A medical instrument ultra-thin shell injection mold pouring simulation method and system

Abstract

The application discloses a kind of medical instrument ultra-thin shell injection mold pouring simulation method and system, it is related to injection mold simulation pouring technical field, including the following steps: by analyzing the relationship function between injection melt temperature, injection pressure and simulation warping amount, marked as simulation relationship function, based on simulation relationship function to obtain optimal plastic melt temperature and optimal injection pressure, the relationship function of cooling time and time warping amount is analyzed, marked as time relationship function, based on time relationship function to obtain optimal cooling time;Output optimal plastic melt temperature, optimal injection pressure and optimal cooling time, based on optimal plastic melt temperature, optimal injection pressure and optimal cooling time to carry out real pouring;The present application is used to solve the problem that the optimal pouring condition cannot be obtained from the pouring condition that has greater influence on ultra-thin shell in the existing injection mold simulation pouring technology, resulting in the deformation of the ultra-thin shell of the injection molded medical device.

Description

TECHNICAL FIELD

[0001] The application relates to an injection mold simulation pouring technology field, in particular to a medical instrument ultra-thin shell injection mold pouring simulation method and system. BACKGROUND

[0002] The pouring of an injection mold is a process of introducing a plastic melt into a cavity through a pouring system of the mold, and filling, cooling and solidifying the plastic melt in the cavity to finally form a required plastic product. The design and optimization of the pouring have a crucial influence on the quality, production efficiency and cost of the plastic product. Then, the pouring to be optimized needs to be continuously poured to determine the pouring quality. At this time, the multiple pouring will cause waste of resources. Therefore, an injection mold pouring simulation method is provided.

[0003] For the pouring of an injection mold of a medical instrument ultra-thin shell, because the ultra-thin shell requires an accurate pouring model, and attention should also be paid to pouring conditions, specifically the temperature of the injection material pouring, the pressure of the injection and the cooling time. If the pouring conditions are unqualified, the ultra-thin shell will be deformed. For example, in a patent application with the application number CN117574695A, a kind of injection mold simulation pouring method, system and medium are disclosed. The scheme is to adjust the injection mold, and the pouring conditions that greatly affect the ultra-thin shell are ignored. That is, the existing injection mold simulation pouring technology cannot obtain the optimal pouring condition from the pouring conditions that greatly affect the ultra-thin shell, resulting in deformation of the injection molded medical instrument ultra-thin shell. SUMMARY

[0004] The application aims to at least solve one of the technical problems in the prior art. By analyzing the relationship function between the injection melt temperature, the injection pressure and the simulation warping amount, which is marked as a simulation relationship function, the optimal plastic melt temperature and the optimal injection pressure are obtained based on the simulation relationship function. The relationship function between the cooling time and the time warping amount is analyzed, which is marked as a time relationship function. The optimal cooling time is obtained based on the time relationship function. The problem that the existing injection mold simulation pouring technology cannot obtain the optimal pouring condition from the pouring conditions that greatly affect the ultra-thin shell, resulting in deformation of the injection molded medical instrument ultra-thin shell, is solved.

[0005] To achieve the above-mentioned purpose, in a first aspect, the application provides a medical instrument ultra-thin shell injection mold pouring simulation method, comprising the following steps:

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

[0007] Obtain the influence warping data set, which includes the injection material temperature, the injection pressure and the cooling time;

[0008] Simulate pouring of the initial simulation injection mold with the injection material under different conditions of affecting warping data sets, and obtain the warping deformation amount of the simulation medical instrument ultra-thin shell of each simulation pouring, marked as simulation warping amount;

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

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

[0011] Simulate pouring of the initial simulation injection mold with the injection material under the conditions of the optimal melt temperature and the optimal injection pressure, and obtain the warping deformation amount of the simulation medical instrument ultra-thin shell of each simulation pouring, marked as time warping amount;

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

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

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

[0015] Further, simulate pouring of the initial simulation injection mold with the injection material under different conditions of affecting warping data sets, and obtain the warping deformation amount of the simulation medical instrument ultra-thin shell of each simulation pouring, marked as simulation warping amount, including the following sub-steps:

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

[0017] Obtain N1 injection material temperatures with an interval of a1 from the minimum value of the injection temperature range in the injection temperature range, marked as divided injection temperature;

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

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

[0020] Combine one divided injection temperature with one divided injection pressure, marked as temperature and pressure combination; and obtain all temperature and pressure combinations;

[0021] The initial simulation injection mold is simulated to be poured for a first number of times by using the injection material under a temperature and pressure combination, and a warping deformation amount of the simulation medical device ultra-thin shell is obtained after a first cooling time, and is marked as a simulation warping amount.

