A Simulation Design Method for the Conveyor Mechanism of an Assembly Machine

Abstract

The present invention relates to the technical field of mechanical simulation, and particularly to a simulation design method for a conveying mechanism of an assembly machine. The method includes the following steps: obtaining physical property data of a disposable infusion set pipeline; establishing a pipeline flexible simulation model based on the flexible characteristics according to the physical property data, and performing mechanical analysis on the bending, torsion and mutual contact of the infusion set pipeline based on the winding mode, so as to generate deformation simulation data of the flexible pipeline; performing pipeline flexible simulation on the pipeline flexible simulation model according to the deformation simulation data, so as to obtain pipeline winding behavior simulation data; obtaining material characteristic data of a plastic film during the hot melt sealing process, and performing thermal-fluid-solid coupling analysis on the material characteristic data, so as to obtain phase change transfer coupling data. The present invention realizes the accurate simulation of complex winding behaviors by establishing a pipeline simulation model based on flexible characteristics.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical simulation, and particularly to a simulation design method for a conveying mechanism of an assembly machine. Background Art

[0002] A disposable infusion set is a medical device used to inject liquid drugs or nutrients into the human body through a vein, usually used only once to avoid cross-infection and maintain sterility. The infusion set consists of multiple parts, including: a hanging bottle needle, used to pierce the rubber stopper of the medicine bottle or hanging bottle to extract the medicine; a dropper, controlling the flow rate of the medicine, usually adjusting the infusion rate by observing the drop speed; an infusion tube, connecting the medicine bottle and the needle to convey the medicine; a filter, filtering out tiny particles or air bubbles in the medicine to prevent them from entering the human body; a regulator, used to adjust the liquid flow rate; a needle, connected to the infusion tube and inserted into the patient's vein for conveying the medicine. These infusion sets are usually made of medical-grade PVC (polyvinyl chloride) or other non-toxic plastic materials and should be discarded after use to prevent infection. Blister packaging is a packaging method that forms a specific shape by heating plastic materials to make them soft and then using vacuum suction to fit them onto a mold. It is usually used to protect products such as electronic products, food, and medicine, and has good transparency and moisture resistance.

[0003] Currently, the simulation design method for the conveying mechanism of the assembly machine in the scenario of blister-packaged disposable infusion sets often has the following problems: The infusion set tubing is soft and deformable, and it is very difficult to accurately simulate its behavior in the simulation; Heat-sealing involves the phase change and flow of materials, which is a complex multi-physics problem. Summary of the Invention

[0004] Based on this, it is necessary for the present invention to provide a simulation design method for a conveying mechanism of an assembly machine to solve at least one of the above technical problems.

[0005] To achieve the above object, a simulation design method for a conveying mechanism of an assembly machine includes the following steps:

[0006] Step S1: Obtain the physical property data of the disposable infusion set tubing; establish a tubing flexibility simulation model based on the flexible characteristics according to the physical property data, and perform mechanical analysis on the bending, torsion, and mutual contact of the infusion set tubing in a winding manner, so as to generate deformation simulation data of the flexible tubing; perform tubing flexibility simulation on the tubing flexibility simulation model according to the deformation simulation data to obtain tubing winding behavior simulation data;

[0007] Step S2: Obtain the material property data of the plastic film during the hot melt sealing process, and conduct a thermal-fluid-solid coupling analysis on the material property data to obtain the phase change transfer coupling data; estimate the temperature field distribution, melting, and solidification processes of the plastic film during the infusion set packaging process based on the phase change transfer coupling data, conduct an analysis of the packaging pressure change, and perform plastic film flow and solidification simulations to obtain the packaging effect simulation data;

[0008] Step S3: Conduct a packaging simulation analysis on the wound infusion set tubing based on the deformation simulation data and the packaging effect simulation data, and simulate the position adjustment of the infusion set tubing in the blister packaging array during the simulation to obtain the packaging behavior simulation data;

[0009] Step S4: Conduct an influence analysis on the air discharge effect inside the packaging bag based on the temperature distribution and pressure change according to the packaging effect simulation data to obtain the air discharge efficiency simulation data; use a vacuum pump to conduct an air extraction simulation based on the air discharge efficiency simulation data to generate the vacuum packaging effect simulation data;

[0010] Step S5: Conduct a multi-physical field comprehensive analysis on the positioning, winding tightness, and vacuum sealing effect of the infusion set tubing during the packaging process based on the packaging behavior simulation data and the vacuum packaging effect simulation data to generate an optimized design scheme for the packaging system.

[0011] By obtaining the physical property data of the disposable infusion set tubing and establishing a tubing simulation model based on its flexible characteristics, the deformation behavior of the infusion set tubing during the winding process can be accurately simulated. This simulation analysis can not only predict the mechanical changes of the tubing during bending, twisting, and mutual contact, but also effectively prevent damage caused by overstretching, twisting, or mutual entanglement of the tubing during the winding process. This step provides basic data for subsequent packaging operations, ensuring that the flexible simulation results of the tubing can accurately reflect the actual production status, and improving the consistency and quality of tubing winding. By obtaining the material property data of the plastic film and performing thermo-fluid-solid coupling analysis, the temperature distribution, melting, and solidification processes of the plastic film during the encapsulation process can be accurately simulated. The analysis of the change in encapsulation pressure further ensures the fluidity and uniform solidification of the plastic film during the encapsulation process. This significantly improves the encapsulation quality of the infusion set, avoiding problems such as loose encapsulation and plastic film leakage caused by improper temperature control, ensuring the tightness and durability of the encapsulation, and enhancing the storage safety of the product. During packaging simulation, by combining the deformation simulation data and the encapsulation effect simulation data, the position adjustment of the wound infusion set tubing in the blister packaging can be accurately simulated. This analysis avoids the problems of tubing misalignment or overlap that are prone to occur during manual operation, so that the infusion set tubing in each packaging array is evenly distributed and tightly wound, improving the packaging efficiency and consistency. This not only increases the degree of mechanization of packaging, but also reduces the problems of packaging damage or production efficiency decline that may be caused by uneven tubing distribution. Through the simulation analysis of the air discharge effect inside the encapsulation bag, the vacuum degree can be accurately controlled based on the temperature distribution and pressure change, and the air extraction is simulated through a vacuum pump. This step ensures that the air inside the encapsulation bag can be efficiently discharged, avoiding air residue and improving the vacuum packaging effect. Efficient air discharge and vacuum sealing not only increase the product's shelf life, but also avoid hygiene problems or product quality decline caused by loose packaging. This step ensures the airtightness and stability of the infusion set packaging. Through the multi-physical field comprehensive analysis of the positioning, winding tightness, and vacuum sealing effect of the infusion set tubing during the packaging process, accurate basis can be provided for the optimized design of the entire packaging system. This comprehensive simulation optimization scheme ensures the quality control of the infusion set throughout the production process. This step ultimately provides a comprehensive optimized design for the packaging system, improving the overall efficiency and reliability of the system, reducing the uncertainty and failure risk on the production line. The optimized design of the packaging system not only improves production efficiency, but also provides flexibility and scalability for future product improvements. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments read in conjunction with the accompanying drawings:

[0013] Figure 1Schematic diagram of the step - by - step process of the simulation design method for the conveying mechanism of the assembly machine of the present invention;

[0014] Figure 2 is Figure 1 The detailed step - by - step schematic diagram of step S1 in

[0015] Figure 3 is Figure 1 The detailed step - by - step schematic diagram of step S2 in Specific embodiments

[0016] 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, not all of them. All other embodiments obtained by those skilled in the art within the scope of the present invention without creative work based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0017] 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, so 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.

[0018] It should be understood that although terms such as "first", "second", etc. may be used here to describe each unit, 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 related items.

[0019] To achieve the above - mentioned purpose, please refer to Figures 1 to 3 , the present invention provides a simulation design method for the conveying mechanism of an assembly machine. The method includes the following steps:

[0020] Step S1: Obtain the physical property data of the disposable infusion set tubing; establish a tubing flexible simulation model based on the flexible characteristics according to the physical property data, and conduct mechanical analysis of the bending, torsion, and mutual contact of the infusion set tubing based on the winding method, so as to generate deformation simulation data of the flexible tubing; conduct tubing flexible simulation on the tubing flexible simulation model according to the deformation simulation data, so as to obtain tubing winding behavior simulation data;

[0021] Step S2: Obtain the material property data of the plastic film during the hot melt sealing process, and perform a thermal-fluid-solid coupling analysis on the material property data to obtain the phase change transfer coupling data; estimate the temperature field distribution, melting, and solidification processes of the plastic film during the infusion set packaging process based on the phase change transfer coupling data, and conduct an analysis of the packaging pressure change, and perform a simulation of the plastic film flow and solidification, so as to obtain the packaging effect simulation data;

[0022] Step S3: Perform a packaging simulation analysis on the wound infusion set pipeline according to the deformation simulation data and the packaging effect simulation data, and simulate the position adjustment of the infusion set pipeline in the thermoformed packaging array during the simulation, so as to obtain the packaging behavior simulation data;

[0023] Step S4: Analyze the influence of the air discharge effect inside the packaging bag based on the temperature distribution and pressure change according to the packaging effect simulation data, so as to obtain the air discharge efficiency simulation data; use a vacuum pump to perform an air extraction simulation based on the air discharge efficiency simulation data to generate vacuum packaging effect simulation data;

[0024] Step S5: Perform a multi-physical field comprehensive analysis on the positioning, winding tightness, and vacuum sealing effect of the infusion set pipeline during the packaging process according to the packaging behavior simulation data and the vacuum packaging effect simulation data, so as to generate an optimized design scheme for the packaging system.

[0025] In the embodiment of the present invention, with reference to Figure 1 as described, it is a schematic diagram of the step flow of a simulation design method for the conveying mechanism of an assembly machine of the present invention. In this example, the simulation design method for the conveying mechanism of the assembly machine includes the following steps:

[0026] Step S1: Obtain the physical property data of the disposable infusion set pipeline; establish a pipeline flexibility simulation model based on the flexible characteristics according to the physical property data, and perform a mechanical analysis of the bending, torsion, and mutual contact of the infusion set pipeline based on the winding method, so as to generate the deformation simulation data of the flexible pipeline; perform a pipeline flexibility simulation on the pipeline flexibility simulation model according to the deformation simulation data, so as to obtain the pipeline winding behavior simulation data;

[0027] In an embodiment of the present invention, physical property data of a disposable infusion set tubing is obtained. First, geometric parameters of the tubing, including length, inner and outer diameters, wall thickness, etc., are collected by a measuring device. The physical properties such as elastic modulus, Poisson's ratio, and density are measured in combination with a mechanical property testing device, and experiments on the change of mechanical properties are carried out under different temperature conditions. Based on these physical property data, a flexible characteristic simulation model is established using finite element analysis (FEA) software, such as ANSYS or ABAQUS. By applying torsional, bending stresses, and winding modes to the model, mechanical analysis is performed, and the mutual contact behavior between the tubings is simulated. During the simulation process, geometric parameters of the tubing winding (such as winding radius 10 mm, number of turns 5, pitch 2 mm) are set to obtain simulation data of the tubing deformation. Finally, using the deformation data, simulation analysis of the winding behavior is carried out to generate simulation data of the tubing winding behavior, showing the stress distribution, twisting condition, and mechanical analysis results of the contact points during the winding process of the tubing.

