Medical instrument ultrathin shell injection mold pouring simulation method and system

Abstract

The invention discloses a medical instrument ultrathin shell injection mold pouring simulation method and system, and relates to the technical field of injection mold simulation pouring, and the method comprises the following steps: analyzing a relation function among an injection molding melt temperature, an injection molding pressure and a simulation warping amount, marking the relation function as a simulation relation function, the optimal plastic melt temperature and the optimal injection molding pressure are obtained based on the simulation relation function, a relation function of the cooling time and the time warping amount is analyzed and marked as a time relation function, and the optimal cooling time is obtained based on the time relation function; the optimal plastic melt temperature, the optimal injection molding pressure and the optimal cooling time are output, and real pouring is conducted based on the optimal plastic melt temperature, the optimal injection molding pressure and the optimal cooling time; the method is used for solving the problem that in an existing injection mold simulation pouring technology, the optimal pouring condition cannot be obtained from the pouring conditions with large influence on the ultrathin shell, and consequently the ultrathin shell of the medical instrument subjected to injection molding deforms.

Description

Technical Field

[0001] The present invention relates to the technical field of injection mold simulation casting, and specifically to a method and system for simulating the casting of an injection mold for an ultra-thin shell of a medical device. Background Technique

[0002] The casting of an injection mold is a process of introducing molten plastic into the cavity through the gating system of the mold, and filling, cooling, and solidifying it in the cavity to finally form the required plastic product. Its design and optimization have a crucial impact on the quality, production efficiency, and cost of plastic products. However, to optimize the casting, continuous casting is required to judge the quality of the casting. At this time, multiple castings will cause waste of resources. Therefore, an injection mold casting simulation method is proposed;

[0003] Regarding the casting of an injection mold for an ultra-thin shell of a medical device, due to the ultra-thin shell, not only an accurate casting model is required, but also the casting conditions need to be concerned, specifically the temperature of the injection material during casting, the pressure during injection, and the cooling time. If these casting conditions are not qualified, the ultra-thin shell will deform. For example, in the patent application with the application publication number CN117574695A, an injection mold simulation casting method, system, and medium are disclosed. This solution ignores the casting conditions that have a greater impact on the ultra-thin shell when adjusting the injection mold, that is, the existing injection mold simulation casting technology fails to obtain the optimal casting conditions from the casting conditions that have a greater impact on the ultra-thin shell, resulting in deformation of the ultra-thin shell of the injection-molded medical device. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems in the prior art to some extent. By analyzing the relationship function between the injection melt temperature, injection pressure, and simulation warpage amount, which is marked as the simulation relationship function, obtaining the optimal injection melt temperature and optimal injection pressure based on the simulation relationship function, analyzing the relationship function between the cooling time and the time warpage amount, which is marked as the time relationship function, and obtaining the optimal cooling time based on the time relationship function, to solve the problem that the existing injection mold simulation casting technology fails to obtain the optimal casting conditions from the casting conditions that have a greater impact on the ultra-thin shell, resulting in deformation of the ultra-thin shell of the injection-molded medical device.

[0005] To achieve the above object, in the first aspect, the present application provides a method for simulating the casting of an injection mold for an ultra-thin shell of a medical device, including the following steps:

[0006] Obtain the structural information of the ultra-thin shell of the medical device and the injection material for this time, and construct an initial simulation injection mold based on the structural information of the ultra-thin shell of the medical device;

[0007] Obtain a warpage data group, and the warpage data group includes: injection material temperature, injection pressure, and cooling time;

[0008] Under different conditions of the warpage data sets affecting the warpage, the initial simulation injection mold is simulated and cast using the current injection molding material, and the warpage deformation amount of the simulated ultra-thin shell of the medical device for each simulation casting is obtained, marked as the simulation warpage amount;

[0009] Analyze the relationship function between the injection melt temperature, injection pressure, and the simulation warpage amount, marked as the simulation relationship function;

[0010] Obtain the optimal injection melt temperature and optimal injection pressure based on the simulation relationship function;

[0011] Under the conditions of the optimal injection melt temperature and optimal injection pressure, the initial simulation injection mold is simulated and cast using the current injection molding material, and the warpage deformation amount of the simulated ultra-thin shell of the medical device for each simulation casting is obtained, marked as the time warpage amount;

[0012] Analyze the relationship function between the cooling time and the time warpage amount, marked as the time relationship function;

[0013] Obtain the optimal cooling time based on the time relationship function;

[0014] Output the optimal injection melt temperature, optimal injection pressure, and optimal cooling time, and perform actual casting based on the optimal injection melt temperature, optimal injection pressure, and optimal cooling time.

[0015] Furthermore, under different conditions of the warpage data sets affecting the warpage, the initial simulation injection mold is simulated and cast using the current injection molding material, and the warpage deformation amount of the simulated ultra-thin shell of the medical device for each simulation casting is obtained, marked as the simulation warpage amount, including the following sub-steps:

[0016] Obtain the range of the injection molding material temperature, marked as the injection temperature range;

[0017] Starting from the minimum value of the injection temperature range within the injection temperature range, obtain N1 injection molding material temperatures with an interval of a1, marked as the divided injection temperatures;

[0018] Obtain the range of the injection pressure, marked as the injection pressure range;

[0019] Starting from the minimum value of the injection pressure range within the injection pressure range, obtain N2 injection pressures with an interval of M2, marked as the divided injection pressures;

[0020] Combine one divided injection temperature and one divided injection pressure and mark it as the temperature and pressure combination; obtain all the temperature and pressure combinations;

[0021] Under the condition of a combination of temperature and pressure, the initial simulation injection mold is simulated and poured for the first number of times using the injection material of this time. After the first cooling time, the warpage deformation amount of the simulated medical device ultra-thin shell is obtained and marked as the simulation warpage amount.

