Control method for injection molding machine, manufacturing method for injection molded article, and injection molding system

Abstract

To provide an injection molding technique capable of achieving stable molded article quality even under variation in material properties.SOLUTION: This control method for a manufacturing device is implemented by a control device. The manufacturing device includes an injection molding machine and a mold attached to the injection molding machine. The method comprises: a collection step for collecting, from a plurality of sensors provided in the manufacturing device, multiple items of process data measured during first injection molding; an acquisition step for acquiring, on the basis of the process data, a plurality of parameters relating to a plurality of material characteristics of a resin material used for injection molding; and a control step for setting, on the basis of the plurality of parameters, molding conditions for second injection molding after the first injection molding.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to a control method for an injection molding machine and an injection molding system. [Background technology]

[0002] In conventional injection molding machines, the resin material is melted mainly by heating with a heater, and the molten resin is measured by rotating and retracting the screw driven by the motor. The measured molten resin is filled and pressurized into the mold by the forward movement of the screw driven by the motor. The molten resin is then sufficiently cooled and solidified in the mold, and is removed from the mold as a plastic molded product.

[0003] The output of the heater used to melt the resin material is controlled to the set temperature by detection of a thermocouple installed in the cylinder. In addition, resin metering is performed simultaneously with melting, and is performed by retreating the screw position until it reaches the set position. At that time, the molten resin is controlled to be in a specified pressure state by detection of a pressure sensor such as a load cell equipped on the screw. In addition, the filling operation of the molten resin is also controlled based on the screw position information, and the screw movement speed and movement amount are operated to follow the set values. After filling, a pressurizing operation called pressure holding is performed. The purpose of this is to generate a compensating flow to compensate for the volumetric shrinkage caused by the shrinkage of the molten resin. This pressurizing operation is generally controlled by detection of a load cell or the like equipped on the screw mentioned above, and the screw advances to follow the set pressure value.

[0004] The set values ​​for the heater temperature, screw movement speed, movement amount, pressure, etc. mentioned above are called molding conditions. The molding conditions must be determined by the equipment user himself depending on the type of resin material used, the volume of the molded product, the specifications of the mold, etc. The user mainly determines the molding conditions so as to obtain the desired molded product quality. The molding conditions can be changed by the user even when the injection molding machine is in mass production operation. However, since a lot of experience and knowledge is required to determine the molding conditions that will ensure quality, changes during mass production tend to be avoided.

[0005] Molding conditions need to be changed during mass production when disturbances cause the quality of the molded product to become unstable. It is especially preferable for the dimensions of the molded product to be stable.

[0006] It has long been pointed out that variations in material properties have a large effect on molded product quality, especially on molded product dimensions. Therefore, technology has been proposed to detect changes in material properties during mass production and adjust molding conditions accordingly to stabilize quality.

[0007] For example, Patent Document 1 discloses a technology in which a viscosity measuring plunger and sensor are newly installed in the plasticizing device of an injection molding machine to calculate the viscosity during molding and adjust the speed, temperature, and back pressure conditions based on the calculation results. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] JP 2005-238519 A Summary of the Invention [Problem to be solved by the invention]

[0009] Through our research, we have found that the variation in molded products cannot be resolved by controlling molding conditions for only one specific material property. Since there are many material properties that affect molded product quality, the variation in multiple material properties can cause the inability to obtain sufficient molded product quality. If it is not possible to detect a single material characteristic during molding and control the molding conditions, sufficient quality improvement cannot be achieved.

