System, supercritical injection molding support method, and program

Abstract

To provide a system that can calculate supercritical injection molding conditions suitable for any mold shape by generating SCF-containing material information based on the results of prototyping with a reference mold and general material information.SOLUTION: The system has one or more processors and one or more memory resources, the memory resources store general material information on materials that do not contain SCF, information on reference mold prototype results, which are prototype results using a reference mold with materials containing SCF, a molding analysis execution program to execute a molding analysis, and a material information generation program for generating SCF-containing material information. The molding analysis program performs molding analysis processing using any SCF-containing material information generated based on the general material information, and the material information generation program generates, based on the comparison of the reference mold analysis result information generated by the molding analysis processing with the reference mold prototype result information, the correct value of SCF-containing material information by changing any SCF-containing material information.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a system, a supercritical injection molding support method, and a program.

Background Art

[0002] Techniques for obtaining molding conditions for mass production by analyzing injection molding in an injection molding machine are disclosed, for example, in Patent Document 1. In the technique of Patent Document 1, an injection pressure curve for molding conditions is obtained by using the analysis result of resin flow by CAE (Computer Aided Engineering).

[0003] Specifically, Patent Document 1 states that "perform resin flow analysis in the mold by CAE or the like to obtain the resin pressure curve Ps at the resin inlet or the resin pressure curve Pn at the nozzle end of the molding machine. Perform injection (air shot) with the nozzle detached from the mold to obtain the injection pressure curve Pa detected at that time. From the injection pressure curve Pa and the resin pressure curve Ps or Pn, obtain the injection pressure command curve P as the molding conditions during mass production. By using the injection pressure curve Pa of the air shot for the resin pressure curves Ps and Pn obtained by resin flow analysis, compensate for the time delay and pressure loss due to the mechanical elements of the injection molding machine, and easily obtain the molding conditions for mass production. Also, obtain the pressure loss Ploss of the nozzle part, and obtain the injection pressure command curve P from Ploss, Pa, and Ps."

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In recent years, there has been an increasing trend in the production of products using injection molding with low-flowability resins such as bioplastics as raw materials. In injection molding using such low-flowability resins, a supercritical injection molding process is employed, which improves the quality of molded products by increasing the fluidity of the resin during molding and improving adhesion to the mold, by injecting and dissolving SCF (Supercritical Fluid) into the molten resin before molding.

[0006] On the other hand, because it is necessary to consider molding parameters that are not present in normal injection molding, such as the amount of SCF injected, there is a challenge in that it takes time to optimize the molding conditions.

[0007] Furthermore, in the technology described in Patent Document 1, the molding conditions for mass production are obtained by using the injection pressure curve of an air shot to compensate for the time delay and pressure delay caused by the mechanical elements of the injection molding machine against the resin pressure curve at the resin inlet obtained by resin flow analysis. In other words, the technology in Patent Document 1 does not take into account the changes in properties due to the mixing of SCF (supercritical fluid) with the molten resin, and it is considered difficult to obtain molding conditions suitable for the supercritical injection molding process.

[0008] This invention has been made in view of the above problems, and aims to calculate supercritical injection molding conditions suitable for any mold shape by generating SCF-containing material information based on prototype results with a standard mold and general material information. [Means for solving the problem]

[0009] The present invention includes several means for solving at least some of the above problems, but an example is as follows. A system according to one aspect of the present invention for solving the above problems is a system having one or more processors and one or more memory resources, wherein the memory resources store general material information relating to materials that do not contain SCF (Supercritical Fluid), reference mold prototype result information which is the result of prototyping using a reference mold with SCF-containing material, a molding analysis execution program that performs molding analysis, and a material information generation program that generates SCF-containing material information, wherein the molding analysis execution program performs molding analysis processing using arbitrary SCF-containing material information generated based on the general material information, and the material information generation program generates correct SCF-containing material information by changing the arbitrary SCF-containing material information based on a comparison between the reference mold analysis result information generated in the molding analysis processing and the reference mold prototype result information. [Effects of the Invention]

[0010] According to the present invention, by generating SCF-containing material information based on prototype results with a standard mold and general material information, it is possible to calculate supercritical injection molding conditions suitable for any mold shape. [Brief explanation of the drawing]