[0022] Further, it is characterized in that the relationship function between the injection melt temperature, the injection pressure, and the simulation warpage amount is analyzed, and the simulation relationship function is marked as including the following sub-steps:

[0023] The simulation warpage amounts are sorted from small to large and marked as Fql 1 to Fql i ;

[0024] Calculate the first proportional value: Db1 = a1 * S1, where Db1 is the first proportional value, a1 is the first proportional coefficient, and the range of a1 is: [0, 0.5], and S1 is the first number;

[0025] If the first proportional value is an integer, mark Fql (Db1) as the first warpage value; if the first proportional value is not an integer, obtain the integers on both sides of Db1, marked as Db1z and Db1y respectively, and calculate the average value of Fql (Db1z) and Fql (Db1y) and mark it as the first warpage value;

[0026] Calculate the second proportional coefficient: a2 = [(1 / a1) - 1] * a1; where a2 is the second proportional coefficient;

[0027] Calculate the second proportional value: Db2 = a2 * S1, where Db2 is the second proportional value;

[0028] If the second proportional value is an integer, mark Fql (Db2) as the second warpage value; if the second proportional value is not an integer, obtain the integers on both sides of Db2, marked as Db2z and Db2y respectively, and calculate the average value of Fql (Db2z) and Fql (Db2y) and mark it as the second warpage value.

[0029] Further, the relationship function between the injection melt temperature, the injection pressure, and the simulation warpage amount is analyzed, and the simulation relationship function is marked as further including the following sub-steps:

[0030] Calculate the difference between the second warpage value and the first warpage value, and mark it as the warpage middle difference;

[0031] Calculate the first warpage threshold: Qy1 = Qq1 - b1 * Qz; where Qy1 is the first warpage threshold, Qq1 is the first warpage value, b1 is the threshold proportion coefficient, and Qz is the warpage middle difference;

[0032] The second warpage threshold is obtained as: Qy2 = Qq2 - b1 * Qz; where Qy2 is the second warpage threshold.

[0033] Furthermore, analyzing the relationship function among the injection molding melt temperature, injection molding pressure, and simulated warpage amount, marked as the simulation relationship function, further includes the following sub-steps:

[0034] Obtain the mean value of the simulated warpage amount between the second warpage value and the first warpage value, marked as the screened simulated warpage amount;

[0035] Obtain the screened simulated warpage amounts for all combinations of temperature and pressure;

[0036] Taking the divided injection molding temperature as the X-axis data, the divided injection molding pressure as the Y-axis data, and the screened simulated warpage amount as the Z-axis data, establish a three-dimensional coordinate system, marked as the data relationship coordinate system;

[0037] Taking the divided injection molding temperature and the divided injection molding pressure in the temperature and pressure combination as the X-axis data and the Y-axis data of the data relationship coordinate point respectively, and the corresponding screened simulated warpage amount as the Z-axis data of the data relationship coordinate point, plot all the relationship coordinate points in the data relationship coordinate system to obtain the relationship scatter plot;

[0038] Perform polynomial fitting on the relationship scatter plot to obtain the simulation relationship function.

[0039] Furthermore, obtaining the optimal injection molding melt temperature and the optimal injection molding pressure based on the simulation relationship function further includes the following sub-steps:

[0040] Obtain the divided injection molding temperature and the divided injection molding pressure corresponding to the minimum screened simulated warpage amount of the simulation relationship function, and mark them as the optimal injection molding melt temperature and the optimal injection molding pressure respectively.

[0041] Furthermore, under the conditions of the optimal injection molding melt temperature and the optimal injection molding pressure, use the injection molding material of this time to perform simulated pouring on the initial simulated injection mold, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell for each simulated pouring, marked as the time warpage amount, including the following sub-steps:

[0042] Under the conditions of the optimal injection molding melt temperature and the optimal injection molding pressure, use the injection molding material of this time to perform the second number of simulated pourings on the initial simulated injection mold, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell at the cooling times from T1 to Tk, marked as the time warpage amount; T1 to Tk are consecutive interval times starting from T1 seconds with an interval of c1 seconds, and mark T1 to Tk as Tj.

[0043] Furthermore, analyzing the relationship function between the cooling time and the time warpage amount, marked as the time relationship function, further includes the following sub-steps:

[0044] Taking the cooling time as the X-axis data and the time warping amount as the Y-axis data, a rectangular coordinate system is established and marked as the time relationship coordinate system;

[0045] Taking Tj and the corresponding time warping amount as the X-axis data and the Y-axis data of the time relationship coordinate points, all the time relationship coordinate points are plotted in the time relationship coordinate system to obtain a time scatter plot;

[0046] The time scatter plot is subjected to polynomial fitting to obtain a time relationship function.

[0047] Furthermore, obtaining the optimal cooling time based on the time relationship function includes the following steps:

[0048] On the time relationship function, v coordinate points starting from T1 with a horizontal coordinate interval of p are obtained and marked as time function coordinate points;

[0049] On the time function coordinate points, a tangent line of the time relationship function is drawn, marked as the time function tangent line, and the absolute value of the slope of the time function tangent line is obtained and marked as the time slope value;

[0050] The abscissa of the time function coordinate point corresponding to the minimum value of the time slope value is obtained and marked as the screened cooling time;

[0051] The minimum value of the screened cooling time is obtained and marked as the optimal cooling time.

