Production process optimization control system and method for thermal shrinkage film

Abstract

The invention relates to the technical field of control systems, in particular to a production process optimization control system and method for a heat shrink film. The method comprises the following steps: obtaining resin characteristic parameters of a heat shrink film raw material, and constructing an initial digital twinborn model by using the resin characteristic parameters; acquiring real-time production data, and updating the initial digital twinborn model by using the real-time production data to obtain a complete digital twinborn model; and performing melt ultrasonic-assisted homogenization and two-way stretching process simulation based on the digital twin model, and performing optimization analysis by using a simulation result to generate optimized process parameters. By constructing and updating the digital twinborn model, the melt uniformity and process parameter optimization are accurately controlled, the quality consistency and stability of the thermal shrinkage film are improved, and the product is ensured to meet the mechanical, optical and thermal shrinkage performance requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of control systems, and in particular to an optimized control system and method for the production process of heat shrinkable films. Background Art

[0002] Heat shrinkable film is a kind of polymer film material widely used in the fields of food packaging, pharmaceutical packaging, and electronic product packaging. Its production process usually includes key steps such as melt extrusion, biaxial stretching, and heat setting. With the development of polymer materials science and precision manufacturing technology, the production process of heat shrinkable film has evolved from traditional unidirectional stretching to modern high-precision biaxial stretching technology, and the process control method has gradually changed from manual empirical adjustment to automatic control. In the early production process, it mainly relied on operators to adjust the extrusion temperature, stretching ratio, and heat setting temperature according to experience, resulting in poor product quality stability. With the development of industrial sensing technology, an on-line monitoring system has been gradually introduced into the production process, which can detect key parameters such as thickness, tensile strength, and heat shrinkage rate in real time, and correct process parameters through a feedback control system. However, the traditional feedback control system relies on linear regression or simple PID control, and it is difficult to accurately predict the impact of process parameters on the performance of the final product, resulting in limited optimization ability. The defects of the existing technology are mainly reflected in the insufficient control of melt uniformity. The traditional melt extrusion process is affected by the fluctuation of resin rheological properties, and it is easy to produce local density non-uniformity, which affects the mechanical properties and optical properties of the film material. Secondly, the adjustment of biaxial stretching process parameters relies on experience, and there is a lack of an accurate mechanical orientation prediction model, resulting in difficult control of stretching uniformity. In addition, the optimization of heat setting temperature lacks a systematic method. The existing technology usually adjusts through experiments and lacks a heat shrinkage rate prediction mechanism, resulting in limited dimensional stability of the final product. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide an optimized control system and method for the production process of heat shrinkable films to solve at least one of the above technical problems.

[0004] To achieve the above object, an optimized control method for the production process of heat shrinkable films includes the following steps: Step S1: Obtain the resin characteristic parameters of the raw materials of the heat shrinkable film, and construct an initial digital twin model by using the resin characteristic parameters; Step S2: Collect real-time production data, and update the initial digital twin model by using the real-time production data to obtain a complete digital twin model; Step S3: Perform melt ultrasonic-assisted homogenization and biaxial stretching process simulation based on the digital twin model, and use the simulation results for optimization analysis to generate optimized process parameters; Step S4: Adjust the actual production process parameters based on the optimized process parameters, and perform ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching, and heat setting on the melt to obtain the actual product parameters; Step S5: Perform performance testing and quality assessment on the actual product parameters to obtain a quality characteristic assessment report; Step S6: Design a process optimization plan based on the quality characteristic assessment report, and use the process optimization plan to perform production process optimization control to obtain the optimal production process parameters.

[0005] The present invention realizes the accurate prediction of the rheological properties, crystallization behavior, and heat shrinkage properties of the melt by obtaining the resin characteristic parameters of the raw materials of the heat shrinkable film and constructing an initial digital twin model, providing basic data support for subsequent process parameter optimization. Real-time collection of production data and updating of the digital twin model enable process control to adapt to batch differences in raw materials and changes in equipment operating conditions, improving the stability of the production process. Based on the complete digital twin model, ultrasonic-assisted homogenization and biaxial stretching process simulations of the melt are carried out, making the control of melt uniformity more precise, optimizing the shear rate distribution and molecular chain orientation degree, improving the mechanical properties and optical properties of the film material. At the same time, through optimization analysis of the simulation results, the generated optimized process parameters can effectively guide the production process. Adjusting the actual production process parameters based on the optimized process parameters enables fine control of the ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching, and heat setting processes, avoiding the uncertainty brought by traditional experience-based adjustments, and improving the thickness uniformity, orientation uniformity, and heat setting dimensional stability of the film material. Performing performance testing and quality assessment on the actual product parameters quantifies the quality data of the produced heat shrinkable film, ensuring that the thickness deviation, tensile strength, heat shrinkage rate, and optical properties all meet the set standards, and providing quality feedback on the production process through the quality characteristic assessment report. Designing a process optimization plan based on the quality characteristic assessment report and using the process optimization plan to perform production process optimization control makes the process parameter adjustment targeted. Through precise optimization of the ultrasonic power, extrusion temperature, stretching ratio, and heat setting temperature, the consistency and stability of the product are further improved, thus ensuring that the finally produced heat shrinkable film meets the high-standard requirements for mechanical properties, optical properties, and heat shrinkage properties.

[0006] Preferably, the present invention also provides a production process optimization control system for a heat shrinkable film, which is used to execute the above-mentioned production process optimization control method for a heat shrinkable film. The production process optimization control system for a heat shrinkable film includes: A digital twin modeling module, which is used to obtain the resin characteristic parameters of the raw materials of the heat shrinkable film and construct an initial digital twin model using the resin characteristic parameters; A real-time data update module, which is used to collect real-time production data and update the initial digital twin model with the real-time production data to obtain a complete digital twin model; A process simulation and optimization module, which is used to simulate the melt ultrasonic-assisted homogenization and biaxial stretching processes based on the digital twin model, and perform optimization analysis using the simulation results to generate optimized process parameters; A product forming implementation module, which is used to adjust the actual production process parameters based on the optimized process parameters, and perform ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching, and heat setting on the melt to obtain actual product parameters; A quality performance evaluation module, which is used to perform performance detection and quality evaluation on the actual product parameters to obtain a quality characteristic evaluation report; A closed-loop process control module, which is used to design a process optimization plan based on the quality characteristic evaluation report, and perform production process optimization control using the process optimization plan to obtain the optimal production process parameters.

[0007] By accurately obtaining the resin characteristic parameters of the raw materials for heat shrinkable films, the present invention can provide a reliable initial digital twin model for the production process, laying a foundation for subsequent process optimization. By collecting real-time parameter data during the production process and updating the initial model, the real-time performance and accuracy of the digital twin model are ensured, making it possible to dynamically adjust and optimize the production process. By simulating the key process steps of melt homogenization and biaxial stretching based on the latest digital twin model, the influence of different process parameters can be accurately predicted, thereby providing an operable optimization plan to improve production efficiency and product quality. Applying the optimized process parameters to actual production ensures the accurate execution of the production process. At the same time, through real-time adjustment and optimization, it can ensure that the final product meets the predetermined quality standards. Conducting comprehensive performance tests and quality evaluations on the products produced in actual production provides a key quality characteristic report, helping to discover potential problems and providing a basis for further optimization. Optimizing the process based on the quality evaluation report ensures that the adjustment of each link in the production process can effectively improve product quality and production efficiency, ensuring that the product always meets high-standard quality requirements. Description of the Drawings

[0008] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objectives, and advantages of the present invention will become more apparent: Figure 1 It is a schematic flow chart of the steps of a production process optimization control method for heat shrinkable films according to the present invention; Figure 2 For Figure 1 a detailed schematic flow chart of step S1 in; Figure 3 For Figure 1Schematic diagram of the detailed step flow of step S2 in Detailed implementation mode

[0009] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0010] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0011] It should be understood that although terms such as "first" and "second" may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0012] To achieve the above object, please refer to Figures 1 to 3 , the present invention provides a production process optimization control method for heat shrinkable film, and the method includes the following steps: Step S1: Obtain the resin characteristic parameters of the heat shrinkable film raw material, and construct an initial digital twin model using the resin characteristic parameters; Step S2: Collect real-time production data, and update the initial digital twin model using the real-time production data to obtain a complete digital twin model; Step S3: Perform melt ultrasonic-assisted homogenization and biaxial stretching process simulation based on the digital twin model, and use the simulation results for optimization analysis to generate optimized process parameters; Step S4: Adjust the actual production process parameters based on the optimized process parameters, and perform ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching and heat setting on the melt to obtain actual product parameters; Step S5: Perform performance detection and quality evaluation on the actual product parameters to obtain a quality characteristic evaluation report; Step S6: Design a process optimization plan based on the quality characteristic evaluation report, and use the process optimization plan to perform production process optimization control to obtain the optimal production process parameters.

[0013] In the embodiment of the present invention, with reference to Figure 1 As shown in the figure, it is a schematic diagram of the step flow of a production process optimization control method for heat shrinkable film according to the present invention. In this example, the production process optimization control method for heat shrinkable film includes the following steps: Step S1: Obtain the resin characteristic parameters of the heat shrinkable film raw material, and use the resin characteristic parameters to construct an initial digital twin model; The resin characteristic parameters obtained in the embodiment of the present invention include measuring the melt index (MI), crystallinity, molecular weight distribution, density, and viscoelastic parameters of polyethylene, polypropylene, or polyethylene terephthalate resin. Specifically, the resin melting point is measured to be 110±2°C and the crystallinity is 45±3% by differential scanning calorimetry (DSC). The melt index at 175°C is measured to be 2.5±0.2 g / 10 min by a capillary rheometer. The number average molecular weight of the resin is measured to be 80000±5000 and the weight average molecular weight is 220000±8000 by gel permeation chromatography (GPC). The resin density is measured to be 0.923±0.002 , and the storage modulus of the resin is measured by a rotational rheometer is 1200±50 Pa, and the loss modulus is 800±40 Pa; the above-mentioned measured resin characteristic parameters are input into POLYFLOW finite element analysis software to construct a three-dimensional digital model including resin physical properties, rheological properties, and thermodynamic properties. The mesh element size is set to 0.5 mm, and the total number of meshes is 50000. The Cross-WLF viscosity model is used to describe the resin rheological behavior, and the Tait equation of state is used to describe the resin PVT relationship. The boundary conditions are set as the die wall temperature of 160±5°C, the extrusion pressure of 15±1 MPa, and the shear rate of 100±10 , and the initial digital twin model is obtained through iterative calculation. The average error between the material flow field, temperature field, and stress field predicted by this model and the experimental measurement values is less than 5%, thus completing the construction of the initial digital twin model.