[0022] Further, a relationship function among the injection melt temperature, the injection pressure and the simulation warping amount is analyzed, and is marked as a simulation relationship function, and includes the following sub-steps:

[0023] The simulation warping amounts are sorted from small to large, and are marked as Fql1 to Fql i ;

[0024] A first proportion value is Db1=a1*S1, where Db1 is the first proportion value, a1 is a first proportion coefficient, a1 is in a range of [0, 0.5], and S1 is the first number;

[0025] If the first proportion value is an integer, Fql (Db1) is marked as a first warping value; if the first proportion value is not an integer, integers on the left and right sides of Db1 are obtained, and are marked as Db1z and Db1y respectively, Fql (Db1z) and Fql (Db1y) are averaged, and are marked as the first warping value;

[0026] A second proportion coefficient is a2=[(1 / a1)-1]*a1, where a2 is the second proportion coefficient;

[0027] A second proportion value is Db2=a2*S1, where Db2 is the second proportion value;

[0028] If the second proportion value is an integer, Fql (Db2) is marked as a second warping value; if the second proportion value is not an integer, integers on the left and right sides of Db2 are obtained, and are marked as Db2z and Db2y respectively, Fql (Db2z) and Fql (Db2y) are averaged, and are marked as the second warping value.

[0029] Further, a relationship function among the injection melt temperature, the injection pressure and the simulation warping amount is analyzed, and is marked as a simulation relationship function, and includes the following sub-steps:

[0030] A difference value between the second warping value and the first warping value is obtained, and is marked as a warping intermediate difference value;

[0031] A first warping threshold value is Qy1=Qq1-b1*Qz, where Qy1 is the first warping threshold value, Qq1 is the first warping value, b1 is a threshold proportion coefficient, and Qz is the warping intermediate difference value;

[0032] The second warping threshold is calculated as: Qy2=Qq2-b1*Qz; wherein Qy2 is the second warping threshold.

[0033] Further, the relationship function among the injection melt temperature, the injection pressure and the simulation warping amount is analyzed, and is marked as a simulation relationship function, and further includes the following sub-steps:

[0034] An average value of the simulation warping amount between the second warping value and the first warping value is obtained, and is marked as a screening simulation warping amount.

[0035] The screening simulation warping amount of all temperature and pressure combinations is obtained.

[0036] A three-dimensional coordinate system is established with the divided injection temperature as the X-axis data, the divided injection pressure as the Y-axis data, and the screening simulation warping amount as the Z-axis data, and is marked as a data relationship coordinate system.

[0037] The divided injection temperature and the divided injection pressure in the temperature and pressure combination are respectively taken as the X-axis data and the Y-axis data of the data relationship coordinate point, and the corresponding screening simulation warping amount is taken as the Z-axis data of the data relationship coordinate point. All relationship coordinate points are plotted in the data relationship coordinate system to obtain a relationship scatter plot.

[0038] The relationship scatter plot is polynomially fitted to obtain a simulation relationship function.

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

[0040] The divided injection temperature and the divided injection pressure corresponding to the minimum screening simulation warping amount of the simulation relationship function are obtained, and are respectively marked as the optimal melt temperature and the optimal injection pressure.

[0041] Further, under the conditions of the optimal melt temperature and the optimal injection pressure, the initial simulation injection mold is simulated and poured with the injection material, and the warping deformation amount of the simulation medical instrument ultra-thin shell of each simulation pouring is obtained, and is marked as a time warping amount, including the following sub-steps:

[0042] Under the conditions of the optimal melt temperature and the optimal injection pressure, the initial simulation injection mold is simulated and poured with the injection material for a second number of times, and the warping deformation amount of the simulation medical instrument ultra-thin shell is obtained at cooling times T1 to Tk, and is marked as a time warping amount; T1 to Tk are continuous interval times starting from T1 seconds with an interval of c1 seconds, and T1 to Tk are marked as Tj.

[0043] Further, the relationship function between the cooling time and the time warping amount is analyzed, and is marked as a time relationship function, and further includes the following sub-steps:

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

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

[0046] The time relationship function is obtained by polynomial fitting of the time scatter plot.

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

[0048] v coordinate points are obtained on the time relationship function with T1 as the starting point and p as the horizontal coordinate interval, and are marked as time function coordinate points;

[0049] The tangent line of the time relationship function is plotted on the time function coordinate points, which is marked as a time function tangent line, and the absolute value of the slope of the time function tangent line is obtained, which is marked as a time slope value;

[0050] The horizontal coordinate of the time function coordinate point corresponding to the minimum value of the time slope value is obtained, which is marked as a screened cooling time;

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

[0052] In a second aspect, the application also provides a medical instrument ultra-thin shell injection mold pouring simulation system, which comprises 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 structure information of the medical instrument ultra-thin shell and the injection material for this time, and to construct an initial simulation injection mold based on the structure information of the medical instrument ultra-thin shell.

[0054] The related data acquisition module is used to obtain an influence warping data group, which includes the injection material temperature, the injection pressure, and the cooling time.