[0052] In a second aspect, the present application also provides a simulation system for pouring an ultra-thin shell injection mold of a medical device, including a mold construction module, a related data acquisition module, a first simulation pouring module, a first function acquisition module, a first data acquisition module, a second simulation pouring module, a second function acquisition module, a second data acquisition module, and an optimal data execution module;

[0053] The mold construction module is used to obtain the structural information of the ultra-thin shell of the medical device and the injection molding material for this time, and construct an initial simulation injection mold based on the structural information of the ultra-thin shell of the medical device;

[0054] The related data acquisition module is used to obtain a set of warping data influencing factors, and the set of warping data influencing factors includes: injection molding material temperature, injection molding pressure, and cooling time;

[0055] The first simulation pouring module is used to perform simulation pouring on the initial simulation injection mold with the injection molding material for this time under different conditions of the set of warping data influencing factors, and obtain the warping deformation amount of the simulated ultra-thin shell of the medical device for each simulation pouring, marked as the simulated warping amount;

[0056] The first function acquisition module is used to analyze the relationship function between the injection molding melt temperature, the injection molding pressure, and the simulated warping amount, marked as the simulation relationship function;

[0057] The first data acquisition module is used to obtain the optimal plastic melt temperature and the optimal injection pressure based on the simulation relationship function;

[0058] The second simulation casting module is used to perform simulation casting on the initial simulation injection mold with the current injection material under the conditions of the optimal plastic melt temperature and the optimal injection pressure, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell for each simulation casting, marked as the time warpage amount;

[0059] The second function acquisition module is used to analyze the relationship function between the cooling time and the time warpage amount, marked as the time relationship function;

[0060] The second data acquisition module is used to obtain the optimal cooling time based on the time relationship function;

[0061] The optimal data execution module is used to output the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time, and perform actual casting based on the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time.

[0062] Advantages of the present invention: By analyzing the relationship function between the injection melt temperature, the injection pressure, and the simulation warpage amount, marked as the simulation relationship function, the present invention obtains the optimal plastic melt temperature and the optimal injection pressure based on the simulation relationship function, analyzes the relationship function between the cooling time and the time warpage amount, marked as the time relationship function, and obtains the optimal cooling time based on the time relationship function. The advantage is that through multiple experiments of simulation casting on the injection mold of the shell, the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time can be obtained, reducing the probability of deformation of the ultra-thin shell of the medical device during injection;

[0063] Advantages of the present invention: By analyzing the relationship function between the injection melt temperature, the injection pressure, and the simulation warpage amount, marked as the simulation relationship function, the advantage is that the relationship function between the injection melt temperature, the injection pressure, and the simulation warpage amount is analyzed through function fitting. The deformation of the shell is represented by the size of the simulation warpage amount. When the deformation of the shell is the smallest, the optimal plastic melt temperature and the optimal injection pressure are obtained, improving the injection molding quality. Description of the Drawings

[0064] Figure 1 is the principle block diagram of the system of the present invention;

[0065] Figure 2 is the schematic diagram of the simulation relationship function of the present invention;

[0066] Figure 3 is the schematic diagram of the time relationship function of the present invention;

[0067] Figure 4 is the schematic diagram of the tangent line of the time function of the present invention;

[0068] Figure 5 This is a flowchart of the steps of the method of the present invention. Specific embodiments

[0069] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0070] Example 1, please refer to Figure 1 As shown, the present application provides a simulation system for casting an ultra-thin shell injection mold of a medical device, including a mold construction module, a relevant data acquisition module, a first simulation casting module, a first function acquisition module, a first data acquisition module, a second simulation casting module, a second function acquisition module, a second data acquisition module, and an optimal data execution module;

[0071] The mold construction module is used to obtain the structural information of the ultra-thin shell of the medical device and the injection material for this time, and construct an initial simulation injection mold based on the structural information of the ultra-thin shell of the medical device;

[0072] The relevant data acquisition module is used to obtain a warpage data set, and the warpage data set includes: injection material temperature, injection pressure, and cooling time; where the units of injection material temperature, injection pressure, and cooling time are °C, MPa, and s respectively; the injection pressure is expressed as the holding pressure;

[0073] The first simulation casting module is used to perform simulation casting on the initial simulation injection mold with the injection material for this time under different warpage data set conditions, and obtain the warpage deformation amount of the simulated ultra-thin shell of the medical device for each simulation casting, marked as the simulated warpage amount; there are various choices for the injection material for this time, such as ASB material, and the unit of the simulated warpage amount is mm;

[0074] The first simulation casting module is configured with a first simulation casting strategy, and the first simulation casting strategy includes:

[0075] Obtain the range of the injection material temperature, marked as the injection temperature range;

[0076] Obtain N1 injection material temperatures with an interval of a1 starting from the minimum value of the injection temperature range within the injection temperature range, marked as the divided injection temperatures;

[0077] Obtain the range of the injection pressure, marked as the injection pressure range;

[0078] Obtain N2 injection pressures at intervals of M2 starting from the minimum value of the injection pressure range within the injection pressure range, and label them as divided injection pressures;

[0079] Combine a divided injection temperature with a divided injection pressure and label it as a temperature-pressure combination; Obtain all temperature-pressure combinations;

