Method for predicting voids in resin molded article, method for reducing voids in resin molded article, and storage medium

Abstract

The method for predicting the generation behavior of voids generated inside an injection-molded article molded by injecting a thermoplastic resin into a mold comprises the steps of: creating an analysis model obtained by dividing the injection-molded article into a plurality of elements; a step for obtaining a temperature distribution and a pressure distribution of the analysis model in the step for molding the thermoplastic resin; altering the temperature profile or the pressure profile; calculating an elastic modulus distribution and a temperature load distribution of the analysis model using temperature dependence data of an elastic modulus of the thermoplastic resin, data of a thermal expansion coefficient, and PVT data measured in advance, on the basis of the changed temperature distribution and pressure distribution; calculating a strain generated by each element of the model for analysis by structural analysis using the elastic modulus distribution and the temperature load distribution; and predicting a generation position of a gap and / or a gap amount according to the strain.

Description

Technical Field

[0001] The present disclosure relates to a method for predicting the occurrence of molding defects in a resin molded product. Background Art

[0002] Injection molding is used to manufacture parts with complex shapes using thermoplastic resins. Depending on the molding conditions and product shape, molding defects called "sink marks (depressions formed on the surface of the molded product)" or "voids (cavities formed inside the molded product)" may occur in resin molded products.

[0003] Sink marks and voids are generated during the process of cooling and solidification of thermoplastic resin injected in a molten state during injection molding of thermoplastic resins. In particular, in the case of crystalline resins, molecular chains that are in a random state immediately after filling the mold are oriented (folded and arranged) due to crystallization, resulting in a decrease (contraction) in volume compared to the volume (mold size) immediately after filling the mold, thereby generating sink marks or voids.

[0004] If these molding defects occur, the dimensional accuracy of the product may be reduced (for example, in a component for airtight purposes, a gap may be generated on the sealing surface in contact with the counterpart member due to a depression) or the strength may be reduced (it is easy to be broken starting from the gap). Therefore, it is necessary to improve the technology related to the suppression of sink marks and gaps.

[0005] As a countermeasure to suppress sink marks and voids, the actual molded product is checked to change the molding conditions, or the gate or wall thickness of the molded product is changed in design, etc. However, since these processes are time-consuming and costly, in recent years, research has been conducted on whether it is possible to predict the occurrence of sink marks and / or voids through injection molding simulation using flow analysis software to optimize product shape and molding conditions.

[0006] In Patent Document 1, the effect of the change in crystallization temperature due to the pressure applied during the flow is considered in the flow analysis of the injection molding process using flow analysis software. In Patent Document 2, the data obtained by the flow analysis software is applied to the strain analysis performed by the structural analysis software to predict the generation of voids.

[0007] Prior art literature

[0008] Patent Literature

[0009] Patent Document 1: Japanese Patent Application Publication No. 2009-233881

[0010] Patent Document 2: Japanese Patent Application Laid-Open No. 2009-233882 Summary of the invention

[0011] Problem that the invention aims to solve

[0012] In conventional techniques, in an injection molding process using a resin material, the generation of voids in a molded product after cooling may not be predicted with sufficient accuracy.

[0013] The purpose of the present disclosure is to provide a method for predicting the void generation behavior of a resin molded product in an injection molding process using a resin material with high accuracy. By solving this problem, the product shape design, mold design, molding condition setting, and molding material for obtaining a molded product without void generation can be pre-assumed in the design stage, and productization can be carried out efficiently.

[0014] Solutions for solving problems

[0015] According to one embodiment of the present disclosure, a method for predicting the generation behavior of voids generated inside an injection molded product obtained by injecting a thermoplastic resin into a mold comprises the following steps: preparing an analytical model obtained by dividing the injection molded product into a plurality of elements; obtaining a temperature distribution and a pressure distribution of the analytical model in a step of molding the thermoplastic resin; changing the temperature distribution or the pressure distribution; calculating an elastic modulus distribution and a temperature load distribution of the analytical model based on the changed temperature distribution and the pressure distribution using temperature dependency data of an elastic modulus, data on a thermal expansion coefficient, and PVT data of the thermoplastic resin measured in advance; calculating strains generated in each element of the analytical model by structural analysis using the elastic modulus distribution and the temperature load distribution; and predicting a generation position and / or a void amount of voids based on the strains. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a figure for demonstrating each process of injection molding.

[0017] Figure 2 This is a flowchart showing an example of a method for predicting the occurrence behavior of a gap according to the first embodiment.

[0018] Figure 3 This is a diagram showing an example of data on the temperature dependency of the elastic modulus of a thermoplastic resin.

[0019] Figure 4 It is a diagram showing an example of PVT data of a thermoplastic resin.

[0020] Figure 5 This is a diagram showing a three-dimensional CAD model of a shape according to the first embodiment.

[0021] Figure 6 This is a cross-sectional view of the analysis model used in Example 1.

[0022] Figure 7This is a comparison of the void generation involved in Example 1. Figure 7 A is a diagram showing an X-ray CT of an actual molded product. Figure 7 B is a diagram showing a comparative example using a conventional method that only performs flow analysis. Figure 7 C is a diagram showing a reference example of performing coupled analysis of flow analysis and structural analysis, and Figure 7 D is a diagram showing Example 1 using Improved Method 1.

[0023] Figure 8 This is a flowchart showing an example of a method for predicting gap generation behavior according to the second embodiment.

[0024] Fig. 9 This is the first shape example (flange type) involved in Example 2, Fig. 9 A is a diagram showing a three-dimensional CAD shape of a flange type in bottom view and top view, Fig. 9 B and Fig. 9 C is a diagram showing an X-ray CT of an actual molded product.

[0025] Fig.10 This is the analytical model used in Example 2.

[0026] Fig.11 It is a diagram showing an example of pressure distribution when VP is switched.

[0027] Fig.12 This is a diagram for explaining pressure distribution obtained by a conventional method.

[0028] Fig.13 is a comparison of the gaps involved in Example 2, Fig.13 A is a diagram showing an X-ray CT of an actual molded product. Fig.13 B is a diagram showing Comparative Example 1 using a conventional method that only performs flow analysis. Fig.13 C is a diagram showing Comparative Example 2 in which coupled analysis (without pressure correction) of flow analysis and structural analysis is performed, and Fig.13 D is a diagram showing Example 2 using Improved Method 2.

[0029] Fig.14 The second shape example (window regulator type) of the third embodiment is described below. Fig.14 A is a diagram showing a three-dimensional CAD shape of a window regulator type, and Fig.14 B is a diagram showing an X-ray CT of an actual molded product.

[0030] Fig.15 This is the analytical model used in Example 3.

[0031] Fig.16 This is a diagram for explaining pressure distribution obtained by a conventional method.

[0032] Fig.17 is a comparison of the gaps involved in Example 3, Fig.17 A is a diagram showing an X-ray CT of an actual molded product. Fig.17 B is a diagram showing Comparative Example 1 using a conventional method that only performs flow analysis. Fig.17 C is a diagram showing Comparative Example 2 in which coupled analysis (without pressure correction) of flow analysis and structural analysis is performed, and Fig.17 D is a diagram showing Example 3 using improved method 2. DETAILED DESCRIPTION

[0033] Figure 1 It is a diagram used to explain each step of injection molding. Figure 1 In FIG. 1 , we focus on one mold and show the time series of molding.