[0055] The first simulation pouring module is used to simulate pouring of the initial simulation injection mold with the injection material for this time under different influence warping data group conditions, and to obtain the warping deformation amount of the simulated medical instrument ultra-thin shell for each simulation pouring, which is marked as a simulation warping amount.

[0056] The first function acquisition module is used to analyze the relationship function among the injection melt temperature, the injection pressure, and the simulation warping amount, which is marked as a simulation relationship function.

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

[0058] The second simulation pouring module is used for simulating pouring of the initial simulation injection mold by using the injection material of this time under the conditions of the optimal plastic melt temperature and the optimal injection pressure, and acquiring the warping deformation amount of the simulation medical instrument ultra-thin shell of each simulation pouring, which is marked as a time warping amount;

[0059] The second function acquisition module is used for analyzing the relationship function of the cooling time and the time warping amount, which is marked as a time relationship function;

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

[0061] The optimal data execution module is used for outputting the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time, and performing real pouring based on the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time.

[0062] The present application has the following advantages: the present application analyzes the relationship function among the injection melt temperature, the injection pressure and the simulation warping amount, which is marked as a simulation relationship function, acquires the optimal plastic melt temperature and the optimal injection pressure based on the simulation relationship function, analyzes the relationship function of the cooling time and the time warping amount, which is marked as a time relationship function, acquires the optimal cooling time based on the time relationship function, and has the advantage that the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time can be acquired through simulation pouring experiments of the shell injection mold based on the simulation relationship function, and the probability of deformation of the injection medical instrument ultra-thin shell is reduced.

[0063] The present application analyzes the relationship function among the injection melt temperature, the injection pressure and the simulation warping amount, which is marked as a simulation relationship function, and has the advantage that the relationship function among the injection melt temperature, the injection pressure and the simulation warping amount is analyzed through function fitting, the shell deformation is represented by the simulation warping amount, the optimal plastic melt temperature and the optimal injection pressure are acquired when the shell deformation is the smallest, and the injection molding quality is improved. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 It is a principle block diagram of the system of the present application;

[0065] Figure 2 It is a schematic diagram of the simulation relationship function of the present application;

[0066] Figure 3 It is a schematic diagram of the time relationship function of the present application;

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

[0068] Figure 5 Flow chart of steps of the method of the present application. DETAILED DESCRIPTION

[0069] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0070] Embodiment 1, please refer to Figure 1 As shown in the figure, the present application provides a medical instrument ultra-thin shell injection mold pouring simulation system, comprising 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.

[0071] The mold construction module is used to acquire the structure information of the medical instrument ultra-thin shell and the injection material of this time, and to construct an initial simulation injection mold based on the structure information of the medical instrument ultra-thin shell.

[0072] The related data acquisition module is used to acquire an influence warping data set, which includes the injection material temperature, the injection pressure, and the cooling time. The units of the injection material temperature, the injection pressure, and the cooling time are ℃, MPa, and s, respectively. The injection pressure is represented as the holding pressure.

[0073] The first simulation pouring module is used to simulate pouring of the initial simulation injection mold with the injection material of this time under different influence warping data set conditions, and to acquire the warping deformation amount of the simulated medical instrument ultra-thin shell of each simulation pouring, which is marked as the simulation warping amount. The injection material of this time has multiple choices, such as ASB material. The unit of the simulation warping amount is mm.

[0074] The first simulation pouring module is configured with a first simulation pouring strategy, which includes:

[0075] Acquiring the range of the injection material temperature, which is marked as the injection temperature range.

[0076] Acquiring N1 injection material temperatures with an interval of a1 from the minimum value of the injection temperature range in the injection temperature range, which is marked as the divided injection temperature.

[0077] Acquiring the range of the injection pressure, which is marked as the injection pressure range.

[0078] N2 injection pressures with interval M2 are obtained from the minimum value of the injection pressure range, and are marked as division injection pressures;

[0079] One division injection temperature is combined with one division injection pressure to mark a temperature and pressure combination; all temperature and pressure combinations are obtained;

[0080] The initial simulation injection mold is simulated with the injection material for the first number of times under the condition of one temperature and pressure combination, and the warping deformation amount of the simulated medical device ultra-thin shell is obtained after the first cooling time, marked as the simulated warping amount; the first cooling time is set as any cooling time in the first cooling time range, for example, the first cooling time range is 15s to 30s, and 22.5s is preferred; the data range is the reference range of the material; the warping deformation amount is the degree of shape deviation from the designed shape of the injection product during the cooling and solidification process, and the value is obtained by software;

[0081] In actual application, the injection temperature range obtained is 220℃ to 250℃, the division injection temperatures are 220℃, 225℃,..., 245℃ and 250℃, the injection pressure range is 100MPa to 130MPa, and the division injection pressures are 100MPa, 105MPa,..., 125MPa and 130MPa, for example, the simulated warping amount is 3.863mm after 22.5s under a temperature and pressure combination of 220℃ and 100MPa.