[0014] Step S2: Collect real-time production data, and use the real-time production data to update the initial digital twin model to obtain a complete digital twin model; In the embodiments of the present invention, the real-time production data is collected by installing a multi-point sensing and monitoring system on the heat shrinkable film production line. Specifically, it includes installing 8 PT100 type temperature sensors in different areas of the extruder barrel to measure the melt temperature, and the real-time collected temperature data range is from 165±5°C to 210±5°C; installing 4 pressure sensors to monitor the extrusion pressure, and the measurement range is from 12±1MPa to 18±1MPa; installing a laser displacement sensor at the outlet of the T-die to measure the film thickness, with an accuracy of ±0.001mm; installing an optical encoder in the stretching section to measure the stretching rate, and the range is from 5±0.5m / min to 15±0.5m / min; installing a power meter in the ultrasonic treatment unit to measure the ultrasonic output power, and the range is from 500±20W to 1500±20W, with a frequency of 20±0.5kHz; using a near-infrared spectrometer to monitor the change of melt crystallinity in real time, with a sampling frequency of 10Hz; the data collected by all sensors is transmitted to the data acquisition unit through the fieldbus, the acquisition frequency is set to 100Hz, and the acquisition duration is 72 hours, obtaining a total of 25,920,000 data points in the real-time production parameter dataset; then using the Kalman filter algorithm to denoise the collected data, filtering out high-frequency noise, and the signal-to-noise ratio is increased to 40dB; inputting the processed real-time production data into the initial digital twin model constructed in step S1, and continuously correcting the parameter values in the model through the Bayesian parameter estimation method, including correcting the resin rheological index n value from 0.35 to 0.32, the activation energy Ea from 40kJ / mol to 38.5kJ / mol, and the interfacial heat transfer coefficient from 1200 adjusted to 1350 ; after 100 times of iterative optimization, the average error between the model prediction value and the measured value is reduced from 5% to 2.5%, and the update of the digital twin model is completed.

[0015] Step S3: Based on the digital twin model, perform melt ultrasonic-assisted homogenization and biaxial stretching process simulation, and use the simulation results for optimization analysis to generate optimized process parameters; In the embodiments of the present invention, based on a complete digital twin model, the ultrasonic-assisted homogenization parameter range is first set. The frequency is fixed at 20 kHz, and 5 levels are set at intervals of 5 μm for the amplitude between 10 μm and 30 μm, 5 levels are set at intervals of 100 W for the power between 800 W and 1200 W, and 5 levels are set at intervals of 0.5 s for the processing time between 0.5 s and 2.5 s. Subsequently, the biaxial stretching parameter range is set. 5 levels are set at intervals of 0.5 for the longitudinal stretching ratio between 3.0 and 5.0, 5 levels are set at intervals of 0.5 for the transverse stretching ratio between 3.0 and 5.0, 5 levels are set at intervals of 5 °C for the longitudinal stretching temperature between 95 °C and 115 °C, 5 levels are set at intervals of 5 °C for the transverse stretching temperature between 120 °C and 140 °C, 5 levels are set at intervals of 10 m / min for the longitudinal stretching rate between 50 m / min and 90 m / min, and 5 levels are set at intervals of 10 m / min for the transverse stretching rate between 40 m / min and 80 m / min. The orthogonal experimental design method DOE is used to determine 125 groups of key process parameter combinations for simulation. Melt rheology numerical simulation is performed for each group of parameter combinations to calculate the melt stress distribution, molecular orientation degree, and temperature field distribution under the action of ultrasonic waves. The simulation grid is divided into 100,000 units, the time step is 0.01 s, and the SIMPLE algorithm is used as the solver. At the same time, finite element analysis of the biaxial stretching film-forming process is performed to simulate and calculate the tensile stress distribution, strain field distribution, and molecular chain orientation distribution. The hyperelastic Neo-Hookean constitutive model is used to describe the material deformation behavior. For each group of simulation results, key quality indicators are extracted, including the thickness uniformity deviation value ≤0.002 mm, tensile strength ≥120 MPa, elongation at break ≥350%, the thermal shrinkage rate S is in the range of 60% ± 5%, haze H ≤ 1.5%, light transmittance T ≥ 90%. The response surface method RSM is used to establish the mapping relationship between process parameters and quality indicators, and parameter sensitivity analysis is performed through the neural network algorithm. The optimal parameter combination is determined as: ultrasonic amplitude 20 μm, power 1000 W, processing time 1.5 s, longitudinal stretching ratio 4.0, longitudinal stretching temperature 105 °C, longitudinal stretching rate 70 m / min, transverse stretching ratio 4.0, transverse stretching temperature 130 °C, transverse stretching rate 60 m / min, and the final optimized process parameter table is generated accordingly.

[0016] Step S4: Adjust the actual production process parameters based on the optimized process parameters, and perform ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching, and heat setting on the melt to obtain the actual product parameters; In the embodiment of the present invention, based on optimized process parameters, the process parameters of the heat shrinkable film production line are first adjusted by a PLC control system. The adjustment contents include setting the temperature of the first section of the extruder to 175±2°C, the temperature of the second section to 195±2°C, the temperature of the third section to 205±2°C, the temperature of the fourth section to 215±2°C, the screw speed to 50±1 rpm, and the die head temperature to 220±2°C; then an ultrasonic-assisted homogenization device is installed between the extruder and the die head, the frequency of the ultrasonic generator is set to 20 kHz, the amplitude is 20 μm, the power is 1000 W, the treatment time is 1.5 s, and the ultrasonic transducer is in direct contact with the melt. At this time, the melt temperature is 210±3°C; then the melt after ultrasonic treatment is extruded and formed through a T-die, the thickness of the extruded film is controlled within 300±10 μm, and the extrusion speed is controlled within 30±1 m / min; the extruded film is longitudinally stretched through an MDO (Machine Direction Orientation) device, the preheating temperature is set to 95±2°C, the stretching temperature is set to 105±2°C, the stretching ratio is set to 4.0, and the stretching rate is set to 70 m / min; the film after longitudinal stretching is cooled to 60±2°C through a transition section, and then enters a TDO (Transverse Direction Orientation) device for transverse stretching, the preheating temperature is set to 120±2°C, the stretching temperature is set to 130±2°C, the stretching ratio is set to 4.0, and the stretching rate is set to 60 m / min; the film after biaxial stretching enters a heat setting device, the setting temperature is set to 140±2°C, and the setting time is set to 5±0.2 s; finally, it is cooled to room temperature through a cooling roll, the temperature of the cooling roll is set to 25±1°C, and the cooling time is set to 3±0.2 s; the winding speed is set to 120±2 m / min, and the winding tension is set to 50±2 N, thereby obtaining a heat shrinkable film with a thickness of 15±0.5 μm and a width of 1500±5 mm. The measured actual product parameters include a thickness uniformity deviation value of 0.001 mm, a tensile strength of 125 MPa, an elongation at break of 380%, a heat shrinkage rate of 62%, a haze of 1.2%, and a light transmittance of 92%.

[0017] Step S5: Perform performance detection and quality evaluation on the actual product parameters to obtain a quality characteristic evaluation report; In the embodiment of the present invention, the actual product parameters are measured for thickness uniformity by a thickness laser gauge through three consecutive scans at five fixed positions with a 10-cm lateral interval on the film material. The longitudinal and lateral tensile strengths and elongation at break are tested using a universal material testing machine in accordance with ASTM D882 standard at 23°C. The longitudinal and lateral thermal shrinkage rates are measured after soaking in a 100°C constant-temperature oil bath for 30 seconds using a thermal shrinkage rate tester. The oxygen transmission rate is detected using a differential pressure gas permeation meter at a differential pressure of 0.1 MPa. The optical haze is measured using a haze meter according to GB / T 2410. The above measured data are input into a quality assessment system and compared with the preset standard parameters. Among them, the absolute value of the thickness deviation exceeding ±2 μm, the longitudinal tensile strength below 50 MPa or the lateral tensile strength below 45 MPa, the longitudinal thermal shrinkage rate below 70% or the lateral thermal shrinkage rate below 65%, and the oxygen transmission rate exceeding 150 and the haze exceeding 3% are all marked as non-conforming items; a quality characteristic assessment report including the measured values, standard thresholds, deviation percentages, and problem location coordinates of each detection item is generated.

[0018] Step S6: Design a process optimization plan based on the quality characteristic assessment report, and use the process optimization plan to control the production process optimization to obtain the optimal production process parameters.

[0019] In the embodiment of the present invention, based on the non-conforming items marked in the quality characteristic assessment report and the associated process parameter data, the process optimization analysis system extracts the screw speed and die lip opening records corresponding to the extrusion molding stage with a thickness deviation exceeding ±2 μm, the longitudinal stretching ratio and transverse stretching temperature data corresponding to the insufficient thermal shrinkage rate in the biaxial stretching stage, and the ultrasonic-assisted homogenization treatment time and melt pressure curve corresponding to the excessive oxygen transmission rate. The multi-variable orthogonal experimental method is used to design an optimization strategy. The power of the ultrasonic generator is adjusted to 2000 W, and the homogenization time is increased by 5 seconds to reduce the melt density fluctuation. The temperature zones of the extruder are set to 180°C / 185°C / 190°C / 190°C / 185°C to improve the thickness uniformity. The biaxial stretching ratio is increased from 3.0×3.0 to 3.2×3.1, and the longitudinal preheating roller temperature is controlled at 85°C and the transverse stretching roller temperature is controlled at 88°C. The melt flow and crystallinity are simulated by loading the optimized parameters through a digital twin model. If the simulated longitudinal thermal shrinkage rate reaches 72% and the transverse thermal shrinkage rate reaches 68% and the thickness fluctuation range is less than ±1.5 μm, the optimized parameter package is sent to the production line PLC controller, triggering the adjustment of the extruder screw speed from 45 rpm to 48 rpm, the calibration of the die lip opening from 2.0 mm to 1.95 mm, and the synchronous increase of the stretching chain clip speed by 2%. After the parameter update, three consecutive production batches are verified. If all the batch detection data meet the preset standards in step S5, the current parameters are locked as the optimal production process parameters and written into the process database.

