Manufacturing method of grain touch film
By using programmable texture rollers and machine learning algorithms to optimize parameters in the fabrication of texture tactile films, the inefficiency and quality instability caused by frequent replacement of texture rollers is solved, and efficient and stable film production is achieved.
Patent Information
- Application Number
- CN202510472387.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-16
- Publication Date
- 2025-07-22
AI Technical Summary
During the manufacturing process of existing texture tactile films, the texture rollers need to be frequently replaced to adjust the pattern, which affects the manufacturing efficiency and is not convenient to optimize the imprinting parameters in real time, resulting in unstable film quality and performance.
The programmable texture rollers and PLC are used to coordinate the control with the inverter, combined with machine learning algorithms and simulation environment verification, and the parameters such as heating time, downforce and speed are optimized in real time, so as to ensure the quality and performance of the film through high-precision sensors and detection devices.
Improve manufacturing efficiency, ensure the stability of film quality and performance, enhance the protective performance of films, and reduce equipment failures and waste of raw materials.
Smart Images
Figure CN120348010A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of processing technologies, and in particular to a method for manufacturing a texture touch film. Background Art
[0002] A texture touch film is a thin film material with special textures and touch effects, which is widely used in fields such as packaging, printing, and electronic products. A texture touch film is a thin film material with specific textures and touch effects on its surface. It usually forms various textures on the film surface through special processing techniques, such as cloth patterns, wood patterns, wire drawing patterns, round dots, rhombus shapes, etc., so as to endow the product with unique visual and tactile experiences. With the economic development and the improvement of people's living standards, dry wipes and wet wipes have become essential items in people's daily lives due to their convenience in carrying and cleaning functions. As an important part of the dry wipes and wet wipes packaging, it has become a bridge connecting the brand and consumers. In addition to paying attention to the conventional functions of the packaging, consumers are paying more and more attention to the visual manifestation of the packaging. The commonly used materials for dry wipes and wet wipes packaging films and bags include composite CPP / CPP, PE / PE, BOPP / VMPET / PE, single-layer CPP, PE, etc. For CPP materials, the commonly used one for dry wipes packaging is copolymerized PP, which has low-temperature brittleness. After lamination, the glue penetrates the film and continues to harden, making it easy to crack and break the bag during bag making, resulting in the failure of the packaging function. After texture treatment, the film deforms under force, improving its toughness and reducing the risk of bag breaking and cracking. For PE materials, PE materials are relatively soft and have strong shrinkage. They are prone to delamination and wrinkles after lamination. After texture treatment, the film deforms under force, increasing its strength, thus reducing the generation of wrinkles and improving the flatness and appearance of the film surface. The texture touch film for dry wipes and wet wipes is prepared by a texture touch film device, which mainly includes a heating device, a pressing device, and a cooling device. The laminated film is first heated to a certain temperature by the heating device, then the customized texture is pressed on the surface of the composite film by the pressing device, and finally the required texture touch film is obtained after cooling.
[0003] In the prior art, during the manufacturing process of the texture touch film, it is necessary to disassemble and replace the texture roller to achieve the purpose of adjusting the pattern, which affects the manufacturing efficiency and is not convenient for real-time optimization of the imprinting parameters, thus resulting in the inability to ensure the quality and performance of the film. Therefore, we propose a method for manufacturing a texture touch film to solve the above problems. Summary of the Invention
[0004] The object of the present invention is to solve the drawbacks existing in the prior art that during the manufacturing process of the texture touch film, it is necessary to disassemble and replace the texture roller to adjust the pattern, which affects the manufacturing efficiency, and it is not convenient to optimize the embossing parameters in real time, resulting in the inability to ensure the quality and performance of the film. A manufacturing method of the texture touch film is proposed.
