Sole spraying control method and system for shoemaking production line
By collecting and analyzing product model and interference parameter data, determining the sole spraying parameters, and introducing correlation coefficients to evaluate the spraying stability, the problem of inconsistent spraying effects on the shoemaking production line is solved, and efficient quality control and cost optimization are achieved.
Patent Information
- Application Number
- CN202510564425.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-30
- Publication Date
- 2025-07-25
AI Technical Summary
The sole spraying process on the existing shoemaking production line lacks accurate data support and systematic control methods, resulting in poor consistency of spraying effects and uneven product quality, which increases production costs and quality control difficulties.
By collecting product model and interference parameter data, the spraying parameter data is determined, including spraying angle, discharge speed, movement speed, spraying times and drying parameters, and the shape stability coefficient, material stability coefficient, comprehensive impact coefficient of interference factors and operator skill variability coefficient are introduced to quantify the stability of the spraying process and dynamically adjust the sampling ratio.
It realizes refined control of the spraying process, ensures consistency of product quality, and reduces inspection costs.
Smart Images
Figure CN120362069A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of sole spraying, and specifically relates to a sole spraying control method and system for a shoe production line. Background Art
[0002] In the shoe-making industry, sole spraying is a key link in the production process. It not only affects the appearance quality of shoes, but also directly relates to performance indicators such as the wear resistance, anti-slip property, and comfort of the soles. The traditional sole spraying process often relies on the experience and intuitive judgment of operators, lacking precise data support and systematic control methods. This makes it difficult to ensure the consistency of the spraying effect, resulting in uneven product quality, increasing production costs and the difficulty of quality control. In addition, product parameters such as sole material, complexity, coating thickness, and paint absorption rate, as well as interference factors such as operator proficiency, ambient temperature, and ambient humidity, will all have a significant impact on the spraying effect.
[0003] However, in the existing production methods, these factors are often ignored or roughly adjusted based on experience, making it difficult to achieve refined control of the spraying process. At the same time, due to the lack of an effective evaluation method for the stability of the spraying process, a unified sampling inspection ratio is often adopted on the production line, which may not only lead to missed inspections of quality problems, but also increase unnecessary inspection costs. Therefore, it is necessary to provide a sole spraying control method and system for a shoe production line, aiming to solve the above problems. Summary of the Invention
[0004] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a sole spraying control method and system for a shoe production line to solve the problems in the above background art.
[0005] The present invention is implemented as follows. A sole spraying control method for a shoe production line, the method includes the following steps: Collect the product model, and determine the product parameter data according to the product model. The product parameter data includes sole material, sole complexity, coating thickness, and paint absorption rate; Collect the interference parameter data. The interference parameter data includes operator proficiency, ambient temperature, and ambient humidity; Determine the spraying parameter data according to the product parameter data and the interference parameter data. The spraying parameter data includes spraying angle, discharge speed, moving speed, spraying times, and drying parameters; Determine the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and the interference parameter data; Evaluate the spraying stability base number and key inspection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, and determine the sampling ratio according to the spraying stability base number.
[0006] As a further solution of the present invention: The step of determining the spraying parameter data according to the product parameter data and the interference parameter data specifically includes: Determine the spraying angle according to the sole complexity, and the relationship in the corresponding process is: θ = 45° + 0.5° × Cp; Wherein, Cp is the sole complexity, and θ is the spraying angle; Determine the material discharge speed according to the sole material and the paint absorption rate, and the relationship in the corresponding process is: Vo = (Vb / Ab) × Mf; Wherein, Vb is the basic material discharge speed, Ab is the paint absorption rate, Mf is the sole material coefficient, and Vo is the material discharge speed; Determine the moving speed according to the sole complexity and the operator proficiency, and the relationship in the corresponding process is: Vm = (Ve × Sf) / (1 + Cp); Wherein, Ve is the basic moving speed, Sf is the operator proficiency, and Vm is the moving speed; Determine the spraying times according to the sole material and the coating thickness, and the relationship in the corresponding process is: N = (Rt / St) × Ma; Wherein, Rt is the coating thickness, St is the average thickness of a single spraying, Ma is the material adjustment coefficient, and N is the spraying times; Determine the drying parameters according to the sole material, environmental temperature, and environmental humidity. The drying parameters include drying temperature and drying duration.
[0007] As a further solution of the present invention: The step of determining the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and the interference parameter data specifically includes: Determine the shape stability coefficient according to the sole complexity, and determine the material stability coefficient according to the sole material; Determine the operator skill variability coefficient according to the operator proficiency, and determine the comprehensive influence coefficient of interference factors according to the environmental temperature and environmental humidity.