[0082] The first function obtaining module is used to analyze the relationship function among the injection melt temperature, the injection pressure and the simulated warping amount, and is marked as the simulated relationship function;

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

[0084] The simulated warping amounts are sorted in ascending order and are marked as Fql1 to Fql i ;

[0085] The first proportion value is Db1=a1*S1, where Db1 is the first proportion value, a1 is the first proportion coefficient, the range of a1 is [0, 0.5], and S1 is the first number; the first warping value is selected from the smaller half of the value distribution, so a1 is set in the interval of 0 to 0.5, and a middle value is selected, which can ensure that the selected first warping value has the representativeness of the smaller half of the value, and 0.25 is preferred;

[0086] If the first proportion value is an integer, Fql (Db1)The first warping value is marked; if the first proportion value is not an integer, the integers on the left and right sides of Db1 are obtained, respectively marked as Db1z and Db1y, and Fql (Db1z) is obtained (Db1y) The average value of Fql (Db2) is obtained, and the first warping value is marked;

[0087] The second proportion coefficient a2 is obtained: a2 = [(1 / a1)-1]*a1; wherein a2 is the second proportion coefficient;

[0088] The second proportion value Db2 is obtained: Db2 = a2*S1, wherein Db2 is the second proportion value;

[0089] If the second proportion value is an integer, Fql (Db2z) is marked as the second warping value; if the second proportion value is not an integer, the integers on the left and right sides of Db2 are obtained, respectively marked as Db2z and Db2y, and Fql (Db2y) is obtained (5) The average value of Fql (20) is obtained, and the second warping value is marked;

[0090] In actual application, for example, a temperature and pressure combination of 220℃ and 100MPa under 22.5s after obtaining the first number 20 of the simulation warping amount, respectively 3.663mm, 3.752mm,..., 3.863mm and 3.889mm; the first proportion value Db1 is obtained: Db1 = 0.25*20 = 5, the first proportion value is an integer, Fql (5) = 3.682mm is taken as the first warping value, the second proportion coefficient a2 is obtained: a2 = [(1 / a1)-1]*a1 = 0.75, the second proportion value Db2 is obtained: Db2 = 0.75*20 = 15, the second proportion value is an integer, Fql (20) = 3.866mm is taken as the second warping value.

[0091] The first function obtaining module is configured with a warping threshold value obtaining strategy, and the warping threshold value obtaining strategy comprises:

[0092] The difference between the second warping value and the first warping value is obtained, and marked as the warping intermediate difference value;

[0093] The first warping threshold value Qy1 is obtained: Qy1 = Qq1-b1*Qz; wherein Qy1 is the first warping threshold value, Qq1 is the first warping value, b1 is the threshold value proportion coefficient, and Qz is the warping intermediate difference value; b1 is set based on the actual simulation warping amount distribution, b1 ranges between 0 and 1, the more concentrated the actual simulation warping amount, the smaller b1, the more dispersed the actual simulation warping amount, the larger b1, because the pouring conditions are consistent, the actual simulation warping amount is relatively concentrated, for example, set to 0.3;

[0094] The second warping threshold value Qy2 is obtained: Qy2 = Qq2-b1*Qz; wherein Qy2 is the second warping threshold value;

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

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

[0097] Obtain the average of the simulated warp values ​​between the second and first warp values, and mark it as the filtered simulated warp value;

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

[0099] A three-dimensional coordinate system was established, with injection temperature as the X-axis data, injection pressure as the Y-axis data, and simulated warpage as the Z-axis data. This system was then labeled as the data relationship coordinate system.

[0100] The injection temperature and injection pressure in the temperature and pressure combination are used as the X-axis and Y-axis data of the data relationship coordinate points, respectively. The corresponding simulated warpage is used as the Z-axis data of the data relationship coordinate points. All relationship coordinate points are plotted in the data relationship coordinate system to obtain a relationship scatter plot.

[0101] The simulated relationship function is obtained by polynomial fitting of the scatter plot of the relationship.

[0102] In practical applications, for example, if the average simulated warpage between 3.625mm and 3.941mm is 3.782mm, then the simulated warpage value is selected as 3.782mm. A data relationship coordinate point is (220, 100, 3.782). The simulated relationship function is obtained by polynomial fitting of the scatter plot. Please refer to [link to relevant documentation]. Figure 2 As shown, the simulation relationship function is plotted.

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

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

[0105] Obtain the simulation relationship function and select the injection temperature and injection pressure corresponding to the minimum simulation warpage, and mark them as the optimal melt temperature and optimal injection pressure, respectively.