[0005] A manufacturing method of the texture touch film provided in this application adopts the following technical solutions: A manufacturing method of the texture touch film includes the following steps: S1: Select materials and perform pretreatment on the materials; S2: Select a texture roller and adjust the texture of the texture roller; S3: Heat and soften the pretreated materials and monitor the heating time and temperature; S4: Emboss the softened materials and monitor the pressing force and speed; S5: Optimize the parameters collected by monitoring in real time; S6: Establish a simulation environment to verify the parameters; S7: Cool and shape the embossed film; S8: Detect the cooled film and treat the film surface; S9: Wind up the treated film to obtain the texture touch film.
[0006] Further, in the S1, composite CPP / CPP is selected as the base material with a total thickness of 48 μm (matte CPP 24 / transparent CPP 24), and the surface of the composite CPP / CPP is activated by plasma treatment technology to improve the effect and adhesion of subsequent texture treatment.
[0007] Further, in the S2, a programmable texture roller is adopted, and the texture of the texture roller is dynamically adjusted through an adjustment module. The adjustment module adopts coordinated control of a PLC (programmable logic controller) and an inverter. The texture roller patterns include dot-shaped, diamond-shaped, circular, square, and irregular shapes, etc.
[0008] Further, in the S3, the pretreated film is heated by a heating device, the heating temperature is 105°C - 160°C, the heating time is 2 - 6 min, and the heating time and heating temperature are monitored in real time by a monitoring device.
[0009] Further, in S4, the softened film material is conveyed to the pressing device by a conveying mechanism, and specific patterns are imprinted on the film surface by the adjusted pattern roller. The pressing speed is 30 - 35 m / min, the pressing pressure is 0.2 - 0.6 MPa, and the pressing pressure and speed are monitored in real time by a monitoring device.
[0010] Further, in S5, a parameter optimization module collects the monitored heating time, heating temperature, pressing pressure, and speed parameters, and uses machine learning algorithms to optimize the heating time, heating temperature, pressing pressure, and speed parameters in real time. The parameter optimization module includes a data acquisition unit, a model training unit, and a parameter optimization unit. The data acquisition unit is connected to the model training unit, and the model training unit is connected to the parameter optimization unit. The data acquisition unit is used to collect the performance data of the film under different process parameters, including dart impact strength, tensile strength, softness, etc. The model training unit uses support vector machine (SVM) and neural network (NN) to train the data and establish a mapping relationship between process parameters and film performance. The parameter optimization unit adjusts the process parameters in real time according to the trained model.
[0011] Further, in S6, a virtual production scenario highly consistent with the actual production process is constructed through high-precision sensor data acquisition and three-dimensional modeling technology to verify the optimized parameter combination, including simulating the operation of the pattern roller, the transmission of the film, and the imprinting process.
[0012] Further, in S7, the imprinted film is cooled by a cooling device to 12℃ - 16℃ for a duration of 2 - 6 min to shape the film.
[0013] Further, in S8 and S9, the appearance quality of the cooled and shaped film is detected by a detection device, and at the same time, a coating is applied to the film surface by a coating device to enhance the protection performance of the film. The processed film is wound and packed by a winding device to obtain a textured touch film.
[0014] In summary, the present application includes at least one of the following beneficial technical effects: 1. This solution collects the monitored heating time, heating temperature, pressing pressure, and speed parameters through a parameter optimization module, and uses machine learning algorithms to optimize the heating time, heating temperature, pressing pressure, and speed parameters in real time, thereby effectively ensuring the quality and performance of the film. 2. This solution uses a programmable pattern roller, and the pattern of the pattern roller is dynamically adjusted by an adjustment module. The adjustment module uses a programmable logic controller (PLC) and a frequency converter for coordinated control, which is convenient for adjusting the pattern of the pattern roller, thereby improving the manufacturing efficiency. 3. In this solution, the inspection device is used to detect the appearance quality of the film after cooling and shaping. Meanwhile, the coating device is used to coat the surface of the film with a coating, which can be an antibacterial coating, a waterproof coating or an antistatic coating, to enhance the protection performance of the film.