[0010] The present disclosure has been made in consideration of the problems with the conventional techniques described above, and aims to provide an injection molding technique that can achieve stable molded product quality even when material properties vary. [Means for solving the problem]

[0011] A first aspect of the present disclosure is A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a first pressure sensor value obtained from a first pressure sensor provided in a plasticizing section of the injection molding machine, a second pressure sensor value obtained from a second pressure sensor provided in a resin flow path in a mold, and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the second pressure sensor for detecting the temperature of the resin material; A first pressure sensor value P when the temperature sensor value is equal to or higher than the glass transition temperature Tg of the resin material during the injection process and the pressure holding process during injection molding. 1 and the second pressure sensor value P 2 A control step of setting molding conditions for injection molding based on the relationship; The present invention relates to a control method for an injection molding machine, comprising:

[0012] A second aspect of the present disclosure is A control method for an injection molding machine executed by a control device, comprising: a collection step of collecting a first pressure sensor value obtained from a first pressure sensor provided in a plasticizing device of the injection molding machine, a second pressure sensor value obtained from a second pressure sensor provided in a resin flow path in a mold, and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the second pressure sensor for detecting the temperature of the resin material; A first pressure sensor value P when the temperature sensor value is equal to or higher than the glass transition temperature Tg of the resin material during the injection and pressure holding steps during molding. 1 and the second pressure sensor value P 2 Difference P 1 - P 2 A control step of changing the molding conditions of the injection molding machine based on the above. The present invention relates to a control method for an injection molding machine, comprising:

[0013] A third aspect of the present disclosure is A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold, a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting the temperature of the resin material, and a screw pressure value of the injection molding machine; The pressure sensor value P when the temperature sensor value falls to the glass transition temperature Tg+10°C or lower of the resin material during the pressure holding process during injection molding. 3 and a control step of setting molding conditions for injection molding based on the relationship between the pressure value Ps of the screw of the injection molding machine and the pressure value Ps of the screw of the injection molding machine. The present invention relates to a control method for an injection molding machine, comprising:

[0014] A fourth aspect of the present disclosure is A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting pressure sensor values ​​obtained from a pressure sensor provided in a resin flow path in the mold and a screw position of the injection molding machine; The change amount ΔLs of the screw position and the change amount ΔP of the pressure sensor value during the injection process during injection molding 4 A control step of setting molding conditions for injection molding based on the relationship between the The present invention relates to a control method for an injection molding machine, comprising:

[0015] A fifth aspect of the present disclosure is a method for manufacturing a semiconductor device comprising: A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting a temperature of the resin material; Pressure sensor value P when the gate of the mold is sealed during the dwelling and cooling processes during injection molding 5 and the pressure sensor value P when the molded product falls below the load deflection temperature 6 and a control step of setting molding conditions for injection molding based on the relationship between the injection volume Vi and the The present invention relates to a control method for an injection molding machine, comprising:

[0016] A sixth aspect of the present disclosure is a method for manufacturing a semiconductor device comprising: A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting a temperature of the resin material; The pressure sensor value P when the gate of the mold is sealed during the dwelling and cooling processes during injection molding 5 and the pressure sensor value P when the molded product becomes equal to or lower than the load deflection temperature. 6 and the weight of the molded product W A A control step of setting molding conditions for injection molding based on the relationship between the The present invention relates to a control method for an injection molding machine, comprising: Effect of the Invention

[0017] According to the present disclosure, stable molded product quality can be achieved even when multiple material properties vary. [Brief description of the drawings]

[0018] [Figure 1] FIG. 1 is a block diagram of an injection molding system having a control device according to a first embodiment of the present invention. [Diagram 2] Control block diagram in the first embodiment [Diagram 3] Flowchart diagram in the first embodiment [Figure 4] Flowchart of injection molding in Comparative Example 1 [Diagram 5] Flowchart of injection molding in Comparative Example 2 [Figure 6] Diagram showing the configuration of Experimental Example 1 [Figure 7] Measurement results of molding weight in Experimental Example 1 [Figure 8] FIG. 1 shows the breakdown of the weight of the molded product in Experimental Example 1. [Figure 9] An example of measuring the elastic modulus in Experimental Example 1 [Figure 10] An example of measuring the viscosity of a resin material in Experimental Example 1 [Figure 11] An example of measuring shrinkage characteristics in Experimental Example 1 [Figure 12] Diagram showing the configuration of Experimental Examples 2 to 5 [Figure 13] Diagram showing the time dependence of viscosity [Figure 14] FIG. 13 is a graph showing the correlation between viscosity (MVR) and differential pressure ΔP in Example 2. [Figure 15] FIG. 1 shows the correlation between the elastic modulus at Tg and the injection volume in Example 3. [Figure 16] FIG. 13 is a graph showing the correlation between the elastic modulus at Tg and the elastic modulus parameter Ps / P3 in Example 3. [Figure 17] A plot of the screw position versus time in Experimental Example 3. [Figure 18] FIG. 13 is a graph showing the correlation between the elastic modulus when melted and the elastic modulus parameter ΔP4 / ΔLs in Example 4. [Figure 19] Graph showing the relationship between resin temperature and pressure after 5.0 seconds in Experimental Example 4 [Figure 20] FIG. 13 is a graph showing the correlation between the specific volume difference and the shrinkage parameter (P5-P6) / Vi in Example 5. [Figure 21] Molding conditions during preliminary test run in Experimental Example 5 [Figure 22] Estimation results of material properties obtained in Experimental Example 5 DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] First, we will briefly explain the molding conditions in injection molding and the material properties that affect the quality of the molded product.