[0008] As a further solution of the present invention: The step of evaluating the spraying stability base number and key inspection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient specifically includes: The spraying stability base number is calculated based on the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient. The corresponding relationship in the process is as follows: SI = (Ms × Ss) / (If × Sv); Where, Ss is the shape stability coefficient, Ms is the material stability coefficient, If is the comprehensive influence coefficient of interference factors, Sv is the operator skill variability coefficient, and SI is the spraying stability base number; The shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient are input into the coefficient item library, and the matching detection items are output; All the detection items are summarized to obtain the key detection items.
[0009] Another object of the present invention is to provide a sole spraying control system for a shoe production line. The system includes: A product parameter data module for collecting the product model and determining the product parameter data according to the product model. The product parameter data includes sole material, sole complexity, coating thickness, and paint absorption rate; An interference parameter data module for collecting interference parameter data. The interference parameter data includes operator proficiency, environmental temperature, and environmental humidity; A spraying parameter data module for determining the spraying parameter data according to the product parameter data and the interference parameter data. The spraying parameter data includes spraying angle, material discharge speed, moving speed, spraying times, and drying parameters; A correlation coefficient determination module for determining the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and the interference parameter data; A spraying stability base number module for evaluating the spraying stability base number and key detection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, and determining the sampling ratio according to the spraying stability base number.
[0010] As a further solution of the present invention: The spraying parameter data module includes: A spraying angle calculation unit for determining the spraying angle according to the sole complexity. The corresponding relationship in the process is as follows: θ = 45° + 0.5° × Cp; Where, Cp is the sole complexity and θ is the spraying angle; A material discharge speed calculation unit for determining the material discharge speed according to the sole material and the paint absorption rate. The corresponding relationship in the process is as follows: Vo = (Vb / Ab) × Mf; Among them, Vb is the basic discharging speed, Ab is the paint absorption rate, Mf is the sole material coefficient, and Vo is the discharging speed; A moving speed calculation unit, which is used to determine the moving speed according to the sole complexity and the operator's proficiency. The relational formula existing in the corresponding process is: Vm = (Ve × Sf) / (1 + Cp); Among them, Ve is the basic moving speed, Sf is the operator's proficiency, Vm is the moving speed, A spraying times calculation unit, which is used to determine the spraying times according to the sole material and the coating thickness. The relational formula existing in the corresponding process is: N = (Rt / St) × Ma; Among them, Rt is the coating thickness, St is the average thickness of a single spraying, Ma is the material adjustment coefficient, and N is the spraying times; A drying parameter determination unit, which is used to determine the drying parameters according to the sole material, the ambient temperature, and the ambient humidity. The drying parameters include the drying temperature and the drying duration.
[0011] As a further solution of the present invention: The correlation coefficient determination module includes: A shape and material stability unit, which is used to determine the shape stability coefficient according to the sole complexity and determine the material stability coefficient according to the sole material; A skill comprehensive influence unit, which is used to determine the operator skill variability coefficient according to the operator's proficiency and determine the comprehensive influence coefficient of interference factors according to the ambient temperature and the ambient humidity.
[0012] As a further solution of the present invention: The spraying stability base number module includes: A spraying stability base number unit, which is used to calculate the spraying stability base number according to the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient. The relational formula existing in the corresponding process is: SI = (Ms × Ss) / (If × Sv); Among them, Ss is the shape stability coefficient, Ms is the material stability coefficient, If is the comprehensive influence coefficient of interference factors, Sv is the operator skill variability coefficient, and SI is the spraying stability base number; An information input and matching unit, which is used to input the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient into the coefficient item library and output the matching detection items; A key detection item unit, which is used to summarize all the detection items to obtain the key detection items.
[0013] Compared with the prior art, the beneficial effects of the present invention are: The present invention accurately determines the spraying parameter data by collecting and analyzing the product parameter data and interference parameter data, realizing the refined control of the spraying process. The method also quantitatively evaluates the stability of the spraying process by introducing evaluation indexes such as the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, so as to dynamically adjust the sampling inspection ratio according to the spraying stability base number, which not only ensures the consistency of product quality but also reduces the detection cost. Brief Description of the Drawings
[0014] Figure 1 It is a flowchart of a sole spraying control method for a shoe-making production line. Detailed Embodiment
[0015] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.
[0016] The following describes in detail the specific implementation of the present invention with reference to specific embodiments.
[0017] As Figure 1 shown, an embodiment of the present invention provides a sole spraying control method for a shoe-making production line. The method includes the following steps: S100, collect the product model, and determine the product parameter data according to the product model. The product parameter data includes sole material, sole complexity, coating thickness, and paint absorption rate; S200, collect the interference parameter data. The interference parameter data includes operator proficiency, environmental temperature, and environmental humidity; S300, determine the spraying parameter data according to the product parameter data and the interference parameter data. The spraying parameter data includes spraying angle, material discharge speed, moving speed, spraying times, and drying parameters; S400, determine the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and the interference parameter data; S500, evaluate the spraying stability base number and key inspection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, and determine the sampling inspection ratio according to the spraying stability base number.