[0034] Injection molding starts with injecting resin into the mold cavity through the gate. Although the delivery speed of the resin is controlled immediately after injection, when, for example, 99% of the predetermined amount of resin is filled, the resin pressure is switched to control (holding pressure) (VP control) to fill the mold cavity with resin. At the time of VP switching, the difference between the maximum pressure and the minimum pressure in the mold cavity is considered to be the largest.

[0035] Here, as one of the indicators for obtaining stable injection molded products, there is gate sealing. Gate sealing refers to the phenomenon that the resin in the gate solidifies and stops flowing. The time when the resin in the gate solidifies and stops flowing is called the gate sealing time. If the pressure holding is stopped before the gate sealing time, the molten resin will flow back to the injection molding machine side through the gate, which will cause filling defects and weight reduction. On the other hand, after the gate sealing time, even if the pressure holding is stopped, the gate will be solidified and the resin will not flow back, so a stable injection molded product can be obtained. Therefore, it is an indicator that must be measured at the molding site.

[0036] The gate sealing time can also be determined by setting the molding conditions so that the weight of the molded product is maximized and the time until the gate is sealed is minimized. The weight of the molded product and the time until the gate is sealed can also be obtained through experiments (measurements). Instead of experiments, the weight of the molded product and the time until the gate is sealed can also be obtained through simulation using flow analysis.

[0037] Alternatively, the time point when the temperature at the gate center reaches the flow stop temperature Ts can be set as the gate sealing time. The time point when the temperature at the gate center reaches the flow stop temperature Ts can be obtained through experiments or calculated using simulations.

[0038] The flow stop temperature Ts can also be set as the inflection point when cooling at a cooling rate within the range from 1 °C / min to 50 °C / min in specific heat measurement.

[0039] Alternatively, for the PVT data, using the data fitting coefficients b5 and b6 of the double-domain Tait PVT model, the flow stop temperature Ts can be set as Ts = b5 + b6 × P under the pressure P. Here, the double-domain Tait PVT model is such that the specific volume v(T, P) of temperature T and pressure P is expressed as v(T, P) = v0(T)[1 - C × ln(1 + P / B(T))] + v t (T, P). In particular, v0(T) is a first-order expression of T, and relative to the specified temperature Tt, v t (T, P) is zero on the high-temperature side (T > Tt), but is an exponential function of T and P on the low-temperature side (T < Tt). Moreover, in this model, according to the PVT data, Tt = b5 + b6 × P is fitted by a first-order expression of P.

[0040] In addition, b5 is the inflection point of the PVT data (refer to Figure 4 ). The slope changes with b5 as the boundary, and solid-liquid phase transition occurs.

[0041] After the holding pressure, during a pre-determined cooling time, the injection molded product is cooled in the mold (in-mold cooling). When the cooling time has elapsed, the mold is opened and the injection molded product is ejected from the mold for demolding. After that, the mold is closed again to form the mold cavity and transferred to the molding for obtaining the next injection molded product. The ejected injection molded product can be cooled outside the mold (out-of-mold cooling). The out-of-mold cooling can continue until, for example, the injection molded product reaches room temperature.

[0042] The injection molded product obtained through such an injection molding process sometimes has a molding defect called voids. Although research is being conducted on predicting the generation of voids using, for example, flow analysis software, it is sometimes difficult to predict with sufficient accuracy using existing methods. Therefore, embodiments capable of predicting the generation of voids with high accuracy are described in detail below. In addition, the present disclosure is not limited to the following embodiments.

[0043] (Embodiment 1)

[0044] In actual injection molded products, especially when the product wall is thick, voids may occur after the product is taken out of the mold (after demolding). In the past, flow analysis software could only calculate the temperature and pressure inside the mold, so it was not possible to calculate the temperature change outside the mold to take into account the actual phenomenon.

[0045] Therefore, it is considered that the generation of voids may not be predicted with high accuracy by the technique using conventional flow analysis software.

[0046] Furthermore, there is no known method for calculating the temperature change outside the mold and predicting the occurrence of voids based on the calculation.

[0047] In the first embodiment, an analysis was performed taking into account cooling after demolding from the mold. It was found that: based on the temperature data thus obtained, the elastic modulus distribution and the volume shrinkage rate distribution were obtained, and by applying the coupled analysis to the structural analysis (strain analysis), the location and amount of void generation could be predicted at a level comparable to the results of the actual product. In addition, in this embodiment, cooling by air cooling inside and outside the mold was described in detail, but the cooling means is not limited to air cooling.

[0048] (Method for predicting void generation behavior)

[0049] Reference Figure 2 An example of a method for predicting void generation behavior according to the present embodiment will be described in detail. In this method, a coupled analysis is performed by applying the results of a flow analysis to a structural analysis.

[0050] like Figure 2 As shown in the flowchart of , an example of the method for predicting the generation behavior of voids according to the present embodiment includes the following steps: preparation of an analytical model (S1), calculation of temperature distribution and pressure distribution in the process of injecting and molding a thermoplastic resin (injection molding process) (S2), calculation of temperature distribution in the cooling process after demolding (out-of-mold cooling analysis) (S3), calculation of elastic modulus distribution and temperature load distribution (S4), calculation of strain generated by each element of the analytical model (S5), and prediction of the generation position of voids and / or the amount of voids (S6).

[0051] (Creation of analysis model (S1))

[0052] In the step (S1) of creating an analytical model by dividing the injection molded product into a plurality of elements, the shape of the injection molded product is divided into small elements to create a model required for executing the simulation (see Figure 6For example, the shape of the injection molded product (which can be the design shape of the injection molded product or the shape of the mold, etc. The shape of the mold also includes conditions such as the position, number, and size of the runner and gate) can be imported into the computer through three-dimensional shape measurement or a CAD system. Then, the shape imported into the computer is divided into a plurality of three-dimensional elements using an element division preprocessor, etc., to create a model for analysis.

[0053] In the case of coupled analysis of flow analysis and structural analysis, a flow analysis model and a different structural analysis model may be prepared to perform analysis. However, in this embodiment, an example of performing analysis by inheriting the same analysis model from flow analysis to structural analysis is described in detail.

[0054] (Calculation of Temperature Distribution and Pressure Distribution in Injection Molding Process (S2))

[0055] In the step (S2) of calculating the temperature distribution and pressure distribution of the analytical model in the process of injecting and molding the thermoplastic resin (injection molding process), the prepared analytical model is used to perform flow analysis (simulation) of injection molding. The temperature and pressure of each element of the analytical model in the process of injecting and molding the thermoplastic resin (which may also include the cooling process in the mold) are calculated by flow analysis. Thus, the temperature distribution and pressure distribution of the analytical model in the injection molding process are calculated.

[0056] When performing flow analysis, the physical property values ​​of the thermoplastic resin used in injection molding are input. The physical property values ​​used in flow analysis include data indicating the relationship between pressure, volume, and temperature (hereinafter referred to as "PVT data"). Figure 4 For example. ), thermal conductivity data and specific heat data, etc.