[0028] Step S2: Obtain material characteristic data of the plastic film during the hot melt sealing process, and perform thermo-fluid-solid coupling analysis on the material characteristic data to obtain phase change transfer coupling data; estimate the temperature field distribution, melting, and solidification processes of the plastic film during the infusion set packaging process according to the phase change transfer coupling data, and perform analysis on the change of packaging pressure, and perform simulation of plastic film flow and solidification to obtain packaging effect simulation data;

[0029] In an embodiment of the present invention, material characteristic data of the plastic film during the hot melt sealing process is obtained, including the melting point, specific heat capacity, thermal conductivity, etc. of the material. A DSC (Differential Scanning Calorimetry) device is used to measure the phase change characteristics of the plastic film, and a thermo-fluid-solid coupling model of the material is constructed in combination with experimental data. In software, such as COMSOL Multiphysics, these material data are input to establish coupled equations of heat conduction, fluid mechanics, and solid mechanics, and analyze the temperature field distribution and phase change transfer behavior of the plastic film during heating, melting, and solidification processes. According to the experimental data, the temperature during plastic film melting is set to 160 °C, the pressure during packaging is 0.5 MPa, and the plastic flow and solidification behavior during the simulation packaging process are simulated to generate packaging effect simulation data for evaluating the sealing strength and airtightness.

[0030] Step S3: Perform packaging simulation analysis on the wound infusion set tubing according to the deformation simulation data and the packaging effect simulation data, and simulate the position adjustment of the infusion set tubing in the blister packaging array during the simulation to obtain packaging behavior simulation data;

[0031] In an embodiment of the present invention, based on the pipeline deformation simulation data in step S1 and the encapsulation effect simulation data in step S2, an initial geometric model of the wound infusion pipeline and the blister packaging array is constructed using 3DCAD software (such as SolidWorks or CATIA), and the physical properties of the packaging material and the infusion device are input. Static interference checking is performed to ensure that the wound pipeline does not interfere with the packaging structure. The position of the pipeline in the package is adjusted through an optimization algorithm. The set position parameters during the adjustment are as follows: the spacing of the packaging array is 50 mm, and the diameter of the wound pipeline is controlled within 15 mm to ensure the stability of the pipeline. In the simulation software, the dynamic process of inserting the pipeline into the package is simulated, the deformation and stress distribution are calculated, and finally the packaging behavior simulation data is generated.

[0032] Step S4: Analyze the influence of the air discharge effect inside the packaging bag based on the temperature distribution and pressure change according to the encapsulation effect simulation data, so as to obtain the air discharge efficiency simulation data; use a vacuum pump to simulate the air extraction according to the air discharge efficiency simulation data to generate the vacuum packaging effect simulation data;

[0033] In an embodiment of the present invention, using the encapsulation effect simulation data, the process of discharging air inside the packaging bag is simulated using computational fluid dynamics simulation software (such as Fluent). The geometric information and material properties of the packaging bag are input, including the thickness distribution and temperature gradient of the sealing area. The pumping speed of the vacuum pump is set to 5 L / min, and the target vacuum degree is 10 Pa. The process of air discharging from the inside of the packaging bag is simulated, and the air discharge efficiency is analyzed to generate the air discharge efficiency simulation data. Using the vacuum pump simulation data, the simulation of the air extraction process is further carried out to obtain the final vacuum packaging effect simulation data and evaluate the airtightness of the packaging bag.

[0034] Step S5: Perform a multi-physics field comprehensive analysis on the positioning, winding tightness, and vacuum sealing effect of the infusion pipeline during the packaging process according to the packaging behavior simulation data and the vacuum packaging effect simulation data, so as to generate an optimized design scheme for the packaging system.

[0035] In an embodiment of the present invention, according to the packaging behavior simulation data and the vacuum packaging effect simulation data, a multi-physics field coupling model is constructed, and the positioning accuracy, winding tightness, and vacuum sealing effect of the infusion pipeline during the packaging process are comprehensively analyzed. Through a multi-objective optimization algorithm, the influence of different encapsulation parameters (such as heat sealing temperature 160 °C, pressure 0.6 MPa, encapsulation time 5 s) on the winding tightness and sealing effect of the pipeline is evaluated. By simulating and analyzing the positioning accuracy and winding tightness data, an optimized design scheme for the packaging system is finally generated to ensure that the infusion pipeline is stable in position, has a good sealing effect, and the airtightness meets the requirements during the packaging process.

[0036] Preferably, step S1 includes the following steps:

[0037] Step S11: Collect the length, inner and outer diameters, and wall thickness information of the disposable infusion set tubing to obtain the tubing geometric data;

[0038] Step S12: Obtain the elastic modulus, Poisson's ratio, and density data of the infusion set tubing material to generate the material physical property data;

[0039] Step S13: Measure the mechanical property changes of the infusion set tubing at different temperatures to obtain the mechanical property data;

[0040] Step S14: Combine the tubing geometric data, material physical property data, and mechanical property data into physical property data;

[0041] Step S15: Establish a tubing flexibility simulation model based on the physical property data and perform mechanical analysis of the bending, torsion, and mutual contact of the infusion set tubing in a winding manner to generate the deformation simulation data of the flexible tubing;

[0042] Step S16: Use the deformation simulation data to perform a tubing flexibility simulation on the tubing flexibility simulation model to obtain the tubing winding behavior simulation data.

[0043] As an embodiment of the present invention, refer to Figure 2 shown in Figure 1 which is the detailed step - by - step process schematic diagram of Step S1. In the embodiment of the present invention, Step S1 includes the following steps:

[0044] Step S11: Collect the length, inner and outer diameters, and wall thickness information of the disposable infusion set tubing to obtain the tubing geometric data;

[0045] In the embodiment of the present invention, a high - precision digital caliper is first used to measure the length, inner and outer diameters, and wall thickness of the disposable infusion set tubing, with an accuracy of 0.01 mm. The measurement points are evenly distributed at multiple parts of the tubing, and the measurement is carried out no less than 10 times. The average value is taken as the final geometric data of the tubing. For example, the length of the tubing of a certain model of infusion set is 1500 mm, the inner diameter is 2 mm, the outer diameter is 3 mm, and the wall thickness is 0.5 mm. These geometric data will be used to determine the initial geometric model of the tubing in subsequent simulations and accurately simulate the deformation behavior of the tubing.

[0046] Step S12: Obtain the elastic modulus, Poisson's ratio, and density data of the infusion set tubing material to generate the material physical property data;

[0047] In the embodiments of the present invention, a material testing device (such as a universal material testing machine) is used to test the elastic modulus, Poisson's ratio, and density of the infusion set tubing material. First, a tensile test is carried out to record the stress-strain relationship of the material during the force application process, and the elastic modulus is obtained. A strain gauge is used to measure the transverse and longitudinal strains of the material, and Poisson's ratio is calculated. The density is calculated by weighing and combining with the geometric volume. For example, the elastic modulus of a certain plastic material is 1.5 GPa, Poisson's ratio is 0.35, and the density is 1.2 g / cm 3 . Based on these data, accurate physical property inputs can be provided for the flexible simulation model.

[0048] Step S13: Measure the changes in the mechanical properties of the infusion set tubing at different temperatures to obtain mechanical property data;

[0049] In the embodiments of the present invention, the mechanical properties of the infusion set tubing material at different temperatures are tested. The tubing samples are placed at different temperatures such as ambient temperature, 30°C, 50°C, etc., and a universal material testing machine is used to test the tensile strength, torsional strength, and shear strength of the tubing respectively. No less than 5 repeated tests are carried out under each temperature condition to ensure the stability and reliability of the data. For example, at room temperature, the tensile strength of the material is 60 MPa, and at 50°C, the tensile strength drops to 45 MPa. Through these mechanical property data, the influence of temperature changes on the mechanical properties of the infusion set tubing during actual use can be understood.

[0050] Step S14: Combine the tubing geometric data, material physical property data, and mechanical property data into physical property data;

[0051] In the embodiments of the present invention, the tubing geometric data obtained in step S11, the material physical property data obtained in step S12, and the mechanical property data in step S13 are combined. Using data processing tools such as MATLAB or Excel, these data are input into a unified database or parameter table as the basic input data for the subsequent flexible simulation model. The table of physical property data includes the length, inner and outer diameters, wall thickness, elastic modulus, Poisson's ratio, density of the tubing, and its mechanical property parameters at different temperatures. Through the integration of these data, a complete physical property dataset of the infusion set tubing is formed, providing a basis for simulation modeling.

[0052] Step S15: Establish a flexible simulation model of the tubing based on the flexible characteristics according to the physical property data, and conduct mechanical analyses of bending, torsion, and mutual contact of the infusion set tubing based on the winding method, so as to generate deformation simulation data of the flexible tubing;

[0053] In an embodiment of the present invention, based on physical property data, a simulation model of the infusion set pipeline with flexible characteristics is established by using finite element analysis software (such as ABAQUS or ANSYS). First, the geometric shape of the pipeline is input into the software, boundary conditions are set, and properties such as the elastic modulus, Poisson's ratio, and density of the material are assigned to the pipeline model. In the simulation software, the winding mode of the pipeline is simulated, including the bending, torsion, and mutual contact of the pipeline. The winding radius of the pipeline is set to 10 mm and the number of winding turns is 5, and the bending and torsion mechanical analyses are carried out to obtain the deformation simulation data of the pipeline. These data show how the pipeline deforms and the stress distribution changes during the winding process.

[0054] Step S16: Perform a pipeline flexible simulation model on the pipeline flexible simulation model according to the deformation simulation data, so as to obtain the pipeline winding behavior simulation data.

[0055] In an embodiment of the present invention, the deformation simulation data is used as input to comprehensively simulate the winding behavior of the pipeline flexible simulation model. By applying various mechanical loads such as torsion, tension, and external pressure, the actual performance of the infusion set pipeline under different winding conditions is simulated. For example, by setting different winding densities and external pressures, the behavior of the pipeline during packaging or use can be simulated. The finally generated winding behavior simulation data includes the deformation amount, torque distribution, stress-strain distribution, etc. of different parts of the pipeline during the winding process. These data can be used to optimize the winding process and design to ensure the reliability of the infusion set pipeline in practical applications.

[0056] Through the accurate acquisition of the length, inner and outer diameters, and wall thickness information of the disposable infusion set tubing, it is ensured that the geometric model used in the simulation process can accurately reflect the physical dimensions of the actual tubing. This provides reliable basic data for subsequent mechanical analysis and simulation model establishment. The accurate geometric data acquisition avoids simulation errors caused by dimensional deviations, helps to achieve high-precision simulation analysis, and thus optimizes the tubing design and winding method in the production process. By collecting the material physical properties such as elastic modulus, Poisson's ratio, and density of the infusion set tubing, the behavior of the tubing material under different mechanical and environmental conditions can be accurately reflected. These property data are the key to subsequent flexible simulation analysis and directly affect the accuracy of the simulation results. The accurate acquisition of material properties helps to predict the strength, durability, and anti-deformation ability of the tubing during use, thus ensuring that the product performance meets the standards and reducing the production of unqualified products. By measuring the mechanical property changes of the infusion set tubing at different temperatures, the actual performance of the tubing under different environmental conditions can be simulated. This helps to identify the influence of temperature on the tubing material, especially the deformation, fracture, or other failure conditions that may occur in extreme environments. Through this step, it is ensured that the infusion set can maintain stable performance in various use environments, improving the reliability and service life of the product. Merging the geometric data, material physical property data, and mechanical property data of the tubing into complete physical property data can provide comprehensive input information for the subsequent simulation model. The process of merging data ensures that the parameters used in the simulation model are consistent and comprehensive, avoiding simulation result deviations caused by data one-sidedness. This comprehensive data processing method improves the accuracy of the simulation and the adaptability of the model, helping to achieve more precise product optimization. Based on the physical property data, a tubing simulation model based on flexible characteristics is established, and mechanical analysis of bending, torsion, and mutual contact during the winding process is carried out. This step can comprehensively simulate the behavior of the disposable infusion set tubing during actual production and use, especially the dynamic deformation behavior of flexible tubing. Through mechanical analysis, potential structural weaknesses or design deficiencies can be identified and adjusted and optimized in advance, thus improving the structural stability and production efficiency of the product. According to the deformation simulation data, further simulation analysis of the tubing flexible simulation model can accurately predict the behavior of the tubing during the winding process. This simulation process can optimize the winding method, reduce the risk of stress concentration or mutual winding of the tubing during the winding process, and thus improve the accuracy of production automation. The winding behavior simulation data provides an important basis for subsequent packaging design, ensuring the tightness and consistency of winding, and effectively improving the efficiency and safety during packaging and transportation. Through the simulation and analysis of the above steps, the tubing design and production process of the disposable infusion set are optimized. These simulation results help to identify various potential problems of the tubing in actual use, ensuring the stability of its structure and performance.During the production process, using these simulation data can reduce the number of tests, lower the development cost, improve the production efficiency, and ensure high-quality output of products.