[0018] It should be noted that product parameters such as sole material, complexity, coating thickness, and paint absorption rate, as well as interference factors such as operator proficiency, ambient temperature, and ambient humidity, will all have a significant impact on the spraying effect. However, in the existing production methods, these factors are often overlooked or roughly adjusted based on experience, making it difficult to achieve fine control of the spraying process.
[0019] In the embodiments of the present invention, first, the product model being produced is determined, and product parameter data is determined according to the product model. The product model and the product parameter data are in one-to-one correspondence. Specifically, the product parameter data includes sole material, sole complexity, coating thickness, and paint absorption rate. At the same time, interference parameter data also needs to be collected. Specifically, the interference parameter data includes operator proficiency at the sole spraying station, ambient temperature in the workshop, and ambient humidity. Then, the embodiments of the present invention will automatically determine spraying parameter data according to the product parameter data and the interference parameter data. Specifically, the spraying parameter data here includes spraying angle, material discharge speed, moving speed, number of spraying times, and drying parameters. In this way, the accurate determination of spraying parameters is achieved, improving the consistency of the spraying effect and product quality. Then, the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient are determined according to the product parameter data and the interference parameter data. Then, the spraying stability base number and key inspection items are automatically evaluated according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient. By introducing quantitative evaluation indicators, the effective evaluation of the stability of the spraying process is realized, providing a scientific basis for dynamically adjusting the sampling inspection ratio. Finally, the sampling inspection ratio is determined according to the spraying stability base number. It is easy to understand that the higher the spraying stability base number, the lower the sampling inspection ratio.
[0020] As a preferred embodiment of the present invention, the step of determining spraying parameter data according to the product parameter data and the interference parameter data specifically includes: S301, determine the spraying angle according to the sole complexity, and the relationship existing in the corresponding process is: θ = 45° + 0.5°×Cp; Where, Cp is the sole complexity, and θ is the spraying angle; S302, determine the material discharge speed according to the sole material and the paint absorption rate, and the relationship existing in the corresponding process is: Vo = (Vb / Ab)×Mf; Where, Vb is the basic material discharge speed, Ab is the paint absorption rate, Mf is the sole material coefficient, and Vo is the material discharge speed; S303, determine the moving speed according to the sole complexity and operator proficiency, and the relationship existing in the corresponding process is: Vm = (Ve×Sf) / (1 + Cp); Among them, Ve is the basic moving speed, Sf is the operator proficiency, and Vm is the moving speed; S304. Determine the spraying times according to the sole material and coating thickness. The relational formula existing in the corresponding process is: N = (Rt / St) × Ma; Among them, Rt is the coating thickness, St is the average thickness of a single spraying, Ma is the material adjustment coefficient, and N is the spraying times; S305. Determine the drying parameters according to the sole material, ambient temperature, and ambient humidity. The drying parameters include the drying temperature and drying duration.
[0021] Specifically, to determine the drying parameters according to the sole material, ambient temperature, and ambient humidity, where the drying parameters include the drying temperature and drying duration, the specific steps are as follows: Perform a natural logarithm function process on the material adjustment coefficient to obtain the material influence factor; Superimpose a unit value as compensation, determine the measured temperature value through the ambient temperature, and determine the reference temperature value through the material; Perform a ratio calculation on the measured temperature value and the reference temperature value to obtain the temperature ratio factor; Determine the measured humidity value through the ambient humidity, determine the reference humidity value through the material, and perform a ratio calculation on the measured humidity value and the reference humidity value to obtain the reference humidity value; Perform a standardization process on the reference humidity value to obtain the standardized reference humidity value, and then perform a square amplification process on the standardized reference humidity value to obtain the humidity compensation coefficient; Perform a multiplication operation on the material influence factor, temperature ratio factor, and humidity compensation coefficient to obtain the set value of the drying temperature; Perform an exponential correction operation on the material adjustment coefficient to obtain the material correction basic parameter; Perform a non - linear amplification conversion process on the measured humidity value using the natural exponential function to obtain the humidity - time compensation factor; Determine the temperature correction parameter through the set value of the drying temperature; Under the condition of ensuring the distribution effectiveness by superimposing the unit value, perform a linear attenuation process on the measured temperature value using the temperature correction parameter to obtain the temperature acceleration factor; Perform a positive multiplication operation on the material correction basic parameter and the humidity - time compensation factor to obtain the intermediate time quantity after humidity compensation; Perform a reverse division operation on the intermediate time quantity after humidity compensation and the temperature acceleration factor to obtain the optimized time quantity after ambient temperature correction; Obtain the reference drying time through the product parameters, and perform a linear superposition on the optimized time quantity after ambient temperature correction and the reference drying time to obtain the drying parameters.