[0011] [Figure 1] This diagram shows an example of a general configuration of a processor system. [Figure 2] This is a flowchart illustrating an example of a supercritical injection molding support process. [Figure 3] This flowchart shows an example of the process for generating information on materials containing SCF (Superficial Cement Factor). [Figure 4] This is a flowchart showing an example of the injection molding condition calculation process according to the first embodiment. [Figure 5] This is a flowchart showing an example of the injection molding condition calculation process according to the second embodiment. [Modes for carrying out the invention]

[0012] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0013] <First Embodiment> The system (processor system 100) according to this embodiment is a system that supports supercritical injection molding. Specifically, the system 100 supports supercritical injection molding by generating information on materials containing SCF (Supercritical Fluid) and calculating injection molding conditions using said information.

[0014] More specifically, the system 100 generates arbitrary SCF-containing material information based on general material information and performs molding analysis processing using the generated information and arbitrary injection molding conditions as input. The system 100 also compares the analysis results with the prototype results using a reference mold and generates appropriate SCF-containing material information by repeatedly changing values ​​such as fluidity in the arbitrary SCF-containing material information until the degree of agreement between the prototype results and the analysis results falls within a predetermined range.

[0015] Furthermore, the system 100 performs quality analysis based on the generated SCF-containing material information, the mold shape of the molded product, and arbitrary injection molding conditions. The system 100 also calculates appropriate injection molding conditions when using SCF-containing material by repeatedly changing the injection molding conditions until the quality analysis results meet the quality standards.

[0016] Thus, the system 100 can calculate supercritical injection molding conditions suitable for any mold shape by generating normal (correct value) SCF-containing material information based on prototype results with a standard mold and general material information.

[0017] <Configuration of Processor System 100> FIG. 1 is a diagram showing an example of the schematic configuration of the processor system 100. As shown in the figure, this system 100 is communicably connected to the external device 10 via, for example, a communication cable or a predetermined communication network (e.g., the Internet, LAN (Local Area Network), or WAN (Wide Area Network)) N.

[0018] <<External device 10>> The external device 10 is a device that transmits input information to the processor system 100. Also, the external device 10 is a device that acquires the information generated by the processor system 100. Specifically, the external device 10 transmits various types of information used in the processes executed by the processor system 100, such as general material information, to the processor system 100. Also, the external device 10 acquires the material information with SCF generated by the processor system 100 and the calculated injection molding conditions from the processor system 100.

[0019] <000^091><<Details of the processor system 100>> The processor system 100 executes the material information generation process with SCF and the injection molding condition calculation process by the processor 30 reading various programs stored in the memory resource 40.

[0020] Note that the processor system 100 is a computer such as a personal computer, tablet terminal, smartphone, server computer, and cloud server, and is a system including at least one or more of these computers.

[0021] Specifically, the processor system 100 has a processor 30, a memory resource 40, a NI (Network Interface Device) 50, and a UI (User Interface Device) 60.

[0022] The processor 30 is an arithmetic unit that reads various programs stored in the memory resource 40 and executes the processing corresponding to each program. Examples of the processor 30 include a microprocessor, CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (Field Programmable Gate Array), or other arithmetic semiconductor devices.

[0023] The memory resource 40 is a storage device that stores various types of information. Specifically, the memory resource 40 is a non-volatile or volatile storage medium such as RAM (Random Access Memory) or ROM (Read Only Memory). The memory resource 40 may also be a rewritable storage medium such as flash memory, a hard disk, or an SSD (Solid State Drive), or a USB (Universal Serial Bus) memory, memory card, or hard disk.

[0024] NI50 is a communication device that communicates information with the external device 10. NI50 communicates information with the external device 10 via a predetermined communication network N, such as a LAN or the Internet. Unless otherwise specified below, it is assumed that information communication between the processor system 100 and the external device 10 is performed via NI50.

[0025] UI60 is an input device that inputs user (operator) instructions to the processor system 100, and an output device that outputs information generated by the processor system 100. Input devices include, for example, pointing devices such as keyboards, touch panels, and mice, and voice input devices such as microphones.

[0026] Output devices include, for example, displays, printers, and speech synthesizers. Unless otherwise specified below, user operations on the processor system 100 (e.g., inputting information, outputting information, and issuing instructions to execute processing) are performed via the UI 60.