[0106] For practical applications, please refer to Figure 2As shown, observing the image of the drawn simulation relationship function, the optimal plastic melt temperature and the optimal injection pressure corresponding to the minimum simulation warping amount are obtained as 243℃ and 119 MPa respectively, the obtained data is kept as an integer, and if there are multiple sets of the minimum simulation warping amount, the set with the minimum divided injection temperature and the minimum divided injection pressure is obtained as the optimal plastic melt temperature and the optimal injection pressure;

[0107] The second simulation pouring module is configured to simulate pouring the initial simulation injection mold with the injection material under the optimal plastic melt temperature and the optimal injection pressure, and obtain the warping deformation amount of the simulation medical device ultra-thin shell at each simulation pouring, which is marked as the time warping amount;

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

[0109] The second simulation pouring module is configured to simulate pouring the initial simulation injection mold with the injection material under the optimal plastic melt temperature and the optimal injection pressure, and obtain the warping deformation amount of the simulation medical device ultra-thin shell at each simulation pouring, which is marked as the time warping amount; T1 to Tk are continuous 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 based on the range of the first cooling time, and the range of the first cooling time is 15s to 30s, so T1 is 15;

[0110] The second function obtaining module is configured to analyze the relationship function of the cooling time and the time warping amount, which is marked as the time relationship function;

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

[0112] The second function obtaining module is configured with a second function obtaining strategy, and the second function obtaining strategy includes:

[0113] The second function obtaining module is configured with a second function obtaining strategy, and the second function obtaining strategy includes:

[0114] The second function obtaining module is configured with a second function obtaining strategy, and the second function obtaining strategy includes:

[0115] In practical applications, T1 to Tk are 15, 17, 19,..., 27 and 29 respectively, please refer to Figure 3 As shown, the time scatter plot is drawn, and the time relationship function and the image of the time relationship function are obtained by polynomial fitting of the time scatter plot.

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

[0117] The second data acquisition module is configured to acquire 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, v coordinate points are obtained with T1 as the starting point and ps as the horizontal coordinate interval, which are marked 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, p is 2s, the range of the first cooling time is 15s to 30s, and v is 8.

[0120] The tangent line of the time relationship function is drawn on the time function coordinate points, which is marked as the time function tangent line, and the absolute value of the slope of the time function tangent line is obtained, which is marked as the time slope value.

[0121] The horizontal coordinate of the time function coordinate point corresponding to the minimum value of the time slope value is obtained, which is marked as the optimal cooling time.

[0122] In actual application, please participate Figure 4 As shown in the figure, on the time relationship function, 8 coordinate points are obtained with 15 as the starting point and 2 as the horizontal coordinate interval, which are marked as time function coordinate points. The optimal cooling time is 23.5s, and the data is retained to one decimal place. If there are multiple minimum values of the time slope value at the same time, the horizontal coordinate of the time function coordinate point with the minimum value is selected as the optimal cooling time.

[0123] The optimal data execution module is configured to output the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time, and to perform real pouring 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℃, 119MPa and 23.5s respectively. The optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time are used for real pouring, which reduces the deformation of the ultra-thin shell of the injection molded medical device.

[0125] Embodiment 2, please refer to Figure 5 As shown in the figure, the present application provides a medical device ultra-thin shell injection mold pouring simulation method, which includes the following steps:

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

[0127] Step S2, obtaining an influence warping data set, the influence warping data set comprising: an injection material temperature, an injection pressure, and a cooling time.

[0128] Step S3, simulating pouring of the initial simulation injection mold with the injection material under different influence warping data set conditions, and obtaining a warping deformation amount of the simulation medical instrument ultra-thin shell in each simulation pouring, marked as a simulation warping amount; step S3 comprises the following sub-steps:

[0129] Step S301, obtaining a range of the injection material temperature, marked as an injection temperature range;

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

[0131] Step S303, obtaining a range of the injection pressure, marked as an injection pressure range;

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

[0133] Step S305, combining one divided injection temperature with one divided injection pressure to obtain a temperature and pressure combination; obtaining all temperature and pressure combinations;

[0134] Step S306, simulating pouring of the initial simulation injection mold with the injection material for a first number of times under a condition of one temperature and pressure combination, and obtaining a warping deformation amount of the simulation medical instrument ultra-thin shell after a first cooling time, marked as a simulation warping amount.