[0080] Under the condition of a temperature-pressure combination, use the current injection material to perform the first number of simulation pourings on the initial simulation injection mold, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell after the first cooling time, and label it as the simulated warpage amount; The first cooling time is set to any cooling time within the first cooling time range. For example, the range of the first cooling time is from 15s to 30s, and 22.5s is preferably selected; All these data ranges are the reference ranges of this material; The warpage deformation amount is the degree to which the shape of the injection molded product deviates from its designed shape due to various factors during the cooling and solidification process, and the value is obtained by software;

[0081] In practical applications, the obtained injection temperature range is from 220°C to 250°C, the divided injection temperatures are 220°C, 225°C,..., 245°C, and 250°C respectively, the injection pressure range is from 100MPa to 130MPa, and the divided injection pressures are 100MPa, 105MPa,..., 125MPa, and 130MPa respectively. For example, at a temperature-pressure combination of 220°C and 100MPa, the simulated warpage amount obtained after 22.5s is 3.863mm.

[0082] The first function acquisition module is used to analyze the relationship function among the injection melt temperature, injection pressure, and simulated warpage amount, and label it as the simulation relationship function;

[0083] The first function acquisition module is configured with a warpage value acquisition strategy, and the warpage value acquisition strategy includes:

[0084] Sort the simulated warpage amounts from smallest to largest and label them as Fql 1 to Fql i ;

[0085] Calculate the first proportional value as: Db1 = a1 * S1, where Db1 is the first proportional value, a1 is the first proportional coefficient, and the range of a1 is: [0, 0.5], and S1 is the first number; The first warpage value selects the values distributed in the smaller half area. Therefore, a1 is set within the range of 0 to 0.5, and a middle value can be selected, which can ensure that the selected first warpage value has the representativeness of the smaller half area, preferably 0.25;

[0086] If the first proportional value is an integer, then Fql (Db1)Marked as the first warpage value; if the first ratio value is not an integer, obtain the integers on both sides of Db1, marked as Db1z and Db1y respectively, and calculate Fql (Db1z) and Fql (Db1y) The mean value of is marked as the first warpage value;

[0087] Calculate the second proportional coefficient as: a2 = [(1 / a1) - 1] * a1; where a2 is the second proportional coefficient;

[0088] Calculate the second ratio value as: Db2 = a2 * S1, where Db2 is the second ratio value;

[0089] If the second ratio value is an integer, mark Fql (Db2) as the second warpage value; if the second ratio value is not an integer, obtain the integers on both sides of Db2, marked as Db2z and Db2y respectively, and calculate Fql (Db2z) and Fql (Db2y) The mean value of is marked as the second warpage value;

[0090] In practical applications, for example, at a temperature and pressure combination of 220°C and 100 MPa, after 22.5 s, the first quantity of 20 simulated warpage amounts are obtained, which are 3.663 mm, 3.752 mm,..., 3.863 mm, and 3.889 mm respectively; calculate the first ratio value as: Db1 = 0.25 * 20 = 5, the first ratio value is an integer, mark Fql (5) = 3.682 mm as the first warpage value, calculate the second proportional coefficient as: a2 = [(1 / a1) - 1] * a1 = 0.75, calculate the second ratio value as: Db2 = 0.75 * 20 = 15, the second ratio value is an integer, mark Fql (20) = 3.866 mm as the second warpage value.

[0091] The first function acquisition module is configured with a warpage threshold acquisition strategy, and the warpage threshold acquisition strategy includes:

[0092] Calculate the difference between the second warpage value and the first warpage value, and mark it as the warpage intermediate difference;

[0093] Calculate the first warpage threshold as: Qy1 = Qq1 - b1 * Qz; where Qy1 is the first warpage threshold, Qq1 is the first warpage value, b1 is the threshold ratio coefficient, and Qz is the warpage intermediate difference; set b1 based on the actual simulated warpage amount distribution, the range of b1 is between 0 and 1, the more concentrated the actual simulated warpage amount, the smaller b1, the more dispersed the actual simulated warpage amount, the larger b1. Because the pouring conditions are the same, the actual simulated warpage amount is relatively concentrated, for example, set to 0.3;

[0094] Calculate the second warpage threshold as: Qy2 = Qq2 - b1 * Qz; where Qy2 is the second warpage threshold;

[0095] In practical applications, the intermediate warpage difference is obtained as: 3.866 - 3.682 = 0.184. The first warpage threshold is obtained as: Qy1 = 3.682 - 0.3 * 0.184 = 3.625 mm. The second warpage threshold is obtained as: Qy2 = 3.866 - 0.3 * 0.184 = 3.941 mm. The calculation results are retained to three decimal places.

[0096] The first function acquisition module is configured with a first function acquisition strategy, and the first function acquisition strategy includes:

[0097] Obtain the average value of the simulated warpage amounts between the second warpage value and the first warpage value, and mark it as the screened simulated warpage amount;

[0098] Obtain the screened simulated warpage amounts for all temperature and pressure combinations;

[0099] Using the divided injection temperature as the X-axis data, the divided injection pressure as the Y-axis data, and the screened simulated warpage amount as the Z-axis data, establish a three-dimensional coordinate system, and mark it as the data relationship coordinate system;

[0100] Take the divided injection temperature and the divided injection pressure in the temperature and pressure combination as the X-axis data and the Y-axis data of the data relationship coordinate point respectively, and the corresponding screened simulated warpage amount as the Z-axis data of the data relationship coordinate point. Plot all the relationship coordinate points in the data relationship coordinate system to obtain a relationship scatter plot;

[0101] Perform polynomial fitting on the relationship scatter plot to obtain a simulated relationship function.