[0027] Furthermore, some or all of the configurations, functions, and processing means of this system 100 may be implemented in hardware, for example, by designing them as integrated circuits. Also, some or all of the functions of this system 100 may be implemented in software, or through the collaboration of software and hardware. Furthermore, this system 100 may use hardware with fixed circuits, or it may use hardware in which at least some of the circuits can be modified.

[0028] Furthermore, this system 100 can also be implemented by having a user (operator) perform some or all of the functions and processes realized by each program.

[0029] Furthermore, the database (DB) and various information within the memory resource 40 described below may be files or other data structures besides databases, as long as there is an area capable of storing data.

[0030] <<General material information DB110>> The General Material Information DB110 is a database that stores general material information corresponding to multiple material model numbers. Here, general material information refers to known information registered in existing flow analysis software or material databases, etc., and includes information showing the relationship between fluidity values ​​such as the MFR (Melt Flow Rate) of the resin corresponding to the material model number, and the temperature and pressure of the molten resin. Note that the fluidity of the molten resin is proportional to the temperature and pressure, and the general material information may also be represented by a curve graph showing this proportional relationship.

[0031] <<Reference mold prototype results information 120>> The standard mold prototype result information 120 is information obtained as a result of performing supercritical injection molding (injection molding using SCF-filled material) using a standard mold having a predetermined shape (hereinafter sometimes referred to as the "standard mold"). Specifically, the standard mold prototype result information 120 includes information showing the relationship between quality information of the molded product prototyped by supercritical injection molding, injection molding conditions, and sensing information regarding the temperature, pressure, and filling speed (time taken for filling) of the molten resin into the standard mold.

[0032] Here, quality information refers to information about the quality of the molded product, and is indicated by values ​​such as the filling volume, which is how far the molten resin has filled the standard mold, and values ​​representing the state of bubble formation (bubble density and size).

[0033] Furthermore, the injection molding conditions are numerical information input to the molding machine when performing supercritical injection molding, and include at least the temperature, pressure, and SCF amount of the molten resin. In addition, the injection molding conditions may include, as necessary, information such as the timing of pressure switching, the timing of SCF injection, the position of the gate into which the molten resin is injected into the mold, the shape of the gate, and the number of gates.

[0034] Furthermore, various pieces of information, such as the volume of resin to be filled into the reference mold, the temperature and pressure of the molten resin, and the filling speed into the reference mold, are acquired by sensors installed in the reference mold that detect these values.

[0035] <<Reference mold analysis results information 130>> The reference mold analysis result information 130 is information obtained as a result of performing supercritical molding analysis using a reference mold. Specifically, the reference mold analysis result information 130 includes analysis results for items corresponding to the reference mold prototype result information 120. More specifically, the reference mold analysis result information 130 includes information showing the relationship between molded product quality information, injection molding conditions, and analysis values ​​for each item such as molten resin temperature, pressure, and filling speed into the reference mold (time taken for filling).

[0036] Such reference die analysis result information 130 is generated in the injection molding condition calculation process described later and stored in the memory resource 40.

[0037] Note that the reference die analysis result information 130 is used for comparison with the reference die prototype result information 120, and is used when determining the probability of any SCF-containing material information (SCF-containing material information generated with arbitrary initial values based on general material information) that generates the analysis result of the reference die analysis result information 130.

[0038] <<SCF-Containing Material Information DB140>> The SCF-containing material information DB140 is a database that stores a plurality of SCF-containing material information. Note that the SCF-containing material information is information indicating the characteristics of the molten resin considering the presence of SCF. Specifically, the SCF-containing material information includes the relationship between the value related to the fluidity of the SCF-containing material (resin), temperature, pressure, and SCF amount. Further, the SCF-containing material information includes the relationship between the value related to bubble generation (hereinafter sometimes referred to as "bubble generation variable"), temperature, pressure, and SCF amount.

[0039] Here, the bubble generation variable is a variable that affects the final bubble generation state of the molded product by supercritical injection molding. For example, at least one of the number of bubble generations, bubble generation rate, bubble generation probability, bubble growth rate, and bubble mobility corresponds to it.

[0040] Such SCF-containing material information is generated in the SCF-containing material information generation process described later and stored in the memory resource 40.