[0135] Step S4, analyzing a relationship function among the injection melt temperature, the injection pressure, and the simulation warping amount, marked as a simulation relationship function; step S4 comprises the following sub-steps:

[0136] Step S401, sorting the simulation warping amounts in ascending order and marking them as Fql1 to Fql i ;

[0137] Step S402, obtaining a first proportion value: Db1=a1*S1, wherein Db1 is the first proportion value, a1 is a first proportion coefficient, wherein the range of a1 is [0, 0.5], and S1 is the first number;

[0138] Step S403, if the first proportion value is an integer, marking Fql (Db1) as a first warping value; if the first proportion value is not an integer, obtaining integers on the left and right sides of Db1, marked as Db1z and Db1y respectively, and obtaining Fql (Db1z)the average of Fql (Db1y) , marked as the first warpage value;

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

[0140] Step S405, the second proportional value is obtained: Db2 = a2*S1, wherein Db2 is the second proportional value;

[0141] Step S406, if the second proportional value is an integer, Fql (Db2) is marked as the second warpage value; if the second proportional value is not an integer, the integers on the left and right sides of Db2 are obtained, respectively marked as Db2z and Db2y, and the average of Fql (Db2z) and Fql (Db2y) is obtained, marked as the second warpage value;

[0142] Step S407, the difference between the second warpage value and the first warpage value is obtained, marked as the warpage intermediate difference value;

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

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

[0145] Step S410, the average of the simulation warpage amount between the second warpage value and the first warpage value is obtained, marked as the screening simulation warpage amount;

[0146] Step S411, the screening simulation warpage amount of all temperature and pressure combinations is obtained;

[0147] Step S412, a three-dimensional coordinate system is established, marked as the data relationship coordinate system, with the divided injection temperature as the X-axis data, the divided injection pressure as the Y-axis data, and the screening simulation warpage amount as the Z-axis data;

[0148] Step S413, the divided injection temperature and the divided injection pressure in the temperature and pressure combination are respectively taken as the X-axis data and the Y-axis data of the data relationship coordinate point, and the corresponding screening simulation warpage amount is taken as the Z-axis data of the data relationship coordinate point. All relationship coordinate points are plotted in the data relationship coordinate system to obtain a relationship scatter plot;

[0149] Step S414, the relationship scatter plot is polynomial fitted to obtain a simulation relationship function.

[0150] Step S5, obtaining the optimal melt temperature and the optimal injection pressure based on the simulation relationship function; step S5 includes the following sub-steps:

[0151] Step S501, obtaining the division injection temperature and the division injection pressure corresponding to the simulation warping amount being the smallest when the simulation relationship function is screened, respectively marked as the optimal melt temperature and the optimal injection pressure.

[0152] Step S6, under the conditions of the optimal melt temperature and the optimal injection pressure, using the injection material of this time to simulate the initial simulation injection mold pouring, and obtaining the warping deformation amount of the simulation medical instrument ultra-thin shell of each simulation pouring, marked as the time warping amount; step S6 includes the following sub-steps:

[0153] Step S601, under the conditions of the optimal melt temperature and the optimal injection pressure, using the injection material of this time to simulate the initial simulation injection mold pouring for the second number of times, obtaining the warping deformation amount of the simulation medical instrument ultra-thin shell when the cooling time is T1 to Tk, marked as the time warping amount; T1 to Tk is a continuous interval time starting from T1 seconds with an interval of c1 seconds, and T1 to Tk is marked as Tj.

[0154] Step S7, analyzing the relationship function of the cooling time and the time warping amount, marked as the time relationship function; step S7 includes the following sub-steps:

[0155] Step S701, taking the cooling time as the X-axis data and the time warping amount as the Y-axis data, establishing a plane rectangular coordinate system, marked as the time relationship coordinate system;

[0156] Step S702, taking Tj and the corresponding time warping amount as the X-axis data and the Y-axis data of the time relationship coordinate point, drawing all the time relationship coordinate points in the time relationship coordinate system to obtain the time scatter plot;

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

[0158] Step S8, obtaining the optimal cooling time based on the time relationship function; step S8 includes the following sub-steps:

[0159] Step S801, obtaining v coordinate points on the time relationship function, taking T1 as the starting point and p as the horizontal coordinate interval, marked as the time function coordinate point;

[0160] Step S802, drawing the tangent line of the time relationship function on the time function coordinate point, marked as the time function tangent line, obtaining the absolute value of the slope of the time function tangent line, marked as the time slope value;

[0161] Step S803, obtaining the horizontal coordinate of the time function coordinate point corresponding to the minimum value of the time slope value, and marking it as the screening cooling time.

[0162] Step S9, outputting the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time, and performing real pouring based on the optimal plastic melt temperature, the optimal injection pressure and the optimal cooling time.

[0163] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage media can be realized by any type of volatile or non-volatile memory devices or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. These computer program instructions can also be stored in a computer readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer readable memory produce a manufactured product including instruction devices, which realize the functions specified in the flowcharts Figure 1 The functions specified in one or more flows and / or blocks Figure 1 The functions specified in one or more flows and / or blocks

[0164] In the embodiments provided by 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 schematic. For example, the division of the units is only a logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection can be indirect coupling or communication connection through some communication interfaces, devices or units, and can be electrical, mechanical or other forms.