[0020] The present invention realizes the accurate prediction of the melt rheological properties, crystallization behavior, and heat shrinkage performance by obtaining the resin characteristic parameters of the heat shrinkable film raw material and constructing an initial digital twin model, providing basic data support for the subsequent optimization of process parameters. The production data is collected in real time and the digital twin model is updated, enabling the process control to adapt to the differences in raw material batches and the changes in equipment operating conditions, and improving the stability of the production process. Based on the complete digital twin model, the melt ultrasonic-assisted homogenization and biaxial stretching process are simulated, making the control of melt uniformity more precise, optimizing the shear rate distribution and molecular chain orientation degree, improving the mechanical properties and optical properties of the film material. At the same time, through the optimization analysis of the simulation results, the generated optimized process parameters can effectively guide the production process. Based on the optimized process parameters, the actual production process parameters are adjusted, enabling the ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching, and heat setting processes to be finely controlled, avoiding the uncertainty brought by traditional experience-based adjustments, and improving the film thickness uniformity, orientation uniformity, and heat setting dimensional stability. The performance of the actual product parameters is detected and quality evaluated, making the quality data of the produced heat shrinkable film quantifiable, ensuring that the thickness deviation, tensile strength, heat shrinkage rate, and optical properties all meet the set standards, and providing production process quality feedback through the quality characteristic evaluation report. Based on the quality characteristic evaluation report, a process optimization plan is designed, and the production process is optimized and controlled using the process optimization plan, making the process parameter adjustment targeted. Through the precise optimization of the ultrasonic power, extrusion temperature, draw ratio, and heat setting temperature, the consistency and stability of the product are further improved, thus ensuring that the finally produced heat shrinkable film meets the high-standard requirements for mechanical properties, optical properties, and heat shrinkage performance.

[0021] Preferably, step S1 includes the following steps: Step S11: Measure the molecular weight distribution of the heat shrinkable film raw material to obtain the molecular weight distribution characteristic parameters; Step S12: Perform differential scanning calorimetry test on the heat shrinkable film raw material to obtain the crystallization characteristic parameters; use the crystallization characteristic parameters to perform biaxial stretching molecular orientation simulation to obtain the biaxial stretching digital module; Step S13: Perform capillary rheology test on the heat shrinkable film raw material to obtain the rheological characteristic parameters; use the rheological characteristic parameters to perform ultrasonic melt homogenization mathematical modeling to obtain the ultrasonic melt homogenization digital module; Step S14: Perform thermogravimetric thermal stability test on the heat shrinkable film raw material to obtain the thermal stability-related parameters; use the thermal stability-related parameters to perform flow-heat transfer coupling simulation of extrusion molding to obtain the extrusion molding digital module; Step S15: Use the molecular weight distribution characteristic parameters and the thermal stability-related parameters to perform molecular structure evolution simulation during the heat setting process to obtain the heat setting digital module; Step S16: Denote the molecular weight distribution characteristic parameter, crystallization characteristic parameter, rheological characteristic parameter, and heat stability related parameter as resin characteristic parameters; Step S17: Integrate and perform correlation mapping on the ultrasonic melt homogenization digital module, biaxial stretching digital module, extrusion molding digital module, and heat setting digital module to obtain an initial digital twin model.

[0022] As an embodiment of the present invention, referring to Figure 2 shown, it is Figure 1 the detailed step flow schematic diagram of step S1 in Step S11: Measure the molecular weight distribution of the heat shrinkable film raw material to obtain the molecular weight distribution characteristic parameter; Step S12: Perform differential scanning calorimetry test on the heat shrinkable film raw material to obtain the crystallization characteristic parameter; use the crystallization characteristic parameter to perform biaxial stretching molecular orientation simulation to obtain the biaxial stretching digital module; Step S13: Perform capillary rheology test on the heat shrinkable film raw material to obtain the rheological characteristic parameter; use the rheological characteristic parameter to perform ultrasonic melt homogenization mathematical modeling to obtain the ultrasonic melt homogenization digital module; Step S14: Perform thermogravimetric heat stability test on the heat shrinkable film raw material to obtain the heat stability related parameter; use the heat stability related parameter to perform flow - heat transfer coupling simulation of extrusion molding to obtain the extrusion molding digital module; Step S15: Use the molecular weight distribution characteristic parameter and the heat stability related parameter to perform molecular structure evolution simulation during heat setting to obtain the heat setting digital module; Step S16: Denote the molecular weight distribution characteristic parameter, crystallization characteristic parameter, rheological characteristic parameter, and heat stability related parameter as resin characteristic parameters; Step S17: Integrate and perform correlation mapping on the ultrasonic melt homogenization digital module, biaxial stretching digital module, extrusion molding digital module, and heat setting digital module to obtain an initial digital twin model.

[0023] In the embodiment of the present invention, the molecular weight distribution characteristic parameters of the resin are measured by a gel permeation chromatograph at a flow rate of 1.0 mL / min and a column temperature of 40 °C in a tetrahydrofuran mobile phase, and the weight average molecular weight Mw and the dispersity D are output; a differential scanning calorimeter DSC Q200 is used to scan the range from -50 °C to 200 °C at a heating rate of 10 °C / min in a nitrogen atmosphere to obtain the melting peak temperature Tm and the crystallinity Xc. The Xc is input into the finite element analysis software ANSYS Polyflow to set the drawing rate of 2.5 m / s and the temperature gradient of 85 - 110 °C for the biaxial drawing molecular orientation simulation, and a biaxial drawing digital module containing the molecular chain orientation angle distribution is generated; a capillary rheometer RH7 is used to test the viscosity curve in the range of shear rates from 100 to 1000 within the range. Based on the Power-law equation, the flow index n = 0.32 is fitted, and a mathematical relationship between the melt viscosity attenuation rate and the homogenization time is established by combining the parameters of the ultrasonic generator frequency of 28 kHz and the amplitude of 15 μm, and written into the ultrasonic melt homogenization digital module; a thermogravimetric analyzer TGA 550 is used to heat up to 600 °C at a rate of 20 °C / min in an air atmosphere, and the 5% thermal weight loss temperature Td5% = 385 °C is recorded. This parameter is imported into ANSYS Fluent to set the screw speed of 45 rpm and the die head temperature of 190 °C to simulate the coupling relationship between the shear rate distribution and the temperature field of the melt in the runner, and an extrusion molding digital module is output; based on the molecular weight distribution parameter Mw = 120,000 and the Td5% data, a polyethylene molecular chain model is constructed using Materials Studio software, and the curve of the change in the molecular chain folding energy barrier during the heat setting stage at 180 °C is calculated under the COMPASS force field to generate a heat setting digital module; the above Mw, Xc, n, Td5% parameters and the four digital modules are transmitted to the TwinBuilder platform through the OPC UA protocol, and a dynamic mapping relationship between the amplitude of the ultrasonic vibration unit and the melt viscosity, an association rule between the temperature zones of the extruder and the runner shear rate, and a feedback logic between the speed of the drawing roll and the molecular orientation angle are established in the three-dimensional production line model to complete the construction of the initial digital twin model.

[0024] By measuring the molecular weight distribution of the raw materials of the heat-shrinkable film, the present invention can accurately characterize the distribution of polymer chain lengths, providing basic data support for subsequent melt rheological property analysis and mechanical property prediction. The crystallization characteristic parameters obtained by differential scanning calorimetry for crystallinity make the simulation of the molecular chain orientation behavior during the biaxial stretching process more accurate, ensuring the reliability of the stretching process optimization. The rheological characteristic parameters provided by capillary rheology tests make the mathematical modeling of the homogenization of the melt under ultrasonic waves more accurate, improving the melt flow uniformity, reducing local stress concentration, and thus improving the mechanical and optical properties of the final film. The thermal stability-related parameters provided by thermogravimetric thermal stability tests enable the flow-heat transfer coupling simulation during the extrusion molding process to more accurately predict the temperature field distribution and melt degradation, improving the stability of the extrusion process and reducing the performance fluctuations of the film caused by thermal decomposition. Using the molecular weight distribution characteristic parameters and thermal stability-related parameters to simulate the molecular structure evolution during the heat setting process makes the optimization of the heat setting temperature more accurate, ensuring the dimensional stability and heat shrinkage performance of the final film. The induction and integration of resin characteristic parameters enable the construction of the subsequent digital twin model to have complete data support, improving the accuracy of the entire production process optimization. Through the integration and correlation mapping of multiple digital modules such as ultrasonic melt homogenization, biaxial stretching, extrusion molding, and heat setting, a systematic digital modeling of the heat-shrinkable film production process is achieved, providing an efficient tool for accurately controlling and optimizing the production process.

[0025] Preferably, step S2 includes the following steps: Step S21: Deploy infrared thermocouples in the heat-shrinkable film production line, and use the infrared thermocouples to collect the temperature during the production process of the heat-shrinkable film as temperature distribution data; Step S22: Deploy piezoelectric sensors in the heat-shrinkable film production line, and use the piezoelectric sensors to collect the pressure during the production process of the heat-shrinkable film as pressure distribution data; Step S23: Deploy ultrasonic transducers in the heat-shrinkable film production line, and use the ultrasonic transducers to collect the ultrasonic energy during the production process of the heat-shrinkable film as ultrasonic parameter data; Step S24: Deploy a laser thickness gauge in the heat-shrinkable film production line, and use the laser thickness gauge to collect the thickness during the production process of the heat-shrinkable film as film thickness data; Step S25: Deploy a fiber Bragg grating tensiometer in the heat-shrinkable film production line, and use the fiber Bragg grating tensiometer to collect the tension during the production process of the heat-shrinkable film as stretching tension data; Step S26: Record the temperature distribution data, pressure distribution data, ultrasonic parameter data, film thickness data, and stretching tension data as real-time production process data; Step S27: Standardize the real-time data of the production process, use the standardized real-time data of the production process to perform real-time mapping on the digital twin model of the production process, and perform parameter calibration to obtain a complete digital twin model.

[0026] As an embodiment of the present invention, refer to Figure 3 As shown in Figure 1 is a detailed step flow schematic diagram of step S2 in Step S21: Deploy infrared thermocouples in the heat shrink film production line, and use the infrared thermocouples to collect the temperature during the production process of the heat shrink film as temperature distribution data; Step S22: Deploy piezoelectric sensors in the heat shrink film production line, and use the piezoelectric sensors to collect the pressure during the production process of the heat shrink film as pressure distribution data; Step S23: Deploy ultrasonic transducers in the heat shrink film production line, and use the ultrasonic transducers to collect the ultrasonic energy during the production process of the heat shrink film as ultrasonic parameter data; Step S24: Deploy a laser thickness gauge in the heat shrink film production line, and use the laser thickness gauge to collect the thickness during the production process of the heat shrink film as film thickness data; Step S25: Deploy a fiber Bragg grating tensiometer in the heat shrink film production line, and use the fiber Bragg grating tensiometer to collect the tension during the production process of the heat shrink film as tensile tension data; Step S26: Record the temperature distribution data, pressure distribution data, ultrasonic parameter data, film thickness data and tensile tension data as real-time data of the production process; Step S27: Standardize the real-time data of the production process, use the standardized real-time data of the production process to perform real-time mapping on the digital twin model of the production process, and perform parameter calibration to obtain a complete digital twin model.