[0015] In the manufacturing process of the texture touch film, the present invention can facilitate the adjustment of the pattern roller pattern, thereby improving the manufacturing efficiency, and is convenient for real-time optimization of the embossing parameters, and can effectively ensure the quality and performance of the film. Brief Description of the Drawings
[0016] Figure 1 is a flowchart of a manufacturing method of a texture touch film proposed by the present invention; Figure 2 is a flowchart of verifying parameters by establishing a simulation environment for a manufacturing method of a texture touch film proposed by the present invention. Detailed Embodiments
[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Embodiment
[0018] Referring to Figure 1 - Figure 2 , a manufacturing method of a texture touch film includes the following steps: S1: Select materials and perform pretreatment on the materials; S2: Select a pattern roller and adjust the pattern of the pattern roller; S3: Heat and soften the pretreated materials and monitor the heating time and temperature; S4: Emboss the softened materials and monitor the pressing pressure and speed; S5: Optimize the parameters collected by monitoring in real time; S6: Establish a simulation environment to verify the parameters; S7: Cool and shape the embossed film; S8: Inspect the cooled film and treat the surface of the film; S9: Wind up the treated film to obtain a texture touch film.
[0019] In this embodiment, in S1, composite CPP / CPP is selected as the base material with a total thickness of 48 μm (matte CPP 24 / transparent CPP 24), and the surface of the composite CPP / CPP is activated by plasma treatment technology to improve the effect and adhesion of subsequent texture treatment.
[0020] In this embodiment, in S2, a programmable texture roller is used, and the texture of the texture roller is dynamically adjusted by an adjustment module. The adjustment module uses a PLC (Programmable Logic Controller) and a frequency converter for coordinated control. The texture roller patterns include dot-shaped, diamond-shaped, circular, square, and irregular shapes, etc.
[0021] In this embodiment, in S3, the pretreated film is heat-treated by a heating device. The heating temperature is 140 °C and the heating time is 4 min. The heating time and heating temperature are monitored in real time by a monitoring device.
[0022] In this embodiment, in S4, the softened film material is conveyed to a pressing device by a conveying mechanism. Specific patterns are imprinted on the film surface by the adjusted texture roller. The pressing speed is 32 m / min and the pressing pressure is 0.4 MPa. The pressing pressure and speed are monitored in real time by a monitoring device.
[0023] In this embodiment, in S5, a parameter optimization module collects the monitored heating time, heating temperature, pressing pressure, and speed parameters, and uses a machine learning algorithm to optimize the heating time, heating temperature, pressing pressure, and speed parameters in real time. The parameter optimization module includes a data acquisition unit, a model training unit, and a parameter optimization unit. The data acquisition unit is connected to the model training unit, and the model training unit is connected to the parameter optimization unit. The data acquisition unit is used to collect the performance data of the film under different process parameters, including dart impact strength, tensile strength, and softness. The model training unit uses a support vector machine (SVM) and a neural network (NN) to train the data and establish a mapping relationship between the process parameters and the film performance. The parameter optimization unit adjusts the process parameters in real time according to the trained model. The machine learning algorithms include: linear regression, logistic regression, and decision tree; 1. Linear regression Simple linear regression: Used to establish a linear relationship model between one independent variable and one dependent variable; Formula:
[0024] where y is the dependent variable, x is the independent variable, w is the weight coefficient, and b is the bias term; Multiple linear regression: Used when there are multiple independent variables; Formula:
[0025] Logistic regression Used to solve binary classification problems. Its basic idea is to map the output of linear regression to the interval (0,1) through a sigmoid function, so as to obtain the probability of belonging to a certain class; Formula:
[0026] Among them, p(y = 1) represents the probability that a sample belongs to the positive class, and e is the base of the natural logarithm; Decision tree A decision tree classifies or regresses data by learning a series of conditional and decision rules. Its construction process is mainly based on indicators such as information gain, information gain ratio, or Gini index. Taking information gain as an example, for a dataset D and a feature A; The calculation formula for information gain:
[0027] Among them, Ent(D) is the entropy of the dataset D, D v is the subset of the dataset D where the feature A takes the v-th value, Ent(D v ) is the entropy of the subset D v , and V is the number of values that the feature A can take; Support Vector Machine (SVM) Support Vector Machine (SVM) is a binary classification model. Its basic model is a linear classifier with the largest margin defined in the feature space. SVM finds an optimal hyperplane that can not only correctly classify two types of samples but also has the largest margin. SVM also includes the kernel trick, which makes it a virtually non-linear classifier. The learning strategy of SVM is to maximize the margin, which can be formalized as a problem of solving a convex quadratic programming or equivalently a problem of minimizing a regularized hinge loss function; Linearly separable support vector machine: The decision function is:
[0028] Among them, w and b are parameters obtained through optimization to maximize the margin between two types of samples. x is the input vector, and sgn is the sign function used to determine which class the input vector belongs to. The optimization objective is:
[0029] The constraint conditions are:
[0030] i = 1, 2, ⋯, n, y i is the class label of the sample x i ; During the training process, the optimal hyperplane is found by maximizing the margin to maximize the margin between two types of data. The Lagrange multiplier method is used to find the optimal solution. Finally, the normal vector w can be expressed as a linear combination of support vectors:
[0031] Where: α i is the Lagrange multiplier, representing the weight of each support vector; y i is the class label of the support vector (usually +1 or -1); x i is the support vector; Neural Network (NN) A neural network (NN) is a computational model that mimics the structure of human brain neurons. It consists of a large number of nodes (neurons) and the weights connecting these nodes. The neural network learns the features and patterns of data by adjusting the weights and biases, thereby achieving tasks such as data classification and regression. A neural network usually consists of an input layer, hidden layers, and an output layer, and is trained through forward propagation and backpropagation algorithms; Forward Propagation: For a simple two-layer neural network, assuming the input is x, the weight of the hidden layer is w1, the bias is b1, the activation function is g, the weight of the output layer is w2, and the bias is b2, then the output of the hidden layer is:
[0032] The final output is:
[0033] Backpropagation: The backpropagation algorithm calculates the gradient of the loss function with respect to each weight and then updates the weights using the gradient descent method. Assuming the loss function is L, the weight update formula is:
[0034] where η is the learning rate.
[0035] In this embodiment, in S6, through high-precision sensor data acquisition and three-dimensional modeling technology, a virtual production scenario highly consistent with the actual production process is constructed to verify the optimized parameter combination, including simulating the operation of the pattern roller, the transmission of the film, and the embossing process. The optimized parameters such as the heating time, heating temperature, pressing pressure, and speed output by the parameter optimization module in S5 are input into the simulation environment, and the simulation operation program is started. During the simulation, key indicators such as the film pattern forming quality, dimensional stability, and equipment operation status in the simulated production are monitored in real time. By comparing and analyzing with the preset quality standards and equipment normal operation thresholds, a feasibility evaluation report of the parameter combination is generated. If the simulation results show potential problems with the parameter combination, such as unclear film patterns, film stretching and deformation, or excessive equipment load, a feedback signal is immediately sent to the parameter optimization module in S5 to prompt the optimization module to readjust the parameters. Only the parameter combination that passes the simulation verification will be officially applied to the actual production process, thereby further correcting errors in advance before the actual production implementation, improving the stability of the production process and the first-pass yield of the product, reducing raw material waste and equipment failure downtime caused by unreasonable parameters, forming a more efficient and reliable parameter optimization closed-loop control system, and effectively ensuring the high-quality continuous production of the pattern touch film.
[0036] In this embodiment, in S7, the embossed film is cooled by a cooling device to 14°C for a duration of 4 minutes to shape the film.