[0057] The specific heat of the thermoplastic resin can be measured by a differential scanning calorimeter (DSC). The thermal conductivity of the thermoplastic resin can be determined by an alternating current steady state method (ISO 22007-6).

[0058] Thermal conductivity measurement methods include AC steady-state method, hot wire method, hot disk method, etc. The AC steady-state method provides good accuracy.

[0059] Next, input the analysis conditions for flow analysis of thermoplastic resin. Molding conditions include resin (cylinder) temperature, mold temperature, injection speed, holding pressure, and holding time. In addition, the mold temperature is the same as the cooling water temperature or the heater setting temperature.

[0060] In addition, the molding conditions include the designation of the start point and the end point of the flow analysis. The start point of the flow analysis can be set, for example, as the time point when the thermoplastic resin starts to be injected into the cavity from the gate of the mold.

[0061] The end point of the flow analysis can be set to the point before the cooling time ends and demolding is performed after the molten thermoplastic resin is injected into the mold cavity. In particular, it can be set to the point in time when demolding is performed. The point in time when demolding is performed in the flow analysis can be specified as the point in time when a certain set time has passed since the start of injection (it can also be determined by comparing with the time until demolding in the actual process).

[0062] (External mold cooling analysis (S3))

[0063] In the step (S3) of cooling analysis outside the mold, the calculated temperature distribution is used to calculate the temperature distribution of each element of the analysis model in the cooling process after demolding. This step can be analyzed using structural analysis software.

[0064] The starting point of the mold-out cooling analysis is the demolding. In the case of the analysis inside the mold, in addition to using the injection molded product, the mold itself is modeled and the interaction between the molded product and the mold is considered, so it is necessary to use a finite element model of the mold. On the other hand, in the case of the analysis outside the mold, since the model of the mold itself is not required, it is necessary to significantly change the model of the injection molded product itself and the boundary conditions, and even as an extension of the analysis inside the mold, the setting of the analysis conditions becomes extremely difficult.

[0065] The end point of the mold cooling analysis can be set, for example, as the time point when the injection molded product reaches room temperature outside the mold. The "time point when the injection molded product reaches room temperature outside the mold" can also be specified, for example, based on the time from the start of injection to the time when the injection molded product reaches room temperature outside the mold measured in the actual process. Alternatively, the time point when the temperature of the injection molded product reaches room temperature in the mold cooling analysis can be obtained. In general, the time point after a certain set time from the start of injection can be set as the end point of the mold cooling analysis.

[0066] (Calculation of elastic modulus distribution and temperature load distribution (S4))

[0067] In the step (S4) of calculating the elastic modulus distribution and the temperature load distribution, the calculated temperature distribution (temperature distribution in the process of molding the thermoplastic resin and the temperature distribution in the cooling process after demolding) and pressure distribution (pressure distribution in the process of molding the thermoplastic resin) are used to obtain the elastic modulus distribution and the temperature load distribution (distribution of temperature difference) of the injection molded product. In particular, the elastic modulus distribution and the temperature load distribution of the injection molded product can be calculated by a conversion program for a computer based on the temperature distribution and the pressure distribution. In addition, the volume shrinkage distribution can also be calculated together with the temperature load distribution.

[0068] (Elastic modulus distribution)

[0069] The elastic modulus distribution of an injection molded product can be obtained by applying temperature dependency data of elastic modulus (Young's modulus, etc., generally a proportionality coefficient between stress and strain) of a molding material (thermoplastic resin) acquired in advance to the temperature distribution obtained by flow analysis.

[0070] Figure 3 The temperature dependence data of the elastic modulus of a certain thermoplastic resin is shown. The horizontal axis is temperature and the vertical axis is elastic modulus (Young's modulus). On the horizontal axis, the transition temperature (T) of the thermoplastic resin is shown. The transition temperature refers to the temperature used to divide the solidification region and the melting region, and is also called the no-flow temperature, solidification temperature, solidification temperature, or solid-liquid transition temperature.

[0071] like Figure 3 As shown in FIG. 2 , if the temperature dependency data of the elastic modulus of the thermoplastic resin is obtained, the distribution of the elastic modulus can be obtained from the temperature distribution.

[0072] In addition, the elastic modulus can include three values: the elastic modulus (Young's modulus) with respect to uniaxial stress, the Poisson's ratio, and the shear elastic modulus. By using these three values ​​of the elastic modulus, a more accurate analysis can be performed.

[0073] (Poisson's ratio distribution)

[0074] The Poisson's ratio distribution of injection molded products can be obtained by applying the value calculated based on the bulk elastic modulus, which is obtained based on the temperature dependence data of the elastic modulus (Young's modulus) of the molding material (thermoplastic resin) and PVT data acquired in advance, to the temperature distribution obtained by flow analysis.

[0075] (Shear elastic modulus distribution)

[0076] The shear elastic modulus distribution of the injection molded product can be obtained by applying a value calculated from the temperature dependency data of the elastic modulus (Young's modulus) and the temperature dependency data of the Poisson's ratio to the temperature distribution obtained by flow analysis.

[0077] (Volume shrinkage distribution)

[0078] The volume shrinkage distribution of injection molded products can be obtained by applying data ("PVT data") representing the relationship between pressure, volume and temperature of the molding material (thermoplastic resin) acquired (actually measured) in advance to the temperature distribution and pressure distribution data obtained by flow analysis.

[0079] Figure 4 The PVT data of a certain thermoplastic resin is shown. The horizontal axis is temperature (in degrees Celsius), and the vertical axis is the inverse of density, i.e. specific volume (in cm 3 / g). Figure 4 The relationship between temperature and specific volume is shown when the pressure (P) is 50 MPa. It is assumed that the relationship between temperature and specific volume is also measured in advance for several pressures other than 50 MPa. The relationship between temperature and specific volume at pressures without measured values ​​can be obtained by, for example, interpolation based on the relationship between temperature and specific volume at pressures with measured values.

[0080] exist Figure 4 In the graph, when the pressure (P) is 50 MPa, the temperature of the thermoplastic resin is 200°C and the specific volume is about 0.82 cm at the time when the thermoplastic resin in the gate is solidified and the flow stops (called "gate sealing time"). 3 Similarly, when the temperature of the injection molded product using the thermoplastic resin reaches the mold temperature, the temperature of the thermoplastic resin is 40°C and the specific volume is about 0.70 cm 3 / g.

[0081] The volume shrinkage distribution of the injection molded product was calculated as follows.

[0082] First, the temperature (T1) and pressure (P1) at a certain time point before shrinkage are calculated based on the temperature distribution data and pressure distribution data obtained by flow analysis, and then converted into the volume (V1) at the time point before shrinkage by applying them to the previously acquired PVT data of the thermoplastic resin.

[0083] exist Figure 4 In the example of gate sealing time, T1 = 200°C, P1 = 50 MPa, and the specific volume is about 0.82 cm 3 / g. That is, the volume per unit weight (1g) at this time point is V1 = about 0.82cm 3 .

[0084] Similarly, the temperature (T2) and pressure (P2) at a certain time point after contraction are obtained from the temperature distribution data and pressure distribution data obtained by flow analysis, and are applied to the PVT data to convert them into the volume (V2) at the time point after contraction.