[0041] <<Supercritical Injection Molding Condition Information DB150>> The supercritical injection molding condition information DB150 is a database that stores a plurality of injection molding conditions calculated in the injection molding condition calculation process described later. That is, the supercritical injection molding condition information DB150 stores a plurality of injection molding conditions input to the molding machine when manufacturing a molded product by supercritical injection molding using SCF-containing material information.

[0042] <<Molding Analysis Execution Program 210>> The molding analysis execution program 210 is a program that performs molding analysis. Specifically, the molding analysis execution program 210 generates arbitrary SCF-containing material information based on general material information. The molding analysis execution program 210 also performs molding analysis processing using predetermined information, including the arbitrary SCF-containing material information, as input, and generates reference mold analysis result information 130. Any generally known techniques can be used for the molding analysis.

[0043] <<Material Information Generation Program 220>> The material information generation program 220 is a program that generates SCF-containing material information. Specifically, the material information generation program 220 generates appropriate (correct) SCF-containing material information by changing arbitrary SCF-containing material information values ​​based on a comparison between the standard mold prototype result information 120 and the standard mold analysis result information 130.

[0044] The processing performed by the molding analysis execution program 210 and the material information generation program 220 will be explained in detail later in the section on SCF-containing material information generation processing.

[0045] <<Quality Analysis Execution Program 230>> The quality analysis execution program 230 is a program that performs quality analysis. Specifically, the quality analysis execution program 230 takes the generated SCF-containing material information and arbitrary injection molding conditions as input, performs quality analysis processing, and outputs the quality analysis results.

[0046] <<Injection Molding Condition Calculation Program 240>> The injection molding condition calculation program 240 is a program that calculates injection molding conditions for supercritical injection molding using SCF-containing material information. Specifically, the injection molding condition calculation program 240 calculates appropriate (correct) injection molding conditions based on a comparison of the generated quality analysis result information with predetermined quality standards. The predetermined quality standards only need to be stored in the memory resource 40 in advance.

[0047] The processing by the quality analysis execution program 230 and the injection molding condition calculation program 240 will be described in detail in the injection molding condition calculation process described later.

[0048] As described above, the details of the processor system 100 have been described.

[0049] <Details of the Supercritical Injection Molding Support Process> FIG. 2 is a flowchart showing an example of the supercritical injection molding support process. This process is started, for example, when an execution instruction is received from an operator of the present system 100.

[0050] When the process is started, the processor system 100 acquires general material information of the material to be the generation target of the SCF-containing material information (step S10). Specifically, the processor system 100 receives, via the UI60, an input of the material type number of the material for generating the SCF-containing material information from the operator. Further, the processor system 100 acquires the general material information of the material (resin) corresponding to the input material type number from the general material information DB110.

[0051] Next, the processor system 100 generates appropriate normal SCF-containing material information based on a comparison between the analysis result of the molding analysis with arbitrary SCF-containing material information generated based on the general material information as an input and the trial production result using the SCF-containing material (step S20).

[0052] Next, the processor system 100 calculates appropriate normal injection molding conditions that satisfy the quality standards based on a comparison between the analysis result of the quality analysis with the SCF-containing material information and arbitrary injection molding conditions as inputs and the quality standards (step S30).

[0053] Also, when the processor system 100 calculates the injection molding conditions, it ends the processing of this flow.

[0054] <<SCF-Containing Material Information Generation Process>> Next, we will explain the details of the SCF-containing material information generation process corresponding to step S20.

[0055] Figure 3 is a flowchart showing an example of the SCF-containing material information generation process. First, the molding analysis execution program 210 generates arbitrary SCF-containing material information having predetermined initial values ​​based on general material information (step S21). Specifically, the molding analysis execution program 210 obtains information from the general material information that shows the relationship between values ​​related to the fluidity of the resin and the temperature and pressure of the molten resin. The molding analysis execution program 210 also associates the amount of SCF, which is an arbitrary initial value, with the said temperature and pressure. The molding analysis execution program 210 also associates the bubble formation variable, which is an arbitrary initial value, with the said temperature and pressure. As a result, arbitrary SCF-containing material information is generated that includes information showing the relationship between values ​​related to fluidity and temperature, pressure and amount of SCF, as well as information showing the relationship between bubble formation variable and temperature, pressure and amount of SCF.