[0022] In the embodiments of the present invention, the spraying angle is usually adjusted according to the complexity of the sole shape. A more complex sole requires a more precise spraying angle to avoid paint accumulation. The spraying angle θ = 45° + 0.5° × Cp, where Cp is the sole complexity and Cp ranges from 1 to 10. The discharging speed is affected by the sole material and the paint absorption rate. Materials with a high absorption rate require a slower discharging speed to avoid overspraying. The discharging speed Vo = (Vb / Ab) × Mf, where Vb is the basic discharging speed, Ab is the paint absorption rate, and Mf is the sole material coefficient. For example, Mf is 1.0 for rubber and 0.8 for leather. The moving speed needs to be coordinated with the discharging speed to ensure a uniform coating. At the same time, considering the operator's proficiency, operators with a higher proficiency can appropriately increase the moving speed. The moving speed Vm = (Ve × Sf) / (1 + Cp), where Ve is the basic moving speed (a fixed value) and Sf is the operator's proficiency (ranging from 1.0 to 1.5). The number of spraying times mainly depends on the coating thickness requirement and the sole material. The number of spraying times N, N = (Rt / St) × Ma, where Rt is the coating thickness, St is the average thickness of a single spraying, and Ma is the material adjustment coefficient (adjusted according to the material absorption characteristics). Finally, the drying parameters are determined according to the sole material, ambient temperature, and ambient humidity.
[0023] As a preferred embodiment of the present invention, the step of determining the drying parameters according to the sole material, ambient temperature, and ambient humidity.
[0024] As a preferred embodiment of the present invention, the step of determining the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and interference parameter data specifically includes: S401, determining the shape stability coefficient according to the sole complexity and the material stability coefficient according to the sole material; S402, determining the operator skill variability coefficient according to the operator's proficiency and the comprehensive influence coefficient of interference factors according to the ambient temperature and ambient humidity.
[0025] Specifically, the steps of determining the shape stability coefficient according to the sole complexity and the material stability coefficient according to the sole material are as follows: Based on the sole complexity, determine the original sole complexity parameter, and perform a cube root calculation on the original sole complexity parameter to obtain the complexity basic conversion value; Based on the product parameters, determine the exponential decay coefficient, and use the exponential decay coefficient to perform a proportional operation on the complexity basic conversion value and the exponential decay function to obtain the preliminary stability compensation value; Based on the sole complexity, determine the complexity threshold, and perform a ratio operation on the original complexity parameter and the complexity threshold to obtain the complexity ratio; Perform arctangent function conversion on the complexity ratio to obtain the threshold adjustment correction value; Linearly superimpose the preliminary stability compensation value and the threshold adjustment correction value to generate the shape stability coefficient; Determine the material parameters of the standard classification through the sole material, and perform natural logarithm processing on the material parameters of the standard classification to generate the material basis conversion value; Based on the sole material, determine the original material parameters and the material threshold, calculate the power-law ratio of the original material parameters to the material threshold, and obtain the barrier adjustment factor; Perform reciprocal operation on the barrier adjustment factor and perform suppression processing to generate the non-linear suppression coefficient; Calculate the superimposed dynamic adjustment coefficient through the material basis conversion value and the non-linear suppression coefficient. Combine the superimposed dynamic adjustment coefficient and perform multiplication operation on the material basis conversion value and the non-linear suppression coefficient to obtain the material stability coefficient.
[0026] Furthermore, determine the operator skill variability coefficient according to the operator proficiency, and determine the comprehensive influence coefficient of interference factors according to the environmental temperature and environmental humidity. The specific steps are as follows: Determine the standardized evaluation value of operation proficiency through the operator proficiency, and perform arctangent function conversion on the standardized evaluation value of operation proficiency to obtain the skill basis conversion value; Determine the original proficiency parameter and the Gaussian attenuation coefficient through the operator proficiency, and perform square value operation on the original proficiency parameter to obtain the square value of the original proficiency parameter; Use the Gaussian attenuation coefficient to perform exponential attenuation operation on the square value of the original proficiency parameter to obtain the Gaussian suppression factor; Perform proportional synthesis operation on the skill basis conversion value and the Gaussian suppression factor to obtain the preliminary skill evaluation value; Based on the original proficiency parameter, determine the critical threshold and the proficiency adjustment weight, and use the critical threshold to perform reciprocal conversion operation of the power-law ratio on the original proficiency parameter to obtain the threshold suppression coefficient; Use the proficiency adjustment weight to perform weight multiplication operation on the threshold suppression coefficient to obtain the suppression correction value, and use the suppression correction value to perform linear superposition operation on the preliminary skill evaluation value to obtain the operator skill variability coefficient; Based on the environmental temperature, determine the measured temperature value and the temperature coefficient, and use the temperature coefficient to perform non-integer power-law operation on the measured temperature value to obtain the temperature basis influence value; Based on the environmental humidity, determine the measured humidity value, and perform power-law operation and time-sharing conversion processing on the measured humidity value in sequence to obtain the humidity suppression factor; Perform fractional division operation on the temperature basis influence value and the humidity suppression factor to obtain the main influence term of temperature and humidity; Perform a natural logarithm operation on the measured humidity value to generate a humidity basic correction value; Perform a cosine function conversion operation on the measured temperature value through the reference temperature value to obtain a temperature adjustment coefficient; Perform a multiplication operation on the humidity basic correction value and the temperature adjustment coefficient to obtain a temperature and humidity product result, and perform a square root compensation process on the temperature and humidity product result to obtain a temperature and humidity auxiliary influence term; Perform a linear superposition operation on the temperature and humidity main influence term and the temperature and humidity auxiliary influence term to obtain a comprehensive influence coefficient of interference factors.