[0085] The time point after shrinkage can be specified as a time point after a set time has passed since the start of injection (for example, it can also be determined by comparing with the time when the injection molded product reaches the mold temperature in the actual process).

[0086] exist Figure 4 In the example of cooling to the mold temperature, T2 = 40 ° C, P2 = 50 MPa, the specific volume is about 0.70 cm 3 / g. That is, the volume per unit weight (1g) at this point in time is V2 = about 0.70 cm 3 .

[0087] Furthermore, based on the volumes of each element before and after shrinkage (V1, V2), the distribution of the volume shrinkage rate of each element ((volume before shrinkage - volume after shrinkage) ÷ (volume before shrinkage), that is, (V1-V2) / V1) is obtained. That is, when the pressure is fixed at 50MPa (P1=P2=50MPa), and the volume shrinkage rate when cooling from T1=200°C to T2=40°C can be calculated as (V1-V2) / V1=(0.82-0.70) / 0.82=0.146, that is, 14.6%.

[0088] Even if the pressure is not constant before and after shrinkage, the temperature (T1) and pressure (P1) of each element before shrinkage, and the temperature (T2) and pressure (P2) of each element after shrinkage are calculated by flow analysis. If the relationship between temperature (T1, T2) and specific volume under pressure (P1, P2) before and after shrinkage (PVT data) is obtained in advance, the volume shrinkage rate (V1-V2) / V1 of each element can be calculated.

[0089] In this way, the volume shrinkage distribution can be calculated from the PVT data and the temperature distribution and pressure distribution.

[0090] (Temperature load)

[0091] The temperature load (distribution of temperature difference) is calculated by converting the volume shrinkage rate of each element into a temperature difference by dividing it by the volume expansion rate of the thermoplastic resin obtained in advance. The volume expansion rate is the coefficient β of the relationship ΔV / V=βΔT when the original volume V changes by ΔV due to a temperature rise of ΔT. In addition, in general, although the volume expansion rate is obtained based on PVT data, in the case where the thermoplastic resin has isotropy, since the volume expansion rate is 3 times the value of the linear expansion rate, the volume expansion rate can also be obtained based on the pre-measured linear expansion rate instead of the volume expansion rate obtained based on the PVT data. The volume expansion rate and the linear expansion rate are collectively referred to as thermal expansion rates. The thermal expansion rate (volume expansion rate and linear expansion rate) can also have temperature dependence.

[0092] In addition, temperature load refers to the "temperature difference before and after shrinkage", which is different from the difference between "temperature at a certain point in time before shrinkage" and "temperature at a certain point in time after shrinkage" used in the process of calculating the shrinkage rate distribution. The latter temperature difference calculated based on the temperature data obtained through flow analysis is just a "temperature only" calculation. In contrast, the former temperature load is calculated by using the volume expansion rate to return to the temperature value after the volume is calculated based on "temperature and pressure" through PVT data, so it is calculated using "temperature and pressure" instead of "temperature only". Therefore, the temperature load is a "temperature difference" that takes into account the influence of pressure on the resin in actual molding. This is different from the difference in temperature at a certain point in time before shrinkage and a certain point in time after shrinkage. Using temperature load will obtain more accurate analysis results.

[0093] (Calculation of strain generated in each element of the analytical model (S5))

[0094] In the step (S5) of calculating the strain generated in each element of the analysis model, a structural analysis is performed using the elastic modulus distribution (especially Young's modulus distribution, Poisson's ratio distribution and shear elastic modulus distribution) and volume shrinkage distribution and / or temperature load distribution (at least one of the volume shrinkage distribution and the temperature load distribution) during the cooling process after demolding to calculate the strain generated in each element of the analysis model (the distribution of strain amounts in the analysis model).

[0095] Furthermore, when obtaining the temperature distribution after demolding, it is necessary to obtain the initial temperature immediately after demolding, and the initial temperature is obtained from the temperature distribution in the mold.

[0096] The time starting point of strain calculation can be set as the time point of demolding after pressure holding and cooling, for example. The time ending point of strain calculation can be set as the time point when the injection molded product reaches room temperature, for example. Alternatively, the time ending point of strain calculation can be set as the time point when a set time (for example, it can also be set by comparison with the actual process) has passed since the start of injection.

[0097] (Prediction of Void Generation Position and / or Void Amount (S6))

[0098] In the step ( S6 ) of predicting the position and / or amount of voids, the amount of deformation is calculated based on the distribution of the strain amount in the analytical model to predict the occurrence of voids.

[0099] First, the generation of a sink mark is predicted based on the distribution of the strain amount, and the generation of a void can be predicted by performing a structural analysis on the shape of the sink mark.

[0100] Alternatively, without predicting the occurrence of sink marks, for example, when the strain of each element of the analysis model becomes equal to or greater than a threshold value for void occurrence determined in advance for each resin material through actual measurement, it can be predicted that voids will occur in the element.

[0101] In the conventional analysis software, since the temperature dependence of elastic modulus (Young's modulus, Poisson's ratio and shear elastic modulus) and linear expansion coefficient is not considered and only elastic constants (one value) at room temperature are input, the change of elastic modulus of each part under temperature change is not considered enough, and the generation of voids cannot be predicted correctly. In contrast, in the improved method involved in the first embodiment, in addition to the elastic modulus distribution (especially Young's modulus distribution, Poisson's ratio distribution and shear elastic modulus distribution) based on the temperature change of each element, the temperature load calculated from the volume shrinkage rate distribution can be used to calculate the strain of each part of the molded product based on the temperature distribution and pressure distribution obtained by flow analysis, so the prediction accuracy of voids is improved.

[0102] Furthermore, in the method according to the first embodiment, by calculating the temperature distribution and pressure distribution of each element of the analytical model during cooling outside the mold ( S3 ), the generation of voids can be predicted taking into account cooling outside the mold, thereby further improving the prediction accuracy.

[0103] Next, examples using the method according to the present embodiment (hereinafter also referred to as "improved method 1") and comparative examples using a conventional method are shown, and prediction of voids according to the present embodiment is specifically described. The present disclosure is not limited to these examples.

[0104] (Product shape and molding material)

[0105] Figure 5A three-dimensional CAD model of a molded product having a rib in a bolt-shaped thick wall according to an embodiment is shown. The molding material (thermoplastic resin) of the actual molded product is DURACON (registered trademark) POM M90-44 (without filler) manufactured by Polyplastics. In addition, the specific heat of the molding material is measured by a differential scanning calorimeter (DSC), and the thermal conductivity is obtained by a thermal conductivity measurement method called an AC steady-state method (ISO22007-6).

[0106] like Figure 5 As shown, the width of the hexagonal flange is 20 mm and the thickness is 6 mm. In addition, the height of the cylinder is 15 mm. A gate is provided on one side of the hexagonal flange.

[0107] In addition, in the flow analysis of the examples and comparative examples, Moldflow (registered trademark) Insight 2019.0.5 (three-dimensional solid model) build 20180921.0959_C70L71 (hereinafter referred to as Moldflow) manufactured by Autodesk was used.

[0108] Adventure Cluster 2021 (hereinafter referred to as ADVC) manufactured by Allied Engineering Co., Ltd. was used in the mold external cooling analysis and structural analysis of the examples.