[0102] In practical applications, for example, if the average value of the simulated warpage amounts between 3.625 mm and 3.941 mm is 3.782 mm, then the screened simulated warpage amount is 3.782 mm, and a data relationship coordinate point is (220, 100, 3.782). Perform polynomial fitting on the relationship scatter plot to obtain a simulated relationship function. Please refer to Figure 2 as shown, the plotted simulated relationship function;

[0103] The first data acquisition module is used to obtain the optimal melt temperature and the optimal injection pressure based on the simulated relationship function;

[0104] The first data acquisition module is configured with a first data acquisition strategy, and the first data acquisition strategy includes:

[0105] Obtain the divided injection temperature and the divided injection pressure corresponding to the minimum screened simulated warpage amount of the simulated relationship function, and mark them as the optimal melt temperature and the optimal injection pressure respectively;

[0106] In practical applications, please refer to Figure 2As shown, observe the graph of the plotted simulation relationship function, and obtain that the optimal plastic melt temperature and the optimal injection pressure corresponding to the minimum screening simulation warpage amount are 243°C and 119 MPa respectively. Round the obtained data to the nearest integer. If there is a group with the minimum divided injection temperature and the minimum divided injection pressure when the screening simulation warpage amount is the smallest, use this group as the optimal plastic melt temperature and the optimal injection pressure;

[0107] The second simulation casting module is used to perform simulation casting on the initial simulation injection mold with the current injection material under the conditions of the optimal plastic melt temperature and the optimal injection pressure, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell for each simulation casting, which is marked as the time warpage amount;

[0108] The second simulation casting module is configured with a second simulation casting strategy, and the second simulation casting strategy includes:

[0109] Under the conditions of the optimal plastic melt temperature and the optimal injection pressure, perform a second number of simulation castings on the initial simulation injection mold with the current injection material, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell at the cooling times from T1 to Tk, which is marked as the time warpage amount; T1 to Tk are consecutive interval times starting from T1 seconds with an interval of c1 seconds, and T1 to Tk are marked as Tj; T1 is set as the minimum value of the range based on the first cooling time, and the range of the first cooling time is 15 s to 30 s, so T1 is 15;

[0110] The second function acquisition module is used to analyze the relationship function between the cooling time and the time warpage amount, which is marked as the time relationship function;

[0111] The second function acquisition module is configured with a second function acquisition strategy, and the second function acquisition strategy includes:

[0112] Take the cooling time as the X-axis data and the time warpage amount as the Y-axis data to establish a plane rectangular coordinate system, which is marked as the time relationship coordinate system;

[0113] Use Tj and the corresponding time warpage amount as the X-axis data and the Y-axis data of the time relationship coordinate points, and plot all the time relationship coordinate points in the time relationship coordinate system to obtain a time scatter plot;

[0114] Perform polynomial fitting on the time scatter plot to obtain the time relationship function;

[0115] In practical applications, T1 to Tk are 15, 17, 19,..., 27 and 29 respectively. Please refer to Figure 3 As shown, plot the time scatter plot, perform polynomial fitting on the time scatter plot to obtain the time relationship function and the graph of the time relationship function.

[0116] Taking the cooling time as the X-axis data and the time warping amount as the Y-axis data, a rectangular coordinate system is established and marked as the time relationship coordinate system.

[0117] The second data acquisition module is used to obtain the optimal cooling time based on the time relationship function.

[0118] The second data acquisition module is configured with a second data acquisition strategy, and the second data acquisition strategy includes:

[0119] On the time relationship function, obtain v coordinate points with T1 as the starting point and ps as the abscissa interval, and mark them as time function coordinate points; the setting of v is based on the maximum value that can be set within the range of the first cooling time. For example, if p is 2s and the range of the first cooling time is 15s to 30s, then v is 8.

[0120] Draw a tangent line of the time relationship function at the time function coordinate points, mark it as the time function tangent line, and obtain the absolute value of the slope of the time function tangent line, marked as the time slope value.

[0121] Obtain the abscissa of the time function coordinate point corresponding to the minimum value of the time slope value, and mark it as the optimal cooling time.

[0122] In practical applications, please participate Figure 4 As shown, on the time relationship function, obtain 8 coordinate points with 15 as the starting point and 2 as the abscissa interval, mark them as time function coordinate points, the optimal cooling time is 23.5s, and the obtained data is reserved to one decimal place. If there are multiple minimum values of the time slope value at the same time, select the one with the smallest abscissa of the time function coordinate point as the optimal cooling time.

[0123] The optimal data execution module is used to output the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time, and perform real casting based on the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time.

[0124] The output optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time are 243°C, 119 MPa, and 23.5 s respectively. Using the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time for real casting reduces the deformation of the ultra-thin outer shell of the medical device being injection-molded.

[0125] Example 2, please refer to Figure 5 As shown, the present application provides a simulation method for casting an ultra-thin outer shell of a medical device injection mold, including the following steps:

[0126] Step S1, obtain the structural information of the ultra-thin outer shell of the medical device and the injection material for this time, and construct an initial simulation injection mold based on the structural information of the ultra-thin outer shell of the medical device.

[0127] Step S2, obtain the warpage influencing data group, which includes: injection material temperature, injection pressure, and cooling time.