[0037] In this embodiment, in S8 and S9, the appearance quality of the cooled and shaped film is detected by a detection device, and at the same time, a coating is applied to the film surface by a coating device. The coating is an antibacterial coating, a waterproof coating, or an anti-static coating to enhance the film protection performance. The processed film is wound and packed by a winding device to obtain the pattern touch film. Embodiment
[0038] The difference between this embodiment and Embodiment 1 is as follows: Refer to Figure 1 - Figure 2 , a manufacturing method of a pattern touch film, comprising the following steps: S1: Select materials and perform pretreatment on the materials, and apply a nano-texture induction layer on the surface of the pretreated composite film; S2: Select a pattern roller and adjust the pattern of the pattern roller; S3: Heat and soften the pretreated materials and monitor the heating time and temperature; S4: Emboss the softened materials and monitor the pressing pressure and speed; S5: Optimize the parameters collected by the monitoring in real time; S6: Establish a simulation environment to verify the parameters; S7: Cool and shape the imprinted film; S8: Inspect the cooled film and treat the film surface; S9: Wind up the treated film to obtain the textured tactile film.
[0039] In this embodiment, in S1, by coating a nano-texture induction layer on the surface of the pretreated composite film, the induction layer contains biocompatible nanoparticles and functional polymers, which can form micro-textures in the subsequent process and further improve the environmental friendliness of the film. Embodiment
[0040] The difference between this embodiment and Embodiment 1 is: Refer to Figure 1 - Figure 2 , a manufacturing method of a textured tactile film, comprising the following steps: S1: Select materials and pretreat the materials; S2: Select a textured roller and adjust the texture of the textured roller; S3: Heat and soften the pretreated materials and monitor the heating time and temperature; S4: Imprint the softened materials, monitor the pressing force and speed, and recycle the waste generated during imprinting; S5: Optimize the parameters collected by monitoring in real time; S6: Establish a simulation environment to verify the parameters; S7: Cool and shape the imprinted film; S8: Inspect the cooled film and treat the film surface; S9: Wind up the treated film to obtain the textured tactile film.
[0041] In this embodiment, in S4, through the waste recycling and treatment system, the waste generated during the production process is classified, recycled and treated, reducing environmental pollution caused by waste and at the same time reducing material waste. Embodiment
[0042] The difference between this embodiment and Embodiment 1 is: Refer to Figure 1 - Figure 2 , a manufacturing method of a textured tactile film, comprising the following steps: S1: Select materials and pretreat the materials; S2: Select a textured roller and adjust the texture of the textured roller; S3: Heat and soften the pretreated materials and monitor the heating time and temperature; S4: Convey the softened material, control the conveying tension and speed, emboss the softened material, and monitor the pressing pressure and speed; S5: Optimize the parameters collected by monitoring in real time; S6: Establish a simulation environment to verify the parameters; S7: Cool and shape the embossed film; S8: Detect the cooled film and treat the film surface; S9: Wind up the treated film to obtain the texture touch film.
[0043] In this embodiment, in S4, the softened material is conveyed by a high-precision tension control system and a conveying device, and the conveying tension and speed are controlled by a control device to ensure the stability and consistency of the bottom film during the embossing process. Embodiment
[0044] The difference between this embodiment and Embodiment 1 is: Refer to Figure 1 - Figure 2 , a manufacturing method of a texture touch film, comprising the following steps: S1: Select materials and preprocess the materials; S2: Select a texture roller and adjust the texture of the texture roller; S3: Heat and soften the preprocessed materials and monitor the heating time and temperature; S4: Emboss the softened materials and monitor the pressing pressure and speed; S5: Optimize the parameters collected by monitoring in real time; S6: Establish a simulation environment to verify the parameters; S7: Cool and shape the embossed film, and recycle the heat of the film; S8: Detect the cooled film and treat the film surface; S9: Wind up the treated film to obtain the texture touch film.
[0045] In this embodiment, in S7, the heat of the film is recycled by a heat recovery device, and the recycled heat is conveyed to a heating device by a conveying device to recycle and reuse the waste heat in the production process, improve the energy utilization efficiency, and reduce the energy consumption.
