JP2006168132A - Injection molding simulation method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an injection molding simulation method which makes it possible to analyze the refractive index distribution of an optical element molded by injection molding with high precision in a short time. <P>SOLUTION: The injection molding simulation method is equipped with at least a first memory part 1 for storing the first molding condition 2 and first shape data 3 of the optical element used in the analysis of a numerical value, a shape data forming part 4 for forming the first shape data 3 from the first molding condition 2 by the analysis of the numerical value, a second memory part 5 for storing the second molding condition 6 and second shape data 7 of the optical element molded by injection molding, a shape data comparing part 8 for comparing the first shape data 3 with the second shape data 7, a correction part 9 for correcting the first molding condition 2 corresponding to a comparison result and a refractive index distribution calculating part 10 for calculating the refractive index distribution based on the corrected first molding condition 2. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an injection molding simulation method.

  In recent years, injection molding simulation has been widely used for shortening the production start-up period of plastic products and countermeasures for production defects. In addition, with regard to optical elements such as plastic lenses and prisms, injection molding simulation software has been actively developed, and it is possible to analyze and display the refractive index distribution of the optical elements.

  By calculating the refractive index distribution using injection molding simulation software, it is possible to analyze the optical performance from the refractive index distribution, and predict the optical performance of the desired optical element without actually creating the optical element. It becomes possible to do.

  However, the existing injection molding simulation software can easily obtain the analysis results of the surface shape and refractive index distribution simply by inputting the molding conditions, but for example, a number of approximate calculations to ensure practical calculation speed. As a result, errors accumulate due to differences in molding machine, screw, mold structure, and the like used, and the accuracy required when evaluating performance as an actual optical element cannot be obtained.

Therefore, when evaluating performance as an optical element, the analysis input parameters such as molding conditions are not input as they are, but values corrected according to the molding system to be used, the molding dimensions of the desired optical element, etc. It is common to ensure accuracy by inputting.
JP 2000-258292 A “Injection molding encyclopedia, industry research committee encyclopedia publication center, 2002, p.485” “Injection Molding Encyclopedia, Industry Research Council Encyclopedia Publishing Center, 2002, p. 468”

  As described above, when simulating the surface shape of an optical element, the analysis input parameters used in the injection molding simulation software by comparing the surface shape of the actually molded optical element with the surface shape of the simulation result It is common to make corrections.

  Therefore, for the refractive index distribution, the refractive index distribution of the actually molded optical element is compared with the refractive index distribution of the simulation result, and the refractive index distribution of the actually molded optical element matches the refractive index distribution of the simulation result. The analysis input parameters may be corrected so that the error is within the allowable range.

However, unlike the surface shape, the refractive index distribution of the optical element is distributed three-dimensionally inside the optical element, so it is very difficult to measure the refractive index distribution three-dimensionally.
For example, since the refractive index can be calculated from the density by using the following well-known Lorentz-Lorenz equation, the refractive index distribution can be obtained from the density distribution. However, although the average density of the optical element itself can be obtained from its weight and volume, it is impossible to easily measure the density distribution.

Here, n: refractive index, ρ: density, A: constant.
Further, since the correlation between the resin pressure, specific volume (reciprocal of density), and resin temperature is represented by a PVT diagram (P: resin pressure, V: volume, T: resin temperature), pressure distribution and temperature distribution From this, the density distribution can be obtained. However, methods for measuring the pressure distribution include a method of measuring via a pressure transmission pin and a method of measuring with an internal pressure sensor using a crystal piezoelectric element (Non-Patent Document 1), but the pressure distribution on the cavity surface portion. Can only be measured. In addition, as a method of measuring the temperature distribution, there is a method of measuring the temperature inside the resin with a thermocouple (Non-Patent Document 2). However, since the heat escape to the mold is too large, a reliable measurement value is obtained. Difficult to get.

Patent Document 1 discloses a method of measuring the refractive index distribution three-dimensionally, but has a problem that it takes time.
The present invention has been made in view of the above-described problems, and a problem to be solved is an injection that enables a refractive index distribution of an optical element to be molded by injection molding to be analyzed in a short time and with high accuracy. It is to provide a molding simulation method.