[0056] Next, the molding analysis execution program 210 performs a molding analysis process based on the reference mold shape, arbitrary SCF-containing material information, and initial values ​​of the injection molding conditions (step S22). Specifically, the molding analysis execution program 210 obtains information indicating the shape of the reference mold from, for example, the reference mold prototype result information 120. The molding analysis execution program 210 also uses, for example, the reference mold prototype result information 120 to identify the injection molding conditions during prototyping using the reference mold and sets these as initial values. Then, the molding analysis execution program 210 performs a molding analysis process using the arbitrary SCF-containing material information generated in step S21, the shape of the reference mold, and the set initial values ​​of the injection molding conditions as inputs, and generates the reference mold analysis result information 130, which is the result of the analysis (step S23).

[0057] Next, the material information generation program 220 determines whether the degree of agreement between the reference mold prototype result information 120 and the reference mold analysis result information 130 is within a predetermined range (step S24). Specifically, the material information generation program 220 compares quality information (values ​​related to filling volume and bubble formation state), which are common items in both pieces of information, with the temperature, pressure, and filling speed of the molten resin into the reference mold (time taken for filling), and determines whether the degree of agreement between them is within a predetermined range.

[0058] Furthermore, since the arbitrary SCF-containing material information is generated based on general material information that does not take into account the presence of SCF, the degree of agreement between the prototype results and the analysis results is usually low. Therefore, as described later, the processor system 100 repeatedly adjusts the values ​​of the arbitrary SCF-containing material information (especially the values ​​of the fluidity and bubble formation variables) to obtain the correct values ​​of the SCF-containing material information, which increases the degree of agreement with the prototype results. In other words, this SCF-containing material information generation process can also be described as a process of determining correction values ​​to generate true (correct) SCF-containing material information based on the arbitrary SCF-containing material information generated from general material information.

[0059] If the degree of match is determined to be outside the predetermined range (No in step S24), the material information generation program 220 proceeds to step S26. On the other hand, if the degree of match is determined to be within the predetermined range (Yes in step S24), the material information generation program 220 proceeds to step S25.

[0060] In step S26, the material information generation program 220 modifies the value of the material information containing SCF and returns to step S22. Specifically, the material information generation program 220 modifies the value related to the fluidity of the resin in the information showing the relationship between the value related to the fluidity of the resin and the temperature, pressure, and amount of SCF of the molten resin. The material information generation program 220 also modifies the bubble formation variable in the information showing the relationship between the bubble formation variable and the temperature, pressure, and amount of SCF of the molten resin.

[0061] Furthermore, any known method, such as Newton's method, variational calculus, or Monte Carlo method, can be used to modify these values.

[0062] Furthermore, in the process of step S22, which is accessed via step S26, the molding analysis execution program 210 performs molding analysis again using arbitrary SCF-containing material information with modified fluidity values ​​and bubble formation variables. Since the processing in this step is the same as described above, a detailed explanation is omitted.

[0063] Furthermore, in step S25, which is accessed if the degree of agreement is determined to be within a predetermined range in step S24, the material information generation program 220 generates appropriate (correct) and standard SCF-containing material information corresponding to the reference mold analysis result when the degree of agreement is within a predetermined range.

[0064] Furthermore, once the material information generation program 220 generates the correct SCF-containing material information, it terminates the processing of this flow.

[0065] The above explains the process for generating information on SCF-containing materials.

[0066] By performing such processing, the processor system 100 can generate SCF-containing material information from general material information that has appropriate values ​​capable of reproducing the actual state of the molded product shown in the reference mold prototype result information 120.

[0067] <<Injection Molding Condition Calculation Process>> Next, we will explain the details of the injection molding condition calculation process corresponding to step S30.

[0068] Figure 4 is a flowchart showing an example of the injection molding condition calculation process. First, the quality analysis execution program 230 obtains the mold shape, initial values ​​for the injection molding conditions, and SCF-containing material information. Specifically, the quality analysis execution program 230 accepts input from the operator, for example, information specifying the mold shape. The information that identifies the mold shape (not shown) only needs to be stored in the memory resource 40 beforehand. The mold shape refers to the mold shape used when actually manufacturing a product by supercritical injection molding.