[0057] Preferably, step S15 includes the following steps:

[0058] Step S151: Conduct a material stress-strain curve analysis based on the physical property data of the infusion set tubing to obtain stress-strain relationship data;

[0059] In the embodiment of the present invention, first, based on the physical property data of the infusion set tubing, a tubing material sample is selected, and a stress-strain curve test is performed using a universal material testing machine. Under different tensile rates, the force and deformation data of the tubing material are recorded to obtain the stress-strain curve. During the test, the material sample is fixed at both ends of the testing machine, and the tensile force is gradually increased while measuring the corresponding strain value. According to the collected data, a stress-strain relationship curve is plotted, and key parameters such as the yield point, elastic region, and plastic region are recorded. For example, in a specific type of plastic material, the elastic modulus is 1.4 GPa, and the yield stress is 45 MPa. These data will be used for subsequent mechanical simulation analysis of the tubing material.

[0060] Step S152: Establish a constitutive model for the tubing material based on the stress-strain relationship data, and analyze the influence of temperature on the constitutive model according to the mechanical property data to obtain a tubing material characteristic dataset;

[0061] In the embodiment of the present invention, based on the stress-strain relationship data, a constitutive model of the material is established using a material constitutive model (such as a linear elastic model, a nonlinear elastic model, or a viscoelastic model). A suitable material model, such as the Neo-Hookean or Mooney-Rivlin model, is selected to analyze the mechanical properties of the material at different temperatures. By comparing the changes in the stress-strain curves at different temperatures, the influence of temperature on the mechanical properties of the material is evaluated. For example, at 25°C, the elastic modulus of the material is 1.5 GPa, and it decreases to 1.2 GPa at 50°C. According to these data, the material characteristics at different temperatures are integrated to form a tubing material characteristic dataset, which is used for assigning material properties during simulation analysis.

[0062] Step S153: Establish a three-dimensional geometric model of the tubing based on the geometric information in the physical property data, and integrate the material properties of the three-dimensional geometric model according to the tubing material characteristic dataset to obtain a material property integrated model;

[0063] In the embodiments of the present invention, a three-dimensional geometric model of the infusion set pipeline is established by using CAD software (such as SolidWorks or AutoCAD) according to the geometric information in the physical property data. First, geometric parameters such as the inner and outer diameters, length, and bending radius of the pipeline are input to generate a three-dimensional geometric entity. Then, the pipeline material property dataset is applied to the three-dimensional geometric model to endow the geometric model with different material properties, such as the elastic modulus, Poisson's ratio, etc. of different regions. After the material properties are integrated, the three-dimensional geometric model not only contains the shape information but also has material properties, forming a material property integrated model, which serves as the basic model for subsequent simulations.

[0064] Step S154: Set the mesh division parameters for the material property integrated model, and determine the boundary conditions and loading methods, so as to obtain the pipeline flexibility simulation model;

[0065] In the embodiments of the present invention, the material property integrated model is imported into finite element analysis software (such as ABAQUS or ANSYS) for mesh division. When dividing the mesh, the size and details of the pipeline need to be considered, and an appropriate mesh density is adopted. For example, for a pipeline with a diameter less than 5 mm, a refined mesh with an element size of 0.1 mm is selected. Then, the boundary conditions and loading methods are set. For example, both ends of the pipeline are fixed and winding torque, tensile force, etc. are applied. Different loading modes need to be set according to the actual winding situation to ensure that the simulation model reflects the true stress state of the pipeline during winding.

[0066] Step S155: Perform a mechanical analysis on the infusion set pipeline according to the preset infusion set pipeline winding model, so as to obtain a pipeline stress state dataset, where the mechanical analysis includes bending stress and strain distribution analysis, pipeline torsion analysis, and contact force distribution analysis;

[0067] In the embodiments of the present invention, according to the preset infusion set pipeline winding model, a mechanical analysis is performed on the pipeline in finite element analysis software. First, the bending stress and strain distribution of the pipeline are analyzed to observe the change of the internal stress of the pipeline under different winding radii. Then, the pipeline torsion analysis is carried out to analyze the stress state of the pipeline when a torque is applied, and the relationship between the torsion angle and the applied load is calculated. Finally, the contact force distribution when the pipelines are in contact with each other during the winding process is analyzed to identify the local stress at the contact part. For example, under the conditions of a winding radius of 10 mm and a torque of 5 N·m, the maximum internal stress of the pipeline is 35 MPa, and the contact force is concentrated in the area where the winding is the tightest.

[0068] Step S156: Apply the pipeline stress state dataset to the pipeline flexibility simulation model to perform a static non-linear analysis of the deformation under the winding state, so as to obtain static deformation data, and simulate the transient deformation behavior during the winding process, so as to obtain dynamic deformation data;

[0069] In the embodiments of the present invention, the pipeline force state data set is applied to the pipeline flexibility simulation model for static and dynamic analysis. First, based on the static non-linear analysis under the winding state, torque and tensile force are applied to calculate the deformation amount of the pipeline under constant loading, and static deformation data is obtained. Then, the transient deformation behavior during winding is simulated, the winding speed is 5 rad / s, and the dynamic deformation during winding is observed. The analysis results include instantaneous stress and displacement distribution, and dynamic deformation data is obtained. These data will be used to evaluate the dynamic performance and structural stability of the infusion set pipeline during winding.

[0070] Step S157: Perform pipeline deformation simulation based on node displacement and stress distribution through the static deformation data and the dynamic deformation data, so as to generate deformation simulation data of the flexible pipeline.

[0071] In the embodiments of the present invention, through comprehensive analysis of the static deformation data and the dynamic deformation data, and using node displacement and stress distribution, pipeline deformation simulation is carried out. The deformation of the pipeline under different winding states is displayed in the simulation software to determine its ultimate states of bending and torsion. By analyzing the displacement and stress changes of key nodes, deformation simulation data of the flexible pipeline is generated. For example, the maximum value of the node displacement is 2 mm, and the stress concentration point is located at the minimum bending radius of the pipeline. Through these data, the design and production process of the infusion set pipeline can be further optimized to ensure its safety and durability in use.

[0072] Through the stress-strain curve analysis of the infusion set tubing material, the mechanical performance of the material under different loads can be accurately understood. This process ensures that in the simulation, the true deformation characteristics of the tubing material can be reflected. The stress-strain relationship data lays the foundation for the subsequent establishment of the constitutive model, enabling the simulation to be more accurate and improving the mechanical property evaluation of the product, avoiding unnecessary material failures in actual production. By establishing the constitutive model of the tubing material and combining the analysis of the influence of different temperatures on the mechanical properties of the material, it is ensured that the simulation model can not only reflect the material behavior at room temperature but also accurately simulate the material response when the temperature changes. This multi-dimensional analysis helps to improve the adaptability of the infusion set tubing under different working environments, ensuring that it can still maintain good mechanical properties under extreme conditions such as high temperature and low temperature, thereby enhancing the reliability of the product. Establishing a three-dimensional geometric model based on physical property data and integrating the material property data helps to perfectly combine the geometric characteristics and material characteristics of the tubing, forming a model with real physical properties. This step ensures that in the simulation process, the simulation of the geometric shape and material behavior has a high degree of consistency, thus improving the simulation accuracy. Through this comprehensive model, the deformation and mechanical performance of the tubing during actual operation can be better predicted. By performing mesh generation and boundary condition setting on the material property integration model, it is ensured that the local and overall stress and strain distributions during the simulation process can be accurately captured. Mesh generation is the core of simulation accuracy, and by reasonably setting the mesh size, the simulation accuracy can be significantly improved. The reasonable setting of boundary conditions also helps to simulate various external forces that the tubing may be subjected to in actual applications, ensuring the reliability of the simulation results. Through detailed mechanical analysis of the bending stress, strain distribution, torsion analysis, and contact force distribution of the infusion set tubing, etc., the force-bearing situation of the tubing in the coiled state can be comprehensively understood. This step provides key data support for the optimization design, enabling the identification of potential problems such as stress concentration or other issues that may occur during the coiling process of the tubing, thereby reducing the risk of failures such as fracture or deformation. Through static non-linear analysis and transient simulation of dynamic deformation behavior, the deformation situation of the infusion set tubing during the coiling process can be comprehensively understood. The static deformation data helps to evaluate the stress and strain distributions at specific positions of the tubing, while the dynamic deformation data can better predict the behavior of the tubing during actual operation. This combined analysis method enables the simulation model to accurately reflect the stability under static conditions and also simulate the transient changes during the dynamic coiling process. By performing deformation simulation on the node displacements and stress distributions, the flexible deformation process of the tubing in the coiled state can be accurately captured. The flexible tubing deformation simulation data generated by this step can help engineers optimize the design of the infusion set tubing, thereby reducing the risk of excessive deformation or material fatigue during the coiling process. The acquisition of these data helps to improve the durability and reliability of the product and ensures that the tubing coiling operation can always be carried out efficiently and with high quality.Through the detailed simulation analysis of the above steps, the flexible behavior of the infusion set tubing during winding and packaging processes has been comprehensively simulated. These analysis results not only improve the quality of the product's structural design but also provide key data support for optimizing the production process. Through accurate simulation, the trial-and-error process in production is avoided, reducing material waste and costs, and enhancing the durability, safety, and production efficiency of the product.

[0073] Preferably, step S155 includes the following steps:

[0074] Step S1551: Determine the geometric configuration of the tubing winding according to the preset infusion set tubing winding model, thereby obtaining the winding geometric parameter data, where the geometric configuration of the tubing winding includes the winding diameter, the number of winding turns, and the winding pitch;

[0075] In the embodiment of the present invention, according to the preset infusion set tubing winding model, the geometric configuration of the winding is first determined. By inputting geometric parameters such as the winding diameter, the number of winding turns, and the winding pitch, the winding shape of the tubing is determined. For example, if the winding diameter is 50 mm, the number of winding turns is 5, and the winding pitch is 10 mm, then a three-dimensional geometric model of the wound tubing can be created using geometric modeling software (such as SolidWorks) to obtain the winding geometric parameter data. These geometric parameters are used for subsequent curvature and stress calculations.

[0076] Step S1552: Calculate the curvature distribution of the tubing in the winding state according to the winding geometric parameter data, thereby obtaining the tubing curvature distribution data;

[0077] In the embodiment of the present invention, the curvature distribution of the tubing in the winding state is calculated according to the winding geometric parameter data. The specific operation is to define the geometric curve of the tubing in the finite element analysis software and calculate the curvature of each point through the differential equation of the geometric curve, especially focusing on the area where the winding bending is most obvious. For example, when the curvature radius is 10 mm, the maximum curvature of the winding may appear in the area where the winding is the tightest. Through these calculations, the curvature distribution data of the entire wound tubing is obtained.

[0078] Step S1553: Calculate the bending stress using the tubing curvature distribution data and the tubing material property dataset, thereby obtaining the tubing bending stress distribution data;

[0079] In the embodiments of the present invention, curvature distribution data and a dataset of pipeline material properties (such as elastic modulus, Poisson's ratio, etc.) are utilized to calculate the bending stress of the pipeline during the winding process. The specific method is to select the curvature value of each cross-section, combine the mechanical properties of the material, and apply the bending stress formula σ = E·κ·y, where E is the elastic modulus, κ is the curvature, and y is the distance from the neutral axis. Through point-by-point calculation, the bending stress distribution data under the entire winding state is obtained. For example, when the winding radius is 10 mm and the elastic modulus of the material is 1.4 GPa, the maximum bending stress may be 45 MPa.