[0027] In the embodiment of the present invention, FLIR A315 infrared thermocouples are symmetrically installed on both sides of the extruder die, and the temperature distribution data in the horizontal range of 0-50cm at the die outlet is collected at a sampling frequency of 10 times per second, and the temperature measurement range is set to 160-220°C; a Kistler 601C piezoelectric sensor is embedded in the contact surface between the ultrasonic vibration plate and the melt, and 5-30MPa pressure fluctuation data is recorded with a time resolution of 0.1ms; the UT-300 ultrasonic transducer of Bidatek is integrated into the homogenization section cylinder, and ultrasonic waves are emitted at a fixed frequency of 28kHz and reflected energy signals are received, and the ultrasonic energy absorption rate in the sound pressure level range of 75-85dB is extracted through spectrum analysis; a KEYENCE LJ-V7080 laser thickness gauge is deployed along the horizontal track of the production line, and the full width of the film material is scanned at a spacing of 0.1mm, and the thickness data is recorded and the coordinate position with a deviation exceeding ±2μm is marked; FOS&S are respectively installed at the longitudinal stretching roller group and the transverse stretching chain clamp. The FBGS-500 fiber Bragg grating tension meter synchronously collects real-time data streams of longitudinal tensile tension of 120-150N and transverse tensile tension of 80-110N at a frequency of 100Hz; the above temperature, pressure, ultrasonic energy, thickness and tension data are aggregated to the industrial server through the Modbus TCP protocol, and the data timestamps are aligned and converted into engineering units using the ISA-88 standard. The temperature data is mapped to the digital twin model extruder temperature control module, the pressure data is associated with the ultrasonic amplitude PID control parameters, and the thickness deviation coordinates are bound to the die lip adjustment mechanism position; the calibration algorithm is used to compare the standard deviation of the real-time thickness data with the predicted value of the digital twin model. When the standard deviation of five consecutive samplings exceeds 0.8μm, the melt flow rate compensation coefficient is triggered to update, and the tension-ratio conversion formula of the biaxial stretching module is synchronously corrected, so that the extrusion flow prediction error rate of the digital twin model is reduced from 1.2% to 0.5%, and the stretch ratio control accuracy is improved to ±0.05.

[0028] The present invention realizes high-precision real-time monitoring of the temperature distribution during the production process by deploying infrared thermocouples in the heat-shrinkable film production line, enabling the accurate capture of changes in the temperature field and providing basic data support for the optimization of melt flow, stretching orientation, and heat setting processes. Piezoelectric sensors are used to obtain pressure distribution data, enabling real-time monitoring of pressure fluctuations during the extrusion and stretching of the melt, which helps to adjust the extrusion rate and stretching tension, and improve the thickness uniformity and mechanical stability of the film material. The application of ultrasonic transducers quantifies the effect of ultrasonic energy during the melt homogenization process, provides data basis for optimizing the ultrasonic power and action time, improves the melt uniformity, and reduces the phenomenon of local density non-uniformity. The deployment of laser thickness gauges enables the acquisition of film thickness data with high resolution, ensures the real-time and accuracy of thickness detection, and provides accurate thickness correction references for the feedback control system. The introduction of fiber Bragg grating tension gauges enables the accurate monitoring of changes in stretching tension during the production process, provides key data support for the optimization of biaxial stretching process parameters, and improves the stretching uniformity and orientation stability. The standardized processing of real-time production process data eliminates data noise and systematic errors, improves data consistency, and ensures the accuracy of real-time mapping. By performing real-time mapping and parameter calibration on the digital twin model of the production process, the dynamic optimization of the digital twin model is achieved, making the process control more precise and laying the foundation for the intelligent control of the production process.

[0029] Preferably, the melt ultrasonic assisted homogenization based on the digital twin model in step S3 includes: Performing rheological property detection on the high-precision digital twin model to obtain melt viscosity distribution data, where the shear viscosity range of the melt viscosity distribution data is to , and the temperature sensitivity parameter is 20 - 120 kJ / mol; Using the melt viscosity distribution data to perform melt ultrasonic sound field simulation to obtain ultrasonic power distribution data; Performing cavitation dynamics simulation based on the ultrasonic power distribution data to obtain bubble dynamic change data; The bubble size in the bubble dynamic change data is 1 - 100 μm, and the bubble number density is to per , and the bubble lifetime is to in the order of seconds; Performing melt molecular chain topology calculus based on the bubble dynamic change data to obtain molecular chain orientation uniformity data; Performing thermo-mechanical coupling analysis of the melt temperature change based on the molecular chain orientation uniformity data to obtain melt temperature distribution data; The temperature gradient of the melt temperature distribution data is 0.5 - 5 °C / mm, and the temperature fluctuation range is ±3 °C; Evaluate the melt homogenization effect of the melt temperature distribution data to obtain the melt uniformity data.

[0030] In the embodiment of the present invention, a cone-plate rotational rheometer is used to perform rheological tests on the raw resin of the heat-shrinkable film. The test temperatures are set at four temperature points of 160 °C, 180 °C, 200 °C, and 220 °C, and the shear rate range is set at 0.01 - 1000 s⁻¹. The shear viscosities measured at each temperature point are respectively to at 175 °C to at 195 °C to , and the temperature sensitivity parameter of the resin is calculated to be 85 kJ / mol through the Arrhenius formula; the rheological test data is imported into the digital twin model, and the zero-shear viscosity of the resin is obtained by fitting through the Cross-WLF model , the characteristic time λ = 0.015 s, and the rheological index n = 0.32; subsequently, the melt viscosity distribution data is input into the ultrasonic sound field simulation calculator. The ultrasonic frequency is set at 20 kHz, the amplitude is 20 μm, the sound source geometry is a cylindrical transducer with a diameter of 25 mm, and the sound field distribution is calculated by the finite-difference time-domain method. The ultrasonic sound pressure distribution is 135 dB in the central region and 120 dB in the edge region, and the sound intensity distribution is 25 in the central region and 10 in the edge region; based on the ultrasonic power distribution data, the dynamic behavior of bubbles in the melt is calculated using the Rayleigh-Plesset equation. The initial bubble diameter is set at 5 μm, the ambient pressure is the atmospheric pressure, and the surface tension is 0.035 N / m. It is calculated that the maximum bubble diameter reaches 45 μm, the compression ratio is 9:1, and the bubble number density is per , and the lifetime of a single bubble is seconds; the bubble dynamic change data is input into the molecular chain topology calculus program and simulated by the Monte Carlo method Regarding the configurational changes of individual molecular chains, the calculated uniformity index of molecular chain orientation increased from the initial value of 0.65 to 0.88, the molecular orientation distribution index increased from 0.58 to 0.82, and the molecular weight distribution index decreased from 2.75 to 2.45; based on the molecular chain orientation uniformity data, the finite volume method was used to calculate the melt temperature field. The number of grids was 200×200×50. The boundary conditions were set as the wall temperature of 220°C and the initial melt temperature of 210°C. The calculated melt temperature gradient was 1.2°C / mm in the central region and 3.8°C / mm in the edge region, and the temperature fluctuation range was ±2.5°C; the melt uniformity was evaluated through standard deviation analysis. The standard deviation of the melt components before ultrasonic treatment was 0.15, the standard deviation of temperature was 8.5°C, and the standard deviation of viscosity was 750 Pa·s. After ultrasonic treatment, the standard deviation of the melt components decreased to 0.05, the standard deviation of temperature decreased to 2.8°C, and the standard deviation of viscosity decreased to 240 Pa·s, completing the evaluation of the melt uniformity data.

[0031] In the present invention, through rheological property detection of the high-precision digital twin model, the viscosity changes of the melt under different shear rates and temperature conditions are quantified, providing accurate data support for optimizing melt flow and processing parameters. The simulation of the ultrasonic sound field of the melt clarifies the spatial distribution of ultrasonic energy, which helps to optimize the input of ultrasonic power and concentrate the energy on the key areas of melt homogenization. The cavitation dynamics simulation accurately predicts the dynamic evolution law of bubbles, including the size, number density, and lifetime of bubbles, providing a quantitative analysis basis for the energy transfer mechanism of ultrasonic action, thereby optimizing the cavitation effect and improving the melt homogenization efficiency. The application of melt molecular chain topology calculus enables quantitative analysis of the molecular chain orientation uniformity under ultrasonic action, providing accurate data support for optimizing the melt structure and improving mechanical properties. The thermo-mechanical coupling analysis further reveals the coupling relationship between the melt temperature change and mechanical behavior, making the optimization control of the temperature gradient and fluctuation range more accurate, improving the thermal stability of the melt, and reducing defects caused by thermal stress. Finally, through the evaluation of the melt homogenization effect, the accurate quantification of the melt uniformity is achieved, enabling the production process to be optimized and adjusted based on data feedback, improving the overall quality stability of the heat shrinkable film.

[0032] Preferably, the biaxial stretching process simulation in step S3 includes: Performing an unsteady temperature field measurement on the high-precision digital twin model to obtain the initial temperature distribution data; Using the initial temperature distribution data to perform a melt pre-stretching stress simulation to obtain the pre-stretching stress distribution data; The stress range of the pre-stretching stress distribution data is 0.5 - 10 MPa, and the stress non-uniformity coefficient is less than 0.2; Based on the pre-stretching stress distribution data, the melt orientation evolution is deduced to obtain the molecular chain orientation degree data, where the specific range of the orientation function value of the molecular chain orientation degree data is 0.3 - 0.8, and the specific range of the orientation function gradient is 0.05 - 0.2 / mm; Based on the molecular chain orientation degree data, the stress field during the transverse stretching process is reconstructed to obtain the transverse stretching stress distribution data; According to the transverse stretching stress distribution data, the dynamic measurement of the heat setting temperature field is calculated to obtain the temperature gradient field tensor data; The specific range of the principal direction temperature gradient in the temperature gradient field tensor data is 0.2 - 2 °C / mm, and the specific range of the secondary direction temperature gradient is 0.1 - 1 °C / mm; Based on the temperature gradient field tensor data, a thermo-mechanical coupling numerical simulation is performed to obtain the thermal stress distribution data; Using the thermal stress distribution data to predict the dimensional stability of the product, the product dimensional deviation data is obtained.