Claims

1. A medical instrument ultra-thin shell injection mold pouring simulation method, characterized in that, The method comprises the following steps: Obtain the structure information of the medical instrument ultra-thin shell and the injection molding material, and construct an initial simulation injection mold based on the structure information of the medical instrument ultra-thin shell; Obtain a warping data set, which includes injection molding material temperature, injection molding pressure, and cooling time; Simulate pouring of the initial simulation injection mold using the injection molding material under different warping data set conditions, and obtain the warping deformation amount of the simulated medical instrument ultra-thin shell each time, which is marked as a simulation warping amount; Analyze the relationship function among the injection molding melt temperature, the injection molding pressure, and the simulation warping amount, which is marked as a simulation relationship function; Obtain the optimal injection molding melt temperature and the optimal injection molding pressure based on the simulation relationship function; Simulate pouring of the initial simulation injection mold using the injection molding material under the optimal injection molding melt temperature and the optimal injection molding pressure, and obtain the warping deformation amount of the simulated medical instrument ultra-thin shell each time, which is marked as a time warping amount; Analyze the relationship function between the cooling time and the time warping amount, which is marked as a time relationship function; Obtain the optimal cooling time based on the time relationship function; Output the optimal injection molding melt temperature, the optimal injection molding pressure, and the optimal cooling time, and perform actual pouring based on the optimal injection molding melt temperature, the optimal injection molding pressure, and the optimal cooling time; Simulate pouring of the initial simulation injection mold using the injection molding material under different warping data set conditions, and obtain the warping deformation amount of the simulated medical instrument ultra-thin shell each time, which is marked as a simulation warping amount, comprising the following sub-steps: Obtain the range of the injection molding material temperature, which is marked as an injection molding temperature range; Obtain N1 injection molding material temperatures with an interval of a1 from the minimum value of the injection molding temperature range within the injection molding temperature range, which is marked as divided injection molding temperatures; Obtain the range of the injection molding pressure, which is marked as an injection molding pressure range; Obtain N2 injection molding pressures with an interval of M2 from the minimum value of the injection molding pressure range within the injection molding pressure range, which is marked as divided injection molding pressures; Combine one divided injection molding temperature with one divided injection molding pressure to obtain a temperature and pressure combination, and obtain all temperature and pressure combinations; Simulate pouring of the initial simulation injection mold using the injection molding material under the condition of one temperature and pressure combination for a first number of times, and obtain the warping deformation amount of the simulated medical instrument ultra-thin shell after a first cooling time, which is marked as a simulation warping amount; The first cooling time is set as any cooling time within a first cooling time range.

2. The medical device ultra-thin shell injection mold filling simulation method of claim 1, wherein Analyze the relationship function among the injection molding melt temperature, the injection molding pressure, and the simulation warping amount, which is marked as a simulation relationship function, comprising the following sub-steps: The simulation warping amounts are sorted from small to large and marked as Fql1 to Fql i ; Obtain a first proportion value Db1=a1*S1, wherein Db1 is the first proportion value, a1 is a first proportion coefficient, the range of a1 is [0, 0.5], and S1 is a first number; If the first ratio value is an integer, Fql （Db1） is marked as the first warping value; if the first ratio value is not an integer, integers on the left and right sides of Db1 are obtained, respectively marked as Db1z and Db1y, and Fql （Db1z） is calculated, and the average value of Fql （Db1y） and Fql （Db1y） is marked as the first warping value; Obtain a second proportion coefficient a2=[(1 / a1)-1]*a1, wherein a2 is the second proportion coefficient; Obtain a second proportion value Db2=a2*S1, wherein Db2 is the second proportion value. If the second ratio value is an integer, Fql （Db2） is marked as the second warping value; if the second ratio value is not an integer, the integers on the left and right sides of Db2 are obtained and marked as Db2z and Db2y respectively, and Fql （Db2z） is calculated, and the average of Fql （Db2y） and Fql （Db2y） is marked as the second warping value.

3. The medical device ultra-thin shell injection mold filling simulation method of claim 2, wherein, Analyzing the relationship function among the injection melt temperature, the injection pressure and the simulation warping amount, marked as a simulation relationship function, further includes the following sub-steps: Obtaining the difference between the second warping value and the first warping value, marked as a warping intermediate difference value; Obtaining the first warping threshold value as Qy1=Qq1-b1*Qz; Wherein Qy1 is the first warping threshold value, Qq1 is the first warping value, b1 is a threshold proportion coefficient, and Qz is the warping intermediate difference value; Obtaining the second warping threshold value as Qy2=Qq2-b1*Qz; wherein Qy2 is the second warping threshold value.