  In order to solve the above problems, an injection molding simulation method according to the present invention numerically analyzes an optical element generated by injection molding based on a first molding condition, and generates first shape information related to the optical element. The first shape information generation processing stored in the first storage unit, the first shape information read from the first storage unit, and the shape information read from the second storage unit, Shape information comparison processing for comparing the second shape information of the optical element molded based on the second molding condition by molding, and the first molding condition so that the comparison result falls within a predetermined range. And a refractive index distribution calculation process for numerically analyzing a density distribution of the optical element molded under the corrected first molding condition and calculating a refractive index distribution from the density distribution. At least to the information processing device Characterized in that to the row.

  In order to solve the above problem, the present invention performs numerical analysis on an optical element generated by injection molding based on the first molding condition, generates first shape information related to the optical element, and performs first analysis. The first shape information generation unit stored in the storage unit, the first shape information read from the first storage unit, and the shape information read from the second storage unit, which are second by injection molding. A shape information comparison unit for comparing the second shape information of the optical element molded based on the molding conditions of the first correction, and a correction for correcting the first molding conditions so that the comparison result is within a predetermined range. And a refractive index distribution calculating unit that numerically analyzes a density distribution of the optical element molded under the corrected first molding condition and calculates a refractive index distribution from the density distribution. Characteristic injection molding simulation device It may be.

  As described above, according to the present invention, it is possible to analyze the refractive index distribution of an optical element molded by injection molding in a short time and with high accuracy.

Hereinafter, embodiments of the present invention will be described with reference to FIGS.
FIG. 1 shows a principle diagram of an injection molding simulation apparatus according to the present embodiment.
The injection molding simulation apparatus shown in FIG. 1 includes a first storage unit 1 that stores molding conditions (first molding conditions 2) and shapes (first shape information 3) of optical elements used for numerical analysis, A shape information generation unit 4 for generating first shape information 3 from numerical molding conditions 1 by numerical analysis, molding conditions for optical elements actually molded by injection molding (second molding conditions 6), and shapes (first The second shape information 7), the shape information comparison portion 8 for comparing the first shape information 3 and the second shape information 7, and the first molding according to the comparison result. A correction unit 9 that corrects the condition 2 and a refractive index distribution calculation unit 10 that calculates a refractive index distribution based on the corrected first molding condition 2 are provided.

  The first storage unit 1 performs a first molding condition 2 which is a molding condition for analyzing molding of an optical element by injection molding simulation, and an injection molding simulation of the optical element under the first molding condition 2. The first shape information 3 which is information on the shape of the optical element obtained by the execution is stored.

  The shape information generation unit 4 reads the first forming condition 2 from the first storage unit 1 and performs an injection molding simulation, and stores the shape of the optical element (first shape information 3) in the first storage unit 1. To do.

  The second storage unit 5 measures the second molding condition 6 which is a molding condition for actually molding the optical element by injection molding, and the shape of the optical element generated under the second molding condition 6. The obtained second shape information 7 is stored.

The shape information comparison unit 8 reads and compares the first shape information 3 and the second shape information 7 from the first storage unit 1 and the second storage unit 5 respectively, and notifies the correction unit 9 of the comparison result. To do.
The correction unit 9 refers to the comparison result from the shape information comparison unit 8 and corrects the first molding condition 2 so that the error between the first shape information 3 and the second shape information 7 is within an allowable range. And the corrected first molding condition 2 is set.

  The refractive index distribution calculation unit 10 reads the corrected first forming condition 2 and performs an injection molding simulation to calculate the density distribution of the optical element. For example, the density is calculated using a generally known Lorentz-Lorenz equation. The refractive index distribution is calculated from the distribution.

  Here, the injection molding simulation apparatus according to the present embodiment is realized by a general information processing apparatus. That is, a CPU for performing numerical analysis, a volatile memory for storing data necessary for numerical analysis, an input device for inputting data, an output device for outputting data, a program and data This is realized by an information processing apparatus (hereinafter referred to as “analysis apparatus”) including at least an external recording apparatus for recording.

  Therefore, the shape information generation unit 4, the shape information comparison unit 8, the correction unit 9, and the refractive index distribution calculation unit 10 shown in the figure are mainly executed by causing a CPU provided in the analysis apparatus to execute a program describing a predetermined process. It is possible to realize.