[0128] Step S3, under different conditions of the warpage influencing data group, use the current injection material to perform simulation casting on the initial simulation injection mold, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell for each simulation casting, marked as the simulated warpage amount; Step S3 includes the following sub-steps:

[0129] Step S301, obtain the range of the injection material temperature, marked as the injection temperature range;

[0130] Step S302, starting from the minimum value of the injection temperature range within the injection temperature range, obtain N1 injection material temperatures with an interval of a1, marked as the divided injection temperatures;

[0131] Step S303, obtain the range of the injection pressure, marked as the injection pressure range;

[0132] Step S304, starting from the minimum value of the injection pressure range within the injection pressure range, obtain N2 injection pressures with an interval of M2, marked as the divided injection pressures;

[0133] Step S305, combine a divided injection temperature and a divided injection pressure and mark it as the temperature and pressure combination; obtain all the temperature and pressure combinations;

[0134] Step S306, under the condition of a temperature and pressure combination, use the current injection material to perform the first number of simulation castings on the initial simulation injection mold, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell after the first cooling time, marked as the simulated warpage amount.

[0135] Step S4, analyze the relationship function among the injection melt temperature, injection pressure, and simulated warpage amount, marked as the simulation relationship function; Step S4 includes the following sub-steps:

[0136] Step S401, sort the simulated warpage amounts from smallest to largest and mark them as Fql 1 to Fql i ;

[0137] Step S402, calculate the first proportional value: Db1 = a1 * S1, where Db1 is the first proportional value, a1 is the first proportional coefficient, and the range of a1 is: [0, 0.5], and S1 is the first number;

[0138] Step S403, if the first proportional value is an integer, then Fql (Db1)Marked as the first warpage value; if the first ratio value is not an integer, obtain the integers on both sides of Db1, marked as Db1z and Db1y respectively, and calculate Fql (Db1z) and Fql (Db1y) Take the mean value of, and mark it as the first warpage value;

[0139] Step S404, calculate the second proportional coefficient as: a2 = [(1 / a1) - 1] * a1; where a2 is the second proportional coefficient;

[0140] Step S405, calculate the second ratio value as: Db2 = a2 * S1, where Db2 is the second ratio value;

[0141] Step S406, if the second ratio value is an integer, mark Fql (Db2) as the second warpage value; if the second ratio value is not an integer, obtain the integers on both sides of Db2, marked as Db2z and Db2y respectively, and calculate Fql (Db2z) and Fql (Db2y) Take the mean value of, and mark it as the second warpage value;

[0142] Step S407, calculate the difference between the second warpage value and the first warpage value, and mark it as the intermediate warpage difference;

[0143] Step S408, calculate the first warpage threshold as: Qy1 = Qq1 - b1 * Qz; where Qy1 is the first warpage threshold, Qq1 is the first warpage value, and Qz is the intermediate warpage difference;

[0144] Step S409, calculate the second warpage threshold as: Qy2 = Qq2 - b1 * Qz; where Qy2 is the second warpage threshold;

[0145] Step S410, obtain the mean value of the simulation warpage amount between the second warpage value and the first warpage value, and mark it as the screened simulation warpage amount;

[0146] Step S411, obtain the screened simulation warpage amounts for all temperature and pressure combinations;

[0147] Step S412, use the divided injection temperature as the X-axis data, the divided injection pressure as the Y-axis data, and the screened simulation warpage amount as the Z-axis data to establish a three-dimensional coordinate system, marked as the data relationship coordinate system;

[0148] Step S413, use the divided injection temperature and the divided injection pressure in the temperature and pressure combination as the X-axis data and the Y-axis data of the data relationship coordinate point respectively, and the corresponding screened simulation warpage amount as the Z-axis data of the data relationship coordinate point, and plot all the relationship coordinate points in the data relationship coordinate system to obtain the relationship scatter plot;

[0149] Step S414: Perform polynomial fitting on the relationship scatter plot to obtain a simulation relationship function.

[0150] Step S5: Obtain the optimal plastic melt temperature and the optimal injection pressure based on the simulation relationship function. Step S5 includes the following sub-steps:

[0151] Step S501: Obtain the divided injection temperature and the divided injection pressure corresponding to the minimum screened simulation warpage amount of the simulation relationship function, and mark them as the optimal plastic melt temperature and the optimal injection pressure respectively.

[0152] Step S6: Under the conditions of the optimal plastic melt temperature and the optimal injection pressure, perform simulation pouring on the initial simulation injection mold using the injection material for this time, and obtain the warpage deformation amount of the simulated medical device ultra-thin shell for each simulation pouring, marked as the time warpage amount. Step S6 includes the following sub-steps:

[0153] Step S601: Under the conditions of the optimal plastic melt temperature and the optimal injection pressure, perform a second number of simulation pourings on the initial simulation injection mold using the injection material for this time. Obtain the warpage deformation amount of the simulated medical device ultra-thin shell when the cooling times are from T1 to Tk, marked as the time warpage amount; T1 to Tk are consecutive interval times starting from T1 seconds with an interval of c1 seconds, and mark T1 to Tk as Tj.

[0154] Step S7: Analyze the relationship function between the cooling time and the time warpage amount, marked as the time relationship function. Step S7 includes the following sub-steps:

[0155] Step S701: Establish a plane rectangular coordinate system with the cooling time as the X-axis data and the time warpage amount as the Y-axis data, marked as the time relationship coordinate system.

[0156] Step S702: Use Tj and the corresponding time warpage amount as the X-axis data and the Y-axis data of the time relationship coordinate points, and plot all the time relationship coordinate points in the time relationship coordinate system to obtain a time scatter plot.

