

[0027] Determine whether the order is marked with an order level in the order level information according to the order information;

[0028] If it is marked, the control items corresponding to the difficulty level of adjustment are selected according to the preset level comparison table based on the order level, and the dyeing intelligent control items are packaged and generated;

[0029] If not marked, the order level is calculated based on the order information using the preset profit level calculation formula;

[0030] Then, based on the order level, the control items with corresponding adjustment difficulty levels are selected according to the preset level comparison table, and the dyeing intelligent control items are packaged and generated.

[0031] Preferably, the step of calculating the order level based on the order information by using a preset profit level calculation formula specifically includes the following steps:

[0032] Obtain the total profit value E of the order based on the order information, and determine the total profit level e of the order according to the preset total profit value comparison table;

[0033] Calculate the unit product profit value F of the order based on the order information, and determine the unit profit level f of the order according to the preset unit profit value comparison table;

[0034] The order level is calculated using a preset profit level calculation formula, which is specifically:

[0035]

[0036] Among them, L1 is the total profit weight, L2 is the unit profit weight, and L1+L2=1. Both L1 and L2 are set by managers.

[0037] In a second aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0038] A computer-readable storage medium, characterized in that it stores a computer program that can be loaded by a processor and execute any of the above methods.

[0039] In summary, the present application includes at least one of the following beneficial technical effects:

[0040] 1. Based on dyeing requirements, the scheme matching model is used to intelligently decide on a dyeing scheme that meets the order requirements, saving manpower and material resources, and avoiding the phenomenon of uneven dyeing, poor color fastness, and insufficient dyeing depth due to insufficient dyeing schemes. This realizes the automation of polyester dyeing and helps improve polyester dyeing efficiency and quality;

[0041] 2. Based on the dyeing scheme, the historical data of the scheme is analyzed through the control analysis model, and the control items with possible improvement are output. Then, based on the actual situation and the order profit, the control items with appropriate intelligent control difficulty are selected as the dyeing intelligent control items, and then the intelligent control scheme is generated by decision. On the basis of consolidating the production cost of the enterprise, the dyeing process can be improved through intelligent control, which is helpful to improve product quality and enhance the competitiveness of the enterprise;

[0042] 3. Score each alternative plan from the four perspectives of production cost, production efficiency, product performance, and the inevitable environmental protection of fiber dyeing, so as to make a comprehensive decision based on multiple factors, which will help improve the scientificity and accuracy of the plan scoring and ensure the company's production efficiency and production profit margin on the basis of meeting the dyeing needs of the order. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 In the embodiment of the present application;

[0044] Figure 2 In the embodiment of the present application;

[0045] Figure 3 In the embodiment of the present application;

[0046] Figure 4 In the embodiment of the present application;

[0047] Figure 5 It is in the embodiment of this application. DETAILED DESCRIPTION

[0048] The following is combined with Figure 1-Figure 5 This application is described in further detail.

[0049] The present application discloses a method for dyeing polyester fibers. Figure 1 , a polyester fiber dyeing method, comprising the following steps:

[0050] S1. Obtaining requirements: Obtaining order information in real time and generating dyeing requirements; the order information includes polyester finished product information, purchase unit information, purchase quantity information and order level information; the dyeing requirements include polyester raw material information, dyeing color requirements and dyeing performance requirements;

[0051] S2. Determine a scheme: Based on dyeing requirements, determine a dyeing scheme by matching a preset scheme matching model; the scheme matching model is a machine learning model obtained by iterative training of historical dyeing data. It should be noted that the specific training steps of the machine learning model are prior art and are not described here; the dyeing scheme includes at least one raw material, at least one dyeing equipment, equipment parameter information, and dyeing process flow information;

[0052] S3, intelligent control determination: based on the order information and the dyeing scheme, the dyeing intelligent control items are determined, and the intelligent control scheme is generated by matching; the intelligent control scheme report includes at least one dyeing monitoring item and dyeing control process information;

[0053] S4, raw material dispatching: generate dispatching instructions according to the dyeing plan and send them to the staff to transport the raw materials to the dyeing equipment;