[0020] Molding conditions include heater temperature, screw movement speed, movement amount, pressure, etc. Molding conditions must be determined according to the type of resin material used, the volume of the molded product, the specifications of the mold, etc. Even if molding is done under the same molding conditions, if the material properties of the resin material vary, stable molded product quality cannot be obtained.

[0021] Material properties can vary even for the same type of resin material from the same manufacturer, and often fluctuate depending on the production lot. In recent years, there has been an increase in the use of recycled resin materials (recycled plastic materials), which are resin materials derived from recycled resin materials (waste plastics). Recycled resin materials are produced by turning waste plastic into flakes or pellets, but waste plastic contains plastics derived from a variety of products, and recycled resin materials often have more variation in material properties than virgin materials. Injection molded products manufactured using recycled resin materials such as recycled pellets are called recycled plastics. The production and use of recycled plastics through material recycling reduces CO 2 It is effective in reducing emissions.

[0022] Resin viscosity is one of the material properties that affects the dimensions of molded products. Viscosity has a large effect on the fluidity of resin, so even under the same molding conditions, the amount of resin filled will differ depending on the viscosity. With high viscosity, the fluidity decreases and the amount of resin filled will be small, and with low viscosity, the fluidity increases and the amount of resin filled will be large. This causes changes in the dimensions of the molded product.

[0023] Additionally, the elastic modulus (elastic constant) of the resin is one of the material properties that affect the dimensions of the molded product. The elastic modulus is a physical quantity that indicates the relationship between external force and strain (deformation), so it has a significant effect on the pressure holding process, which is controlled by the detection value of the pressure sensor. For example, materials with a high elastic modulus have a large response stress associated with screw movement, so the amount of screw movement relative to the set pressure value is small. This reduces the mass of the compensation flow into the mold, and the dimensions of the molded product tend to be smaller.

[0024] Shrinkage characteristics are also one of the material characteristics that affect the dimensions of molded products. The shrinkage characteristics of a material are often expressed as PVT characteristics, which are the ratio of pressure [MPa], temperature [℃], and specific volume [cm3] during cooling. 3 / g]. Therefore, a material that has a large change in specific volume during the process from a high temperature state where the resin material melts to a low temperature state where it cools and solidifies will have a large amount of shrinkage. In other words, even if the same volume of molten resin is filled into the mold, the larger the change in specific volume of the material, the smaller the dimensions of the molded product will be.