  The first storage unit 1 and the second storage unit 5 are realized by a volatile memory (for example, RAM, hereinafter simply referred to as “memory”) or an external storage device (for example, a magnetic disk) provided in the analysis apparatus. It is possible.

  In addition, although the main body of the process of the injection molding simulation apparatus according to the present embodiment described below is a CPU provided in the apparatus, the shape information generation unit 4, the shape information comparison unit 8, and the correction unit are provided for the sake of simplicity. 9 and the refractive index distribution calculation unit 10 will be described as the subject of processing.

FIG. 2 shows a configuration example of an optical element (hereinafter simply referred to as a “molded product”) made of a substantially square parallel plate having a thickness of 3 mm actually generated by injection molding used in this embodiment.
The molded product 13 shown in the figure is a parallel flat plate that includes a first optical surface 11 and a second optical surface 12, and the first optical surface 11 and the second optical surface 12 are in a parallel relationship with each other.

FIG. 3 shows a configuration example of an analysis target to be analyzed by the injection molding simulation according to the present embodiment.
The analysis object shown in FIG. 2 is the shape of the molded product 13 shown in FIG. 2, the shape of the molded product with a flow path with the gate 14, the runner 15, and the sprue 16.

Hereinafter, the injection molding simulation process according to the present embodiment will be described with reference to the flowchart of FIG.
FIG. 4 is a flowchart showing a process of injection molding simulation according to the present embodiment.

  In step S401, the operator or the like actually molds the molded product 13 shown in FIG. 2 by injection molding. At this time, molding is performed by setting conditions necessary for molding including a holding pressure value shown in Table 1 and injection resin temperature (second molding condition 6) as molding conditions.

  And the surface shape of the 1st optical surface 11 and the 2nd optical surface 12 of the shape | molded molded product 13 is measured using an interferometer, a contact-type measuring device, etc., and PV (Peak to Valley) value is calculated from a measurement result. . The PV value is a value indicating the maximum shape error with respect to the ideal surface.

  Here, examples of interference fringes of the first optical surface 11 and the second optical surface 12 of the molded product 13 measured by the interferometer are shown in FIGS. 5 and 6, respectively. Further, the PV values at this time were 1.2 μm for the first optical surface 11 and 1.1 μm for the second optical surface 12, respectively, so that the central portions of both the first optical surface 11 and the second optical surface 12 were concave. You can see that

Further, the volume and weight of the molded product 13 are measured, and the average density is calculated from the measurement result. In the molded product 13 according to this example, the average density was 1.19 g / cm ³ .
When the above processing is completed, the operator or the like can perform the molding conditions shown in Table 1 (second molding conditions 6), the average density, the interference fringe shape (surface shape) shown in FIGS. 5 and 6, and PV. The second shape information 7 including the value is stored in the second storage unit 5 of the injection molding simulation apparatus using an input unit (not shown).

  An operator or the like causes the injection molding simulation apparatus to start an injection molding simulation when the collection of data relating to the molded product 13 and the input to the injection molding simulation apparatus are completed in the process of step S401.

  First, in step S402, the shape information generation unit 4 reads out the molding conditions (first molding condition 2) stored in advance in the first storage unit 1, and further, the molded product with flow path shown in FIG. An analysis model in which the shape is divided into a plurality of pieces (for example, data obtained by dividing the shape of the molded product with flow path in order to perform analysis by the finite element method) is read from a storage unit (not shown).

  Note that the analysis model may be stored in the storage unit in advance by an operator or the like generating data on the shape of the molded product with a flow path shown in FIG. 3 using a tool such as a three-dimensional modeler and dividing the mesh. In step S402 according to the present embodiment, the same information as the second molding condition 6 is used as the initial value of the first shape information 3.

  The injection molding process (deformation analysis) is performed using an analysis model by an analysis method of a finite element method generally used for the injection molding processing of the molded product shape with a flow path in the first molding condition 2, and the displacement Calculate the amount. Further, the shapes of the first optical surface 11 and the second optical surface 12 are calculated based on the calculated displacement amount.