[0109] In the calculation ( S5 ) of the elastic modulus distribution and the volume shrinkage distribution in the examples, a conversion program prepared in-house using Visual Basic (registered trademark) was used.

[0110] (Example 1)

[0111] The molding conditions of the actual molded product and the analysis conditions of the present method are shown in Table 1. In Example 1, the physical property values ​​of the thermoplastic resin were set to be the same as those of the actual molded product.

[0112] [Table 1]

[0113]

[0114] In addition, Figure 6 2 is a cross-sectional view of the analysis model used in Example 1.

[0115] In Example 1, analysis of injection, pressure holding, and cooling in the mold was performed ( Figure 2 S2), according to the analysis of cooling outside the mold ( Figure 2The temperature load (S3) calculated from the elastic modulus distribution (especially Young's modulus distribution, Poisson's ratio distribution, and shear elastic modulus distribution) and volume shrinkage distribution of the injection molded product (inside and on the surface) is obtained through a conversion program. Figure 2 S4), structural analysis, strain calculation, and prediction of the location and amount of voids ( Figure 2 of S5 and S6).

[0116] (Comparative Example)

[0117] In the comparative example of the conventional method, the physical property values ​​of the thermoplastic resin (excluding the temperature dependence of the elastic modulus, etc.) and the same analytical conditions as those of Example 1 were used, and the voids were predicted using the same analytical model as that of Example 1 based on the values ​​of the volume shrinkage distribution calculated by flow analysis. As described above, in the conventional method, since the elastic modulus (Young's modulus, Poisson's ratio, and shear elastic modulus) and the linear expansion coefficient do not take into account the temperature dependence, the change in the elastic modulus of each part when the temperature changes is not considered. That is, in the comparative example, the analytical accuracy of the cooling in the mold is poor.

[0118] In the comparative example, coupling analysis for predicting voids was not performed, but voids were predicted based on the volume shrinkage rate distribution obtained by flow analysis.

[0119] (Reference example)

[0120] In the reference example, the same thermoplastic resin physical property values ​​(including temperature dependence of elastic modulus, etc.) and the same analysis conditions as those in Example 1 were used to perform coupled analysis on the same analysis model as in Example 1, and prediction of voids was performed based on the strain obtained by structural analysis. The analysis conditions in the reference example were made the same as the molding conditions of the actual molded product in Table 1. In addition, in the reference example, the physical property values ​​of the thermoplastic resin were made the same as the physical property values ​​of the thermoplastic resin of the actual molded product.

[0121] In addition, in the reference example, the analysis of the cooling outside the mold was not performed, and only the analysis of the cooling inside the mold was performed.

[0122] (Comparison of gap predictions)

[0123] exist Figure 7 1 and 2 show comparisons of void generation in an actual molded product, a comparative example using a conventional method, a reference example in which no external cooling analysis is performed, and Example 1 using Improved Method 1.

[0124] exist Figure 7 A to D (hereinafter referred to as Figure 7 A to Figure 7In D), there are shown X-ray CT of an actual molded product, a comparative example using a conventional method that performs only flow analysis, a reference example that performs coupled analysis of flow analysis and structural analysis but does not perform mold cooling analysis, and Example 1 using Improved Method 1.

[0125] In the comparative example, voids were generated throughout the entire interior of the molded product, and the difference between the void generation locations and those in the actual molded product was large.

[0126] In Example 1, the actual molded product and the analyzed void generation site are close to each other, and the actual void generation phenomenon can be expressed with high accuracy by coupling analysis.

[0127] (Implementation Method 2)

[0128] In actual injection molded products, the pressure near the gate is high and the pressure from the gate is reliably transmitted, so it is thought that voids are unlikely to occur. On the other hand, the pressure is low at a location far from the gate, and the pressure from the gate is not reliably transmitted, so the volume shrinkage rate is large at a location far from the gate, and voids are thought to be likely to occur.

[0129] In the conventional analysis method, calculations are performed without considering the gate seal in order to deal with such phenomena in actual molded products. Therefore, the pressure is sometimes the same at any location regardless of the gate position. Therefore, it is considered that the prediction accuracy of the generation of voids is reduced.

[0130] Therefore, in Embodiment 2, flow analysis is performed taking into account the pressure generated in the mold. It was found that the elastic modulus distribution (especially Young's modulus distribution, Poisson's ratio distribution, and shear elastic modulus distribution) and volume shrinkage distribution and / or temperature load are obtained from the temperature data and pressure data obtained thereby, and by applying coupled analysis to structural analysis (strain analysis), the location and amount of void generation can be predicted at a level comparable to the results of actual products.

[0131] (Method for predicting void generation behavior)

[0132] Reference Figure 8 An example of a method for predicting the generation behavior of voids according to this embodiment will be described in detail. Figure 8 In, with Figure 2 The same parts are denoted by the same reference numerals, and their descriptions are omitted. Figure 8 In the method shown, coupled analysis is performed in which the results of flow analysis are applied to structural analysis.

[0133] like Figure 8As shown in the flowchart of , an example of the method for predicting the generation behavior of voids according to the present embodiment includes the following steps: preparation of an analytical model (S1), calculation of temperature distribution and pressure distribution in a process of injecting and molding a thermoplastic resin (injection molding process) (S2), correction of pressure in a mold cavity (S11), calculation of elastic modulus distribution and temperature load (S4), calculation of strain generated by each element of the analytical model (S12), and prediction of the generation position of voids and / or the amount of voids (S6).

[0134] (Correction of pressure in mold cavity (S11))

[0135] In the step (S11) of correcting the pressure in the mold cavity, the pressure distribution Pa(t) at a certain time t is corrected, and the pressure used for calculating the volume shrinkage distribution (hereinafter referred to as the volume shrinkage calculation pressure) Pc is calculated. In addition, the time t can be set to the time from the start of injection.

[0136] By correcting the pressure in the mold cavity, it is possible to predict the occurrence of voids in consideration of the pressure generated in the mold.

[0137] In particular, the volume shrinkage calculation pressure Pc can be calculated by the following formula (1) using the pressure correction coefficient α.

[0138] Pc=α·Pa(t)···(1)

[0139] In the above formula (1), Pc is the pressure used for calculating the volume shrinkage rate, Pa(t) is the pressure obtained by flow analysis, α is the pressure correction coefficient, and t is the time from the start of injection.

[0140] Here, the pressure correction coefficient α can be set within the range of 0 to 30.

[0141] In addition, the time t from the start of injection can be set to a time at which the difference between the maximum pressure and the minimum pressure in the mold cavity becomes maximum.

[0142] When the difference between the maximum pressure and the minimum pressure in the mold cavity is maximized, it is considered that the pressure distribution is also maximized. Therefore, it is possible to predict the occurrence of voids that better reflects the pressure distribution generated in the mold.

[0143] (Calculation of strain generated in each element of the analysis model (S12))

[0144] In the step (S12) of calculating the strain generated by each element of the analytical model, a structural analysis is performed using the elastic modulus distribution (particularly Young's modulus distribution, Poisson's ratio distribution, shear elastic modulus distribution, and volume shrinkage distribution) and the volume shrinkage distribution and / or the temperature load distribution (at least one of the volume shrinkage distribution and the temperature load distribution) to calculate the strain generated by each element of the analytical model (the distribution of the strain amount in the analytical model).