[0025] In the case where multiple of such material properties vary, control based on a single material property may not provide stable molded product quality. The present disclosure achieves more stable molded product quality than ever before by detecting multiple material properties during molding and controlling molding conditions according to changes in the multiple material properties. As a result of intensive research, the present inventors have found that in order to stabilize the dimensions of a molded product, it is preferable to perform control taking into account at least two of the viscosity, elastic modulus, and shrinkage properties, and preferably these three. Furthermore, it has been found that it is also preferable to be able to control molding conditions taking into account thermal properties such as the melt density, specific heat, and thermal conductivity of the material. In addition, the present disclosure also proposes to accurately estimate the viscosity, elastic modulus, and shrinkage properties of the material for the above control. Note that the resin materials applicable to the injection molding of the present disclosure are typically Although the resin is a thermoplastic resin, it may be a thermosetting resin, a crystalline resin or an amorphous resin, a general-purpose plastic or an engineering plastic. The resin material may be, for example, a polyolefin such as polyethylene (PE) or polypropylene (PP), a polyester such as polystyrene (PS), polyethylene terephthalate (PET) or polybutylene terephthalate (PBT), polyvinyl chloride (PVC), polyoxymethylene (POM), acrylonitrile-butadiene-styrene (ABS), polycarbonate (PC), polyphthalamide (PPA), or acrylic (PMMA). Examples of resin materials suitable for material recycling include polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyvinyl chloride (PVC). In addition, the resin material applicable to the injection molding of the present disclosure may be a composite material in which a filler or an elastomer is dispersed in a resin matrix, or a mixture of multiple resin materials.

[0026] (composition) The control device and control method for an injection molding machine and the method for estimating material properties according to the present disclosure are described below in detail. The control device for an injection molding machine according to the present disclosure acquires a plurality of parameters related to a plurality of material properties of a resin material used in injection molding based on a plurality of process data measured during injection molding, and sets molding conditions using the parameters.

[0027] 1 is a configuration diagram of an injection molding system representing an example of an embodiment of the present disclosure. The injection molding system includes an injection molding machine 10, a control device 51, and a mold 1.

[0028] Injection molding machine 10 is composed of plasticizing device 11 and mold clamping device 12, and is controlled by control device 51. Injection molding machine 10, together with mold 1 attached to injection molding machine 10, can be regarded as constituting a manufacturing device for injection molded products. Moreover, plasticizing device 11 can be regarded as a plasticizing section of the manufacturing device. Moreover, control device 51 can be regarded as a device that controls the manufacturing device.

[0029] The mold clamping device 12 is provided with a mold opening / closing servo motor 23 and an ejector motor 24. The mold opening / closing servo motor 23 is not only used to clamp the mold 1 installed in the mold clamping device 12 with a predetermined force, but is also used for opening and closing the mold. The ejector motor 24 is used when releasing the injection molded product from the mold.

[0030] The plasticizing device 11 is equipped with a cylinder 13, a screw 14, a cylinder heater 31, a metering servomotor 21, an injection servomotor 22, and a load cell 15. Inside the cylinder 13, the screw 14 retreats and the molten resin is metered to the front of the cylinder. The retreating movement of the screw 14 is achieved by the melting of the material by the action of the cylinder heater 31 and the rotational movement of the metering servomotor 21. The metered molten resin is filled into the mold by the forward movement of the screw 14. The forward movement of the screw 14 is achieved by the rotational movement of the injection servomotor 22. A load cell 15 is provided at the rear end of the screw 14 and is used to control the pressure state during metering and filling.

[0031] Each servo motor can instantly detect analog data such as the number of rotations, torque, speed, and position, and output it from the data output unit 16 as molding machine data 101. Similarly, analog data of the pressure acquired by the load cell 15 is also included in the molding machine data 101. The output molding machine data 101 is input to the control device 51.

[0032] The molding machine data 101 may include values ​​other than analog data, such as a minimum cushion position, a dwelling completion position, a filling peak pressure, and a VP switching position, which are calculated as actual values ​​for one cycle by a calculator in the injection molding machine.

[0033] The mold 1 is equipped with one or more mold sensors 61. The sensor 61 may be composed of different types of sensors, such as a pressure sensor that detects the pressure state inside the mold and a resin temperature sensor that detects the temperature state of the molded product. Other sensors that may be used include a gap sensor that detects the amount of mold opening, a thermocouple that detects the mold temperature, and a speed sensor that detects the flow speed of the molten resin. The detected data is output as mold data 201 and input to the control device 51.

[0034] A cylinder sensor 71 may be installed in the cylinder 13. A plurality of sensors may be used, and a resin temperature sensor, a pressure sensor, a speed sensor, etc. are selected. The detected data is output as cylinder data 301 and input to the control device 51.