  Through the above processing, the shapes of the first optical surface 11 and the second optical surface 12 shown in FIGS. 7 and 8 (hereinafter referred to as “surface shape”) are obtained. 7 and 8 show the differences from the planes of the first optical surface 11 and the second optical surface 12 in a contour diagram, respectively, and both the first optical surface 11 and the second optical surface 12 have a recessed central portion. I understand. The PV values at this time were 2.4 μm for the first optical surface 11 and 2.3 μm for the second optical surface 12.

Further, the average density of the entire molded product is calculated from the density and volume of each cell (each cell of the analysis model mesh-divided for the finite element method analysis) after the deformation of the surface shape. As a result of analysis, the average density was 1.54 g / cm ³ .

The surface shape, PV value, and average density obtained by the above processing are stored in the first storage unit 1 as the first shape information by the shape information generation unit 4.
Here, the above-described injection molding simulation can be realized by using generally used software for injection molding simulation (or a part of its function).

When the calculation processing of the surface shape, PV value, and average density of the molded product with flow path is completed by the above processing, the analysis apparatus proceeds to step S403.
In step S <b> 403, the shape information comparison unit 8 stores the first shape information 3 (surface shape, PV value, and average density) stored in the first storage unit 1 and the second storage unit 5. The second shape information 7 (surface shape, PV value, and average density) is read and compared.

  For example, in order to compare the surface shapes, a contour diagram is generated by image processing from the interference fringes measured in the processing of step S401 (surface shape in the second shape information 7 shown in FIGS. 5 and 6), Contour lines may be extracted from the generated contour map and the contour map (surface shape in the first shape information 3 shown in FIGS. 7 and 8) obtained by the processing in step S402, and the contour line shapes may be compared.

In the process of step S401, a contour map may be directly generated on the optical surface using a contact-type measuring device, and the contour map obtained by the process of step S402 may be compared with the contour line.
Further, the comparison of the contour line shape is performed by, for example, calculating an error of the contour line in the surface shape of the first shape information 3 with respect to the contour line in the surface shape of the second shape information 7. You may judge that it is the same.

  As a result of comparison, the surface shapes shown in the present example (FIGS. 5 and 6 and FIGS. 7 and 8) have the same surface tendency, but it can be confirmed that the PV value is larger in the analysis result. It can also be seen that the average density is greater in the analysis result.

  In step S404, the correction unit 9 has the same trend of the surface shape of the optical element used in the present embodiment from the result of the process of step S403, and therefore the resin temperature distribution and the resin pressure distribution only match the actual molding. The injection resin temperature and the pressure holding value, which are the first molding condition 2, are corrected as shown in Table 2 below, for example.

  In the above description, the case where the surface shape tendency (or the surface shape) coincides has been described. However, also in the case where there is a difference in the surface shape tendency, the injection resin temperature, In addition, the holding pressure value may be corrected.

  When the correction of the injection resin temperature and the holding pressure value is completed by the above process, the process proceeds to step S405, the shape information generation unit 4 performs the same process as step S402, and the corrected injection resin temperature, The surface shape, PV value, and average density (first shape information 3) are calculated using the holding pressure value.

As a result, there is no change in the surface shape tendency of the first optical surface 11 and the second optical surface 12, the PV value of each optical surface is 1.8 μm, 1.7 μm, and the average density is 1.37 g / cm ^3. It became.
When the surface shape, PV value, and average density are calculated by the above processing, the processing proceeds to step S406, and the first shape information 3 and the second shape information 7 are stored in the storage unit 1, as in step S403. 5 is read out and compared.

That is, it is determined whether an error between the molded product data and the analysis result is within an allowable range (PV value ± 0.5 μm, average density ± 0.1 g / cm ³ ). The process proceeds to step S407, and if it is outside the allowable range, the process proceeds to step S404, and the processes in steps S404 to S406 are performed until the error between the molded product data and the analysis result falls within the allowable range.

  For example, since the error between the above-described molded product data and the analysis result is not within the allowable range, the process proceeds to step S404, and the holding pressure value is corrected as shown in Table 3, and step S405 is performed. The average density and surface shape are calculated by this process.

As a result, the shapes of the first optical surface 11 and the second optical surface 12 are as shown in FIGS. 9 and 10 are contour views similar to FIGS. 7 and 8, and both the first optical surface 11 and the second optical surface 12 are recessed at the center. The PV values were 1.2 μm for the first optical surface 11 and 1.1 μm for the second optical surface 12. The average density was 1.21 g / cm ³ .