[0157] Step S703: Perform polynomial fitting on the time scatter plot to obtain the time relationship function.

[0158] Step S8: Obtain the optimal cooling time based on the time relationship function. Step S8 includes the following sub-steps:

[0159] Step S801: Obtain v coordinate points on the time relationship function starting from T1 with a horizontal coordinate interval of p, marked as time function coordinate points.

[0160] Step S802: Draw a tangent line of the time relationship function at the time function coordinate points, marked as the time function tangent line, and obtain the absolute value of the slope of the time function tangent line, marked as the time slope value.

[0161] Step S803: Obtain the abscissa of the coordinate point of the time function corresponding to the minimum value of the time slope, and mark it as the screened cooling time.

[0162] Step S9: Output the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time, and perform actual pouring based on the optimal plastic melt temperature, the optimal injection pressure, and the optimal cooling time.

[0163] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, abbreviated as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, abbreviated as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, abbreviated as EPROM), programmable read-only memory (Programmable Red-Only Memory, abbreviated as PROM), read-only memory (Read-OnFqlemory, abbreviated as ROM), magnetic memory, flash memory, magnetic disk or optical disc. These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device implements the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 in one block or multiple blocks.

[0164] In the embodiments provided in the present application, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

Claims

1. A method for simulating casting of an ultra-thin shell injection mold for medical devices, characterized in that: The steps include: Obtaining structural information of the ultra-thin shell of the medical device and the injection molding material, and constructing an initial simulation injection mold based on the structural information of the ultra-thin shell of the medical device; Acquire a data group affecting warpage, the data group affecting warpage includes: injection material temperature, injection pressure and cooling time; Under different conditions affecting the warpage data groups, the initial simulated injection mold is simulated cast using the injection molding material, and the warpage deformation amount of the simulated medical device ultra-thin shell in each simulated casting is obtained, which is marked as the simulated warpage amount; Analyze the relationship function between injection melt temperature, injection pressure and simulated warpage, and mark it as simulation relationship function; Obtain the optimal melt temperature and injection pressure based on the simulation relationship function; Under the conditions of the optimal melt temperature and the optimal injection pressure, the initial simulated injection mold is simulated cast using the injection molding material, and the warping deformation of the simulated medical device ultra-thin shell in each simulated casting is obtained, which is marked as the time warping amount; Analyze the relationship function between cooling time and time warping, and mark it as time relationship function; Obtain the optimal cooling time based on the time relationship function; Output the optimal melt temperature, injection pressure and cooling time, and perform real pouring based on the optimal melt temperature, injection pressure and cooling time.

2. A method for simulating casting of an ultra-thin shell injection mold for medical devices according to claim 1, characterized in that: Under different conditions affecting the warpage data group, the initial simulated injection mold is simulated cast using the injection molding material, and the warpage deformation amount of the simulated medical device ultra-thin shell of each simulated casting is obtained, which is marked as the simulated warpage amount and includes the following sub-steps: Get the range of injection material temperature, marked as injection temperature range; Obtain N1 injection material temperatures with an interval of a1 within the injection temperature range starting from the minimum value of the injection temperature range, and mark them as divided injection temperatures; Get the range of injection pressure, marked as injection pressure range; Obtain N2 injection pressures with an interval of M2 within the injection pressure range starting from the minimum value of the injection pressure range, and mark them as divided injection pressures; Combine a divided injection temperature and a divided injection pressure and mark them as a temperature and pressure combination; obtain all temperature and pressure combinations; Under a combination of temperature and pressure, the initial simulated injection mold is simulated cast for a first number of times using the injection molding material, and the warping deformation of the simulated ultra-thin shell of the medical device is obtained after the first cooling time, which is marked as the simulated warping amount.

3. A method for simulating casting of an injection mold for an ultra-thin housing of a medical device according to claim 2, characterized in that The relationship function between the injection melt temperature, injection pressure and the simulated warpage is analyzed and marked as the simulation relationship function, which includes the following sub-steps: The simulated warpage is sorted from small to large and marked as Fql1 to Fql i ; The first proportional value is obtained as follows: Db1 = a1*S1, where Db1 is the first proportional value, a1 is the first proportional coefficient, the range of a1 is: [0, 0.5], and S1 is the first quantity; If the first ratio value is an integer, Fql (Db1) Marked as the first warp value; if the first ratio value is not an integer, obtain the integers on the left and right sides of Db1, marked as Db1z and Db1y respectively, and calculate Fql (Db1z) With Fql (Db1y) The mean of , marked as the first warping value; The second proportional coefficient is obtained as follows: a2 = [(1 / a1) - 1] * a1; wherein a2 is the second proportional coefficient; The second proportional value is obtained as follows: Db2 = a2*S1, where Db2 is the second proportional value; If the second ratio value is an integer, Fql (Db2) Marked as the second warp value; if the second ratio value is not an integer, obtain the integers on the left and right sides of Db2, marked as Db2z and Db2y respectively, and calculate Fql (Db2z) With Fql (Db2y) The mean of , marked as the second warping value.

4. A method for simulating casting of an ultra-thin shell injection mold for medical devices according to claim 3, characterized in that: The relationship function between the injection melt temperature, injection pressure and the simulated warpage is analyzed, and the simulation relationship function is also marked as the simulation relationship function, which includes the following sub-steps: Calculate the difference between the second warpage value and the first warpage value, and mark it as the warpage middle difference; The first warping threshold is obtained as: Qy1 = Qq1-b1*Qz; Where Qy1 is the first warping threshold, Qq1 is the first warping value, b1 is the threshold ratio, and Qz is the warping middle difference; The second warping threshold is obtained as: Qy2=Qq2-b1*Qz; wherein Qy2 is the second warping threshold.