[0027] In the embodiment of the present invention, it is necessary to pre-construct a relationship formula between the sole complexity and the shape stability coefficient, a relationship formula between the sole material and the material stability coefficient, a relationship formula between the operator proficiency and the operator skill variability coefficient, and a relationship formula between the ambient temperature and humidity and the comprehensive influence coefficient of interference factors.
[0028] As a preferred embodiment of the present invention, the step of evaluating the spraying stability base number and key detection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient specifically includes: S501, calculate the spraying stability base number according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient. The relationship formula existing in the corresponding process is: SI=(Ms×Ss) / (If×Sv); Wherein, Ss is the shape stability coefficient, Ms is the material stability coefficient, If is the comprehensive influence coefficient of interference factors, Sv is the operator skill variability coefficient, and SI is the spraying stability base number; S502, input the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient into the coefficient item library, and output the matching detection items; S503, summarize all the detection items to obtain the key detection items.
[0029] Specifically, the steps of summarizing all the detection items to obtain the key detection items are as follows: Determine the stability adjustment weights of each coefficient through the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient; Adjust the weights using the stability of each coefficient, and perform saturation enhancement compensation processing on the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively to obtain the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively; Determine the historical detection abnormal evaluation frequency based on the coefficient item library, and perform unit time frequency normalization processing on the historical detection abnormal evaluation frequency to obtain the historical abnormal frequency quantization value; Perform fractional conversion operations on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively to obtain the compensation coefficients of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively; Perform a multiplication operation on the compensation coefficients of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient to obtain the initial product factor; Apply natural logarithm compensation operation to the historical abnormal frequency quantization value to obtain the historical abnormal frequency compensation coefficient; Perform exponential decay processing on the historical abnormal frequency compensation coefficient to obtain the abnormal frequency suppression factor; Perform exponential weight adjustment operation on the initial product factor and the abnormal frequency suppression factor to obtain the modulated core influence value; Determine the weight coefficients of the conversion values based on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient; Use the weight coefficients of the conversion values to perform non-linear function conversion on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient to generate the comprehensive weight evaluation value; Perform power compensation operations on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively to obtain the power compensation results of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively; Perform square root suppression processing on the power compensation results of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient to generate the system balance factor; Perform fractional synthesis on the comprehensive weight evaluation value and the system balance factor to obtain the comprehensive balance evaluation value; Perform a multiplication operation on the comprehensive balance evaluation value and the modulated core influence value to obtain the project priority coefficient, and determine the key detection items based on the project priority coefficient.
[0030] In the embodiment of the present invention, the spraying stability base number SI will be automatically calculated according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, SI = (Ms × Ss) / (If × Sv), and then the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient are input into the coefficient project library. The coefficient project library contains various coefficient ranges, and each coefficient range corresponds to several detection items, and the matching detection items are automatically output. Summarizing the output detection items will obtain the key detection items.
[0031] The embodiment of the present invention also provides a sole spraying control system for a shoe-making production line, and the system includes: A product parameter data module 100, which is used to collect the product model and determine the product parameter data according to the product model. The product parameter data includes sole material, sole complexity, coating thickness, and paint absorption rate; An interference parameter data module 200, which is used to collect interference parameter data. The interference parameter data includes operator proficiency, environmental temperature, and environmental humidity; A spraying parameter data module 300, which is used to determine the spraying parameter data according to the product parameter data and the interference parameter data. The spraying parameter data includes spraying angle, material discharge speed, moving speed, spraying times, and drying parameters; A correlation coefficient determination module 400, which is used to determine the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and the interference parameter data; A spraying stability base number module 500, which is used to evaluate the spraying stability base number and key detection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, and determine the sampling ratio according to the spraying stability base number.