[0080] Step S1554: Calculate the torsional stress based on the torsional angle of each cross-section of the pipeline based on the winding geometric parameter data, so as to obtain the pipeline torsional stress data;

[0081] In the embodiments of the present invention, according to the winding geometric parameter data, the torsional angle of each cross-section of the pipeline is calculated, and the torsional stress is calculated based on these torsional angles. In finite element analysis, the torsional stress formula τ = T·r / J is used, where T is the torque, r is the cross-sectional radius, and J is the polar moment of inertia. For each cross-section, different torsional angles are input, and the torsional stress of the pipeline is calculated one by one. For example, if the torque applied during the winding process is 2 N·m and the torsional angle is 30 degrees, the maximum torsional stress may be generated at the outermost cross-section. Finally, the pipeline torsional stress data is obtained.

[0082] Step S1555: Identify the contact points during the pipeline winding process for the infusion set pipeline winding model, and calculate the normal force and tangential force of the contact points, so as to obtain the contact force distribution data;

[0083] In the embodiments of the present invention, the contact points of the pipeline during the winding process are identified in the pipeline winding model, and the normal force and tangential force of the contact points are calculated. In the simulation software, using the contact force analysis module, the friction coefficient between the pipeline contact surfaces is set, and the dynamic behavior of the pipelines contacting each other during the winding process is simulated to identify the contact parts. The normal force is calculated by the force in the orthogonal direction of the contact surface, and the tangential force is calculated according to the friction force calculation formula F t = μ·F n (μ is the friction coefficient, F n is the normal force). For example, if the friction coefficient is set to 0.3 and the normal force of the contact point is 10 N, then the tangential force is 3 N. The contact force distribution data is obtained through analysis.

[0084] Step S1556: Combine the pipeline bending stress distribution data, the pipeline torsional stress data, and the contact force distribution data into pipeline strain distribution data, and perform axial tension and compression effect analysis, so as to obtain the pipeline stress state dataset.

[0085] In the embodiments of the present invention, the pipeline bending stress distribution data, torsional stress data, and contact force distribution data are integrated into the strain distribution data of the pipeline. In the simulation software, these stress data are uniformly applied to the finite element model of the pipeline, and the axial tension and compression effect analysis is carried out. Axial tension and compression forces are set. For example, the tensile force is set to 50 N and the compression force is set to 30 N to simulate the stress state of the infusion pipeline during the winding process, and particular attention is paid to the deformation behavior of the pipeline after winding. Through these calculations, the overall stress state data set of the pipeline is obtained for subsequent design optimization and winding process evaluation.

[0086] The present invention determines the winding diameter, number of turns, and winding pitch of the pipeline, thereby defining the geometric configuration parameters of the winding. The determination of these geometric parameters provides accurate inputs for subsequent simulations, ensuring that various variables during the winding process can be accurately simulated under actual conditions. Precise control of the winding geometric parameters helps avoid situations of over-tightening or over-loosening during winding, preventing pipeline deformation or damage during storage and transportation. By calculating the curvature distribution of the pipeline in the winding state, the local bending conditions of the pipeline during winding can be accurately understood. The change in pipeline curvature is directly related to the bending stress during actual operation of the pipeline. The curvature distribution data helps analyze whether excessive bending will occur at certain points of the pipeline, thereby avoiding local excessive deformation or damage. These data provide an accurate basis for subsequent stress analysis and optimized design. Based on the pipeline curvature distribution data and material property data, the bending stress is calculated to predict the specific stress conditions borne by the pipeline during the winding process. The bending stress distribution data can help identify stress concentration areas during the winding process, avoiding pipeline fracture or fatigue caused by excessive local stress. At the same time, this step can optimize the winding design to ensure that the stress during the winding process is controlled within a safe range, thereby extending the service life of the pipeline. By calculating the torsional stress of each cross-section of the pipeline based on geometric parameters, the torsional effect on the pipeline during the winding process can be evaluated. This is very important for ensuring that the pipeline does not undergo excessive torsional deformation during winding. Especially when the winding is dense, the torsional stress may cause material fatigue or failure of the pipeline. By controlling the torsional stress, the winding parameters can be adjusted during the design process to reduce stress concentration and prevent material damage. Identifying the contact points of the pipeline during the winding process and calculating the contact force distribution can analyze whether the pipeline will undergo local deformation due to the normal force and tangential force at the contact points during winding. A reasonable distribution of the contact point forces helps avoid permanent indentations or damage to the pipeline during the winding process. Through the analysis of the contact forces, the winding method of the pipeline can be optimized to reduce the negative impact of the contact forces on the pipeline, thereby ensuring the overall integrity of the infusion set pipeline. Combining the bending stress, torsional stress, and contact force data into the strain distribution data of the pipeline and analyzing the axial tensile and compressive effects can comprehensively evaluate the multi-dimensional mechanical effects on the pipeline during the winding process. This comprehensive analysis helps identify whether the pipeline will undergo structural failure due to multiple stress effects during the winding process. At the same time, these data provide a reliable basis for further optimizing the pipeline design, thereby reducing risks during actual use at the design stage. Through the above steps, the distribution and changes of the bending, torsional, and contact stresses suffered by the pipeline during the winding process can be comprehensively simulated. These mechanical data help optimize the winding scheme of the infusion set pipeline, avoid problems such as material fatigue, deformation, and even fracture caused by stress concentration, and improve the reliability and durability of the infusion set product. In addition, the analysis of the comprehensive strain data can effectively prevent performance degradation caused by uneven material stress or excessive compression, thereby extending the service life of the product and reducing risks during production and transportation.

[0087] Preferably, step S16 includes the following steps:

[0088] Step S161: Geometrically update the pipeline flexible simulation model according to the node displacement information of the deformation simulation data, so as to obtain the updated pipeline geometric model;

[0089] In the embodiment of the present invention, according to the node displacement information in the deformation simulation data generated in the previous step, the pipeline flexible simulation model is geometrically updated. In the simulation software, the geometric model of the pipeline is updated by using the node displacement. The deformation data of each node is used as an input parameter to reconstruct the geometric shape of the pipeline after winding. For example, if a certain node has a displacement of 0.5 mm during the winding process, this displacement is applied to the corresponding node position in the geometric model, and by recalculating the overall geometric structure of the pipeline, the updated pipeline geometric model is generated.

[0090] Step S162: Apply a preload to the infusion pipeline according to the pipeline geometric model based on the deformation prestress that may be generated during the winding process, so as to generate preload data;

[0091] In the embodiment of the present invention, according to the updated geometric model, considering the deformation prestress generated during the winding process, a preload is applied to the pipeline. In the simulation environment, by setting the prestress of each section of the pipeline (for example, bending stress, torsional stress, etc.), preload data is generated. In specific operations, the stress values can be calculated through mechanical formulas according to the bending radius and angle of the pipeline, and these stresses are applied to the key parts of the geometric model. For example, in the pipeline section with a winding diameter of 30 mm, the prestress may be 20 MPa. The preload data generated by calculation is used for subsequent boundary condition setting.

[0092] Step S163: Use the preload data to set the mechanical boundary conditions for the pipeline winding, so as to determine the winding boundary condition data, where the mechanical boundary conditions include the boundary conditions of bending, torsion and contact stress;

[0093] In the embodiment of the present invention, the preload data in step S162 is used to set the mechanical boundary conditions, including the boundary conditions of bending, torsion and contact stress. In the simulation system, the preload data is combined with the actual boundary conditions, such as fixing the positions of both ends of the winding, setting a certain torque, and the normal force and tangential force at the contact point. For example, the boundary conditions may include a constraint condition with a bending stress of 30 MPa and a torsional angle of 45 degrees. These settings can reflect the actual stress situation of the pipeline during the winding process and generate the winding boundary condition data.

[0094] Step S164: Conduct a mechanical analysis of the flexible pipeline during the winding process based on the winding boundary condition data, calculate the deformation amplitude and force variation of the pipeline at different winding positions, and thus obtain the winding position stress data;

[0095] In the embodiment of the present invention, a mechanical analysis of the flexible pipeline during the winding process is carried out according to the set winding boundary conditions. In the finite element analysis, various boundary conditions are input, and the force and deformation analysis at each point is carried out to calculate the stress change and deformation amplitude at different winding positions. For example, in the area with the tightest winding, the deformation of the pipeline may be the largest, reaching 3 mm, and the force reaches 50 MPa, while in the looser winding area, the deformation may be only 1 mm. The winding position stress data at different winding positions are obtained through calculation.

[0096] Step S165: Conduct a local stress concentration area analysis based on the winding position stress data and the pipeline material property dataset, and optimize the winding parameters of the infusion set pipeline winding model, so as to obtain the optimized winding parameter data;

[0097] In the embodiment of the present invention, the area of local stress concentration is analyzed according to the winding position stress data. The pipeline material property dataset is matched to identify the positions where stress concentration may occur, and the winding parameters are optimized and adjusted. For example, if it is found that the stress concentration is too high in some areas, which may lead to material fatigue, the winding pitch or winding angle can be adjusted to reduce the stress in these areas. For example, if the stress at a certain cross-section reaches the limit value of 80 MPa, the pitch is adjusted from 10 mm to 12 mm to reduce the stress at this place to 60 MPa. Finally, the optimized winding parameter data are obtained.

[0098] Step S166: Conduct a pipeline flexibility simulation through the optimized winding parameter data and the pipeline geometric model, so as to obtain the pipeline winding behavior simulation data.

[0099] In the embodiment of the present invention, the pipeline flexibility simulation is carried out again by using the optimized winding parameter data. In the simulation software, the updated winding parameters and geometric model are input, and the overall simulation analysis of the winding behavior is carried out. For example, by gradually loading the optimized winding parameters, the deformation and stress changes during the winding process are observed, and the overall effect of winding under the new parameters is analyzed. The updated winding behavior data can be obtained through simulation, which is used to verify the rationality of the optimized design, and finally generate the pipeline winding behavior simulation data. These data provide optimization guidance for the winding process in the subsequent actual production process.

[0100] Through geometric updates of the pipeline flexible simulation model based on deformation simulation data, the present invention can ensure that the shape and structure of the model in the simulation are consistent with the actual state after winding. The introduction of node displacement information enables real-time correction of the pipeline geometric model, making the simulation more accurately reflect the deformations that may occur during the winding process. This step provides a more precise basis for subsequent mechanical analysis and optimization design, ensuring a high level of credibility for the simulation results. By applying preloads to the pipeline, the prestress generated by the initial stress state during the winding process can be simulated. The preload data helps to understand the stress state of the pipeline at the beginning of winding and predict in advance the stress response of the material during the winding process. This is important for avoiding deformation failures caused by over-tight or over-loose winding of the pipeline, thereby enhancing the stress resistance of the infusion set pipeline and optimizing the winding process. The setting of mechanical boundary conditions ensures that the actual situations of bending, torsion, and contact stress can be accurately simulated during the simulation process. By setting the winding boundary conditions in detail, the simulation model can be made closer to the mechanical environment during the actual winding process, ensuring the accuracy of the simulation results. This step helps to identify in advance the stress concentration areas that may occur during the winding process and reduce damage or excessive deformation of the material caused by unreasonable boundary conditions. Through mechanical analysis of the stress and deformation at different positions of the pipeline during the winding process, the changing trends of the forces during the winding process can be identified. The stress data at the winding positions can help engineers analyze the stress distribution of the pipeline at different winding positions, ensuring that there are no problems of excessive stress concentration or out-of-control local deformation during the winding process. Through this analysis, the winding parameters can be further optimized to enhance the stability and safety of the overall design. By using the analysis of local stress concentration areas, the high-stress areas that may be generated in the pipeline during the winding process can be identified. By optimizing these stress concentration areas, the material fatigue or rupture caused by local stress can be effectively reduced, and the service life of the infusion set pipeline can be enhanced. The winding parameter optimization data provides a basis for further adjusting the winding geometric configuration, making the stress during the winding process more evenly distributed and reducing the failure risk caused by uneven winding. By using the winding parameter optimization data and the updated pipeline geometric model to conduct a more accurate flexible simulation, simulation data on the pipeline winding behavior closer to the actual situation can be obtained. This step not only provides a reliable basis for subsequent production and manufacturing but also provides precise data support for further optimizing the winding process. The accuracy of the simulation data helps to improve production efficiency, reduce rework and material waste during the winding process, thereby reducing the manufacturing cost. Through these steps, a comprehensive simulation and optimization of the winding behavior of the infusion set pipeline can be achieved. The application of preloads, the setting of boundary conditions, and stress analysis can help identify and solve potential mechanical problems during the winding process and avoid stress concentration and material deformation failures. The analysis of local stress concentration areas and the optimization of winding parameters provide effective optimization solutions for the winding process design, further improving the durability and performance of the infusion set.The finally generated simulation data of the winding behavior can significantly improve the accuracy of the simulation design and provide strong support for the actual production and quality control of the product.