[0145] The starting point of strain calculation can be set to a certain time point when the injection molded product is cooled by pressure holding from gate sealing to demolding. The end point of strain calculation can be set to a certain time point (for example, demolding time point) after the starting point of strain calculation and before demolding (before demolding).

[0146] In the conventional analysis software, since the temperature dependence of elastic modulus (Young's modulus, Poisson's ratio and shear elastic modulus) and linear expansion coefficient is not considered and only the elastic constant (one value) at room temperature is input, the change of elastic modulus of each part under temperature change is not considered enough, and the generation of voids cannot be predicted correctly. In contrast, in the improved method involved in the second embodiment, in addition to the elastic modulus distribution (especially Young's modulus distribution, Poisson's ratio distribution and shear elastic modulus distribution) based on the temperature change of each element, the temperature load calculated from the volume shrinkage rate distribution can be used to calculate the strain of each part of the molded product based on the temperature distribution and pressure distribution obtained by flow analysis, so the prediction accuracy is improved.

[0147] Furthermore, in the method according to the second embodiment, by correcting the pressure in the mold cavity ( S11 ), the generation of voids can be predicted taking into account the pressure generated in the mold, so that the prediction accuracy is further improved.

[0148] Next, regarding the flange type (first shape example) and the window lifter type (second shape example), examples using the method involved in this embodiment (hereinafter, also referred to as "improved method 2") and comparative examples using the conventional method are shown to specifically illustrate the prediction of the gap involved in this embodiment. In addition, the present disclosure is not limited to these examples.

[0149] In addition, for the flange type and the window regulator type, the molding material (thermoplastic resin) of the actual molded product is DURACON (registered trademark) POM M90-44 (unfilled material) manufactured by Polyplastics. The specific heat of the molding material was measured by a differential scanning calorimeter (DSC), and the thermal conductivity was obtained by a thermal conductivity measurement method called the AC steady-state method (ISO22007-6).

[0150] In addition, in the flow analysis of the examples and comparative examples, Moldflow (registered trademark) Insight 2019.0.5 (three-dimensional solid model) build 20180921.0959_C70L71 (hereinafter referred to as Moldflow) manufactured by Autodesk was used.

[0151] In the structural analysis of the Examples, Adventure Cluster 2021 (hereinafter referred to as ADVC) manufactured by Allied Engineering Co., Ltd. was used.

[0152] In the calculation of the elastic modulus distribution and the volume shrinkage distribution ( S12 ) of the examples, a conversion program prepared in-house using Visual Basic (registered trademark) was used.

[0153] In the embodiment, flow analysis on injection, holding pressure and cooling is performed ( Figure 8 After S2) the pressure in the mold cavity is corrected ( Figure 8 The elastic modulus distribution and temperature load of the injection molded product (internal and surface) are obtained by conversion program ( Figure 8 S4). In addition, structural analysis is performed to calculate strain ( Figure 8 S12), the location and amount of voids are predicted based on the strain magnitude ( Figure 8 S6).

[0154] (Example 2-flange type)

[0155] Fig. 9 This is the first shape example (flange type) involved in Example 2. Fig. 9 A to C (hereinafter referred to as Fig. 9 A to Fig. 9 C) shows the three-dimensional CAD shape of the flange type ( Fig. 9 A) and X-ray CT of the actual molded product ( Fig. 9 B and Fig. 9 C).

[0156] Fig. 9 A shows the three-dimensional CAD shape of the flange type in the bottom view and top view on the left and right. In the top view, four protruding features from feature 1 to feature 4 can be seen.

[0157] Feature 1 is close to "gate1" in the figure. Feature 2 is close to "gate2" in the figure.

[0158] Fig. 9B is an X-ray CT of an actual molded product obtained by injection molding from the gate "gate1" in the figure. An enlarged view of the vicinity of feature 1 (the portion surrounded by a quadrilateral) is attached. Feature 1 is near gate 1. No voids are seen near feature 1.

[0159] Fig. 9 C is an X-ray CT of an actual molded product obtained by injection molding from the gate "gate2" in the figure. An enlarged view of the vicinity of feature 1 (the portion surrounded by a quadrilateral) is attached. Feature 1 is far from gate 2. A gap can be seen near feature 1.

[0160] (Flange type embodiment)

[0161] The injection molding conditions of the actual molded product and the analysis conditions of the present method are shown in Table 2. In Example 2, the physical property values ​​of the thermoplastic resin were set to be the same as those of the actual molded product.

[0162] [Table 2]

[0163]

[0164] exist Fig.10 The analytical model used in Example 2 is shown in FIG. The three-dimensional CAD shape of the injection molded product is divided into small elements to create an analytical model ( Fig.10 ).

[0165] In addition, in the step (S11) of correcting the pressure in the mold cavity, the pressure distribution Pa(t) at the time of VP switching t is corrected using formula (1), and the volume shrinkage calculation pressure Pc used in the calculation of the volume shrinkage distribution is calculated. In formula (1), α is set to 10. In addition, in the analysis, t is set to a value almost the same as t at the time of VP switching in actual molding (experiment) to correct the pressure distribution Pa(t).

[0166] Fig.11 It is for Fig. 9 The shape of A is a diagram showing an example of pressure distribution when VP is switched. Fig.11 The distribution of Pc when the gate is at gate1 is shown in FIG. 1. In addition, the pressure at gate1 becomes 7.578 MPa when VP is switched. Here, if α=10 in equation (1), the pressure P for calculating the volume shrinkage at gate1 is c If a holding pressure of 50 MPa is further applied, for example, a total pressure of 125.78 MPa is applied at the position of gate 1. The pressure of 125.78 MPa is the apparent pressure used for calculating the shrinkage amount.

[0167] (Comparative Example 1 of Flange Type)

[0168] In Comparative Example 1 (refer to Fig.13 In B), the same physical properties of the thermoplastic resin as in Example 2 (excluding the temperature dependence of the elastic modulus, etc.) and the same analysis conditions are used, and the same analysis model as in Example 2 is used to predict the voids based on the values ​​of the volume shrinkage distribution calculated by flow analysis.

[0169] That is, in Comparative Example 1, coupling analysis was not performed, and prediction of voids was performed based on the volume shrinkage rate distribution obtained by flow analysis.

[0170] Furthermore, in Comparative Example 1, the pressure in the mold cavity was not corrected.

[0171] Fig.12 It is used for Fig. 9 The pressure distribution obtained by the conventional method is explained by the shape of A. The pressure during gate sealing is zero throughout the entire analytical model, so there is no pressure gradient.

[0172] (Comparative Example 2 of Flange Type)

[0173] In Comparative Example 2 (ref. Fig.13 C), using the same physical properties of the thermoplastic resin as in Example 2 (including the temperature dependence of the elastic modulus, etc.) and the same analysis conditions, a coupled analysis is performed on the same analysis model as in Example 2, and the voids are predicted based on the strain obtained by the structural analysis.

[0174] In Comparative Example 2, the pressure in the mold cavity was not corrected.