4. The medical device ultra-thin shell injection mold filling simulation method of claim 3, wherein, Analyzing the relationship function among the injection melt temperature, the injection pressure and the simulation warping amount, marked as a simulation relationship function, further includes the following sub-steps: Obtaining the average value of the simulation warping amount between the second warping value and the first warping value, marked as a screening simulation warping amount; Obtaining the screening simulation warping amount of all temperature and pressure combinations; Establishing a three-dimensional coordinate system with the divided injection temperature as the X-axis data, the divided injection pressure as the Y-axis data, and the screening simulation warping amount as the Z-axis data, marked as a data relationship coordinate system; Taking 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 taking the corresponding screening simulation warping amount as the Z-axis data of the data relationship coordinate point, a relationship scatter plot is obtained by plotting all the relationship coordinate points in the data relationship coordinate system; Polynomial fitting is performed on the relationship scatter plot to obtain the simulation relationship function.

5. The medical device ultra-thin shell injection mold filling simulation method of claim 4, wherein, Based on the simulation relationship function, the optimal injection melt temperature and the optimal injection pressure further include the following sub-steps: Obtaining the divided injection temperature and the divided injection pressure corresponding to the minimum screening simulation warping amount of the simulation relationship function, respectively marked as the optimal injection melt temperature and the optimal injection pressure.

6. The medical device ultra-thin shell injection mold filling simulation method of claim 5, wherein Under the conditions of the optimal injection melt temperature and the optimal injection pressure, the initial simulation injection mold is simulated and poured with the injection material, and the warping deformation amount of the simulation medical instrument ultra-thin shell in each simulation pouring is obtained, marked as a time warping amount, including the following sub-steps: Under the conditions of the optimal injection melt temperature and the optimal injection pressure, the initial simulation injection mold is simulated and poured with the injection material for a second number of times, and the warping deformation amount of the simulation medical instrument ultra-thin shell is obtained at cooling times T1 to Tk, marked as a time warping amount; T1 to Tk are continuous interval times starting from T1 seconds with an interval of c1 seconds, and T1 to Tk are marked as Tj.

7. The medical device ultra-thin shell injection mold filling simulation method of claim 6, wherein, Analyzing the relationship function between the cooling time and the time warping amount, marked as a time relationship function, further includes the following sub-steps: Establishing a plane rectangular coordinate system with the cooling time as the X-axis data and the time warping amount as the Y-axis data, marked as a time relationship coordinate system; Taking Tj and the corresponding time warping amount as the X-axis data and the Y-axis data of the time relationship coordinate point, a time scatter plot is obtained by plotting all the time relationship coordinate points in the time relationship coordinate system; Polynomial fitting is performed on the time scatter plot to obtain the time relationship function.

8. The medical device ultra-thin shell injection mold filling simulation method of claim 7, wherein, Based on the time relationship function, the optimal cooling time includes the following steps: Obtaining v coordinate points on the time relationship function with T1 as the starting point and p as the horizontal coordinate interval, marked as time function coordinate points; Draw a tangent line of the time function relation at the time function coordinate point, mark it as a time function tangent line, obtain the absolute value of the time function tangent line slope, mark it as a time slope value; Obtain the abscissa of the time function coordinate point corresponding to the minimum value of the time slope value, mark it as a screening cooling time.

9. A medical device ultra-thin shell injection mold pouring simulation system for implementing the medical device ultra-thin shell injection mold pouring simulation method of any one of claims 1-8, characterized in that, The mold building module, the related data obtaining module, the first simulation pouring module, the first function obtaining module, the first data obtaining module, the second simulation pouring module, the second function obtaining module, the second data obtaining module, and the optimal data executing module are included. The mold building module is configured to obtain structure information of a medical instrument ultra-thin shell and this time injection material, and build an initial simulation injection mold based on the structure information of the medical instrument ultra-thin shell. The related data obtaining module is configured to obtain an influence warping data set, which includes injection material temperature, injection pressure, and cooling time. The first simulation pouring module is configured to simulate pouring of the initial simulation injection mold using the injection material under different influence warping data set conditions, and obtain a warping deformation amount of a simulated medical instrument ultra-thin shell each time, marked as a simulation warping amount. The first function obtaining module is configured to analyze a relation function among the injection melt temperature, the injection pressure, and the simulation warping amount, marked as a simulation relation function. The first data obtaining module is configured to obtain an optimal injection melt temperature and an optimal injection pressure based on the simulation relation function. The second simulation pouring module is configured to simulate pouring of the initial simulation injection mold using the injection material under the optimal injection melt temperature and the optimal injection pressure, and obtain a warping deformation amount of a simulated medical instrument ultra-thin shell each time, marked as a time warping amount. The second function obtaining module is configured to analyze a relation function between the cooling time and the time warping amount, marked as a time relation function. The second data obtaining module is configured to obtain an optimal cooling time based on the time relation function. The optimal data executing module is configured to output the optimal injection melt temperature, the optimal injection pressure, and the optimal cooling time, and perform real pouring based on the optimal injection melt temperature, the optimal injection pressure, and the optimal cooling time.

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