[0054] S5, parameter setting: sending the equipment parameter information to the dyeing equipment for parameter setting;

[0055] S6, intelligent control dyeing: Generate dyeing process instructions according to the dyeing scheme, control the dyeing equipment to dye the polyester fiber according to the dyeing process, collect data on the dyeing monitoring items during the dyeing process, and generate control instructions in real time according to the dyeing control process to adjust the parameters of the dyeing equipment to obtain the polyester fiber required for the order. Through the above steps, based on the dyeing needs, the scheme matching model makes intelligent decisions to meet the order requirements, saving manpower and material resources, avoiding the phenomenon of uneven dyeing, poor color fastness, and insufficient dyeing depth due to insufficient dyeing schemes, realizing the automation of polyester dyeing, and helping to improve the efficiency and quality of polyester dyeing. At the same time, based on the dyeing scheme, the control analysis model analyzes the historical data of the scheme, outputs the control items that may be improved, and then selects the control items with appropriate intelligent control difficulty as the dyeing intelligent control items based on the actual situation and the order profit, and then decides to generate an intelligent control scheme, which can improve the dyeing process with intelligent control on the basis of solid enterprise production costs, which helps to improve product quality and enhance enterprise competitiveness.

[0056] The dyeing performance requirements include one or more of color fastness, color accuracy, uniformity and degree of fiber damage. The color fastness includes rubbing fastness, washing fastness, sunlight fastness and sublimation fastness; the color accuracy includes color brightness, color hue, color saturation and color depth.

[0057] Reference Figure 2 The dyeing scheme is determined based on the dyeing requirements by matching a preset scheme matching model, and specifically includes the following steps:

[0058] A1. Matching scheme: Based on the dyeing requirement, at least one backup scheme that meets the dyeing requirement is determined through matching of a preset scheme matching model;

[0059] A2. Calculate the score: Calculate the score of each alternative plan using the preset plan score calculation formula;

[0060] A3. Select a plan: Sort the alternative plans based on their scores, and select the alternative plan with the highest score as the target plan.

[0061] The calculation formula for the above scheme score is as follows:

[0062]

[0063] Among them, X 1 is the preset cost scoring coefficient, A is the preset unit base cost, and A i is the unit product cost of the ith alternative; X 2 is the preset cost scoring coefficient, B is the preset dyeing benchmark time per unit product, and B iis the dyeing time of the unit product of the ith alternative; 3 is the preset environmental protection factor, C i is the dyeing environmental protection score of the ith alternative, C is the preset dyeing environmental protection benchmark score; X 4 is the preset dyeing performance coefficient, n is the total number of performance requirements in the dyeing performance requirements, D ik is the performance value of the kth performance requirement item of the ith alternative solution, E k is the demand value of the kth performance requirement item in the dyeing performance requirement;

[0064] Among them, m is the total number of environmental protection indicators of the ith alternative plan, w ij is the pre-set weight of the jth environmental indicator of the ith backup plan, s ij Score the jth environmental index of the ith alternative plan. The scoring rules for each environmental index are set according to industry environmental standards and policies. Score each alternative plan from the four options of production cost, production efficiency, product performance, and the inevitable environmental protection of fiber dyeing, so as to achieve a comprehensive decision-making based on multiple factors, which is helpful to improve the scientificity and accuracy of the plan scoring, and ensure the production efficiency and production profit margin of the enterprise on the basis of meeting the dyeing needs of the order; at the same time, by setting a separate dyeing environmental scoring calculation formula, it can adapt to the scoring rules of different dyeing plans, which helps enterprises to assume environmental protection obligations.