Therefore, in the process of step S406, it is determined that the error between the molded product data and the analysis result is within the allowable range, and the process proceeds to step S407.
In the above description, as in step S404, the case where the surface shape tendency (or surface shape) is the same has been described. And the holding pressure value may be corrected.

  Here, as described above, regarding the surface shape, the PV value, and the average density, the difference between the actually measured value (second shape information 7) and the analysis result (first shape information 3) is within the setting allowable error range. The reason why the parameter (first molding condition 2) that affects the pressure distribution and the temperature distribution is corrected so as to enter is as follows.

  The surface shape results from the difference between the surface shape of the mold and the shrinkage rate. This difference in shrinkage represents a difference in volume. Therefore, it can be seen from the PVT diagram that the surface shape results from the resin temperature difference and the resin pressure difference. That is, if the surface shapes match, it is considered that the resin temperature difference and the resin pressure difference match.

  The average density is the reciprocal of the specific volume, and the specific volume depends on the resin temperature and the resin pressure from the relationship of the PVT diagram. Therefore, the average density depends on the average resin temperature and the average resin pressure. That is, if the average densities match, it is considered that the average resin temperature and the average resin pressure of the optical elements match.

Therefore, if the surface shape and the average density match, it can be determined that the resin temperature distribution and the resin pressure distribution are appropriate.
When the first molding condition 2 corresponding to the second molding condition 6 is determined by the above process, the process proceeds to step S407, and the first molding condition 2 and the second molding condition are determined by the correction relational expression determination process. The correction method (correction relational expression) is determined based on the relationship with 6.

  For example, the linear form is determined from the relationship between the holding pressure value under the first molding condition 2 (see Table 3) and the holding pressure value under the second molding condition 6 (see Table 1). Since the holding pressure value (Y) of the first molding condition 2 is ½ of the holding pressure value (X) of the second molding condition 6, a relational expression of Y = (1/2) * X Is obtained.

  Similarly, the linear form is determined from the relationship between the injection resin temperature under the first molding condition 2 (see Table 3) and the injection resin temperature under the second molding condition 6 (see Table 1). From Table 1 and Table 3, the injection resin temperature (Y) in the first molding condition 2 is a relationship in which the injection resin temperature (X) in the second molding condition 6 is linearly shifted by 10 ° C. Therefore, Y = A relational expression of X + 10 is obtained.

However, it is not intended to be limited to the correction relational expression described above, and the relational expression may be determined by a combination of functions as necessary.
When the correction relational expression is determined in step S407, the process proceeds to step S408, and the refractive index distribution calculation unit 10 calculates the density distribution. In this case, the correction unit 9 reads the second molding condition 6 from the second storage unit 5, corrects the holding pressure value and the injected resin temperature using the correction relational expression determined in step S406, and the first Is stored as the first molding condition 2.

  Then, the refractive index distribution calculation unit 10 calculates a density distribution from the analysis model based on the first molding condition 2, and calculates the refractive index distribution from the density distribution using the Lorentz-Lorenz equation shown in Equation (1). Will be calculated.

  In the present embodiment, polycarbonate is used as the material of the molded product 13, and therefore a value of 0.2439494 is used for the constant A shown in the equation (1). The constant A can be calculated if the refractive index and density of a material having a uniform density are known.

  FIG. 11 shows the calculated refractive index distribution. FIG. 11 shows the average value of the refractive index in the thickness direction in a contour diagram. The average value of the refractive index is 1.49832 and the refractive index difference is 38 / 100,000.

In addition, although the average density of the whole optical element was measured in step S401, it may cut out partially and may process step S401-S406 about an optical element.
In the above description, the correction relational expression is determined in step S407, but the process in step S407 may be omitted. That is, after the processing of steps S401 to S406, in step S408, the correction unit 9 reads the second molding condition 6 from the second storage unit 5, and further stores a correction relational expression prepared in advance. Read from. Then, the second molding condition 6 (for example, the pressure holding value and the injection resin temperature) is corrected using the read relational expression, and is stored as the first molding condition 2 in the first storage unit 1. Further, the refractive index distribution calculation unit 10 calculates the density distribution from the analysis model based on the first molding condition 2, and calculates the refractive index distribution from the Lorentz-Lorenz equation shown in Equation (1). That's fine.