[0033] In the embodiment of the present invention, the three-dimensional transient heat conduction equation is used to calculate the temperature distribution during the production process of the heat shrinkable film. The temperatures of the four sections of the extruder barrel are set to 175 °C, 195 °C, 205 °C, and 215 °C respectively, the die head temperature is 220 °C, the ambient temperature is 25 °C, the melt thermal conductivity is 0.25 W / (m·K), the specific heat capacity is 2.1 kJ / (kg·K), and the density is 0.923 , using the implicit difference format, the time step is 0.01 s, the spatial grid size is 0.5 mm, and the calculated melt temperature distribution range is 195 °C to 220 °C, the radial temperature gradient is 2.8 °C / mm, and the axial temperature gradient is 0.5 °C / mm; the initial temperature distribution data is input into the non-linear viscoelastic mechanics equation to calculate the pre-stretching stress of the melt at the die head of the extruder. The melt shear modulus is set to 1.5 MPa, the relaxation time is 0.8 s, and the stretching rate is 15 , the pre-tensile stress is 1.8 MPa in the central region and 5.2 MPa in the edge region, and the stress non-uniformity coefficient is 0.15; based on the pre-tensile stress distribution data, the Doi-Edwards tube model is used to calculate the molecular chain orientation evolution process. The molecular weight is set to 200,000 g / mol, the characteristic tube length is 50 nm, and the tube diameter is 5 nm. The calculated molecular chain orientation function is 0.65 at the center of the longitudinal stretching zone and 0.45 at the edge, and the orientation function gradient is 0.12 / mm; the molecular chain orientation degree data is input into the transverse stretching mechanical equation. The transverse stretching rate is set to 50 m / min, the stretching ratio is 4.0, and the stretching temperature is 130 °C. The calculated transverse stretching stress is 6.5 MPa at the center of the film width direction and 8.2 MPa at the edge, and the stress distribution uniformity is 0.88; the transverse stretching stress distribution data is substituted into the energy equation of the heat setting process. The setting temperature is set to 140 °C, the setting time is 5 s, and the heat dissipation coefficient is 15 , and the temperature gradient field of the film during the heat setting process is calculated. The main direction temperature gradient is 1.2 °C / mm, the secondary direction temperature gradient is 0.7 °C / mm, and the temperature field uniformity index is 0.92; based on the temperature gradient field tensor data, the thermo-mechanical coupling constitutive model is used to calculate the thermal expansion coefficient as / °C, the linear elastic modulus is 850 MPa, the Poisson's ratio is 0.38, the thermal stress distribution range is 0.8 MPa to 2.6 MPa, and the thermal stress uniformity is 0.87; the size stability of the product under standard conditions (23 °C, 50% relative humidity) is predicted by combining the thermal stress distribution data with the strain field calculation. The longitudinal size deviation is ±0.5%, the transverse size deviation is ±0.7%, the thickness deviation is ±3%, the area deviation is ±1.2%, and the diagonal deviation is ±0.8%, thus completing the product size deviation data.

[0034] Through the measurement of the unsteady temperature field, the present invention accurately obtains the temperature distribution characteristics inside the melt, making the temperature control in the subsequent processing more refined and improving the thermal field uniformity. The simulation of the pre-stretching stress of the melt enables the accurate prediction of the stress state of the melt before stretching, which helps to optimize the process parameters in the pre-stretching stage, thereby reducing the stress non-uniformity and enhancing the processing stability. The deduction of the melt orientation evolution quantifies the variation law of the molecular chain orientation degree, provides a reliable basis for controlling the orientation uniformity, and optimizes the mechanical properties of the material. The reconstruction of the transverse tensile stress field makes the stress distribution more uniform during the transverse stretching of the melt, improves the stretching uniformity, and reduces the defect risk caused by local stress concentration. The dynamic measurement of the heat setting temperature field quantifies the distribution law of the temperature gradient during the heat setting process, provides accurate data support for optimizing the temperature control strategy, and thus improves the dimensional stability of the product. The thermo-mechanical coupling numerical simulation further reveals the evolution law of the thermal stress during the heat setting process, makes the stress control more accurate, and reduces the influence of the residual stress inside the heat shrinkable film on the performance of the final product. Finally, through the prediction of the product size deviation data, the production process can be optimized and adjusted in real time, improving the dimensional accuracy and consistency of the product.

[0035] Particularly importantly, the optimization analysis using the simulation results in step S3 includes: Performing a prediction calculation of the mechanical properties of the heat shrinkable film based on the melt uniformity data and the molecular chain orientation degree data to obtain the predicted mechanical property indexes; Performing a sensitivity analysis of the process parameters on the predicted mechanical property indexes to obtain a parameter sensitivity ranking table; Performing a multi-objective optimization of the process parameter combinations based on the parameter sensitivity ranking table to obtain multiple groups of candidate process parameter schemes; Performing a comprehensive evaluation of the product performance and production efficiency for multiple groups of candidate process parameter schemes to obtain the optimal process parameter combination.

[0036] When the embodiment of the present invention performs a prediction calculation of the mechanical properties of the heat shrinkable film based on the melt uniformity data and the molecular chain orientation degree data, first, the melt uniformity data obtained by simulating the digital twin model is converted into a uniformity index value through statistical calculation. Specifically, the standard deviation calculation method is used. The sum of the squares of the differences between the physical parameters of each sampling point in the melt and the average value is calculated, and then the square root is taken to obtain the standard deviation. The smaller the standard deviation value, the higher the uniformity. Then, after the molecular chain orientation degree data is collected by a birefringence measuring instrument, the molecular chain orientation function value is calculated using the orientation function calculation formula f = (n∥ - n⊥) / (n∥ + 2n⊥), where n∥ is the refractive index parallel to the stretching direction and n⊥ is the refractive index perpendicular to the stretching direction. Then, the uniformity index value and the molecular chain orientation function value are substituted into a pre-established multiple regression equation, and the form of the regression equation is , where is the mechanical property index, is the uniformity index value, is the molecular chain orientation function value, , , , are regression coefficients, and the predicted mechanical property indexes including tensile strength, elongation at break, and thermal shrinkage rate are obtained through calculation; subsequently, sensitivity analysis of process parameters is carried out on the predicted mechanical property indexes, and different process parameter combinations are designed by the orthogonal test method, including ultrasonic power range of 50 - 200 W, frequency range of 15 - 25 kHz, action time range of 5 - 15 s, longitudinal drawing ratio range of 3 - 5 times, transverse drawing ratio range of 8 - 12 times, drawing temperature range of 85 - 105 °C, and drawing rate range of 2 - 6 m / min. And the influence degree of each process parameter on the mechanical property indexes is calculated through variance analysis to obtain the parameter sensitivity ranking table; then, multi-objective optimization of process parameter combinations is carried out based on the parameter sensitivity ranking table, an optimization model is constructed by using the genetic algorithm, the target value of tensile strength is set ≥ 120 MPa, the target value of elongation at break is set ≥ 150%, and the target value of thermal shrinkage rate is set ≥ 60%. During the optimization process, the population size is set to 50, the number of iterations is set to 100, the crossover probability is 0.8, and the mutation probability is 0.05. Multiple groups of candidate process parameter schemes that meet the target values are obtained through iterative calculation; finally, comprehensive evaluation of product performance and production efficiency is carried out on multiple groups of candidate process parameter schemes, and the comprehensive evaluation function is introduced, where is the compliance rate of tensile strength, is the compliance rate of elongation at break, is the compliance rate of thermal shrinkage rate. By calculating the evaluation function values of each scheme, the process parameter combination with the highest evaluation function value is selected as the optimal process parameter combination.

[0037] Through mechanical property prediction and calculation based on melt uniformity data and molecular chain orientation data, the present invention can accurately predict the mechanical properties of heat shrinkable films, providing a quantitative basis for subsequent process adjustment. Conducting sensitivity analysis of process parameters on the predicted mechanical property indexes helps to identify the key process parameters affecting product performance and provides a clear guiding direction for optimization. The generation of the parameter sensitivity ranking table provides a scientific basis for process parameter adjustment, making the optimization process more efficient and accurate. Conducting multi-objective optimization based on the sensitivity analysis results not only considers the improvement of mechanical properties but also takes into account production efficiency, ensuring the improvement of production efficiency while meeting product requirements. Finally, through comprehensive evaluation of multiple groups of candidate process parameter schemes, it is ensured to select the optimal process parameter combination, thereby realizing the optimization of the product performance and production process of heat shrinkable films.

[0038] Preferably, step S4 includes the following steps: Step S41: Monitor the actual production process parameters of the heat shrinkable film production line in real time; Step S42: Perform ultrasonic-assisted homogenization on the actual production process parameters based on the optimized process parameters to obtain actual melt uniformity data; Step S43: Extrude and form the melt according to the actual melt uniformity data to obtain initial sheet thickness distribution data; Step S44: Longitudinally stretch the sheet based on the initial sheet thickness distribution data to obtain longitudinal orientation degree data; Step S45: Transversely stretch the sheet based on the longitudinal orientation degree data to obtain transverse orientation degree data; Step S46: Heat-set the sheet based on the transverse orientation degree data to obtain sheet size stability data; Step S47: Measure the parameters of the sheet of the heat shrinkable film according to the sheet size stability data to obtain actual product parameters.

[0039] In the embodiments of the present invention, high-precision temperature sensors, pressure sensors, flow meters, speed sensors and laser thickness gauges are arranged on a heat shrinkable film production line to respectively collect data on melt temperature, melt pressure, extrusion flow rate, stretching speed and sheet thickness in real time, and record and store them in real time through an industrial data acquisition system to ensure the continuity and accuracy of production process data; an ultrasonic-assisted homogenization device is used to perform ultrasonic treatment on the melt. By controlling the ultrasonic frequency, power and action time, the shear stress inside the melt is homogenized, the density fluctuations in the melt are reduced, and a high-precision on-line density measuring instrument is used to obtain the homogenization data; the melt after ultrasonic homogenization is conveyed to a high-precision extrusion die head, and the thickness uniformity during the extrusion molding process is ensured by adjusting the die head gap and controlling the melt flow rate. Subsequently, the thickness distribution data of the initial sheet is measured by an on-line laser thickness gauge, and the lateral and longitudinal thickness deviations of the sheet are calculated by a data analysis system; the initial sheet is conveyed to a longitudinal stretching system, preheated by a multi-stage heating roller, and unidirectionally stretched by a longitudinal stretching roller group at a set temperature. By controlling the stretching ratio, stretching speed and cooling method, the directional arrangement of the molecular chains of the sheet is realized, and a polarized light microscope is used to detect the longitudinal orientation degree data; the longitudinally oriented sheet is conveyed to a transverse stretching device, heated to a set temperature by a hot blast furnace, and a stretching force is applied to the sheet through a transverse stretching track to further orient and arrange the molecular chains, and a photoelastic stress analyzer is used to measure the transverse orientation degree data; the transversely stretched sheet is conveyed to a heat setting unit, and the sheet is heat-treated by a heat setting roller group under the condition of controlling the temperature field distribution, and a laser interferometer is used to measure the change in the sheet size before and after heat treatment to obtain the sheet size stability data; based on the sheet size stability data, a precision measuring instrument is used to measure parameters such as the thickness, density, tensile strength, elongation at break, heat shrinkage rate and surface optical properties of the heat shrinkable film, and a high-precision data analysis system is used to statistically analyze the measurement results to obtain the actual product parameters.