[0069] Furthermore, the quality analysis execution program 230 obtains initial values ​​for the injection molding conditions. Specifically, the quality analysis execution program 230 obtains the injection molding conditions for the material corresponding to the material model number from general material information as initial values, and sets these as the arbitrary injection molding conditions.

[0070] Furthermore, the quality analysis execution program 230 obtains SCF-containing material information for the corresponding material model number from the SCF-containing material information DB 140. In other words, the quality analysis execution program 230 obtains appropriate SCF-containing material information generated by the SCF-containing material information generation process.

[0071] Next, the quality analysis execution program 230 performs a quality analysis process using the mold shape, arbitrary injection molding conditions, and SCF-filled material as inputs (step S32). The quality analysis execution program 230 outputs quality analysis results, including values ​​related to the filling volume, which indicates how far the molten resin has filled the reference mold, and the state of bubble formation (bubble density and size).

[0072] In addition to the above, the quality analysis results may also include other information used to measure quality, such as product strength and surface roughness.

[0073] Next, the injection molding condition calculation program 240 determines whether the quality analysis results meet the quality standards (step S33). Specifically, the injection molding condition calculation program 240 obtains information (not shown) in which the required quality standards are registered from the memory resource 40, and compares the quality analysis results with the quality standards registered in that information, which include values ​​related to the filling volume of molten resin and information indicating quality standards related to the bubble generation state.

[0074] Furthermore, since the arbitrary injection molding conditions (initial values ​​of the injection molding conditions) are obtained from general material information that does not take into account the presence of SCF, the quality analysis results usually do not meet the quality standards. Therefore, as described later, the processor system 100 changes the values ​​of the arbitrary injection molding conditions (in particular, the values ​​of the molten resin temperature, pressure, and SCF amount) and repeatedly adjusts the injection molding conditions until the quality standards are met.

[0075] If the quality analysis results determine that the quality standards are met (Yes in step S33), the injection molding condition calculation program 240 proceeds to step S34. On the other hand, if the quality analysis results determine that the quality standards are not met (No in step S33), the injection molding condition calculation program 240 proceeds to step S35.

[0076] In step S35, the injection molding condition calculation program 240 changes the value of an arbitrary injection molding condition. Specifically, the injection molding condition calculation program 240 changes the value of one of the injection molding conditions, namely the temperature, pressure, or SCF amount of the molten resin, and returns the process to step S32.

[0077] Furthermore, any known method, such as Newton's method, variational calculus, or Monte Carlo method, can be used to modify these values.

[0078] Furthermore, in the process of step S32, which is accessed via step S35, the quality analysis execution program 230 performs quality analysis using injection molding conditions in which one of the values ​​of the molten resin temperature, pressure, or SCF amount has been changed. Since the process in this step is the same as described above, a detailed explanation is omitted.

[0079] Furthermore, in step S34, which is accessed if it is determined in step S33 that the quality standards are met, the injection molding condition calculation program 240 calculates the injection molding conditions that resulted from the quality analysis that met the quality standards as appropriate and correct injection molding conditions.

[0080] Furthermore, once the injection molding condition calculation program 240 calculates appropriate and standard injection molding conditions, it terminates the processing of this flow.

[0081] The above explains the injection molding condition calculation process.

[0082] According to such a processor system 100, by generating SCF-containing material information based on prototype results with a reference mold and general material information, it is possible to calculate supercritical injection molding conditions suitable for any mold shape.

[0083] In particular, the processor system 100 makes it easy to optimize injection molding conditions, even in supercritical injection molding, where optimizing conditions is more difficult compared to conventional injection molding.

[0084] Furthermore, in particular, the processor system 100 can optimize injection molding conditions without conducting actual molding tests by changing the injection molding conditions until the quality analysis results satisfy the quality standards.

[0085] <Second Embodiment> Next, a second embodiment of the system 100 will be described. In the second embodiment, the processor system 100 performs a process to change the mold shape based on certain rules if the quality standards are not met even after changing the values ​​of the injection molding conditions during the injection molding condition calculation process. Since the basic configuration of the processor system 100 in the second embodiment is the same as that of the first embodiment described above, a detailed explanation will be omitted.