[0101] Preferably, step S2 includes the following steps:

[0102] Step S21: Obtain the material property data of the plastic film during the heat-sealing process, including the melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship, and crystallization kinetics parameters;

[0103] Step S22: Establish a multi-scale structure model for the plastic film material based on the material thermophysical data to obtain the material microstructure model, where the multi-scale structure includes the structures of molecular chains, crystals, and amorphous regions;

[0104] Step S23: Construct a thermal-fluid-solid coupling analysis model based on the coupling of the heat conduction equation, fluid mechanics equation, and solid mechanics equation according to the material microstructure model to obtain the phase change transfer coupling data;

[0105] Step S24: Estimate the temperature field distribution, melting, and solidification processes of the plastic film during the infusion set packaging process according to the phase change transfer coupling data, analyze the change of the packaging pressure, and perform the simulation of the plastic film flow and solidification to generate the temperature change and phase change simulation data during the solidification process;

[0106] Step S25: Perform the packaging effect simulation of the plastic film on the temperature change and phase change simulation data, and perform the packaging effect analysis based on the sealing performance, strength, and airtightness to obtain the packaging effect simulation data.

[0107] As an embodiment of the present invention, referring to Figure 3 shown, for Figure 1 the detailed step flow diagram of step S2 in

[0108] Step S21: Obtain the material property data of the plastic film during the heat-sealing process, including the melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship, and crystallization kinetics parameters;

[0109] In the embodiment of the present invention, during the heat-sealing process, it is first necessary to obtain the material property data of the plastic film, including the melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship, and crystallization kinetics parameters. The melting point and specific heat capacity of the plastic film are measured by a differential scanning calorimeter (DSC), the thermal conductivity is measured by a thermal conductivity meter, and the viscosity of the plastic film at different temperatures is measured by a rheometer to obtain the viscosity-temperature relationship curve. In addition, combining the crystal growth kinetics theory, the crystallization kinetics parameters of the plastic film material are obtained. These data provide basic information for the subsequent thermal-fluid-solid coupling analysis.

[0110] Step S22: Establish a multi-scale structure model for the plastic film material based on the material thermophysical property data, so as to obtain the material microstructure model, where the multi-scale structure includes the structures of molecular chains, crystals, and amorphous regions;

[0111] In the embodiment of the present invention, according to the obtained material thermophysical property data, a multi-scale structure model of the plastic film is established. First, the arrangement of the molecular chains of the plastic film is analyzed by molecular dynamics simulation to obtain the structural parameters of the molecular chains; then, the crystal region in the plastic film is analyzed by using X-ray diffraction (XRD) technology to construct a crystal structure model; finally, the structural characteristics of the amorphous region in the plastic film are analyzed in combination with a scanning electron microscope (SEM). The molecular chains, crystals, and amorphous regions are combined to form a multi-scale material microstructure model for subsequent thermal-fluid-solid coupling analysis.

[0112] Step S23: Construct a thermal-fluid-solid coupling analysis model based on the coupling of the heat conduction equation, the fluid mechanics equation, and the solid mechanics equation according to the material microstructure model, so as to obtain the phase change transfer coupling data;

[0113] In the embodiment of the present invention, based on the material microstructure model of the plastic film, a thermal-fluid-solid coupling analysis model is constructed by combining the heat conduction equation, the fluid mechanics equation, and the solid mechanics equation. In specific operations, the heat conduction equation is used to describe the temperature field distribution of the plastic film during melting and solidification, the fluid mechanics equation is used to describe the flow behavior of the molten plastic film, and the solid mechanics equation is used to analyze the stress distribution of the material during the solidification process. Through finite element simulation software, these equations are coupled to generate the phase change transfer coupling data of the plastic film during the hot melt sealing process.

[0114] Step S24: Estimate the temperature field distribution, melting, and solidification processes of the plastic film during the infusion set packaging process according to the phase change transfer coupling data, and conduct an analysis of the packaging pressure change, and conduct a simulation of the plastic film flow and solidification, so as to generate the temperature change and phase change simulation data during the solidification process;

[0115] In the embodiment of the present invention, according to the phase change transfer coupling data, the temperature field distribution, melting, and solidification processes of the plastic film during the infusion set packaging process are analyzed. By calculating the change of temperature with time, the whole process of the plastic film from heating to the melting point, melting and flowing to cover the surface of the infusion set, and then cooling and solidifying is simulated. At the same time, by analyzing the change of the packaging pressure, the external force acting on the plastic film during the packaging process is determined to determine its fluidity and solidification effect. For example, when the temperature reaches 180°C, the plastic film begins to melt, the packaging pressure is 1 MPa, and the flow rate of the film is 5 mm / s. Finally, the temperature change and phase change simulation data during the solidification process are obtained.

[0116] Step S25: Simulate the encapsulation effect of the plastic film on the temperature change and phase change simulation data, and perform an analysis of the encapsulation effect based on tightness, strength, and airtightness, so as to obtain the simulation data of the encapsulation effect.

[0117] In the embodiment of the present invention, the temperature change and phase change simulation data are used to simulate the encapsulation effect of the plastic film. During the simulation process, key performance parameters such as tightness, strength, and airtightness are considered to evaluate the effect of the plastic film after encapsulation. For example, through the airtightness test, the leakage situation of the plastic film in a vacuum environment of 0.1 Pa is simulated, and through the tensile simulation test, whether the encapsulation strength meets the set standard (such as the tensile strength is 20 MPa). After comprehensive analysis, the simulation data of the encapsulation effect are generated, providing a basis for further optimizing the encapsulation process.

[0118] The present invention obtains key material characteristic data of the plastic film, such as melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship, and crystallization kinetic parameters, to ensure a comprehensive understanding of the thermal response and mechanical properties of the material during the hot melt sealing process. These data provide reliable input parameters for subsequent thermal-fluid-solid coupling analysis, enabling more accurate simulation of the melting and solidification processes of the plastic film, and thus improving the accuracy of the encapsulation simulation. Establishing a multi-scale structural model of the plastic film (molecular chains, crystals, and amorphous regions) helps accurately simulate the influence of the microscopic structural characteristics of the plastic film on its macroscopic properties. Through a detailed description of the microscopic structure, it is possible to better understand how the material deforms and flows during the hot melt sealing process, especially capturing the changes in the microscopic structure during the melting and solidification processes, thereby enhancing the accuracy of the simulation model and ensuring that the sealing effect meets expectations. By constructing a coupled model of heat conduction, fluid mechanics, and solid mechanics equations, it is possible to accurately simulate how the plastic film conducts heat, flows, and solidifies during the hot melt process. The phase change transfer coupling data provides phase change information of the plastic film in different states, such as the transition from melting to solidification, which is crucial for the encapsulation quality. The coupled model can not only reflect the changes in the temperature field but also provide distribution information of pressure, stress, and flow velocity, thus comprehensively evaluating the sealing performance and structural integrity of the plastic film. Based on the phase change transfer coupling data, it is possible to accurately predict the temperature distribution, melting, and solidification processes of the plastic film during the encapsulation process. This process helps ensure that the plastic film is uniformly heated and cooled during the encapsulation process, avoiding encapsulation defects caused by local overheating or uneven cooling. Through pressure change analysis, it is possible to determine the optimal pressure during the encapsulation process to ensure that the plastic film closely adheres to the infusion set tubing, thereby enhancing the sealing performance and strength. Through the temperature change and phase change simulation data, detailed encapsulation effect simulation can be carried out to ensure that the plastic film can maintain good sealing performance, airtightness, and strength after encapsulation. The analysis of sealing performance and airtightness helps verify whether the plastic film can effectively prevent the entry of air or other external substances after encapsulation, thus ensuring the quality and safety of the infusion set. The encapsulation effect simulation data can provide support for process optimization, improving the reliability of the encapsulation process and the consistency of the product. Through the implementation of the above steps, it is possible to comprehensively and accurately simulate the behavior of the plastic film during the hot melt sealing process, ensuring that it is uniformly heated, effectively flows, and forms a tight seal during the encapsulation process. The establishment of the multi-scale structural model and the application of thermal-fluid-solid coupling analysis improve the accuracy of the simulation, providing a scientific basis for optimizing the encapsulation parameters and enhancing the product quality. The encapsulation effect simulation ensures that the finished product has reliable performance in actual applications by analyzing the sealing performance, strength, and airtightness, thereby improving the encapsulation quality of disposable infusion sets.

[0119] Preferably, step S24 includes the following steps:

[0120] Step S241: Perform a temperature field simulation of the plastic film during the hot melt sealing process based on the phase change transfer coupling data, so as to obtain temperature distribution data;

[0121] In the embodiment of the present invention, during the hot melt sealing process of the plastic film, first, a temperature field simulation model of the plastic film in the heating stage is established according to the phase change transfer coupling data. By applying a heating power to the plastic film (for example, setting the temperature to 200 °C and the power to 500 W), the heat conduction equation is solved using the finite element method to simulate the temperature change of each point inside the plastic film over time. The simulation results show that the temperature in the central part of the plastic film rises faster, while the temperature in the edge area rises slower due to heat dissipation. Based on these data, temperature distribution data of the plastic film during the hot melt sealing process is generated, providing a basis for the subsequent melting behavior simulation.

[0122] Step S242: Simulate the temperature distribution of the plastic film in the heating stage according to the temperature distribution data, and predict the melting behavior, so as to generate melting simulation data;

[0123] In the embodiment of the present invention, after obtaining the temperature distribution data, a detailed simulation of the temperature distribution in the heating stage is carried out. The specific operations include analyzing the temperature change rate in different regions of the plastic film during the heating process, and the critical point where melting begins. Through the melting point parameter (for example, the melting point of the plastic film is 180 °C), the time point and position where each region of the plastic film starts to melt are determined, and its melting behavior is predicted. At the same time, by adjusting the heating rate and temperature control strategy, the melting speed and uniformity can be optimized, and finally melting simulation data is generated. For example, when the heating rate is 10 °C / s, the melting time of the plastic film is 15 seconds, and the melting range is a 30 mm diameter area.

[0124] Step S243: Based on the melting simulation data, simulate the flow behavior of the plastic film during the sealing process based on the flow path, thickness change, and contact surface morphology of the melted plastic, so as to obtain plastic flow simulation data;

[0125] In the embodiment of the present invention, based on the melting simulation data, the flow behavior of the plastic film after melting is simulated. During the simulation process, first, the flow path of the plastic film needs to be set, and the flow trend of the melted plastic film is mainly calculated through the influence of gravity, packaging pressure, and surface tension. For example, under the condition that the packaging pressure is 1.5 MPa, the melted plastic film flows to the surface of the infusion tube at a speed of 3 mm per second. Then, a simulation of the thickness change is carried out to determine the thickness change of the plastic film at different positions; at the same time, the contact surface morphology between the plastic film and the infusion tube is analyzed to evaluate the uniformity and integrity of its packaging. After multiple simulations, plastic flow simulation data is generated, showing the film thickness change curve and contact surface quality during the flow process.