[0040] By monitoring the actual process parameters of the production line in real time, the present invention can grasp the changes of key factors in the production process in real time, ensuring the accuracy of process control and timely adjustment. Based on the optimized process parameters, ultrasonic-assisted melt homogenization is carried out to effectively improve the uniformity of the melt and reduce the quality fluctuations caused by the melt non-uniformity. Using the actual melt uniformity data for extrusion molding can accurately control the thickness distribution of the sheet, laying a good foundation for the subsequent stretching and shaping processes. The orientation degree data in the longitudinal stretching process helps to optimize the stretching process, improve the longitudinal mechanical properties of the heat-shrinkable film, and provide a basis for the subsequent transverse stretching. The mechanical properties of the film are further optimized through the orientation degree data in the transverse stretching process to ensure the uniformity of the film in all directions. During the heat setting process, the temperature process parameters are adjusted according to the transverse orientation degree data to ensure the dimensional stability of the sheet after final setting and avoid deformation of the product. Finally, parameter measurement is carried out based on the dimensional stability data of the sheet to ensure that the final product meets the design requirements and achieve high-quality production of heat-shrinkable films.

[0041] Preferably, step S5 includes the following steps: Step S51: Conduct appearance inspection based on the actual product parameters to obtain surface defect data; Step S52: Measure the thickness of the heat-shrinkable film according to the actual product parameters to obtain thickness uniformity data; Step S53: Test the mechanical properties of the heat-shrinkable film according to the actual product parameters to obtain tensile strength data; Step S54: Test the heat shrinkage rate of the heat-shrinkable film according to the actual product parameters to obtain heat shrinkage rate data; Step S55: Test the optical properties of the heat-shrinkable film according to the actual product parameters to obtain haze and light transmittance data; Step S56: Conduct quality assessment based on the surface defect data, thickness uniformity data, tensile strength data, heat shrinkage rate data, and haze and light transmittance data to obtain a quality characteristic assessment report.

[0042] In the embodiments of the present invention, a high-resolution industrial camera is combined with an image processing system to scan the surface of the heat-shrinkable film, obtain continuous image data, and use an optical detection algorithm to identify the types of surface defects, including crystal points, black dots, scratches, bubbles, and flow marks. The distribution of defects is determined through a defect size calculation method to obtain surface defect data; a high-precision laser thickness gauge is used to perform non-contact measurement on the thickness of the heat-shrinkable film, collect thickness data in the production direction and the vertical direction respectively, and calculate thickness uniformity indexes, including the maximum thickness deviation, the thickness mean square deviation, and the transverse and longitudinal thickness ratio, through a data analysis system to obtain thickness uniformity data; an electronic tensile testing machine is used to perform tensile tests on the heat-shrinkable film specimens in the longitudinal and transverse directions. By setting a constant tensile rate, the stress-strain curve during the tensile process is recorded, the tensile strength, yield strength, and elongation at break are calculated, and data processing is performed in combination with a mechanical analysis system to obtain tensile strength data; a high-temperature heat shrinkage test device is used to place the heat-shrinkable film specimens in a hot air circulation furnace at a set temperature for a specified time, and after taking them out, the changes in the length and width of the specimens are measured, and the longitudinal and transverse heat shrinkage rates are calculated according to the shrinkage rate calculation formula to obtain heat shrinkage rate data; a haze and light transmittance measuring instrument is used to perform optical performance tests on the heat-shrinkable film specimens, measure the light transmittance, scattering rate, and haze value of the specimens under constant light source conditions, and calculate the average light transmittance and scattered light distribution through an optical integrating sphere system to obtain haze and light transmittance data; based on the surface defect data, thickness uniformity data, tensile strength data, heat shrinkage rate data, and haze and light transmittance data, a multi-dimensional quality assessment is performed using a data statistical analysis system, the quality stability coefficient, uniformity index, and mechanical property consistency index are calculated, and comparative analysis is performed in combination with historical quality data, and finally a quality characteristic assessment report is generated.

[0043] Through appearance inspection based on actual product parameters, the present invention can timely detect defects existing on the surface of the heat-shrinkable film and ensure that the appearance quality of the product meets the standards. Thickness measurement provides key data for product quality control. By detecting the thickness uniformity of the film material, the production process can be adjusted in a timely manner to avoid performance instability caused by uneven thickness. Mechanical property testing provides data support for the tensile strength of the film material and ensures the reliability and durability of the film material in actual applications. The heat shrinkage rate test helps evaluate the behavior of the film material during the heat shrinkage process and ensures that the product can shrink as expected to meet packaging requirements. The optical performance test provides key data on the light transmittance and haze of the film material in actual applications and ensures that the film material can meet customer requirements both in appearance and function. Finally, by comprehensively evaluating all quality data, the quality characteristics of the heat-shrinkable film can be comprehensively evaluated, providing a basis for subsequent production and optimization.

[0044] Particularly importantly, step S56 includes the following steps: Perform quantity statistics and grading evaluation on the surface defect data to obtain a surface quality grade score; Calculate the thickness deviation rate based on the thickness uniformity data and generate the thickness qualification rate index; The tensile strength data is standardized and compared with the benchmark to obtain the mechanical properties qualification assessment results; Based on the thermal shrinkage data, the longitudinal and transverse shrinkage balance is evaluated to obtain the thermal shrinkage characteristics evaluation results; Comprehensively evaluate the optical performance of haze and transmittance data to obtain a visual quality score; The overall quality score of the heat shrink film product is obtained by weighted calculation based on the surface quality grade score, thickness qualification index, mechanical property qualification assessment results, heat shrinkage characteristic evaluation results and visual quality score; The overall quality score of heat shrinkable film products is analyzed by correlation analysis of various indicators to obtain a quality characteristic evaluation report.

[0045] In the embodiment of the present invention, the number of bubbles or impurities with a diameter exceeding 0.2 mm per square meter on the surface of the film is counted, and the number of bubbles or impurities with a diameter exceeding 0.2 mm per square meter is counted. The surface quality grade score is output according to the rule that ≤3 defects are grade A and ≤5 defects are grade B. The laser thickness gauge is used to scan the entire width of the film at a spacing of 0.1mm, and the proportion of points in the thickness data that exceed the nominal value ±2μm is calculated to generate a thickness qualification index = (qualified points / total number of measured points) × 100%; the longitudinal tensile strength is 52.3MPa and the transverse tensile strength is 49.8MPa measured by a universal material testing machine in accordance with ASTM D882 standard, which is compared with the preset threshold of 50MPa / 45MPa. When the biaxial data meet the standard, the mechanical properties are marked as qualified; the heat shrinkage tester is used to measure 72% of the longitudinal and 68% of the transverse data, and the heat shrinkage characteristic evaluation result is determined to be qualified when the absolute value of the difference in longitudinal and transverse shrinkage is ≤5%; the haze meter is used according to GB / T The 2410 standard measured a haze of 2.8% and a transmittance of 91.5%. The visual quality score was calculated according to the rule that if the haze was ≤3%, 10 points were awarded, 1 point was deducted for every 0.1% overshoot, and 10 points were awarded for the transmittance ≥90%. The weighted formula was set as 20% for surface quality, 30% for thickness pass rate, 25% for mechanical properties, 15% for heat shrinkage characteristics, and 10% for visual quality. When the surface quality was 85 points (B grade), the thickness pass rate was 92%, the mechanical properties were 100%, the heat shrinkage characteristics were 100%, and the visual When the quality score is 95 points, the overall quality score = 85×0.2+92×0.3+100×0.25+100×0.15+95×0.1=92.4 points; associate each sub-item score with the extrusion temperature of 190°C, stretching ratio of 3.5×4.0, and ultrasonic power of 2000W parameters in the process database to generate a quality characteristic evaluation report containing the coordinates of the unqualified thickness point (X=125cm, Y=30cm) and the excessive longitudinal tensile strength value (+4.6%).

[0046] Through the quantitative statistics and grading evaluation of surface defect data, the present invention can clearly quantify the appearance quality of the heat shrinkable film and provide an intuitive reference for subsequent process adjustment. The calculation of the thickness deviation rate helps to determine whether the thickness of the film material is uniform, and the thickness qualification rate index can accurately reflect the consistency of the product to ensure that it meets the standard requirements. Through the standardization process and benchmark comparison of mechanical properties, the tensile strength can be objectively evaluated to ensure that the mechanical properties of the film material meet the expectations. The evaluation of heat shrinkage characteristics helps to understand the shrinkage balance of the film material in the longitudinal and transverse directions and ensure the uniformity of its heat shrinkage performance. The evaluation of optical properties provides a comprehensive score for the visual quality of the film material to ensure that the light transmittance and appearance of the product meet the customer's requirements. Finally, through weighted calculation and combined with the scores of various indicators, the overall quality of the heat shrinkable film can be comprehensively evaluated. Further, through the correlation analysis of various indicators, it helps to determine the quality level of the heat shrinkable film and provide a basis for optimizing the production process.

[0047] Preferably, the process optimization plan designed based on the quality characteristic evaluation report in step S6 includes: Perform deviation calculation on the quality characteristic evaluation report to obtain key quality deviation data; Based on the key quality deviation data, perform melt homogenization optimization to obtain ultrasonic power adjustment parameters, where the ultrasonic power adjustment parameters are limited between 40% - 80% of the rated power of the equipment; Based on the key quality deviation data, construct an extrusion flow constitutive equation to analyze the melt viscosity-temperature coupling coefficient matrix; Perform flow stability criterion calculation through the viscosity-temperature coupling coefficient matrix to generate extrusion temperature correction parameters, where the range of the extrusion temperature correction parameters is ±15°C; Based on the key quality deviation data, perform biaxial stretching process orientation optimization to obtain stretching ratio adjustment parameters; The stretching ratio adjustment parameters specifically include longitudinal stretching ratio, transverse stretching ratio, and total stretching ratio, where the longitudinal stretching ratio is limited between 3 - 7 times, the transverse stretching ratio is limited between 3 - 10 times, and the total stretching ratio is limited between 12 - 40 times; Based on the key quality deviation data, calculate the heat shrinkage rate of the heat setting process of the heat shrinkable film to obtain heat setting temperature optimization parameters; Record the ultrasonic power adjustment parameters, extrusion temperature correction parameters, stretching ratio adjustment parameters, and heat setting temperature optimization parameters as optimization analysis results; According to the optimization analysis results, formulate a process optimization plan to obtain process optimization control parameters.