5. A method for simulating casting of an ultra-thin shell injection mold for medical devices according to claim 4, characterized in that: The relationship function between the injection melt temperature, injection pressure and the simulated warpage is analyzed, and the simulation relationship function is also marked as the simulation relationship function, which includes the following sub-steps: Obtaining an average of the simulated warpage values ​​between the second warpage value and the first warpage value, and marking the average as the screened simulated warpage value; Get the screening simulation warpage for all temperature and pressure combinations; The injection temperature is divided into X-axis data, the injection pressure is divided into Y-axis data, and the simulated warpage is selected as Z-axis data to establish a three-dimensional coordinate system, which is marked as the data relationship coordinate system; The divided injection temperature and the divided injection pressure in the temperature and pressure combination are respectively used as the X-axis data and the Y-axis data of the data relationship coordinate point, and the corresponding screening simulation warpage amount is used as the Z-axis data of the data relationship coordinate point. All the relationship coordinate points are plotted in the data relationship coordinate system to obtain a relationship scatter plot; The relationship scatter plot is fitted with a polynomial to obtain the simulation relationship function.

6. A method for simulating casting of an ultra-thin shell injection mold for medical devices according to claim 5, characterized in that: Obtaining the optimal melt temperature and injection pressure based on the simulation relationship function also includes the following sub-steps: The divided injection temperature and divided injection pressure corresponding to the simulation relationship function when the screening simulation warpage amount is minimized are obtained, and are marked as the optimal melt temperature and the optimal injection pressure, respectively.

7. A method for simulating casting of an injection mold for an ultra-thin housing of a medical device according to claim 6, characterized in that Under the conditions of optimal melt temperature and optimal injection pressure, the initial simulated injection mold is simulated cast using the injection molding material, and the warping deformation of the simulated medical device ultra-thin shell of each simulated casting is obtained, which is marked as the time warping amount and includes the following sub-steps: Under the conditions of optimal melt temperature and optimal injection pressure, the initial simulated injection mold is cast for the second number of simulated casts using the injection molding material. The warping deformation of the simulated ultra-thin shell of the medical device is obtained when the cooling time is T1 to Tk, which is marked as the time warping amount; T1 to Tk is a continuous interval time starting from T1 second and with an interval of c1 second, and T1 to Tk is marked as Tj.

8. A method for simulating casting of an ultra-thin shell injection mold for medical devices according to claim 7, characterized in that: Analyzing the relationship function between the cooling time and the time warping amount, which is marked as the time relationship function, also includes the following sub-steps: With cooling time as X-axis data and time warping as Y-axis data, a plane rectangular coordinate system is established, marked as the time relationship coordinate system; Taking Tj and the corresponding time warp as the X-axis data and Y-axis data of the time relationship coordinate point, all the time relationship coordinate points are plotted in the time relationship coordinate system to obtain a time scatter plot; The time relationship function was obtained by fitting the time scatter plot with a polynomial.

9. A method for simulating casting of an injection mold for an ultra-thin housing of a medical device according to claim 8, characterized in that: Obtaining the optimal cooling time based on the time relationship function includes the following steps: On the time relationship function, obtain v coordinate points starting from T1 and with p as the horizontal coordinate interval, and mark them as time function coordinate points; Draw a tangent line of the time relationship function at the time function coordinate point, mark it as the time function tangent line, obtain the absolute value of the slope of the time function tangent line, mark it as the time slope value; Get the horizontal coordinate of the time function coordinate point corresponding to the minimum time slope value, and mark it as the screening cooling time.

10. A medical device ultra-thin shell injection mold casting simulation system, used to implement a medical device ultra-thin shell injection mold casting simulation method according to any one of claims 1 to 9, characterized in that: It includes a mold construction module, a related data acquisition module, a first simulation casting module, a first function acquisition module, a first data acquisition module, a second simulation casting module, a second function acquisition module, a second data acquisition module, and an optimal data execution module; The mold construction module is used to obtain the structural information of the ultra-thin shell of the medical device and the injection material of this time, and to construct an initial simulation injection mold based on the structural information of the ultra-thin shell of the medical device; The relevant data acquisition module is used to acquire a data group affecting warpage, wherein the data group affecting warpage includes: injection material temperature, injection pressure and cooling time; The first simulation casting module is used to simulate casting of the initial simulation injection mold using the injection molding material under different conditions affecting the warping data group, and obtain the warping deformation amount of the simulated medical device ultra-thin shell in each simulation casting, which is marked as the simulated warping amount; The first function acquisition module is used to analyze the relationship function between the injection melt temperature, the injection pressure and the simulated warpage, which is marked as a simulation relationship function; The first data acquisition module is used to obtain the optimal plastic melt temperature and the optimal injection pressure based on the simulation relationship function; The second simulation casting module is used to simulate casting the initial simulation injection mold with the current injection molding material under the conditions of the optimal plastic melt temperature and the optimal injection pressure, and obtain the warping deformation amount of the simulated medical device ultra-thin shell in each simulation casting, which is marked as the time warping amount; The second function acquisition module is used to analyze the relationship function between the cooling time and the time warping amount, which is marked as the time relationship function; The second data acquisition module is used to obtain the optimal cooling time based on the time relationship function; The optimal data execution module is used to output the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time, and perform real pouring based on the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time.

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