  Even if the three-dimensional refractive index distribution inside the optical element cannot be measured by the above processing, the refractive index distribution can be calculated by the surface shape and PV value that can be measured by the interferometer and the average density that can be easily measured. Necessary analysis input parameters can be corrected. By performing an injection molding simulation using the corrected analysis input parameters, the refractive index distribution of the optical element (molded product) to be molded can be increased in a short time. It is possible to predict with accuracy.

  In addition, since it is possible to evaluate the refractive index distribution of the molded product before actually molding the optical element, the mold is actually fabricated and the optical element is molded by injection molding to evaluate the optical performance. If the required optical performance cannot be obtained, it is possible to shorten the optical element start-up period by omitting the steps of correcting the mold and changing the material.

In the processing of steps S401 to S407 described above, the correction relational expression is determined using the same molding condition of the molded product having the same shape, but the present invention is not limited to this.
For example, the correction relational expression may be determined using a plurality of different molding conditions for a molded product having the same shape.

  That is, in step S401, the molded product 13 shown in FIG. 2 is molded by injection molding under a plurality of molding conditions (second molding condition 6, for example, holding pressure value, injection resin temperature), and each molded product is molded. The surface shape, PV value, and average density of the product 13 are measured.

  Then, the first molding condition 2 is obtained for each second molding condition 6 by the processing in steps S402 to S406, and further, the second molding condition 6 obtained in step S401 and steps S402 to S406 are obtained in step S407. A correction relational expression is determined by extracting a function from the relationship with the first molding condition 2 obtained by the above process.

  For example, as shown in FIG. 12, a plurality of coordinate points (X, X) of the second molding condition 6 (X) obtained in step S401 and the first molding condition 2 (Y) obtained in the processes of steps S402 to S406. From Y), the correction relational expression may be determined by functioning using the least square method or the like.

Although FIG. 12 shows only the holding pressure value, the correction relational expression can be similarly determined for other molding conditions (for example, the injected resin temperature).
The refractive index distribution can be calculated in step S408 using the correction relational expression obtained by the above processing.

  As a result, even when the mutual relationship between the first molding condition 2 and the second molding condition 6 is non-linear, the first molding condition 2 can be obtained with high accuracy, and the accuracy of refractive index distribution calculation is improved. be able to.

Further, the correction relational expression may be determined using a plurality of different molded products.
For example, in step S401, the molded product 13 shown in FIG. 2, the molded product 14 of the lens shown in FIG. 13 whose two convex surfaces are two aspherical surfaces, and the molded product 15 of the triangular prism shown in FIG. The surface shape, the PV value, and the average density of each molded product are measured by injection molding under the molding condition 6.

  Then, the first molding condition 2 corresponding to the second molding condition 6 is obtained for each of the molded product 13, the molded product 14, and the molded product 15 by the processing of steps S402 to S406. A correction relational expression is determined by extracting a function from the relationship between the second molding condition 6 obtained in step 1 and the first molding condition 2 obtained in the processes of steps S402 to S406.

  For example, as shown in FIG. 15, the second molding condition 6 (X) obtained in step S401 and the first molding condition obtained in steps S402 to S406 in the molded product 13, the molded product 14, and the molded product 15. What is necessary is just to obtain | require a correction | amendment relational expression by function-izing using the least squares method etc. from the coordinate point (X, Y) of 2 (Y).

  Further, as shown in FIG. 16, for each of the molded product 13, the molded product 14, and the molded product 15, a first molding condition 2 for a plurality of different molding conditions (second molding condition 6) is calculated, and a correction relational expression May be determined.

  That is, in step S401, the molded product 13, the molded product 14, and the molded product 15 are molded by injection molding under a plurality of different molding conditions (second molding conditions 6), and the second molding is performed by the processing in steps S402 to S406. The first molding condition 2 corresponding to the condition 6 is obtained (measurement of the surface shape of the molded product 14 and the molded product 15 is measured with a three-dimensional measuring device or the like).