[0175] (Comparison of gap prediction for flange type)

[0176] Fig.13 It is for Fig. 9 Comparison of the gaps in the shape examples. Fig.13 A to D (hereinafter referred to as Fig.13 A to Fig.13 D) is respectively shown with Fig. 9 A graph comparing the voids in the corresponding actual molded product, the voids predicted by the conventional method, and the voids predicted by the present method.

[0177] exist Fig.13 The upper part of A shows the X-ray CT of the actual molded product when the gate is set to gate1. Fig.13 The upper part of A is Fig. 9 The same as B.

[0178] exist Fig.13 The lower part of A shows the X-ray CT of the actual molded product when the gate is set to gate2. Fig.13 The lower part of A is Fig. 9 The same as C.

[0179] exist Fig.13 The upper part of B shows Comparative Example 1 using the conventional method of performing only flow analysis when the gate is set to gate 1.

[0180] exist Fig.13 The lower part of B shows Comparative Example 1 using the conventional method of performing only flow analysis when the gate is set to gate 2.

[0181] exist Fig.13 The upper part of C shows Comparative Example 2 in which a coupled analysis of flow analysis and structural analysis is performed when the gate is set to gate1 (however, the pressure gradient in the mold cavity is not corrected).

[0182] exist Fig.13 The lower part of C shows Comparative Example 2 in which a coupled analysis of flow analysis and structural analysis is performed when the gate is set to gate2 (however, correction of the pressure gradient in the mold cavity is not performed).

[0183] exist Fig.13 The upper part of D shows Example 2 using Improved Method 2 when the gate is set to gate1.

[0184] exist Fig.13 The lower part of D shows Example 2 using Improved Method 2 when the gate is set to gate2.

[0185] (Comparison when the gate is set to gate1)

[0186] As mentioned above, in Fig.13 The upper part of A (actual molded product) is attached Fig. 9 This is an enlarged view of the vicinity of feature 1 (the portion surrounded by a quadrilateral) of A. Feature 1 is located near gate 1. No gap is seen near feature 1.

[0187] exist Fig.13 In the upper part of B (Comparative Example 1), voids are predicted near all four protruding features, namely, Features 1 to 4.

[0188] exist Fig.13 In the upper part of C (Comparative Example 2), a gap is predicted near Feature 1.

[0189] exist Fig.13 In the upper part of D (Example 2), no gap is predicted near feature 1.

[0190] Therefore, in Comparative Example 1, voids are generated in the vicinity of all the features 1 to 4, and the difference between the void generation sites and the actual molded product becomes large.

[0191] In Comparative Example 2 as well, voids were generated near Feature 1, and there was a deviation from the void generation location in the actual molded product.

[0192] In Example 2, no voids are generated near Feature 1, and the actual void generation phenomenon can be expressed with high accuracy.

[0193] (Comparison when the gate is set to gate2)

[0194] As mentioned above, in Fig.13 The lower part of A (actual molded product) is attached Fig. 9 Enlarged view of the vicinity of feature 1 and feature 2 of A (both are parts surrounded by quadrilaterals). Feature 1 is close to "gate1". Feature 2 is close to "gate2". A gap can be seen near feature 1. No gap can be seen near feature 2.

[0195] exist Fig.13 In the lower part of B (Comparative Example 1), no gap is predicted near Feature 1.

[0196] exist Fig.13 In the lower part of C (Comparative Example 2), a gap is predicted near feature 1. A gap is predicted near feature 2 which is near gate 2.

[0197] exist Fig.13 In the lower part of D (Example 2), a gap is predicted near feature 1. No gap is predicted near feature 2 which is near gate 2.

[0198] Therefore, in Comparative Example 1, since no voids are generated near Feature 1, the difference between the void generation location and the actual molded product becomes large.

[0199] In Comparative Example 2 as well, voids were generated near Feature 2, and there was a deviation from the void generation location in the actual molded product.

[0200] In Example 2, voids are generated near Feature 1 and no voids are generated near Feature 2, so the actual void generation phenomenon can be expressed with high accuracy.

[0201] (Evaluation of gap prediction for flange type)

[0202] Based on the prediction of void generation when the gate is gate1 or gate2, Comparative Example 2 in which the coupling analysis is performed shows the void generation phenomenon better than Comparative Example 1.

[0203] Compared with Comparative Examples 1 and 2, Example 2 exhibits the void generation phenomenon better.

[0204] (Example 3 - Window Lifter Type)

[0205] Fig.14 This is the second shape example (window regulator type) involved in Example 3. Fig.14 A and B (hereinafter referred to as Fig.14 A and Fig.14 In B), a three-dimensional CAD shape of a window regulator is shown ( Fig.14 A) and X-ray CT of actual molded products ( Fig.14 B).

[0206] Fig.14 Figure A shows a 3D CAD shape of a window regulator. Protruding features can be seen (features 5 to 7).

[0207] Fig.14 B is an X-ray CT of an actual molded product obtained by injection molding from the gate of the "gate" in the figure. Feature 5 is near the gate. No voids are seen near feature 5.

[0208] (Window regulator type embodiment)

[0209] The injection molding conditions of the actual molded product and the analysis conditions of the present method are shown in Table 3. In Example 3, the physical property values ​​of the thermoplastic resin were set to be the same as those of the actual molded product.

[0210] [Table 3]

[0211]

[0212] exist Fig.15 The analytical model used in Example 3 is shown in FIG. The three-dimensional CAD shape of the injection molded product is divided into small elements to create an analytical model ( Fig.15 ).

[0213] In the step (S11) of correcting the pressure gradient in the mold cavity, the pressure distribution Pa(t) at the time of VP switching is corrected by equation (1), and the volume shrinkage calculation pressure Pc used in the calculation of the volume shrinkage distribution is calculated. In equation (1), α=10 is assumed.

[0214] (Comparative Example 1 of Window Lifter Type)

[0215] In Comparative Example 1 (refer to Fig.17In B), the same physical property values ​​of the thermoplastic resin as in Example 3 (excluding the temperature dependence of the elastic modulus, etc.) and the same analysis conditions are used, and the same analysis model as in Example 3 is not coupled for analysis, but the prediction of voids is performed based on the value of the volume shrinkage distribution calculated by flow analysis.

[0216] Fig.16 It is used for Fig.14 The pressure distribution obtained by the conventional method is explained by the shape of A. During the pressure holding process from the time when the internal pressure of the mold cavity is maximum, the pressure becomes substantially uniform throughout the entire analytical model, and there is almost no pressure gradient.

[0217] (Comparative Example 2 of Window Lifter Type)

[0218] In Comparative Example 2 (ref. Fig.17 C), using the same physical properties of the thermoplastic resin as in Example 3 (including the temperature dependence of the elastic modulus, etc.) and the same analysis conditions, a coupled analysis is performed on the same analysis model as in Example 3, and the voids are predicted based on the strain obtained by the structural analysis.

[0219] In Comparative Example 2, the pressure gradient in the mold cavity was not corrected.

[0220] (Comparison of gap prediction for window regulator type)

[0221] Fig.17 It is for Fig.14 Comparison of the gaps in the shape examples. Fig.17 A to D (hereinafter referred to as Fig.17 A to Fig.17 D) is respectively shown with Fig.14 A graph comparing the voids in the corresponding actual molded product, the voids predicted by the conventional method, and the voids predicted by the present method.