[0046] Test Example Test Purpose Compare the differences between the manufacturing method of the texture touch film and the conventional manufacturing method in terms of product performance, quality, production efficiency, etc., and evaluate the advantages and improvement effects of the above-mentioned manufacturing method of the texture touch film; II. Experimental Design Experimental Materials and Equipment Materials: Select common dry towel packaging film materials, such as CPP / CPP, PE / PE, etc., to ensure consistent material sources and uniform thickness; Equipment: Textured touch film manufacturing equipment (including heating device, pressing device, cooling device, programmable texture roller, etc.) and conventional textured touch film manufacturing equipment; Experimental Methods 1. Sample Preparation: Manufacturing method of textured touch film: Prepare textured touch film samples according to the above manufacturing process flow, and strictly control process parameters, such as heating temperature, pressing speed, pressing pressure, etc.; Conventional manufacturing method: Prepare textured touch film samples using the conventional manufacturing process flow, and also strictly control process parameters; The textured touch film samples prepared by the manufacturing method of textured touch film are set as Group A, and the textured touch film samples prepared by the conventional manufacturing method are set as Group B; 2. Performance Testing: Mechanical property testing: Test mechanical property indexes of the samples, such as tensile strength, elongation at break, dart impact strength, etc., and conduct tests according to relevant standards, such as GB / T1040.3 - 2006 "Determination of Tensile Properties of Plastics - Part 3: Test Conditions for Films and Sheets", etc.; Abrasion resistance and scratch resistance testing: Use a friction coefficient tester to determine the friction coefficient of the textured touch film and a friction testing machine to test the scratch resistance of the samples, and record the friction coefficient and scratch resistance situation (friction coefficient ≤ 0.45, use A4 paper or kraft paper to rub the textured touch film on the adhered object back and forth 50 times, no texture deformation and shedding are allowed, rating: 1 - 10 levels, 10 levels being the best); Weather resistance testing: Place the samples under different climate conditions (such as high temperature, low temperature, high humidity, etc.) for aging tests, (age for 72 hours in an environment of 55℃ - 80℃, and age for 48 hours in an environment with a relative humidity of 75%) to test the appearance changes, performance retention, etc. of the samples; Touch effect testing: Evaluate the touch effect of the samples through a combination of subjective evaluation and objective measurement, such as inviting volunteers to conduct touch experience evaluations, and using a touch measurement instrument to measure the surface roughness of the samples, etc. (satisfaction score: 1 - 10 points); Production efficiency testing: Record data such as production time and output of the two manufacturing methods, and calculate the production efficiency; Data Comparison According to the requirements of the experimental design, record the experimental data, compare the differences between the manufacturing method of textured touch film and the conventional manufacturing method in terms of product performance, quality, and production efficiency. The experimental data are as follows in the table: Table 1 Experimental Data on the Influence of Different Manufacturing Methods on Product Performance
[0047] Table 2 Test data on the influence of different manufacturing methods on quality and production efficiency
[0048] The above table shows that the tensile strength of the CPP / CPP texture touch film prepared by the texture touch film manufacturing method is increased by 10%-20% compared with the conventional method, the dart impact strength is increased by 20%-30%, the abrasion resistance times are increased by 30%-50%, the scratch resistance hardness is increased by 1-2 levels. At the same time, it has better stability under conditions such as high temperature and high humidity, with no obvious change in appearance, the performance retention rate is increased by 15%-25%, the surface roughness is reduced by 10%-15%, the satisfaction of volunteers is increased by 20%-30%, and the production efficiency is increased by 20%-30%. Through the comparative analysis of the test data, it is concluded that the above-mentioned texture touch film manufacturing method has obvious advantages compared with the conventional manufacturing method in terms of mechanical properties, abrasion resistance, scratch resistance, weather resistance, touch effect and production efficiency.
[0049] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes should be covered within the protection scope of the present invention.