[0035] In this embodiment, the measurement results of the measuring machine may also be treated as data. For example, molded product measuring machine 81 is installed near the injection molding machine, and can measure the molded product online. A plurality of measuring machines may be used, such as a weight measuring machine, a length measuring machine, and a density measuring machine. The measurement results are output as measurement data 401 and input to control device 51.

[0036] The control device 51 may be implemented in any manner as long as it is capable of communicating with the injection molding machine 10 and the molded product measuring machine 81. For example, the control device 51 may be implemented by a device different from the injection molding machine 10, or may be provided inside the injection molding machine 10. The control device 51 may be a computer installed in the same facility as the injection molding machine 10, or may be a remote computer installed in a different facility and connected to a network. The remote computer includes a cloud computer or a distributed computer.

[0037] The data input to the control device 51 requires at least one of molding machine data 101, mold data 201, cylinder data 301, and measurement data 401. The control device 51 performs calculations based on the input data and outputs modified molding conditions 901. The modified conditions 901 are input as a command signal from the data input unit 17 provided in the injection molding machine, and the molding conditions for the next shot are rewritten.

[0038] 2 is a control block diagram showing an example of an embodiment of the present disclosure. An injection molding machine 10 molds a molded product in each cycle, and outputs molding machine data 101 and cylinder data 301. The molded product is instantaneously measured online by a measuring machine 81, which outputs measurement data 401. A sensor installed in the mold 1 outputs mold data 201 in each cycle. One or more of the molding machine data 101, mold data 201, cylinder data 301, and measurement data 401 are input to a control device 51.

[0039] The data input to the control device 51 is collected in the data detection unit 52. The data detection unit 52 converts continuous numerical information such as analog data into a single numerical data. For example, the data detection unit 52 converts the input data into an integral value, a change amount, a maximum value, a minimum value, or the like within a given range. The data detection unit 52 also calculates a different numerical value from a plurality of pieces of numerical information. For example, the data detection unit 52 can calculate the injection volume by performing a calculation that takes into account the cross-sectional area of ​​the cylinder inner diameter from the screw position information included in the molding machine data 101. The converted numerical value group is input from the data detection unit 52 to the material property calculation unit 53 as feature amount 501.

[0040] The feature amount 501 is sent to a material property calculation unit 53 and used to estimate (obtain) material property 511 of the resin material being used. For the calculation process of the estimation, a calculation formula based on an experiment, a prediction model based on machine learning, etc. are used. The material property 511 is, for example, at least one of resin viscosity, elastic modulus, PVT property, shrinkage rate, density, specific heat, thermal conductivity, etc. 3. Estimate two or more of these material properties.

[0041] The material property 511 estimated by the material property calculation unit 53 may be estimated as any value in any format as long as it is a value according to the actual material property or a value that corresponds one-to-one to the actual material property. The estimated value obtained by the material property calculation unit 53 may deviate from the numerical value extracted according to ISO, and further, the unit system of the estimated value may differ from the unit system of the original material property. In this disclosure, the estimated value obtained by the material property calculation unit 53 is treated as a parameter related to the material property. The estimated value obtained by the material property calculation unit 53 can be considered as a parameter correlated to the material property. The parameter related to or correlated to the material property can be associated one-to-one with the material property by a predetermined calculation, for example.

[0042] The estimated material properties 511 are compared with the reference material properties in the comparison unit 54. The reference material properties are values ​​when the molded product quality is guaranteed, and correspond to the target values ​​for molding a good product. These reference material properties are derived in advance by a test run using the same method as the calculation by the material property calculation unit 53 described above. The material properties are compared for each property type, and the difference 521 from the reference is calculated for each property type. Since two or more material properties are detected, the difference 521 from the reference is also made up of the same number of values. The reference material properties are expressed as parameters in the same format as the estimated values ​​so that they can be compared with the estimated values.

[0043] The numerical value of the difference 521 from the reference is sent to the control amount calculation unit 55, which extracts molding correction conditions 901 that suppress the influence on molding quality. The calculation process of the correction conditions uses an experimentally based calculation formula, a prediction model based on machine learning, etc. As mentioned above, since there are multiple material properties to be compared, the correction conditions 901 are often composed of multiple molding machine control parameters.