[0032] As a preferred embodiment of the present invention, the spraying parameter data module 300 includes: A spraying angle calculation unit, which is used to determine the spraying angle according to the sole complexity. The relational expression existing in the corresponding process is: θ = 45° + 0.5° × Cp; where Cp is the sole complexity and θ is the spraying angle; The discharge speed calculation unit is used to determine the discharge speed according to the sole material and the paint absorption rate. The relational formula in the corresponding process is: Vo = (Vb / Ab) × Mf; Where, Vb is the basic discharge speed, Ab is the paint absorption rate, Mf is the sole material coefficient, and Vo is the discharge speed; The moving speed calculation unit is used to determine the moving speed according to the sole complexity and the operator proficiency. The relational formula in the corresponding process is: Vm = (Ve × Sf) / (1 + Cp); Where, Ve is the basic moving speed, Sf is the operator proficiency, and Vm is the moving speed; The spraying times calculation unit is used to determine the spraying times according to the sole material and the coating thickness. The relational formula in the corresponding process is: N = (Rt / St) × Ma; Where, Rt is the coating thickness, St is the average thickness of a single spraying, Ma is the material adjustment coefficient, and N is the spraying times; The drying parameter determination unit is used to determine the drying parameters according to the sole material, the environmental temperature, and the environmental humidity. The drying parameters include the drying temperature and the drying duration.
[0033] As a preferred embodiment of the present invention, the correlation coefficient determination module 400 includes: The shape and material stability unit is used to determine the shape stability coefficient according to the sole complexity and the material stability coefficient according to the sole material; The comprehensive skill influence unit is used to determine the operator skill variability coefficient according to the operator proficiency and the comprehensive influence coefficient of interference factors according to the environmental temperature and the environmental humidity.
[0034] As a preferred embodiment of the present invention, the spraying stability base number module 500 includes: The spraying stability base number unit is used to calculate the spraying stability base number according to the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient. The relational formula in the corresponding process is: SI = (Ms × Ss) / (If × Sv); Where, Ss is the shape stability coefficient, Ms is the material stability coefficient, If is the comprehensive influence coefficient of interference factors, Sv is the operator skill variability coefficient, and SI is the spraying stability base number; The information input and matching unit is used to input the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient into the coefficient item library and output the matching detection items; The key detection item unit is used to summarize all detection items to obtain the key detection items.
[0035] The above only describes the preferred embodiments of the present invention in detail and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.
[0036] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages does not necessarily have to be sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.
[0037] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
[0038] Other embodiments of the present disclosure will be readily contemplated by those skilled in the art after considering the disclosure in the specification and the embodiments. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common general knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the true scope and spirit of the present disclosure are pointed out by the claims.
Claims
1. A sole spraying control method for a shoe-making production line, characterized in that The method includes the following steps: Collect the product model, and determine the product parameter data according to the product model. The product parameter data includes sole material, sole complexity, coating thickness, and paint absorption rate; Collect the interference parameter data. The interference parameter data includes operator proficiency, ambient temperature, and ambient humidity; Determine the spraying parameter data according to the product parameter data and the interference parameter data. The spraying parameter data includes spraying angle, material discharge speed, moving speed, number of spraying times, and drying parameters; Determine the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and the interference parameter data; Evaluate the spraying stability base number and key inspection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, and determine the sampling ratio according to the spraying stability base number.
2. The sole spraying control method for a shoe-making production line according to claim 1, characterized in that, The step of determining the spraying parameter data according to the product parameter data and the interference parameter data specifically includes: Determine the spraying angle according to the sole complexity. The relational formula existing in the corresponding process is: θ = 45° + 0.5°×Cp; where Cp is the sole complexity and θ is the spraying angle; Determine the material discharge speed according to the sole material and the paint absorption rate. The relational formula existing in the corresponding process is: Vo = (Vb / Ab)×Mf; where Vb is the basic material discharge speed, Ab is the paint absorption rate, Mf is the sole material coefficient, and Vo is the material discharge speed; Determine the moving speed according to the sole complexity and the operator proficiency. The relational formula existing in the corresponding process is: Vm = (Ve×Sf) / (1 + Cp); where Ve is the basic moving speed, Sf is the operator proficiency, and Vm is the moving speed; Determine the number of spraying times according to the sole material and the coating thickness. The relational formula existing in the corresponding process is: N = (Rt / St)×Ma; where Rt is the coating thickness, St is the average thickness of a single spraying, Ma is the material adjustment coefficient, and N is the number of spraying times; Determine the drying parameters according to the sole material, ambient temperature, and ambient humidity. The drying parameters include drying temperature and drying duration.