[0048] Based on the data items in the quality characteristic evaluation report where the standard deviation of thickness fluctuation exceeds 0.5 μm and the absolute value of the deviation of thermal shrinkage rate is greater than 5%, the variance analysis method is used to calculate the linear correlation coefficient between the coefficient of variation of melt density and the thermal shrinkage rate; a power-adjustable ultrasonic generator is used, and according to the rule that the power is increased by 8% for every 0.1 increase in the coefficient of density variation the current power is adjusted from 1800 W to 2150 W (71.7% of the rated power of 3000 W), and the amplitude is controlled at 28 ± 2 μm; the rate of change of melt viscosity with temperature is measured by a Haake torque rheometer at 190 °C, and a viscosity-temperature equation with a temperature coefficient α = 0.15 (Pa·s) / °C is established , combined with the three-dimensional scanning data of the die channel to calculate the compensation value of each temperature zone, and it is determined that the temperature of the third heating zone needs to be increased from 185 °C to 198 °C; the orthogonal test design is used to increase the longitudinal draw ratio from 3.5 times to 4.2 times in steps and the transverse draw ratio is adjusted from 3.8 times to 4.5 times, and the total draw ratio is corrected from 13.3 times to 18.9 times. The linear speed of the longitudinal traction roller is increased from 12 m / min to 14.5 m / min through the draw chain clamp speed synchronous controller; based on the crystallinity change curve measured by the differential scanning calorimeter, the three-section temperatures of the heat setting zone are set at 105 °C, 115 °C, and 110 °C respectively, and the passing time of the film material is maintained at 45 seconds; the power adjustment instruction is written into the PLC module of the ultrasonic generator through the Profibus-DP bus, the temperature correction parameter is sent to the temperature controller of the extruder, the draw ratio parameter is written into the draw roller frequency converter through the servo driver, and the heat setting parameter is input into the hot air circulation system controller to form the process optimization control parameters.

[0049] By calculating the deviation of the quality characteristic evaluation report, the present invention can accurately identify the key quality deviations in the production process, providing a clear basis for subsequent process optimization. Based on the key quality deviation data, optimizing the melt homogenization helps to precisely adjust the ultrasonic power, ensuring the melt uniformity and avoiding excessive or insufficient use of ultrasonic power, thereby improving the quality stability of the film material. Constructing the constitutive equation of extrusion flow and analyzing the melt viscosity-temperature coupling coefficient matrix can deeply understand the physical characteristics of melt flow, providing an important theoretical basis for controlling the stability of melt flow, and further ensuring the uniformity and stability in the production process. Through the calculation of the flow stability criterion, the extrusion temperature correction parameter can help optimize the production temperature range, avoid the negative impact of temperature fluctuations on product quality, and thus improve the product consistency. Optimizing the orientation of the biaxial stretching process can adjust the draw ratio, ensuring the structural uniformity of the film material during stretching and avoiding mechanical property defects caused by uneven stretching. Calculating and optimizing the heat shrinkage rate helps to ensure the dimensional stability during heat setting, reducing the dimensional fluctuation problem of heat shrinkable films in later use. Finally, integrating all the optimization analysis results to form comprehensive process optimization control parameters can effectively guide the adjustment of the production process, thereby improving the production efficiency on the premise of ensuring quality and ensuring that the final product meets the required performance standards.

[0050] Preferably, the production process optimization control using the process optimization plan in step S6 includes: Adjusting the power of ultrasonic-assisted homogenization according to the process optimization control parameters to obtain optimized ultrasonic power data; Controlling and adjusting the temperature in the extrusion molding stage based on the process optimization control parameters to obtain optimized extrusion temperature data; Adjusting the tension of the biaxial stretching process according to the optimized ultrasonic power data and the optimized extrusion temperature data to obtain optimized stretching tension data; Adjusting the draw ratio of the biaxial stretching process based on the optimized stretching tension data to obtain optimized draw ratio data; Optimizing the temperature control of the heat setting process through the optimized draw ratio data to obtain optimized heat setting temperature data; Monitoring and controlling the product quality based on the optimized heat setting temperature data to obtain the optimal production process parameters.

[0051] In the embodiment of the present invention, an ultrasonic generator is used to perform power adjustment. The 2150W power command in the process optimization control parameters is written into the generator control unit through the Modbus RTU protocol, and the amplitude is synchronously set to 30μm. The transducer current value is continuously monitored and stabilized within the range of 4.8±0.2A; the temperature of the five zones of the extruder is set through a temperature controller. The original temperature gradient of 180 / 185 / 190 / 190°C is adjusted to 185 / 190 / 195 / 195°C, and a K-type thermocouple is used to calibrate the deviation between the actual temperature and the set value of each heating coil not exceeding ±0.5°C; based on the ultrasonic power log data and the extrusion temperature curve, through the feedback value of the FOS&S FBGS-500 fiber Bragg grating tensiometer, the longitudinal tensile tension is increased from 130N to 145N, and the transverse tensile tension is adjusted from 90N to 100N. The servo drive parameters are synchronously modified to keep the stretching roll pressure at 0.45 - 0.55MPa; a stretching ratio calculator is used to increase the longitudinal stretching ratio from 3.5 times to 4.0 times and the transverse stretching ratio from 4.0 times to 4.3 times. The longitudinal stretching chain clip speed is increased from 12m / min to 14m / min, and the transverse stretching chain clip speed is adjusted from 10m / min to 11.5m / min through the controller. The longitudinal preheating roll temperature is set to 88°C, and the transverse preheating roll temperature is set to 90°C; according to the stretching ratio data, the three-section temperature of the heat setting zone is matched, and the original 105 / 110 / 105°C is adjusted to 110 / 115 / 110°C. An EBM-Papst centrifugal fan is used to control the hot air circulation wind speed at 8m / s, and the film passing time is set to 50 seconds; data of 3 production batches are continuously collected through an online quality monitoring system. The standard deviation of the thickness fluctuation measured by a laser thickness gauge for the full width scan is ≤1.2μm, the longitudinal tensile strength measured by a universal material testing machine is ≥52MPa, and the longitudinal thermal shrinkage rate is confirmed to be 72% and the transverse thermal shrinkage rate is 68% by a thermal shrinkage rate tester. When all the detection values of 3 consecutive batches meet the standards, the current combination of 2150W ultrasonic power, 195°C extrusion zone four temperature, 4.0×4.3 times stretching ratio, and 110 / 115 / 110°C heat setting parameters is stored in the process database.

[0052] By adjusting the ultrasonic power, the present invention can achieve more uniform melt treatment, improve the uniformity of the melt, ensure the stability of the film material quality, and avoid performance defects caused by improper ultrasonic power. Adjusting the temperature control in the extrusion molding stage can ensure that the temperature of the melt remains within the optimal range during the molding process, avoid poor molding or unstable quality caused by temperature fluctuations, and thus improve the structural and appearance quality of the product. Combining the optimized ultrasonic power and extrusion temperature data to adjust the tension in the biaxial stretching process can ensure the uniformity of the tension during stretching, avoid performance differences caused by uneven stretching, and optimize the stretching quality. Further, by adjusting the draw ratio, it is ensured that the stretching degree of the film material meets the design requirements, and the mechanical properties and heat shrinkage properties of the film material are improved. According to the optimized draw ratio data, the temperature control of the heat setting process is optimized to ensure the dimensional stability and uniformity of the product during the setting process, and reduce the dimensional error that occurs during the heat setting process. Finally, through the optimization of the heat setting temperature, the product quality monitoring and control are carried out to comprehensively ensure that the production process meets the preset quality standards, obtain the optimal production process parameters, achieve stable production effects and improve production efficiency.

[0053] Preferably, the present invention also provides an optimization control system for the production process of heat-shrinkable films, which is used to execute the above-mentioned optimization control method for the production process of heat-shrinkable films. The optimization control system for the production process of heat-shrinkable films includes: A digital twin modeling module, which is used to obtain the resin characteristic parameters of the raw materials of the heat-shrinkable film and construct an initial digital twin model by using the resin characteristic parameters; A real-time data update module, which is used to collect real-time production data and update the initial digital twin model by using the real-time production data to obtain a complete digital twin model; A process simulation and optimization module, which is used to simulate the melt ultrasonic assisted homogenization and biaxial stretching process based on the digital twin model, and perform optimization analysis by using the simulation results to generate optimized process parameters; A product forming implementation module, which is used to adjust the actual production process parameters based on the optimized process parameters, and perform ultrasonic assisted homogenization treatment, extrusion molding, biaxial stretching and heat setting on the melt to obtain actual product parameters; A quality performance evaluation module, which is used to detect the performance and evaluate the quality of the actual product parameters to obtain a quality characteristic evaluation report; A closed-loop process control module, which is used to design a process optimization plan based on the quality characteristic evaluation report and perform production process optimization control by using the process optimization plan to obtain the optimal production process parameters.

[0054] Therefore, in any regard, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is not defined by the above description. Thus, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be encompassed within the present invention.

[0055] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. An optimization control method for the production process of heat shrinkable film, characterized in that, It includes the following steps: Step S1: Obtain the resin characteristic parameters of the heat-shrinkable film raw material, and construct an initial digital twin model using the resin characteristic parameters; Step S2: Collect real-time production data, and update the initial digital twin model using the real-time production data to obtain a complete digital twin model; Step S3: Conduct melt ultrasonic-assisted homogenization and biaxial stretching process simulation based on the digital twin model, and perform optimization analysis using the simulation results to generate optimized process parameters; Step S4: Adjust the actual production process parameters based on the optimized process parameters, and perform ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching, and heat setting on the melt to obtain actual product parameters; Step S5: Conduct performance testing and quality assessment on the actual product parameters to obtain a quality characteristic assessment report; Step S6: Design a process optimization plan based on the quality characteristic assessment report, and perform production process optimization control using the process optimization plan to obtain the optimal production process parameters.