[0065] Referring to FIG. 3 , the dyeing intelligent control items are determined based on the order information and the dyeing scheme, and the matching and generation of the intelligent control scheme specifically include the following steps:

[0066] B1. Outputting the control items and their control difficulty levels that can be controlled in the dyeing scheme through a preset control analysis model according to the dyeing scheme; the control analysis model is a neural network model obtained by iterative training through historical dyeing control data. The specific training steps of the neural network model are prior art and will not be described in detail here;

[0067] B2. Select control items based on order information matching to generate dyeing intelligent control items;

[0068] B3. Generate intelligent control schemes through matching with preset control analysis models based on intelligent control items. Based on the dyeing scheme, the historical data of the scheme is analyzed through the control analysis model, and the control items with possible improvements and the difficulty of adjustment are output. Then, based on the actual situation and order profit, the control items with appropriate intelligent control difficulty are selected as the dyeing intelligent control items, and then the intelligent control scheme is generated by decision. It can improve the dyeing process with intelligent control on the basis of solid enterprise production costs, which is helpful to improve product quality and enhance enterprise competitiveness.

[0069] Reference Figure 4The method of selecting control items based on order information matching to generate dyeing intelligent control items specifically includes the following steps:

[0070] C1. Determine whether the order level is marked in the order level information according to the order information;

[0071] C2. Package and generate dyeing intelligent control items: If marked, select the control items with the corresponding adjustment difficulty level according to the preset level comparison table based on the order level, and package and generate dyeing intelligent control items;

[0072] C3. Calculate order level: If not marked, the order level is calculated based on the order information using the preset profit level calculation formula;

[0073] C4. Package and generate dyeing intelligent control items: Based on the order level, select the control items with the corresponding adjustment difficulty level according to the preset level comparison table, and package and generate dyeing intelligent control items. Grading each order based on the order profit, while leaving managers with level adjustment space, can effectively balance the difficulty of intelligent control of dyeing schemes, ensure the profit space of the enterprise, improve dyeing efficiency and quality, enable enterprises to adapt to technological development, and seamlessly connect advanced production concepts, which is conducive to the healthy development of enterprises.

[0074] Reference Figure 5 , the step of calculating the order level based on the order information by using a preset profit level calculation formula specifically includes the following steps:

[0075] D1. Determine the total profit level of the order: obtain the total profit value E of the order based on the order information, and determine the total profit level e of the order according to the preset total profit value comparison table;

[0076] D2. Determine the unit profit level of the order: Calculate the unit product profit value F of the order based on the order information, and determine the unit profit level f of the order according to the preset unit profit value comparison table;

[0077] D3. Calculate order level: Calculate order level using a preset profit level calculation formula. The profit level calculation formula is as follows:

[0078]

[0079] Among them, L1 is the total profit weight, L2 is the unit profit weight, and L1+L2=1, and L1 and L2 are set by management personnel. Through the above steps, starting from the total profit of the order and the profit of the single product, the order level is intelligently determined, which helps to improve the rationality of the order level setting, helps enterprises optimize resource allocation, and thus achieve a win-win situation for enterprises and users.

[0080] The embodiment of the present application also discloses a computer-readable storage medium, which stores a computer program that can be loaded by a processor and executed as in the above method. The computer-readable storage medium includes, for example: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0081] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the scope of protection of the invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on these embodiments, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in this field can still combine, add, delete or make other adjustments to the features in the various embodiments of the present invention according to the circumstances without conflict, without making creative work, so as to obtain different other technical solutions that do not deviate from the concept of the present invention in essence, and these technical solutions also belong to the scope of protection of the present invention.

Claims

1. A polyester fiber dyeing method, characterized in that: The following steps are involved: Acquire order information in real time and generate dyeing requirements; the order information includes polyester finished product information, purchase unit information, purchase quantity information and order level information; the dyeing requirements include polyester raw material information, dyeing color requirements and dyeing performance requirements; Based on dyeing requirements, a dyeing scheme is determined by matching a preset scheme matching model; the scheme matching model is a machine learning model obtained by iterative training of historical dyeing data; the dyeing scheme includes at least one raw material, at least one dyeing equipment, equipment parameter information and dyeing process flow information; Determine the dyeing intelligent control items based on order information and dyeing scheme, and match and generate intelligent control scheme; The intelligent control scheme report includes at least one dyeing monitoring item and dyeing control process information; Generate scheduling instructions according to the dyeing plan and send them to the staff to transport the raw materials to the dyeing equipment; Send the equipment parameter information to the dyeing equipment for parameter setting; Generate dyeing process instructions according to the dyeing plan, control the dyeing equipment to dye the polyester fiber according to the dyeing process flow, collect data on dyeing monitoring items during the dyeing process, and generate control instructions in real time according to the dyeing control process to adjust the dyeing equipment parameters to produce the polyester fiber required for the order.