Claims
1. A manufacturing method of a texture touch film, characterized in that: It includes the following steps: S1: Select materials and perform pre-treatment on the materials; S2: Select a pattern roller and adjust the pattern of the pattern roller; S3: Heat and soften the pre-treated materials, and monitor the heating time and temperature; S4: Imprint the softened materials, and monitor the pressing-down pressure and speed; S5: Optimize the parameters collected by monitoring in real time; S6: Establish a simulation environment to verify the parameters; S7: Cool and shape the imprinted film; S8: Inspect the cooled film and treat the film surface; S9: Wind up the treated film to obtain a pattern tactile film.
2. The manufacturing method of a texture touch film according to claim 1, characterized in that: In S1, select composite CPP / CPP as the base material with a total thickness of 48 μm, and activate the surface of the composite CPP / CPP by plasma treatment technology.
3. The manufacturing method of a texture touch film according to claim 2, characterized in that: In S2, use a programmable pattern roller, and dynamically adjust the pattern of the pattern roller through an adjustment module. The adjustment module adopts coordinated control of a PLC and an inverter. The pattern types of the pattern roller include dot-shaped, diamond-shaped, circular, square-shaped, and irregular-shaped.
4. The manufacturing method of a texture touch film according to claim 3, characterized in that: In S3, heat-treat the pre-treated film through a heating device. The heating temperature is 105°C - 160°C, and the heating time is 2 - 6 min. The heating time and heating temperature are monitored in real time through a monitoring device.
5. The manufacturing method of a texture touch film according to claim 4, characterized in that: In S4, convey the softened film material to a pressing-down device through a conveying mechanism, imprint a specific pattern on the film surface through the adjusted pattern roller. The pressing-down speed is 30 - 35 m / min, and the pressing-down pressure is 0.2 - 0.6 MPa. The pressing-down pressure and speed are monitored in real time through a monitoring device.
6. The manufacturing method of a texture touch film according to claim 5, characterized in that: In S5, collect the monitored heating time, heating temperature, pressing-down pressure, and speed parameters through a parameter optimization module, and perform real-time optimization on the heating time, heating temperature, pressing-down pressure, and speed parameters through a machine learning algorithm.
7. The manufacturing method of a texture touch film according to claim 6, characterized in that: In S5, the parameter optimization module includes a data acquisition unit, a model training unit, and a parameter optimization unit. The data acquisition unit is connected to the model training unit, and the model training unit is connected to the parameter optimization unit. The data acquisition unit is used to collect the performance data of the film under different process parameters, including dart impact strength, tensile strength, and softness. The model training unit uses a support vector machine and a neural network to train the data and establish a mapping relationship between the process parameters and the film performance. The parameter optimization unit adjusts the process parameters in real time according to the trained model. The support vector machine decision function is: ； where w and b are parameters obtained through optimization to maximize the interval between two types of samples, x is the input vector, sgn is the sign function used to determine which class the input vector belongs to, and the optimization objective is: ； The constraint condition is: ； i = 1, 2, ⋯, n, y i is the class label of the sample x i ; During the training process, find the optimal hyperplane by maximizing the interval to maximize the interval between two types of data. Use the Lagrange multiplier method to find the optimal solution. Finally, the normal vector w can be expressed as a linear combination of support vectors: ； Where: α i is the Lagrange multiplier, representing the weight of each support vector; y i is the class label of the support vector; x i is the support vector.
8. The manufacturing method of a texture touch film according to claim 7, characterized in that: In S6, through high-precision sensor data acquisition and three-dimensional modeling technology, a virtual production scenario highly consistent with the actual production process is constructed to verify the optimized parameter combinations, including simulating the operation of the texture roller, the transmission of the film, and the imprinting process.
9. The manufacturing method of a texture touch film according to claim 8, characterized in that: In S7, the imprinted film is cooled by a cooling device to 12°C - 16°C for a duration of 2 - 6 minutes to shape the film.
10. The manufacturing method of a texture touch film according to claim 9, characterized in that: In S8 and S9, the appearance quality of the cooled and shaped film is detected by a detection device, and at the same time, a coating is applied to the film surface by a coating device to enhance the protective performance of the film. The processed film is wound and packaged by a winding device to obtain a textured touch film.