[0126] Step S244: Perform a phase change analysis on the solidification behavior of the plastic film after cooling based on the plastic flow simulation data, so as to generate the temperature change and phase change simulation data during the solidification process.

[0127] In the embodiment of the present invention, based on the plastic flow simulation data, a phase change analysis is performed on the solidification behavior of the plastic film during the cooling process. During the simulation, cooling conditions are applied (for example, the cooling temperature is 25°C), and the temperature drop of the plastic film over time is analyzed according to the temperature change model. By dynamically analyzing the temperature field, the phase change process of the plastic film from the liquid state to the solid state is captured, and its solidification rate and solidification time are determined. At the same time, the solidification strength at different positions of the plastic film is evaluated to determine whether stress concentration areas will be generated during the solidification process. Finally, through these phase change analyses, the temperature change and phase change simulation data during the solidification process are generated. For example, in an environment of 25°C, the time required for the plastic film to completely solidify is 30 seconds, and the solidification strength at the contact surface reaches 10 MPa, ensuring the airtightness and strength of the package.

[0128] Through the temperature field simulation of the plastic film during the hot melt sealing process by coupling data according to phase change transfer, the temperature distribution data of the plastic film at different positions and time points can be obtained. This process ensures the accurate evaluation of the heating uniformity and heat conduction efficiency of the plastic film, helps to predict the performance of the plastic film during the melting process, and thus provides basic data for the optimization of the entire packaging process. Understanding the temperature distribution can also help identify possible hot spot areas and reduce the risk of packaging defects. By simulating the temperature distribution of the plastic film during the heating stage with the temperature distribution data, the melting behavior can be predicted in more detail. This prediction of the melting behavior not only helps to understand the temperature change of the plastic film during the heating process, but also determines the optimal heating time and temperature, so as to ensure that the plastic film can reach the best molten state. This process can reduce unnecessary energy consumption, improve production efficiency, and ensure that the plastic can flow effectively and fit the infusion set during packaging. Based on the melting simulation data, the flow behavior of the plastic film during the sealing process is simulated, and the flow path, thickness change and contact surface morphology of the melted plastic can be analyzed in depth. This step is crucial because the flow behavior directly affects the integrity and sealing effect of the package. Understanding the flow characteristics of the plastic helps to optimize the mold design and processing parameters, ensure that the plastic can fully fill all voids during the packaging process, and thus improve the sealing performance and avoid air leakage or weak sealing problems. By performing a phase change analysis on the solidification behavior of the plastic film after cooling according to the plastic flow simulation data, the temperature change and phase change simulation data during the solidification process can be generated. This analysis can help to understand the solidification situation of the plastic film during the cooling process, so as to ensure the strength and airtightness of the final product. By predicting the temperature change during the solidification process, the cooling time and conditions can be optimized to ensure that the plastic film can maintain its structure and performance after solidification. This is crucial for improving the packaging quality and consistency, especially in medical device applications with high requirements. By implementing these steps, a comprehensive understanding and precise control of the hot melt sealing process can be achieved, ensuring that the plastic film can be uniformly heated, flow effectively and finally form a stable solidified state during the entire packaging process. This detailed simulation and analysis can not only improve the packaging efficiency, reduce material waste in the production process, but also ensure the safety and reliability of the final product, thus enhancing the market competitiveness of the product.

[0129] Preferably, step S3 includes the following steps:

[0130] Step S31: Construct a three-dimensional geometric model of the infusion set pipeline after winding according to the deformation simulation data and the packaging effect simulation data, obtain the geometric dimensions and material property data of the blister packaging array, and establish an initial assembly model of the infusion set pipeline and the blister packaging, so as to obtain the initial assembly data;

[0131] In an embodiment of the present invention, based on the deformation simulation data and encapsulation effect simulation data generated in the early stage, a three-dimensional geometric model of the infusion set tubing after winding is first established. The model is constructed by inputting the geometric information of the tubing, such as length, diameter, winding diameter, and number of turns, and combining the material properties of the tubing (such as elastic modulus, Poisson's ratio), and three-dimensional modeling is carried out using finite element software. Next, the geometric dimensions of the blister packaging array (for example, the length of a single package is 50 mm, the width is 30 mm, and the height is 20 mm) and material properties (such as the elastic modulus and tensile strength of thermoplastic plastics) are obtained. Based on these data, an initial assembly model of the infusion set tubing and the blister packaging is established, and initial assembly data is obtained through the definition of the assembly relationship.

[0132] Step S32: Perform a static interference check on the initial assembly data, identify the collision points between the tubing and the packaging, and optimize and adjust the position of the infusion set tubing in the blister packaging array to obtain position adjustment data;

[0133] After obtaining the initial assembly data in an embodiment of the present invention, the interference detection function in CAD software is used to perform a static interference check on the model. This operation will identify the collision points and potential interference areas between the infusion set tubing and the blister packaging. Suppose 3 collision points are found at the edge of the tubing and the packaging in the model, and the position of the tubing needs to be optimized according to the actual assembly situation. By adjusting the rotation angle and insertion depth of the tubing, the number of collision points is gradually reduced. After several rounds of position adjustment, the collision points are completely eliminated, and position adjustment data is generated to ensure that the tubing can be successfully assembled in the blister packaging array.

[0134] Step S33: Perform a dynamic insertion simulation on the initial assembly model using the position adjustment data, simulate the deformation and stress distribution during the process of inserting the tubing into the packaging, and evaluate the stability and fixing effect of the tubing in the packaging to obtain fixing effect data;

[0135] In an embodiment of the present invention, the generated position information is used to simulate the dynamic insertion process of the tubing using a simulation tool. The specific operation steps include: setting the insertion speed (such as 5 mm / s), the friction coefficient of the packaging (such as 0.3), and the material characteristic parameters of the tubing. The deformation and stress distribution during the process of inserting the tubing into the packaging are calculated through simulation, especially the distribution of bending deformation and contact pressure. The simulation results show that the maximum deformation position of the tubing during insertion is at the winding part, and the deformation amount is 2 mm. The maximum stress appears near the edge of the packaging, which is 50 MPa. When evaluating the stability, the focus is on analyzing the fixing effect of the tubing in the packaging to ensure that the tubing will not have obvious displacement in the packaging array, and finally generate fixing effect data.

[0136] Step S34: Analyze the pipeline displacement and deformation during the packaging process based on the fixed effect data, and locally optimize the packaging design to obtain optimized design data;

[0137] In the embodiment of the present invention, based on the fixed effect data, the pipeline displacement and deformation during the packaging process are further analyzed to identify the possible displacement deviation and deformation of the pipeline during the insertion process. By adjusting the clamping force and boundary conditions of the packaging, the local structure is optimized. For example, if it is found that a certain section of the pipeline has a displacement of 5 mm during insertion, by increasing the depth of the fixed groove of the blister packaging in this area and optimizing the clamping force, the displacement is reduced to within 1 mm. Based on these optimization measures, optimized design data is generated to improve the assembly stability and deformation control of the pipeline.

[0138] Step S35: Perform dynamic simulation of the position in the blister packaging array according to the optimized design data and the initial assembly data to obtain packaging behavior simulation data.

[0139] In the embodiment of the present invention, dynamic simulation in the blister packaging array is performed according to the optimized design data and the initial assembly data. Through the dynamic simulation of the packaging behavior, the deformation, displacement, and force changes of the pipeline during the assembly process are observed. The simulation results show that after optimization, the maximum displacement of the pipeline in the packaging is reduced to 0.5 mm, and the stress concentration area is significantly reduced. Based on these simulation results, packaging behavior simulation data is generated to guide the subsequent actual packaging design optimization.

[0140] In the embodiments of the present invention, a three-dimensional geometric model of the infusion set pipeline after winding is constructed based on deformation simulation data and encapsulation effect simulation data, and the geometric dimensions and material property data of the blister packaging array are obtained, which can ensure a full understanding of the mutual relationship between the pipeline and the packaging at the initial stage of design. The establishment of this preliminary assembly model provides basic data for subsequent interference checking and optimization, enabling the design team to more accurately identify potential problems and reduce the complexity and cost of subsequent modifications. Performing a static interference check on the initial assembly data can effectively identify the collision points between the pipeline and the packaging. This process ensures that design defects can be discovered and resolved before product assembly, reducing assembly problems in actual production. By optimizing and adjusting the position of the infusion set pipeline in the blister packaging array, the overall assembly efficiency can be improved, and the stability of the pipeline in the final product can be ensured, reducing the risk of material loss and rework. Using the position adjustment data to perform a dynamic insertion simulation on the initial assembly model can detail the deformation and stress distribution during the process of inserting the pipeline into the packaging. This dynamic analysis can help designers evaluate the stability and fixing effect of the pipeline during the packaging process, ensuring that the pipeline will not experience unexpected displacement or damage during the entire packaging process. Based on the understanding of the stress distribution, the packaging design can be further optimized to ensure the fixing and protection effect of the pipeline. Performing pipeline displacement and deformation analysis during the packaging process based on the fixing effect data can identify potential problems that may occur in actual packaging. By locally optimizing the packaging design, the adaptability of the packaging and the protection effect of the pipeline can be improved, ensuring that the pipeline is not damaged during transportation and storage. This optimization not only improves the product quality but also reduces the after-sales cost caused by product damage. Performing a dynamic simulation in the blister packaging array based on the optimized design data and the initial assembly data can simulate the behavior during the actual packaging process and obtain packaging behavior simulation data. This step can provide a profound understanding of the packaging effect, ensuring that the performance and quality of the final product can be evaluated at the design stage. By simulating and analyzing the packaging behavior, potential packaging problems can be identified and resolved before production, thereby enhancing the market competitiveness of the product. Overall, by implementing these steps, the packaging design quality and production efficiency of disposable infusion sets can be effectively improved. Through precise modeling, interference checking, and dynamic simulation, not only can rework and material loss in production be reduced, but also the safety and reliability of the final product can be ensured. These optimization measures will ultimately make the product more competitive in the market and meet the increasingly stringent user requirements.

[0141] Preferably, step S4 includes the following steps:

[0142] Step S41: Extract the geometric shape, material properties, sealing area structure, and thickness distribution information of the packaging bag according to the encapsulation effect simulation data, so as to generate three-dimensional geometric model data;

[0143] In an embodiment of the present invention, according to the simulation data of the packaging effect, the geometric shape and material properties of the packaging bag are first extracted, including the external dimensions of the packaging bag (such as 300 mm in length, 200 mm in width, and 0.2 mm in thickness) and the structural characteristics and thickness distribution of the sealing area (for example, the thickness of the sealing area is 0.3 mm, which is thicker than other areas). Using these data, a three-dimensional geometric model of the packaging bag is created in three-dimensional modeling software. The material properties include the elastic modulus, density, and thermal conductivity of the plastic material, and these properties are also input into the model to generate three-dimensional geometric model data, which is prepared for subsequent heat conduction and air discharge simulations.

[0144] Step S42: Set the temperature field distribution of the packaging material using the three-dimensional geometric model data, and simulate the heat conduction behavior of the material during the sealing process to obtain the heat conduction data of the sealing area, where the temperature field distribution includes the temperature gradient and the material softening area of the sealing area;

[0145] In an embodiment of the present invention, the temperature field distribution of the packaging material is set using the generated three-dimensional geometric model data. The specific steps include: First, set different temperature gradients for the sealing area, such as the sealing temperature is set to 180 °C, the temperature near the seal is 150 °C, and the other areas are at room temperature. Then, based on the thermal conductivity and specific heat capacity of the material, use finite element simulation software to simulate the heat conduction behavior of the sealing area, focusing on analyzing the change of the temperature gradient during the sealing process and the size of the material softening area. Through the heat conduction simulation, the heat conduction data of the sealing area is generated to determine the heating width and softening depth of the sealing area.