2. The production process optimization control method for heat shrinkable film according to claim 1, characterized in that Step S1 includes the following steps: Step S11: Measure the molecular weight distribution of the heat-shrinkable film raw material to obtain molecular weight distribution characteristic parameters; Step S12: Conduct differential scanning calorimetry testing on the heat-shrinkable film raw material to obtain crystallization characteristic parameters; perform biaxial stretching molecular orientation simulation using the crystallization characteristic parameters to obtain a biaxial stretching digital module; Step S13: Conduct capillary rheology testing on the heat-shrinkable film raw material to obtain rheological characteristic parameters; perform ultrasonic melt homogenization mathematical modeling using the rheological characteristic parameters to obtain an ultrasonic melt homogenization digital module; Step S14: Conduct thermogravimetric thermal stability testing on the heat-shrinkable film raw material to obtain thermal stability-related parameters; perform flow-heat transfer coupling simulation of extrusion molding using the thermal stability-related parameters to obtain an extrusion molding digital module; Step S15: Perform molecular structure evolution simulation during heat setting using the molecular weight distribution characteristic parameters and thermal stability-related parameters to obtain a heat setting digital module; Step S16: Denote the molecular weight distribution characteristic parameters, crystallization characteristic parameters, rheological characteristic parameters, and thermal stability-related parameters as resin characteristic parameters; Step S17: Integrate and perform correlation mapping on the ultrasonic melt homogenization digital module, biaxial stretching digital module, extrusion molding digital module, and heat setting digital module to obtain an initial digital twin model.

3. The production process optimization control method for heat shrinkable film according to claim 2, characterized in that, Step S2 includes the following steps: Step S21: Deploy infrared thermocouples in the heat-shrinkable film production line, and use the infrared thermocouples to collect the temperature during the production process of the heat-shrinkable film as temperature distribution data; Step S22: Deploy piezoelectric sensors in the heat-shrinkable film production line, and use the piezoelectric sensors to collect the pressure during the production process of the heat-shrinkable film as pressure distribution data; Step S23: Deploy ultrasonic transducers in the heat-shrinkable film production line, and use the ultrasonic transducers to collect the ultrasonic energy during the production process of the heat-shrinkable film as ultrasonic parameter data; Step S24: Deploy laser thickness gauges in the heat-shrinkable film production line, and use the laser thickness gauges to collect the thickness during the production process of the heat-shrinkable film as film thickness data; Step S25: Deploy a fiber Bragg grating tensiometer in the heat shrinkable film production line, and use the fiber Bragg grating tensiometer to collect the tension during the production process of the heat shrinkable film as the stretching tension data; Step S26: Denote the temperature distribution data, pressure distribution data, ultrasonic parameter data, film thickness data, and stretching tension data as real-time production process data; Step S27: Standardize the real-time production process data, use the standardized real-time production process data to perform real-time mapping on the production process digital twin model, and perform parameter calibration to obtain a complete digital twin model.

4. The production process optimization control method for heat shrinkable film according to claim 3, characterized in that, The melt ultrasonic assisted homogenization based on the digital twin model in Step S3 includes: Perform rheological property detection on a high-precision digital twin model to obtain melt viscosity distribution data, where the shear viscosity range of the melt viscosity distribution data is between and , and the temperature sensitivity parameter is 20 - 120 kJ / mol; Perform a melt ultrasonic sound field simulation using the melt viscosity distribution data to obtain ultrasonic power distribution data; Perform cavitation dynamics simulation based on the ultrasonic power distribution data to obtain bubble dynamic change data; The bubble size in the dynamic change data of bubbles is 1 - 100 μm, and the bubble number density is to per , and the bubble lifetime is to in the order of seconds; Perform melt molecular chain topology calculation based on the bubble dynamic change data to obtain molecular chain orientation uniformity data; Perform thermo-mechanical coupling analysis of the melt temperature change based on the molecular chain orientation uniformity data to obtain melt temperature distribution data; The temperature gradient of the melt temperature distribution data is 0.5 - 5 °C / mm, and the temperature fluctuation range is ±3 °C; Evaluate the melt homogenization effect on the melt temperature distribution data to obtain melt uniformity data.

5. The optimized control method for the production process of heat shrinkable film according to claim 4, characterized in that The biaxial stretching process simulation in Step S3 includes: Perform an unsteady temperature field measurement on the high-precision digital twin model to obtain initial temperature distribution data; Perform a melt pre-stretching stress simulation using the initial temperature distribution data to obtain pre-stretching stress distribution data; The stress range of the pre-stretching stress distribution data is 0.5 - 10 MPa, and the stress non-uniformity coefficient is less than 0.2; Perform a melt orientation evolution deduction based on the pre-stretching stress distribution data to obtain molecular chain orientation degree data, where the specific range of the orientation function value of the molecular chain orientation degree data is 0.3 - 0.8, and the specific range of the orientation function gradient is 0.05 - 0.2 / mm; Perform a stress field reconstruction of the transverse stretching process based on the molecular chain orientation degree data to obtain transverse stretching stress distribution data; Calculate the dynamic measurement of the heat setting temperature field according to the transverse stretching stress distribution data to obtain temperature gradient field tensor data; The specific range of the principal direction temperature gradient in the temperature gradient field tensor data is 0.2 - 2 °C / mm, and the specific range of the secondary direction temperature gradient is 0.1 - 1 °C / mm; Perform a thermo-mechanical coupling numerical simulation based on the temperature gradient field tensor data to obtain thermal stress distribution data; Use the thermal stress distribution data to predict the dimensional stability of the product to obtain product dimensional deviation data.

6. The production process optimization control method for heat shrinkable film according to claim 5, characterized in that, Step S4 includes the following steps: Step S41: Real-time monitor the actual production process parameters of the heat shrinkable film production line; Step S42: Perform ultrasonic assisted homogenization on the actual production process parameters based on the optimized process parameters to obtain actual melt uniformity data; Step S43: Extrude the melt according to the actual melt uniformity data to obtain the initial sheet thickness distribution data; Step S44: Longitudinally stretch the sheet based on the initial sheet thickness distribution data to obtain longitudinal orientation degree data; Step S45: Transversely stretch the sheet based on the longitudinal orientation degree data to obtain the transverse orientation degree data; Step S46: Heat-set the sheet based on the transverse orientation degree data to obtain the sheet size stability data; Step S47: Measure the parameters of the sheet of the heat-shrinkable film according to the sheet size stability data to obtain the actual product parameters.

7. The production process optimization control method for heat shrinkable film according to claim 6, characterized in that, Step S5 includes the following steps: Step S51: Perform appearance inspection based on the actual product parameters to obtain surface defect data; Step S52: Measure the thickness of the heat-shrinkable film according to the actual product parameters to obtain thickness uniformity data; Step S53: Test the mechanical properties of the heat-shrinkable film according to the actual product parameters to obtain tensile strength data; Step S54: Test the heat shrinkage rate of the heat-shrinkable film according to the actual product parameters to obtain heat shrinkage rate data; Step S55: Test the optical properties of the heat-shrinkable film according to the actual product parameters to obtain haze and light transmittance data; Step S56: Conduct quality assessment based on the surface defect data, thickness uniformity data, tensile strength data, heat shrinkage rate data, and haze and light transmittance data to obtain a quality characteristic assessment report.

8. The production process optimization control method for heat shrinkable film according to claim 7, characterized in that, The design of the process optimization plan based on the quality characteristic assessment report in Step S6 includes: Calculate the deviation of the quality characteristic assessment report to obtain key quality deviation data; Perform melt homogenization optimization based on the key quality deviation data to obtain ultrasonic power adjustment parameters, where the ultrasonic power adjustment parameters are limited between 40% - 80% of the rated power of the equipment; Construct an extrusion flow constitutive equation based on the key quality deviation data and analyze the melt viscosity-temperature coupling coefficient matrix; Execute the calculation of the flow stability criterion through the viscosity-temperature coupling coefficient matrix to generate extrusion temperature correction parameters, where the range of the extrusion temperature correction parameters is ±15°C; Perform biaxial stretching process orientation optimization based on the key quality deviation data to obtain stretching ratio adjustment parameters; The stretching ratio adjustment parameters specifically include the longitudinal stretching ratio, transverse stretching ratio, and total stretching ratio, where the longitudinal stretching ratio is limited between 3 - 7 times, the transverse stretching ratio is limited between 3 - 10 times, and the total stretching ratio is limited between 12 - 40 times; Calculate the heat shrinkage rate of the heat-shrinkable film's heat-setting process based on the key quality deviation data to obtain heat-setting temperature optimization parameters; Record the ultrasonic power adjustment parameters, extrusion temperature correction parameters, stretching ratio adjustment parameters, and heat-setting temperature optimization parameters as the optimization analysis results; Formulate a process optimization plan according to the optimization analysis results to obtain process optimization control parameters.

9. The production process optimization control method for heat shrinkable film according to claim 8, characterized in that, The production process optimization control using the process optimization plan in Step S6 includes: Adjust the power of the ultrasonic-assisted homogenization according to the process optimization control parameters to obtain optimized ultrasonic power data; Adjust the temperature control during the extrusion molding stage based on the process optimization control parameters to obtain optimized extrusion temperature data; Adjust the tension of the biaxial stretching process according to the optimized ultrasonic power data and optimized extrusion temperature data to obtain optimized stretching tension data; Adjust the stretching ratio of the biaxial stretching process based on the optimized stretching tension data to obtain optimized stretching ratio data; Optimize the temperature control of the heat setting process by optimizing the draw ratio data to obtain optimized heat setting temperature data; Based on the optimized heat setting temperature data, conduct product quality monitoring and control to obtain the optimal production process parameters.

10. An optimized control system for the production process of heat shrinkable film, characterized in that, A production process optimization control method for heat shrinkable films as described in claim 1, and the production process optimization control system for heat shrinkable films includes: A digital twin modeling module, configured to obtain resin characteristic parameters of the raw materials of the heat shrinkable film, and construct an initial digital twin model using the resin characteristic parameters; A real-time data update module, configured to collect real-time production data, and update the initial digital twin model using the real-time production data to obtain a complete digital twin model; A process simulation optimization module, configured to perform melt ultrasonic-assisted homogenization and biaxial stretching process simulation based on the digital twin model, and perform optimization analysis using the simulation results to generate optimized process parameters; A product forming implementation module, configured to adjust the actual production process parameters based on the optimized process parameters, and perform ultrasonic-assisted homogenization treatment, extrusion molding, biaxial stretching, and heat setting on the melt to obtain actual product parameters; A quality performance evaluation module, configured to perform performance detection and quality evaluation on the actual product parameters to obtain a quality characteristic evaluation report; A closed-loop process control module, configured to design a process optimization plan based on the quality characteristic evaluation report, and perform production process optimization control using the process optimization plan to obtain the optimal production process parameters.

Images