[0086] Figure 5 is a flowchart showing an example of the injection molding condition calculation process according to the second embodiment. Note that the processes in steps S41 to S44 are the same as steps S31 to S34 in the injection molding condition calculation process of the first embodiment, so a detailed explanation is omitted.

[0087] In step S45, the injection molding condition calculation program 240 changes the mold shape or the value of an arbitrary injection molding condition. Specifically, if the injection molding condition calculation program 240 determines that the quality analysis result does not meet the quality standard even after changing the value of an arbitrary injection molding condition more than a predetermined number of times, that is, even after repeating the processes in steps S41 to S43 a predetermined number of times, in step S45, it changes the mold shape in addition to the injection molding conditions and returns to step S42.

[0088] Modifying the mold shape could involve, for example, widening the diameter of a certain part of the mold or increasing its thickness. This allows molten resin to flow more easily, increasing the filling volume, and the increased thickness enhances the strength of the molded product. As a result, quality analysis results improve, leading to meeting quality standards.

[0089] Furthermore, known methods such as Newton's method, variational calculus, or Monte Carlo method can be used to modify these values.

[0090] Furthermore, in step S34, the injection molding condition calculation program 240 calculates (outputs) injection molding conditions and mold shape that meet the quality standards.

[0091] According to the processor system 100 of this second embodiment, even if it is not possible to calculate appropriate (correct) injection molding conditions that meet quality standards by simply changing arbitrary injection molding conditions, it becomes possible to calculate appropriate injection molding conditions by changing the mold shape.

[0092] <Third Embodiment> Next, a third embodiment of the system 100 will be described. In the processor system 100 according to the third embodiment, the color and transparency (light transmittance) of the molded product are considered as quality criteria. Specifically, the injection molding condition calculation program 240 of the processor system 100 according to this embodiment also analyzes the values ​​of the color and transparency (light transmittance) of the molded product and obtains the analysis results.

[0093] Regarding the color of the molded product, one method for obtaining analysis results is to analyze the temperature and pressure history of the molded product surface. Regarding transparency, one method for obtaining analysis results is to analyze based on information on the bubble formation state and the inherent transparency of the resin. If the quality analysis results including these elements do not meet the quality standards, the injection molding condition calculation program 240 will, as described above, repeatedly change the injection molding conditions such as temperature, pressure, SCF amount, or mold shape according to a certain rule (for example, Newton's method or variational method) to calculate injection molding conditions that meet the quality standards.

[0094] The basic configuration of the processor system 100 according to the third embodiment is the same as that of the first and second embodiments described above, and the process for obtaining the quality analysis results is the same as that for the injection molding condition calculation process described above, so a detailed explanation of these will be omitted.

[0095] According to the processor system 100 of this third embodiment, it is possible to obtain appropriate injection molding conditions for obtaining molded products that take color and transparency into consideration, or molded products in which the color and transparency are modulated in different parts.

[0096] It should be noted that the present invention is not limited to the embodiments and modifications described above, and various modifications are included within the scope of the same technical idea. For example, the embodiments described above are described in detail to make the present invention easier to understand, and are not necessarily limited to those having all the configurations described. Furthermore, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add configurations from other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace parts of the configuration of each embodiment with other configurations.

[0097] Furthermore, the control lines and information lines shown above are those deemed necessary for the explanation, and do not necessarily represent all control lines and information lines present in the actual product. In reality, it is safe to assume that almost all components are interconnected. [Explanation of symbols]

[0098] 100...Processor system, 30...Processors, 40...Memory resources, 50...NI (Network Interface Device), 60...UI (User Interface Device), 110...General material information DB, 120...Reference mold prototype result information, 130...Reference mold analysis result information, 140...SCF-containing material information DB, 150...Supercritical injection molding condition information DB, 210...Molding analysis execution program, 220...Material information generation program, 230...Quality analysis execution program, 240...Injection molding condition calculation program, 10...External devices, N...Communication network

Claims

1. A system having one or more processors and one or more memory resources, The aforementioned memory resources are General material information regarding materials that do not contain SCF (Supercritical Fluid), The prototype results information for the standard mold, which is the result of prototyping using a standard mold with SCF-containing material, A molding analysis execution program that performs molding analysis, A material information generation program that generates SCF-containing material information, and stores it. The aforementioned molding analysis execution program, Using arbitrary SCF-containing material information generated based on general material information, a molding analysis process is performed. The aforementioned material information generation program is By comparing the reference mold analysis result information generated in the molding analysis process with the reference mold prototype result information, the arbitrary SCF-containing material information is modified to generate the correct SCF-containing material information. A system characterized by the following features.