[0222] exist Fig.17 A shows the X-ray CT of the actual molded product. Fig.17 A and Fig.14 The same as B.

[0223] exist Fig.17 B shows Comparative Example 1 using the conventional method of performing only flow analysis.

[0224] exist Fig.17 C shows Comparative Example 2 in which a coupled analysis of flow analysis and structural analysis is performed (however, the pressure in the mold cavity is not corrected).

[0225] exist Fig.17 In D, Example 3 using improved method 2 is shown.

[0226] (Comparison of gap generation)

[0227] As mentioned above, in Fig.17 In A, Fig.14 The feature 5 of A is near the gate. Although no gap is seen near the feature 5 (the portion surrounded by the quadrilateral in the upper center), a gap is formed in the lower left portion (the portion surrounded by the quadrilateral in the lower left) which is far from the gate.

[0228] exist Fig.17 In B, since the amount of voids generated in the lower left portion far from the gate is small, there is a deviation from the amount of voids generated in the actual molded product.

[0229] exist Fig.17 In C, gaps are predicted almost entirely including the vicinity of feature 5.

[0230] exist Fig.17 In D, no gap is predicted near feature 5, but a gap is predicted in the lower left part far away from the gate.

[0231] Therefore, in Comparative Example 1, the predicted voids are smaller than those in the actual molded product as a whole, and the difference between the predicted void generation amount and the actual molded product becomes larger.

[0232] In Comparative Example 2 as well, voids were generated near Feature 5, and there was a deviation from the void generation location in the actual molded product.

[0233] In Example 3, no voids are generated near Feature 5, and voids are predicted throughout the entirety as in an actual molded product. Therefore, the actual void generation phenomenon can be expressed with high accuracy.

[0234] (Evaluation of gap prediction)

[0235] According to the gap prediction when the flange type is used and the gate is gate1 or gate2, and the gap prediction of the window regulator type, Example 3 shows the gap generation phenomenon better than Comparative Examples 1 and 2.

[0236] (Methods to reduce gaps)

[0237] The present disclosure also includes a method for reducing voids generated inside an injection-molded product obtained by injecting a thermoplastic resin into a mold.

[0238] That is, the method of predicting the void generation behavior described above is repeated while predicting the void amount while changing one or more of the design, molding conditions, and molding materials until the predicted void amount decreases to or below a predetermined amount.

[0239] The present disclosure is not limited to the above-described embodiments, and includes various modifications of the above-described configurations by adding, deleting, or converting the components. In addition, the embodiments can be combined in various ways.

[0240] In particular, in the present disclosure, the shapes, materials, or conditions should not be interpreted as being limited to the above-described embodiments or examples.

[0241] In addition, a program for causing one or more processors to execute the method for predicting the generation of gaps or the method for reducing gaps according to the present disclosure is also included in the present disclosure. The program can also be recorded in a computer-readable non-transitory storage medium and provided.

Claims

1. A method for predicting the generation behavior of voids generated inside an injection molded product obtained by injecting a thermoplastic resin into a mold, the method comprising the following steps: creating an analytical model by dividing the injection molded product into a plurality of elements; determining a temperature distribution and a pressure distribution of the analytical model in a step of molding a thermoplastic resin; Changing the temperature distribution or the pressure distribution; Calculating the elastic modulus distribution and the temperature load distribution of the analytical model based on the changed temperature distribution and the pressure distribution using previously measured data on the temperature dependency of the elastic modulus of the thermoplastic resin, data on the thermal expansion coefficient, and PVT data; calculating strain generated in each element of the analytical model by structural analysis using the elastic modulus distribution and the temperature load distribution; and The location where voids will be generated and / or the amount of voids can be predicted based on the strain.

2. The method according to claim 1, wherein: The changing step is a step of calculating the temperature distribution of the analysis model in the cooling process after mold release using the temperature distribution.

3. The method according to claim 1, wherein: The step of obtaining the temperature distribution and pressure distribution of the analysis model in the step of molding the thermoplastic resin is the following step: in the step of demolding after injecting the thermoplastic resin from the gate of the mold into the mold cavity, the temperature distribution and pressure distribution of the analysis model are obtained.

4. The method according to claim 1, wherein: In the step of calculating the elastic modulus distribution and the temperature load distribution of the analytical model, the elastic modulus distribution and the temperature load distribution are calculated with gate sealing as a starting point and with a set time elapsed from the start of injection as an end point.

5. The method according to claim 2, wherein: In the step of calculating the strain, the strain is calculated using the elastic modulus distribution and the temperature load distribution that take into account the temperature dependence calculated from the temperature distribution, starting from the time when the injection molded product is demolded after being pressure-held and cooled and ending at a set time from the start of injection.

6. The method according to claim 4, wherein: In the flow analysis of the analytical model, the gate sealing is determined by setting molding conditions so that the weight of the injection molded product is maximized and the time until the gate is sealed is minimized.

7. The method according to claim 4, wherein: The gate sealing is the time point when the temperature of the center portion of the gate reaches the flow stop temperature Ts.

8. The method according to claim 7, wherein: For the PVT data, the flow stop temperature Ts at pressure P was set to Ts=b5+b6×P using the data fitting coefficients b5 and b6 of the dual-domain Tait PVT model.

9. The method according to claim 7, wherein: The flow stop temperature Ts is set as an inflection point when cooling is performed at a cooling rate within a range of 1° C. / min to 50° C. / min in specific heat measurement.

10. The method according to claim 1, wherein: In the step of obtaining the temperature distribution and pressure distribution of the analytical model in the step of molding the thermoplastic resin, thermal conductivity obtained using a thermal conductivity measurement method called an AC steady-state method based on ISO 22007-6 is used for calculation.

11. The method according to claim 1, wherein: The changing step is a step of correcting the pressure in the mold cavity.

12. The method according to claim 11, wherein: In the step of correcting the pressure in the mold cavity, the pressure Pc used for calculation is calculated by the following formula (1) using the pressure correction coefficient α and the time t from the start of injection, Pc=α·Pa(t)…(1) In the above formula (1), Pc is the pressure used for calculating the volume shrinkage rate, Pa(t) is the pressure obtained by flow analysis, α is the pressure correction coefficient, and t is the time from the start of injection.

13. The method according to claim 12, wherein: In the step of correcting the pressure in the mold cavity, the pressure correction coefficient α is set in the range of 0 to 30, the time t is set to the time when the difference between the maximum pressure and the minimum pressure in the mold cavity becomes the maximum, and the pressure Pc used for calculation is calculated by the formula (1).

14. The method according to claim 11, wherein: In the step of calculating the strain, an elastic modulus distribution taking into account temperature dependence is calculated based on the temperature distribution starting from a certain time point when the injection molded product is pressurized and cooled between gate sealing and demolding and ending at a certain time point before demolding.

15. A method for reducing voids generated inside an injection molded product obtained by injecting a thermoplastic resin into a mold, wherein: The method according to claim 1 is repeated to predict the void amount while changing one or more of the design, molding conditions, and molding materials until the predicted void amount decreases to or below a predetermined amount. 16 . A computer-readable storage medium storing a program for causing a computer to execute the method according to claim 1 .

17. A computer-readable storage medium storing a program for causing a computer to execute the method according to claim 15.

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