[0146] Step S43: Based on the heat conduction data of the sealing area and the three-dimensional geometric model data, preliminarily calculate the air volume inside the packaging bag, and perform a simulation of the air discharge inside the packaging bag to generate preliminary air discharge effect data;

[0147] In an embodiment of the present invention, according to the heat conduction data of the sealing area and the three-dimensional geometric model data, the initial air volume inside the packaging bag is calculated. First, determine the effective volume inside the packaging bag through the geometric model (such as 600 cubic centimeters), and then simulate the process of air being discharged by setting the material deformation degree and sealing effect during sealing. Using the CFD simulation tool, perform a preliminary simulation on the flow path, flow rate, and discharge amount of air during the packaging process to generate preliminary air discharge effect data. The results show that during the sealing process, about 90% of the air can be naturally discharged.

[0148] Step S44: Perform a dynamic simulation of air extraction based on the vacuum pump simulation according to the preliminary air discharge effect data, and analyze the residual air volume inside the packaging bag based on the change of air flow and vacuum degree to obtain the generated residual air distribution data;

[0149] In an embodiment of the present invention, based on the preliminary air discharge effect data, a dynamic simulation model of a vacuum pump is used to simulate the further air extraction process. First, the operating parameters of the vacuum pump are set, such as a vacuum degree of -0.09 MPa and an extraction rate of 5 L / min. The residual air volume inside the packaging bag is calculated through the air flow and pressure change equations. In the simulation, as the vacuum degree increases, the air discharge rate gradually decreases, and finally the residual air volume is 10 cubic centimeters. The generated residual air distribution data describes the air distribution at different positions. For example, at the corners of the packaging bag, it is more difficult to discharge the air.

[0150] Step S45: Analyze the air discharge efficiency at different positions inside the packaging bag according to the residual air distribution data, and generate air discharge efficiency simulation data;

[0151] In an embodiment of the present invention, the residual air distribution data is used to analyze the air discharge efficiency at different positions inside the packaging bag. By comparing the air flow rates at each position, it is found that the air discharge efficiency is higher at the sealing area and the edges of the bag, while the discharge efficiency at the corner position is lower, only 70%. Based on this analysis, the extraction method of the vacuum pump and the bag structure during the packaging process are adjusted to optimize the air discharge path, and air discharge efficiency simulation data is generated.

[0152] Step S46: Use the vacuum pump to simulate air extraction according to the air discharge efficiency simulation data to generate vacuum packaging effect simulation data.

[0153] In an embodiment of the present invention, according to the air discharge efficiency simulation data, the extraction process of the vacuum pump is further optimized. The working cycle and extraction duration of the vacuum pump are set to simulate the final air discharge effect. By increasing the vacuum degree and extending the extraction time, the air discharge efficiency is increased to 95%, and the residual air volume is reduced to 5 cubic centimeters. Finally, vacuum packaging effect simulation data is generated, providing a reference for the optimization of the vacuum packaging process.

[0154] The present invention can generate accurate three-dimensional geometric model data by extracting information on the geometric shape, material properties, seal area structure, and thickness distribution of the packaging bag based on the simulation data of the packaging effect. This process ensures a comprehensive understanding of the packaging bag design, enabling subsequent heat conduction and air evacuation analyses to be carried out based on an accurate model. This accuracy will reduce errors in the design process, thereby lowering the later modification costs. By setting the temperature field distribution of the packaging material using the three-dimensional geometric model data and simulating the material heat conduction behavior during the sealing process, heat conduction data for the seal area can be obtained, including the temperature gradient and the material softening area. This analysis is crucial for optimizing the sealing process, ensuring uniform heating of the material during hot melt sealing and avoiding poor sealing caused by uneven heat distribution, thereby improving the product's sealing performance and safety. Based on the heat conduction data of the seal area and the three-dimensional geometric model data, a preliminary calculation of the air volume inside the packaging bag is performed, and an air evacuation simulation inside the packaging bag is carried out to generate preliminary air evacuation effect data. This step provides a preliminary understanding of the air evacuation process, enabling subsequent vacuum extraction and efficiency analyses to be optimized based on this data. This preliminary assessment helps to identify potential problems and improve the design. By performing a dynamic simulation of air extraction based on a vacuum pump simulation according to the preliminary air evacuation effect data, the residual air volume inside the packaging bag can be analyzed. This process simulates the relationship between air flow and vacuum degree changes, helping the design team to understand the efficiency and effect of air extraction under different operating conditions. This in-depth analysis ensures that the expected vacuum effect can be achieved in actual applications and optimizes the vacuum packaging process. By analyzing the air evacuation efficiency at different positions inside the packaging bag based on the residual air distribution data, air evacuation efficiency simulation data can be generated. This analysis helps to identify the air extraction effects in different regions, ensuring that the air evacuation scheme can be optimized specifically during the design stage. This targeted adjustment can significantly improve the sealing performance of the final packaging and reduce product quality problems caused by air residues during transportation and storage. Using a vacuum pump to perform an air extraction simulation according to the air evacuation efficiency simulation data to generate vacuum packaging effect simulation data. This final step provides a detailed prediction and analysis of the performance of the packaging bag in actual applications, helping to optimize the production process and ensure the competitiveness of the product in the market. By obtaining real packaging effect simulation data, product quality control can be enhanced, and data support can be provided for improving the production process. Overall, by implementing these steps, the design quality and production efficiency of the packaging bag can be effectively improved. Through accurate modeling, heat conduction simulation, and dynamic air evacuation analysis, not only can the vacuum packaging effect be optimized, but also the production costs and product losses caused by design defects can be reduced. These optimization measures will ultimately enhance the market competitiveness of the product and meet the growing consumer demands.

[0155] Preferably, step S5 includes the following steps:

[0156] Step S51: Establish a multi - physical - field coupling model based on packaging behavior simulation data and vacuum packaging effect simulation data;

[0157] In the embodiment of the present invention, according to the previously obtained packaging behavior simulation data and vacuum packaging effect simulation data, a multi - physical - field coupling model is first constructed in a multi - physical - field simulation software. This model combines the basic equations of heat conduction, fluid dynamics, and solid mechanics to comprehensively analyze the interaction of each physical field during the packaging process. Specifically, the temperature field in the heat - sealing area, the velocity field of air flow, and the stress field of the material are defined. By coupling these physical fields, the overall system response is obtained. The parameter settings include a heat - sealing temperature of 180 °C, a pressure of 0.5 MPa, and a time of 3 seconds, ensuring that the model can accurately reflect the physical phenomena in actual operation.

[0158] Step S52: Analyze the positioning accuracy of the infusion set tubing during the packaging process using the multi - physical - field coupling model, so as to obtain tubing positioning accuracy evaluation data;

[0159] In the embodiment of the present invention, the established multi - physical - field coupling model is used to analyze the positioning accuracy of the infusion set tubing. By setting different positioning errors (such as ±1 mm, ±2 mm), the influence of these errors on the position of the tubing during the packaging process is simulated. By tracking the dynamic changes of the tubing during packaging, the influence data of the positioning error on the final position is collected. Further, the deviation between the actual position and the ideal position of the tubing is calculated and analyzed, so as to generate tubing positioning accuracy evaluation data. It is expected that the positioning accuracy can reach more than 95%, ensuring the packaging quality.

[0160] Step S53: Evaluate the winding tightness of the infusion set tubing based on the multi - physical - field coupling model, and conduct a vacuum sealing process to evaluate the influence of different packaging parameters on the sealing effect, so as to obtain winding tightness data and vacuum sealing effect evaluation data, where the packaging parameters include heat - sealing temperature, pressure, and time;

[0161] In the embodiment of the present invention, based on the multi - physical - field coupling model, the winding tightness of the infusion set tubing is evaluated. First, different packaging parameters are set, such as heat - sealing temperature (170 °C, 180 °C, 190 °C), packaging pressure (0.4 MPa, 0.5 MPa, 0.6 MPa), and packaging time (2 s, 3 s, 4 s), and multiple groups of experimental simulations are carried out. By observing the strain and deformation of the tubing in the winding state, the relationship between the winding tightness and the vacuum sealing effect is evaluated. Finally, the winding tightness data and vacuum sealing effect evaluation data are collected, and it is found that the best combination of winding tightness and packaging parameters can achieve the highest sealing effect. The sealing test results show that the gas leakage rate is less than 1%.

[0162] Step S54: Perform multi-objective optimization analysis based on the pipeline positioning accuracy evaluation data, winding tightness data, and vacuum sealing effect evaluation data, so as to obtain an optimized design scheme for the packaging system.

[0163] In the embodiment of the present invention, multi-objective optimization analysis is performed based on the pipeline positioning accuracy evaluation data, winding tightness data, and vacuum sealing effect evaluation data. The specific steps include setting optimization objectives, such as minimizing the packaging cost, maximizing the sealing effect, and optimizing the pipeline positioning accuracy. Using optimization algorithms (such as genetic algorithms or particle swarm optimization), search for the optimal solution among different combinations of packaging parameters (such as temperature, pressure, and time). After multiple iterations and evaluations, an optimized design scheme for the packaging system is finally obtained, in which the recommended heat sealing temperature is set at 185 °C, the pressure is 0.55 MPa, and the time is 3 seconds. These parameters can achieve the highest overall packaging performance.

[0164] By establishing a multi - physical - field coupling model based on packaging behavior simulation data and vacuum packaging effect simulation data, the present invention can comprehensively consider the interactions of multiple physical fields such as heat, fluid, and solid mechanics. Such a multi - physical - field model can provide a more realistic and comprehensive analysis of system behavior, reveal the impacts of each physical field on the packaging process, and provide a scientific basis for subsequent accuracy evaluation and optimization. Through a more comprehensive model, the design team can better understand the performance of the packaging system under different conditions and then make more effective design adjustments. Using the multi - physical - field coupling model to analyze the positioning accuracy of the infusion set tubing during the packaging process can generate tubing positioning accuracy evaluation data. This analysis helps to identify possible position deviations of the tubing during the packaging process and ensure the accurate positioning of the tubing in the final product. High positioning accuracy can guarantee the functionality and safety of the product and reduce the usage risks caused by inaccurate positioning. In addition, through precise positioning, production efficiency can also be improved, reducing unnecessary adjustments and rework. Based on the multi - physical - field coupling model, evaluate the winding tightness of the infusion set tubing and analyze the effects of different packaging parameters (such as heat - sealing temperature, pressure, and time) on the sealing effect, which can generate winding tightness data and vacuum sealing effect evaluation data. The optimization of winding tightness directly affects the sealing performance and stability of the packaging, ensuring the safety of the product during transportation and storage. By evaluating the effects of different packaging parameters, the design team can find the optimal packaging conditions, thereby improving the overall quality and reliability of the packaging and preventing leakage or contamination during use. Conduct multi - objective optimization analysis based on the tubing positioning accuracy evaluation data, winding tightness data, and vacuum sealing effect evaluation data to obtain an optimized design solution for the packaging system. This process comprehensively considers different design objectives to ensure the efficient use of resources and production costs while meeting all performance requirements. Through multi - objective optimization, the efficiency and economy of the design can be achieved, ultimately enhancing the market competitiveness and user satisfaction of the product. Overall, through the implementation of these steps, the design quality and production efficiency of the packaging system can be effectively improved. Establishing a multi - physical - field coupling model enables a deeper understanding of complex system behavior and thus ensures the stability and safety of the product under different physical conditions. At the same time, precise positioning and winding evaluation help to improve the packaging quality of the product and prevent potential quality problems. In addition, through multi - objective optimization analysis, the design team can develop a more forward - looking design solution, promote the effective use of resources and reduce production costs, further enhancing the market competitiveness and brand image of the enterprise.