[0044] The corrected conditions 901 output from the control device 51 are input to the injection molding machine 10. The molding conditions of the injection molding machine 10 are set in accordance with the corrected conditions 901, and are reflected in molding from the next shot onwards.

[0045] Regarding the corrected molding, various data are collected in the same manner as above and sent to the data detection unit 52. Thereafter, the same processing is repeated recursively.

[0046] FIG. 3 is a flow chart for providing a supplementary explanation of the control method for the injection molding machine 10 performed by the control device 51, which has been described above.

[0047] First, a manufacturing apparatus including an injection molding machine 10 and a mold 1 attached to the injection molding machine 10 is prepared, and injection molding is performed by the injection molding machine 10 in an injection molding step ST1. The injection molding operation currently being focused on is referred to as a first injection molding operation. In the loop processing shown in the flowchart of Fig. 3, the injection molding operation after the first injection molding operation (which may be after several cycles other than immediately after) is referred to as a second injection molding operation.

[0048] In collection step ST2, data associated with the injection molding operation (one or more of data 101, 201, 301, and 401 in Fig. 1 and Fig. 2) is collected. Specifically, control device 51 collects a plurality of process data measured during the first injection molding from a plurality of sensors provided in injection molding machine 10 or mold 1.

[0049] In step ST3, a feature quantity 501 is derived from the data content. In steps ST4 and ST5, two or more material properties (material property 511 in FIG. 2) are estimated from the feature quantity 501. In FIG. 3, two material properties, material property a and material property b, are estimated. Steps ST3 to ST5 are an acquisition process for acquiring multiple material properties of the resin material used in injection molding, or multiple parameters related to multiple material properties, based on the collected process data. corresponds to a step.

[0050] In steps ST6 and ST7, material property a is compared with reference material property A, and material property b is compared with reference material property B, and the difference from the reference (difference from reference 521 in FIG. 2) is calculated. In the next steps ST8 and ST9, it is determined whether the calculated difference from references A and B is within the allowable range. If it is within the allowable range, the process proceeds to step ST13. If it is outside the allowable range, the process proceeds to steps ST10 and ST11, where correction conditions α and β (correction conditions 901 in FIG. 1 and FIG. 2) for the molding machine are derived. In step ST12, the correction conditions α and β are reflected in the molding conditions, and the process proceeds to step ST13. Steps ST6 to ST12 correspond to a control step of setting molding conditions for the first injection molding and the second injection molding based on the multiple parameters acquired in the acquisition step.

[0051] In step ST13, it is determined whether the production quantity is sufficient. If it is sufficient, the flow ends, but if it is insufficient, the flow returns to step ST1 and molding is performed again.

[0052] In FIG. 3, the acquisition of process data, the estimation of material properties, and the correction of molding conditions are described as being performed for each cycle, but the present disclosure is not limited thereto. For example, process data may be acquired over multiple cycles, and material properties may be estimated based on the acquired process data. As an example, material properties may be estimated from statistical information of process data over multiple cycles. In the present disclosure, one or more cycles for collecting process data to estimate material properties are referred to as an injection molding operation. The molding conditions corrected based on the process data collected in the first injection molding operation are applied to a second injection molding operation that is performed after the first injection molding operation. The second injection molding operation does not need to be performed immediately after the first injection molding operation, and may be an injection molding operation at any timing as long as it is performed later in time than the first injection molding operation.

[0053] <Example 1> The quality of a molded product molded using the control device according to the present disclosure is compared with that of a molded product molded using a conventional injection molding method. Example 1 is an example of injection molding using a control device and a control method as shown in Figs. 1 to 3. As described above, in this disclosure, a plurality of material properties of a resin material are estimated using a plurality of sensors provided on an injection molding machine and a mold, and molding conditions are controlled based on the tendency. Example 1 is an example of molding condition control by estimating viscosity and elastic modulus. In other words, in Example 1, material property a shown in Fig. 3 is viscosity, and material property b is elastic modulus.