3. The sole spraying control method for a shoe-making production line according to claim 2, wherein Determine the drying parameters according to the sole material, ambient temperature, and ambient humidity. The drying parameters include drying temperature and drying duration. The specific steps are as follows: Perform a natural logarithm function process on the material adjustment coefficient to obtain the material influence factor; Superimpose unit values as compensation, determine the measured temperature value through the ambient temperature, and determine the reference temperature value through the material; Perform a ratio calculation on the measured temperature value and the reference temperature value to obtain the temperature ratio factor; Determine the measured humidity value through the ambient humidity, determine the reference humidity value through the material, and perform a ratio calculation on the measured humidity value and the reference humidity value to obtain the reference humidity value; Perform a standardization process on the reference humidity value to obtain the standardized reference humidity value, and then perform a square amplification process on the standardized reference humidity value to obtain the humidity compensation coefficient; Perform a continuous multiplication operation on the material influence factor, the temperature ratio factor, and the humidity compensation coefficient to obtain the set value of the drying temperature; Perform an exponential correction operation on the material adjustment coefficient to obtain the material correction basic parameter; Apply the natural exponential function to the measured humidity value for non-linear amplification conversion processing to obtain the humidity time compensation factor; Determine the temperature correction parameter based on the set value of the drying temperature; Under the condition of ensuring the distribution validity by superimposing unit values, perform linear attenuation processing on the measured temperature value using the temperature correction parameter to obtain the temperature acceleration factor; Perform a positive multiplication operation on the material correction basic parameter and the humidity time compensation factor to obtain the intermediate time quantity after humidity compensation; Perform an inverse division operation on the intermediate time quantity after humidity compensation and the temperature acceleration factor to obtain the optimized time quantity after ambient temperature correction; Obtain the reference drying time through product parameters, and linearly superimpose the optimized time quantity after ambient temperature correction and the reference drying time to obtain the drying parameter; 4. The sole spraying control method for a shoe-making production line according to claim 3, characterized in that, The steps of determining the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to product parameter data and interference parameter data specifically include: Determine the shape stability coefficient according to the sole complexity, and determine the material stability coefficient according to the sole material; Determine the operator skill variability coefficient according to the operator proficiency, and determine the comprehensive influence coefficient of interference factors according to the ambient temperature and ambient humidity; 5. The sole spraying control method for a shoe-making production line according to claim 4, characterized in that, Determine the shape stability coefficient according to the sole complexity, and determine the material stability coefficient according to the sole material. The specific steps are as follows: Determine the original sole complexity parameter based on the sole complexity, and perform a cube root calculation on the original sole complexity parameter to obtain the complexity basic conversion value; Determine the exponential decay coefficient based on product parameters, and use the exponential decay coefficient to perform a proportional operation on the complexity basic conversion value and the exponential decay function to obtain the preliminary stability compensation value; Determine the complexity threshold based on the sole complexity, and perform a ratio operation on the original complexity parameter and the complexity threshold to obtain the complexity ratio; Perform a positive and inverse tangent function conversion processing on the complexity ratio to obtain the threshold adjustment correction value; Linearly superimpose the preliminary stability compensation value and the threshold adjustment correction value to generate the shape stability coefficient; Determine the material parameters of the standard classification through the sole material, and perform a natural logarithm processing on the material parameters of the standard classification to generate the material basic conversion value; Determine the original material parameter and the material threshold based on the sole material, and calculate the power-law ratio of the original material parameter and the material threshold to obtain the barrier adjustment factor; Perform a reciprocal operation on the barrier adjustment factor and perform an inhibition processing to generate the non-linear inhibition coefficient; Calculate the superimposed dynamic adjustment coefficient through the material basic conversion value and the non-linear inhibition coefficient, and combine the superimposed dynamic adjustment coefficient to perform a multiplication operation on the material basic conversion value and the non-linear inhibition coefficient to obtain the material stability coefficient; 6. The sole spraying control method for a shoe-making production line according to claim 5, wherein, Determine the operator skill variability coefficient according to the operator proficiency, and determine the comprehensive influence coefficient of interference factors according to the ambient temperature and ambient humidity. The specific steps are as follows: Determine the standardized evaluation value of operation proficiency through the operator proficiency, and perform a positive and inverse tangent function conversion processing on the standardized evaluation value of operation proficiency to obtain the skill basic conversion value; Determine the original proficiency parameter and the Gaussian decay coefficient based on the operator's proficiency. Perform a square value operation on the original proficiency parameter to obtain the square value of the original proficiency parameter; Perform an exponential decay operation on the square value of the original proficiency parameter using the Gaussian decay coefficient to obtain the Gaussian suppression factor; Perform a proportional synthesis operation on the skill base conversion value and the Gaussian suppression factor to obtain the preliminary skill evaluation value; Determine the critical threshold and the proficiency adjustment weight based on the original proficiency parameter. Perform a reciprocal conversion operation of the power-law ratio on the original proficiency parameter using the critical threshold to obtain the threshold suppression coefficient; Perform a weighted product operation on the threshold suppression coefficient using the proficiency adjustment weight to obtain the suppression correction value, and perform a linear superposition operation on the preliminary skill evaluation value using the suppression correction value to obtain the operator skill variability coefficient; Determine the measured temperature value and the temperature coefficient based on the ambient temperature. Perform a non-integer power-law operation on the measured temperature value using the temperature coefficient to obtain the temperature base influence value; Determine the measured humidity value based on the ambient humidity. Perform a power-law operation and a time-sharing conversion process on the measured humidity value in sequence to obtain the humidity suppression factor; Perform a fractional division operation on the temperature base influence value and the humidity suppression factor to obtain the temperature and humidity main influence term; Perform a natural logarithm operation on the measured humidity value to generate the humidity base correction value; Perform a cosine function conversion operation on the measured temperature value using the reference temperature value to obtain the temperature adjustment coefficient; Perform a multiplication operation on the humidity base correction value and the temperature adjustment coefficient to obtain the temperature and humidity product result, and perform a square root compensation process on the temperature and humidity product result to obtain the temperature and humidity auxiliary influence term; Perform a linear superposition operation on the temperature and humidity main influence term and the temperature and humidity auxiliary influence term to obtain the comprehensive influence coefficient of interference factors.