[0165] Therefore, from any perspective, the embodiments should be regarded as exemplary and non - restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, 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.

[0166] 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, and 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 will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A simulation design method for a conveying mechanism of an assembly machine, characterized in that: The following steps are involved: Step S1: obtaining physical property data of a disposable infusion set pipeline; establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of bending, twisting and mutual contact of the infusion set pipeline based on a winding method, thereby generating deformation simulation data of the flexible pipeline; performing pipeline flexibility simulation on the pipeline flexibility simulation model according to the deformation simulation data, thereby obtaining simulation data of pipeline winding behavior; Step S2: obtaining material property data of the plastic film during the hot melt sealing process, and performing a thermal-fluid-solid coupling analysis on the material property data, thereby obtaining phase change transfer coupling data; According to the phase change transfer coupling data, the temperature field distribution, melting and solidification process of the plastic film during the infusion set packaging process are estimated, and the packaging pressure change analysis is performed, and the plastic film flow and solidification simulation is performed to obtain the packaging effect simulation data; Step S3: performing packaging simulation analysis on the wound infusion set tube according to the deformation simulation data and the packaging effect simulation data, and simulating the position adjustment of the infusion set tube in the blister packaging array in the simulation, so as to obtain packaging behavior simulation data; Step S4: analyzing the effect of air exhaust inside the packaging bag based on the temperature distribution and pressure change according to the packaging effect simulation data, thereby obtaining air exhaust efficiency simulation data; Using a vacuum pump to simulate air extraction based on air exhaust efficiency simulation data to generate vacuum packaging effect simulation data; Step S5: Perform a multi-physics field comprehensive analysis on the positioning, winding tightness and vacuum sealing effect of the infusion set tubing during the packaging process according to the packaging behavior simulation data and the vacuum packaging effect simulation data, so as to generate an optimal design scheme for the packaging system.

2. The simulation design method of the conveying mechanism of the assembly machine according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: collecting the length, inner and outer diameters, and wall thickness information of the disposable infusion set pipeline, thereby obtaining pipeline geometry data; Step S12: Acquire the elastic modulus, Poisson's ratio and density data of the infusion set tubing material, thereby generating material physical property data; Step S13: measuring the change of mechanical properties of the infusion set pipeline at different temperatures, thereby obtaining mechanical property data; Step S14: merging pipeline geometry data, material physical property data and mechanical property data into physical property data; Step S15: establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of the bending, twisting and mutual contact of the infusion set pipeline based on the winding method, thereby generating deformation simulation data of the flexible pipeline; Step S16: simulating the winding behavior of the pipeline flexibility simulation model according to the deformation simulation data, so as to obtain pipeline winding behavior simulation data.

3. The simulation design method of the conveying mechanism of the assembly machine according to claim 2 is characterized in that: Step S15 includes the following steps: Step S151: performing material stress-strain curve analysis according to the physical property data of the infusion set pipeline, thereby obtaining stress-strain relationship data; Step S152: Establishing a constitutive model for the pipeline material according to the stress-strain relationship data, and analyzing the influence of temperature on the constitutive model according to the mechanical property data, thereby obtaining a pipeline material characteristic data set; Step S153: establishing a three-dimensional geometric model of the pipeline according to the geometric information in the physical property data, and integrating the material properties of the three-dimensional geometric model according to the pipeline material property data set, thereby obtaining a material property integrated model; Step S154: setting meshing parameters for the material property integrated model, and determining boundary conditions and loading methods, thereby obtaining a pipeline flexibility simulation model; Step S155: performing mechanical analysis on the infusion set pipeline according to the preset infusion set pipeline winding model, thereby obtaining a pipeline stress state data set, wherein the mechanical analysis includes bending stress and strain distribution analysis, pipeline torsion analysis, and contact force distribution analysis; Step S156: applying the pipeline stress state data set to the pipeline flexibility simulation model to perform static nonlinear analysis based on deformation under winding state, thereby obtaining static deformation data, and simulating transient deformation behavior during winding, thereby obtaining dynamic deformation data; Step S157: Perform pipeline deformation simulation based on node displacement and stress distribution using static deformation data and dynamic deformation data, thereby generating deformation simulation data of the flexible pipeline.

4. The simulation design method for the conveying mechanism of the assembly machine according to claim 3 is characterized in that: Step S155 includes the following steps: Step S1551: determining the geometric configuration of the pipeline winding according to the preset infusion set pipeline winding model, thereby obtaining winding geometric parameter data, wherein the geometric configuration of the pipeline winding includes winding diameter, winding number and winding pitch; Step S1552: Calculating the curvature distribution of the pipeline in the winding state according to the winding geometric parameter data, thereby obtaining the pipeline curvature distribution data; Step S1553: Calculate the bending stress using the pipeline curvature distribution data and the pipeline material characteristic data set, thereby obtaining the pipeline bending stress distribution data; Step S1554: Calculating the torsional stress based on the torsional angle of each section of the pipeline based on the winding geometric parameter data, thereby obtaining pipeline torsional stress data; Step S1555: identifying the contact points of the infusion set tubing winding model during the tubing winding process, and calculating the normal force and tangential force of the contact points, thereby obtaining contact force distribution data; Step S1556: Combine the pipeline bending stress distribution data, pipeline torsional stress data and contact force distribution data into pipeline strain distribution data, and perform axial tension and compression effect analysis to obtain a pipeline stress state data set.

5. The simulation design method for the conveying mechanism of the assembly machine according to claim 4, characterized in that: Step S16 includes the following steps: Step S161: geometrically updating the pipeline flexibility simulation model according to the node displacement information of the deformation simulation data, thereby obtaining an updated pipeline geometric model; Step S162: applying a preload based on the deformation prestress generated during the winding process to the infusion set pipeline according to the pipeline geometric model, thereby generating preload data; Step S163: using the preload data to set mechanical boundary conditions for pipeline winding, thereby determining winding boundary condition data, wherein the mechanical boundary conditions include boundary conditions of bending, torsion and contact stress; Step S164: performing mechanical analysis of the flexible pipeline during the winding process according to the winding boundary condition data, and calculating the deformation amplitude and force change of the pipeline at different winding positions, thereby obtaining stress data of the winding position; Step S165: performing local stress concentration area analysis based on the winding position stress data and the pipeline material characteristic data set, and optimizing the winding parameters of the infusion set pipeline winding model, thereby obtaining winding parameter optimization data; Step S166: Perform pipeline flexibility simulation using winding parameter optimization data and pipeline geometric model to obtain pipeline winding behavior simulation data.

6. The simulation design method for the conveying mechanism of the assembly machine according to claim 5, characterized in that: Step S2 includes the following steps: Step S21: obtaining material property data of the plastic film during the hot melt sealing process, including melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship and crystallization kinetic parameters; Step S22: Establishing a multi-scale structural model of the plastic film material according to the material thermal property data, thereby obtaining a material microstructure model, wherein the multi-scale structure includes the structures of molecular chains, crystals, and amorphous regions; Step S23: constructing a heat-fluid-solid coupling analysis model based on the coupling of heat conduction equations, fluid mechanics equations and solid mechanics equations according to the material microstructure model, thereby obtaining phase change transfer coupling data; Step S24: estimating the temperature field distribution, melting and solidification process of the plastic film during the packaging of the infusion set according to the phase change transfer coupling data, analyzing the packaging pressure change, and simulating the flow and solidification of the plastic film, thereby generating temperature change and phase change simulation data of the solidification process; Step S25: Simulate the packaging effect of the plastic film based on the temperature change and phase change simulation data, and analyze the packaging effect based on sealing, strength and airtightness, thereby obtaining packaging effect simulation data.

7. The simulation design method for the conveying mechanism of the assembly machine according to claim 6, characterized in that: Step S24 includes the following steps: Step S241: performing temperature field simulation of the plastic film during the hot melt sealing process according to the phase change transfer coupling data, thereby obtaining temperature distribution data; Step S242: simulating the temperature distribution of the plastic film during the heating stage according to the temperature distribution data, and predicting the melting behavior, thereby generating melting simulation data; Step S243: Based on the melting simulation data, the flow behavior of the plastic film during the sealing process is simulated based on the flow path, thickness change and contact surface morphology of the melted plastic, thereby obtaining plastic flow simulation data; Step S244: performing phase change analysis on the solidification behavior of the plastic film after cooling according to the plastic flow simulation data, thereby generating temperature change and phase change simulation data of the solidification process.

8. The simulation design method for the conveying mechanism of the assembly machine according to claim 7, characterized in that: Step S3 includes the following steps: Step S31: constructing a three-dimensional geometric model of the infusion set pipeline after winding according to the deformation simulation data and the packaging effect simulation data, obtaining the geometric dimensions and material property data of the blister packaging array, and establishing an initial assembly model of the infusion set pipeline and the blister packaging, thereby obtaining initial assembly data; Step S32: Performing a static interference check on the initial assembly data, identifying the collision point between the pipeline and the package, and optimizing and adjusting the position of the infusion set pipeline in the blister packaging array, thereby obtaining position adjustment data; Step S33: using the position adjustment data to perform dynamic insertion simulation on the initial assembly model, and simulating the deformation and stress distribution of the pipeline during the insertion into the package, evaluating the stability and fixation effect of the pipeline in the package, thereby obtaining fixation effect data; Step S34: performing pipeline displacement and deformation analysis during the packaging process according to the fixed effect data, and performing local optimization on the packaging design, thereby obtaining optimized design data; Step S35: Dynamically simulate the position in the blister packaging array according to the optimized design data and the initial assembly data, so as to obtain packaging behavior simulation data.

9. The simulation design method for the conveying mechanism of the assembly machine according to claim 8, characterized in that: Step S4 includes the following steps: Step S41: extracting the geometric shape, material properties, sealing area structure and thickness distribution information of the packaging bag according to the packaging effect simulation data, thereby generating three-dimensional geometric model data; Step S42: using the three-dimensional geometric model data to set the temperature field distribution of the packaging material, and simulating the thermal conduction behavior of the material during the sealing process, thereby obtaining thermal conduction data of the sealing area, wherein the temperature field distribution includes the temperature gradient of the sealing area and the material softening area; Step S43: Preliminarily calculating the air volume in the packaging bag according to the heat conduction data of the sealing area and the three-dimensional geometric model data, and simulating the exhaust of air inside the packaging bag to generate preliminary air exhaust effect data; Step S44: performing air extraction dynamic simulation based on vacuum pump simulation according to the preliminary air exhaust effect data, analyzing the residual air volume inside the packaging bag based on air flow and vacuum degree changes, thereby generating residual air distribution data; Step S45: analyzing the air exhaust efficiency at different positions in the packaging bag according to the residual air distribution data, and generating air exhaust efficiency simulation data; Step S46: using a vacuum pump to perform air extraction simulation according to the air exhaust efficiency simulation data to generate vacuum packaging effect simulation data.

10. The simulation design method for the conveying mechanism of the assembly machine according to claim 9, characterized in that: Step S5 includes the following steps: Step S51: establishing a multi-physics field coupling model according to packaging behavior simulation data and vacuum packaging effect simulation data; Step S52: Analyze the positioning accuracy of the infusion tube during the packaging process using a multi-physics field coupling model, thereby obtaining the evaluation data of the tube positioning accuracy; Step S53: evaluating the winding tightness of the infusion set tubing based on the multi-physics field coupling model, and performing a vacuum sealing process to evaluate the influence of different packaging parameters on the sealing effect, thereby obtaining winding tightness data and vacuum sealing effect evaluation data, wherein the packaging parameters include heat sealing temperature, pressure and time; Step S54: Perform multi-objective optimization analysis based on the pipeline positioning accuracy evaluation data, the winding tightness data, and the vacuum sealing effect evaluation data, so as to obtain an optimized design solution for the packaging system.

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