2. A polyester fiber dyeing method according to claim 1, characterized in that: The dyeing performance requirements include one or more of color fastness, color accuracy, uniformity and fiber damage degree. The color fastness includes rubbing fastness, washing fastness, sunlight fastness and sublimation fastness; the color accuracy includes color brightness, color hue, color saturation and color depth.

3. A polyester fiber dyeing method according to claim 1, characterized in that: The method of determining the dyeing scheme based on the dyeing requirement by matching the preset scheme matching model specifically includes the following steps: Based on the dyeing requirement, at least one backup solution that meets the dyeing requirement is determined by matching a preset solution matching model; Calculate the scheme score of each alternative scheme by using a preset scheme score calculation formula; The alternative plans are sorted based on their scores, and the alternative plan with the highest score is selected as the target plan.

4. A polyester fiber dyeing method according to claim 3, characterized in that: The specific calculation formula for the scheme score is: Among them, X1 is the preset cost scoring coefficient, A is the preset unit benchmark cost, and A i is the unit product cost of the ith alternative; X2 is the preset cost scoring coefficient, B is the preset unit product dyeing benchmark time, B i is the dyeing time of the unit product of the ith alternative; X3 is the preset environmental protection coefficient, C i is the dyeing environmental protection score of the ith alternative plan, C is the preset dyeing environmental protection benchmark score; X4 is the preset dyeing performance coefficient, n is the total number of performance requirements in the dyeing performance requirement, D ik is the performance value of the kth performance requirement item of the ith alternative solution, E k is the demand value of the kth performance requirement item in the dyeing performance requirement; m is the total number of environmental protection indicators of the ith alternative plan, w ij is the pre-set weight of the jth environmental indicator of the ith backup plan, s ij The j-th environmental indicator score of the ith alternative plan.

5. A polyester fiber dyeing method according to claim 1, characterized in that: Determining the dyeing intelligent control items based on the order information and the dyeing scheme, and matching and generating the intelligent control scheme specifically include the following steps: Outputting control items that can be controlled in the dyeing scheme and their adjustment difficulty levels through a preset control analysis model according to the dyeing scheme; the control analysis model is a neural network model obtained by iterative training through historical dyeing control data; Select control items based on order information matching to generate dyeing intelligent control items; Based on the intelligent control items, an intelligent control plan is generated by matching the pre-set control analysis model.

6. A polyester fiber dyeing method according to claim 5, characterized in that: The method of selecting control items based on order information matching to generate dyeing intelligent control items specifically includes the following steps: Determine whether the order is marked with an order level in the order level information according to the order information; If it is marked, the control items corresponding to the difficulty level of adjustment are selected according to the preset level comparison table based on the order level, and the dyeing intelligent control items are packaged and generated; If not marked, the order level is calculated based on the order information using the preset profit level calculation formula; Then, based on the order level, the control items with corresponding adjustment difficulty levels are selected according to the preset level comparison table, and the dyeing intelligent control items are packaged and generated.

7. A polyester fiber dyeing method according to claim 6, characterized in that: The method of calculating the order level based on the order information by using a preset profit level calculation formula specifically includes the following steps: Obtain the total profit value E of the order based on the order information, and determine the total profit level e of the order according to the preset total profit value comparison table; Calculate the unit product profit value F of the order based on the order information, and determine the unit profit level f of the order according to the preset unit profit value comparison table; The order level is calculated using a preset profit level calculation formula, which is specifically: Among them, L1 is the total profit weight, L2 is the unit profit weight, and L1+L2=1. Both L1 and L2 are set by managers.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and executes the method according to any one of claims 1 to 7.

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