2. The system according to claim 1, The aforementioned memory resources are A quality analysis execution program that performs quality analysis, It has an injection molding condition calculation program that calculates injection molding conditions, The aforementioned quality analysis execution program, Using the correct SCF-containing material information and arbitrary injection molding conditions, a quality analysis process is performed. The injection molding condition calculation program is: The correct values ​​for injection molding conditions are calculated by changing the arbitrary injection molding conditions so that the results of the quality analysis meet predetermined quality standards. A system characterized by the following features.

3. The system according to claim 1, The aforementioned SCF-containing material information is, The relationship between the fluidity of the molten resin, which is the material for molded products, and the temperature, pressure, and SCF (Surface Coolant) content of the molten resin. The relationship between the values ​​related to bubble formation and the temperature, pressure, and SCF amount of the molten resin is described. A system characterized by the following features.

4. The system according to claim 2, The aforementioned quality standards are: This standard is indicated by a value relating to the volume of molten resin filling the mold and a value representing the state of bubble formation. A system characterized by the following features.

5. The system according to claim 2, The injection molding conditions are: Includes the temperature, pressure, and SCF amount of the molten resin. A system characterized by the following features.

6. The system according to claim 5, The injection molding conditions mentioned above are further, This includes the location of the gates into which molten resin is injected into the mold, the shape of the gates, and the number of gates. A system characterized by the following features.

7. The system according to claim 2, The injection molding condition calculation program is: By changing at least one of the arbitrary injection molding conditions and mold shape so that the results of the quality analysis satisfy predetermined quality standards, the correct values ​​for injection molding conditions and mold shape are calculated. A system characterized by the following features.

8. The system according to claim 4, The aforementioned quality standards are: Includes standards indicated by the color and transparency (light transmittance) values ​​of the molded product. A system characterized by the following features.

9. The system according to claim 3, The values ​​related to bubble formation include: This includes at least one of the following: number of bubbles generated, bubble generation rate, bubble generation probability, bubble growth rate, and bubble mobility. A system characterized by the following features.

10. A supercritical injection molding support method performed by a system having one or more processors and one or more memory resources, The aforementioned processor, The steps include: performing a molding analysis using arbitrary SCF-containing material information generated based on general material information regarding materials that do not contain SCF (Supercritical Fluid); The process involves a step of generating correct SCF-containing material information by modifying the arbitrary SCF-containing material information based on a comparison between the reference mold analysis result information generated in the molding analysis process and the reference mold prototype result information, which is the result of prototyping using a reference mold with SCF-containing material. A supercritical injection molding support method characterized by the following features.

11. A supercritical injection molding support method according to claim 10, The aforementioned processor, The steps include performing a quality analysis using the correct SCF-containing material information and arbitrary injection molding conditions, The steps include: calculating the correct injection molding conditions by changing the arbitrary injection molding conditions so that the results of the quality analysis meet predetermined quality standards; and A supercritical injection molding support method characterized by the following features.

12. A program that a processor reads from a memory resource and executes in a system having one or more processors and one or more memory resources, The molding analysis execution program executed by the aforementioned processor is: Using arbitrary SCF-containing material information generated based on general material information for materials that do not contain SCF (Supercritical Fluid), a molding analysis process is performed. The material information generation program executed by the aforementioned processor is: By comparing the reference mold analysis result information generated in the molding analysis process with the reference mold prototype result information, which is the result of prototyping using a reference mold with SCF-containing material, the arbitrary SCF-containing material information is modified to generate the correct SCF-containing material information. A program characterized by the following features.

13. The program according to claim 12, The quality analysis execution program executed by the aforementioned processor is: Using the correct SCF-containing material information and arbitrary injection molding conditions, a quality analysis process is performed. The injection molding condition calculation program executed by the aforementioned processor is: The correct values ​​for injection molding conditions are calculated by changing the arbitrary injection molding conditions so that the results of the quality analysis meet predetermined quality standards. A program characterized by the following features.

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