7. The sole spraying control method for a shoe-making production line according to claim 6, characterized in that, The steps of evaluating the spraying stability base number and the key detection items according to the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient specifically include: Calculate the spraying stability base number according to the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient. The corresponding relationship in the process is: SI = (Ms × Ss) / (If × Sv); Among them, Ss is the shape stability coefficient, Ms is the material stability coefficient, If is the comprehensive influence coefficient of interference factors, Sv is the operator skill variability coefficient, and SI is the spraying stability base number; Input the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient into the coefficient item library, and output the matching detection items; Summarize all the detection items to obtain the key detection items.
8. The sole spraying control method for a shoe-making production line according to claim 7, wherein, Summarize all the detection items to obtain the key detection items. The specific steps are as follows: Determine the stability adjustment weight of each coefficient through the shape stability coefficient, the material stability coefficient, the comprehensive influence coefficient of interference factors, and the operator skill variability coefficient; Adjust the weights using the stability of each coefficient, and perform saturation enhancement compensation processing on the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively to obtain the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively; Determine the historical detection abnormal evaluation frequency based on the coefficient item library, and perform unit-time frequency normalization processing on the historical detection abnormal evaluation frequency to obtain the historical abnormal frequency quantization value; Perform fractional conversion operations on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively to obtain the compensation coefficients of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively; Perform a multiplication operation on the compensation coefficients of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient to obtain the initial product factor; Apply natural logarithm compensation operation to the historical abnormal frequency quantization value to obtain the historical abnormal frequency compensation coefficient; Perform exponential decay processing on the historical abnormal frequency compensation coefficient to obtain the abnormal frequency suppression factor; Perform exponential weight adjustment operation on the initial product factor and the abnormal frequency suppression factor to obtain the modulated core influence value; Determine the weight coefficients of the conversion values based on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient; Use the weight coefficients of the conversion values to perform non-linear function conversion on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient to generate the comprehensive weight evaluation value; Perform power compensation operations on the conversion values of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively to obtain the power compensation results of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient respectively; Perform square root suppression processing on the power compensation results of the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient to generate the system balance factor; Perform fractional synthesis on the comprehensive weight evaluation value and the system balance factor to obtain the comprehensive balance evaluation value; Perform a multiplication operation on the comprehensive balance evaluation value and the modulated core influence value to obtain the project priority coefficient, and determine the key detection items based on the project priority coefficient.
9. A sole spraying control system for a shoe-making production line, characterized in that, The system applies the sole spraying control method for a shoe-making production line as described in any one of claims 1 to 8 above, and the system includes: The product parameter data module is used to collect the product model and determine the product parameter data according to the product model. The product parameter data includes sole material, sole complexity, coating thickness, and paint absorption rate; The interference parameter data module is used to collect the interference parameter data. The interference parameter data includes operator proficiency, ambient temperature, and ambient humidity; The spraying parameter data module is used to determine the spraying parameter data according to the product parameter data and the interference parameter data. The spraying parameter data includes spraying angle, discharge rate, moving speed, number of spraying times, and drying parameters; The correlation coefficient determination module is used to determine the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient according to the product parameter data and the interference parameter data; The spraying stability base number module is used to evaluate the spraying stability base number and key inspection items according to the shape stability coefficient, material stability coefficient, comprehensive influence coefficient of interference factors, and operator skill variability coefficient, and determine the sampling ratio according to the spraying stability base number.