  Then, by the process of step S407, from the coordinate point (X, Y) of the second molding condition 6 (X) obtained in step S401 and the first molding condition 2 (Y) obtained in the processes of steps S402 to S406. What is necessary is just to obtain | require a correction | amendment relational expression by functionalizing using the least squares method etc.

  FIG. 16 shows only the case where three second molding conditions 6 (holding pressure values) are used for each of the molded article 13, the molded article 14, and the molded article 15, but other molding conditions (for example, injection resin) are shown. The correction relational expression can be similarly determined for (temperature).

Then, the refractive index distribution can be calculated in step S408 using the correction relational expression determined in step S407.
By the above processing, even when the molding conditions such as the resin temperature and the pressure holding condition change due to the difference in the molded product shape, for example, the lens thickness, a correction relational expression that does not depend on the molded product shape is determined. Therefore, the analysis accuracy of the refractive index distribution simulation is improved.

  Further, by determining a correction relational expression from a plurality of different molding conditions for a plurality of different molded products, data on the relationship between the first molding condition 2 and the second molding condition 6 as shown in FIG. Therefore, it becomes possible to determine the analysis input parameters with higher accuracy, and the simulation analysis accuracy of the refractive index distribution is further improved.

  In the present embodiment, the surface shape, the PV value, and the average density are used for the shape information (first shape information 3, second shape information 7). However, the present invention is not limited to this. Instead of the PV value indicating the difference between the highest point (Peak) and the lowest point (Valley), an RMS (Root Mean Square) value that is the standard deviation may be used.

  In this embodiment, the injection resin temperature and the pressure holding value are changed as the first molding condition 2 in order to maintain the tendency of the resin temperature distribution and pressure distribution of the optical element and to make a difference in the resin temperature and pressure. However, the present invention is not limited to this. For example, the mold temperature and the pressure holding time may be used as the shapes of the first molding condition 2 and the second optical surface 12.

  Moreover, although the average density may obtain | require the average density of the whole optical element, you may use what calculated | required the average density about the predetermined part of the optical element.

The principle figure of the injection molding simulation apparatus which concerns on a present Example is shown. It is a figure which shows the structural example of the optical element actually produced | generated by the injection molding used by a present Example. It is a figure which shows the structural example of the analysis object analyzed by the injection molding simulation which concerns on a present Example. It is a flowchart which shows the process of the injection molding simulation which concerns on a present Example. It is a figure which shows the example of the interference fringe of the 1st optical surface of the molded article which concerns on the present Example measured with the interferometer. It is a figure which shows the example of the interference fringe of the 2nd optical surface of the molded article which concerns on the present Example measured with the interferometer. It is the contour figure of the 1st optical surface computed by the numerical analysis which concerns on a present Example. It is the contour figure of the 2nd optical surface computed by the numerical analysis which concerns on a present Example. It is the contour figure of the 1st optical surface computed by the numerical analysis which concerns on a present Example. It is the contour figure of the 2nd optical surface computed by the numerical analysis which concerns on a present Example. It is a contour figure of the refractive index distribution computed by the numerical analysis concerning a present Example. It is a figure which shows the example of the correction function which concerns on a present Example. It is a side view which shows the example of the molded article used by a present Example. It is a perspective view which shows the example of the molded article used by a present Example. It is a figure which shows the example of the correction function which concerns on a present Example. It is a figure which shows the example of the correction function which concerns on a present Example.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... 1st memory | storage part 2 ... 1st shaping | molding condition 3 ... 1st shape information 4 ... Shape information generation part 5 ... 2nd memory | storage part 6 ... 2nd Molding conditions 7 ... second shape information 8 ... shape information comparison unit 9 ... correction unit 10 ... refractive index distribution calculation unit 11 ... first optical surface 12 ... second optical Surface 13 ... Molded article 14 ... Gate 15 ... Runner 16 ... Sprue

Claims (16)

A first shape information generation process for numerically analyzing an optical element generated by injection molding based on a first molding condition, generating first shape information about the optical element, and storing the first shape information in a first storage unit; ,
The first shape information read from the first storage unit and the shape information read from the second storage unit, the second shape of the optical element molded based on the second molding condition by injection molding Shape information comparison processing for comparing shape information;
Correction processing for correcting the first molding condition so that the comparison result falls within a predetermined range;
A refractive index distribution calculation process for numerically analyzing a density distribution of the optical element molded under the corrected first molding condition and calculating a refractive index distribution from the density distribution;
An injection molding simulation method characterized by causing at least an information processing device to execute. A correction relational expression determination process for determining a correction relational expression from the first molding condition and the second molding condition corrected by the correction process;
The refractive index distribution calculation process numerically analyzes a density distribution of the optical element molded under molding conditions obtained from the second molding condition and the correction relational expression, and calculates a refractive index distribution from the density distribution. The injection molding simulation method according to claim 1, wherein the injection molding simulation method is calculated.   The first molding condition and the second molding condition are configured by at least one of an injection resin temperature, a pressure holding value, a mold temperature, and a pressure holding time. Injection molding simulation method.   3. The injection molding simulation method according to claim 1, wherein the first shape information and the second shape information include an average density of an optical element and an optical surface shape.   2. The correction process according to claim 1, wherein the first molding condition y and the second molding condition x are corrected such that y = a * x with respect to a predetermined constant a. Or the injection molding simulation method of 2.   The correction process is performed such that the first molding condition y and the second molding condition x are corrected such that y = a * x + b with respect to predetermined constants a and b. Item 3. The injection molding simulation method according to Item 1 or 2.   In the correction relational expression determination process, the plurality of different first molding conditions for the same optical element are corrected by the first shape information generation process, the shape information comparison process, and the correction process. The injection molding simulation method according to claim 2, wherein a correction relational expression is determined from the first molding condition and the second molding condition corresponding to each of the first molding conditions.   In the correction relational expression determination process, the corrected first obtained by the first shape information generation process, the shape information comparison process, and the correction process for the first molding condition for a plurality of different optical elements. 3. The injection molding simulation method according to claim 2, wherein a correction relational expression is determined from the molding conditions and the second molding conditions corresponding to the first molding conditions. A first shape information generation unit that numerically analyzes an optical element generated by injection molding based on a first molding condition, generates first shape information about the optical element, and stores the first shape information in a first storage unit; ,
The first shape information read from the first storage unit and the shape information read from the second storage unit, the second shape of the optical element molded based on the second molding condition by injection molding A shape information comparison unit for comparing shape information;
A correction unit that corrects the first molding condition so that the comparison result falls within a predetermined range;
A numerical distribution analysis of the density distribution of the optical element molded under the corrected first molding condition, and a refractive index distribution calculating unit that calculates a refractive index distribution from the density distribution;
An injection molding simulation apparatus comprising: A correction relational expression determination unit that determines a correction relational expression from the first molding condition and the second molding condition corrected by the correction unit;
The refractive index distribution calculation unit numerically analyzes a density distribution of the optical element molded under molding conditions obtained from the second molding condition and the correction relational expression, and calculates a refractive index distribution from the density distribution. The injection molding simulation apparatus according to claim 9, wherein the calculation is performed.   The first molding condition and the second molding condition are configured by at least one of an injection resin temperature, a pressure holding value, a mold temperature, and a pressure holding time. Injection molding simulation equipment.   11. The injection molding simulation apparatus according to claim 9, wherein the first shape information and the second shape information include an average density of optical elements and an optical surface shape.   The correction unit corrects the first molding condition y and the second molding condition x so that a predetermined constant a has a relationship of y = a * x. Or the injection molding simulation apparatus of 10.   The correction unit corrects the first molding condition y and the second molding condition x so that a predetermined constant a and b have a relationship of y = a * x + b. Item 11. The injection molding simulation apparatus according to Item 9 or 10.   The correction relational expression determination unit is corrected by the first shape information generation unit, the shape information comparison unit, and the correction unit with respect to a plurality of different first molding conditions for the same optical element. The injection molding simulation apparatus according to claim 10, wherein a correction relational expression is determined from the first molding condition and the second molding condition corresponding to each of the first molding conditions. The correction relational expression determination unit corrects the first obtained by the first shape information generation unit, the shape information comparison unit, and the correction unit with respect to the first molding condition for a plurality of different optical elements. The injection molding simulation apparatus according to claim 10, wherein a correction relational expression is determined from the molding conditions and the second molding conditions corresponding to the first molding conditions.