[0054] For comparison with Example 1, Comparative Example 1 and Comparative Example 2 in which injection molding is performed using conventional technology will be described.

[0055] Fig. 4 is a flowchart showing the control method of Comparative Example 1. Comparative Example 1 is an example in which injection molding is performed without estimating material properties or controlling molding conditions. In Comparative Example 1, only the execution of injection molding in step S61 and the determination of whether the required production quantity has been reached in step ST69 are performed.

[0056] FIG. 5 is a flowchart showing a control method of Comparative Example 2. In Comparative Example 2, material property estimation is performed for only one material property. The process from execution of injection molding in step ST51 to derivation of feature quantities in step ST53 is generally the same as in Example 1, but estimation of material property in step ST54 is performed for only one material property. Therefore, the process from step ST55 to step ST57 is not branched. In this way, Comparative Example 2 is characterized by estimation and molding condition control for one specific material property. Comparative Example 2 is an example in which only viscosity is estimated and molding condition control is performed.

[0057] FIG. 6(a) is a diagram showing an experimental setup 1 for comparing the effects of Example 1 and Comparative Examples 1 and 2. In the experimental setup 1, two molding materials with different viscosities and elastic moduli were charged into a hopper 18 capable of storing materials for approximately 100 shots. In this experiment, HIPS (high impact polystyrene) material was used, and material A 91 and material B 92 with significantly different viscosities and elastic moduli were prepared. The viscosities were compared based on the measurement results of MVR (Melt Volume Rate: ISO 1133 200°C / 5kg), and the elastic moduli were compared based on values ​​measured near the glass transition temperature (110°C) using a rotational rheometer. Material A has a smaller MVR, a higher viscosity, and a higher elastic modulus than material B. Incidentally, the specific gravities of the materials are the same. FIG. 6(b) shows the viscosities and elastic moduli of material A and material B.

[0058] In the experiment configuration 1, first, 50 shots of material A were put into the hopper, followed by 50 shots of material B. When injection molding was performed in this state, only material A was plasticized and molded in the initial stage, but as material A was consumed, the inside of the hopper 18 became filled with material B. At this time, the two materials slowly mix together, so the boundary 93 between the two materials in the hopper becomes unclear.

[0059] Under the above environment, molding was repeated until the material in the hopper was depleted, and the results of measuring the weight of the molded product after each shot are shown in Figure 7. In Comparative Examples 1 and 2, which are conventional technologies, a change in weight was observed from about the 40th to 60th shots. However, the weight change in Comparative Example 2 tended to be smaller than that of Comparative Example 1. On the other hand, in Example 1, no change in weight was observed until the 100th shot, when molding was completed.

[0060] The weight change between Comparative Example 1 and Comparative Example 2 is believed to be due to the change in molding behavior caused by the replacement of materials. Up until the 40th shot, injection molding was performed mainly with material A, but between the 40th and 60th shots, the two materials were slowly mixed together, and it is believed that this was influenced by the material properties of the two materials. In addition, after the 60th shot, the inside of the hopper was completely switched to material B, and it is believed that the material properties of material B had an effect.

[0061] The results of the analysis of the breakdown of the molded product weight are shown in Figure 8(a) and Figure 8(b). Figure 8(a) shows the weight filled in the injection process, and Figure 8(b) shows the weight filled in the packing process. Packing process filling weight W p [g] is the cylinder inner cross-sectional area A [cm 2 ], Screw stroke during pressure retention S p [mm], specific gravity of resin material ρ [g / cm 3 ] is derived from equation (1). Holding pressure process filling amount: W p =ρAS p / 10 ···(1)

[0062] On the other hand, the injection process filling amount W i [g] is the weight of the molded product W A It is calculated using formula (2) using [g]. Injection process filling amount: W i =W A - W P (2)

[0063] 8(a) and 8(b), the filling amount in both the dwelling process and the injection process fluctuates in Comparative Example 1. Also, the filling amount in only the dwelling process fluctuates in Comparative Example 2. On the other hand, in Example 1, neither the filling amount in the dwelling process nor the injection process fluctuates.

[0064] In a normal injection molding machine, the injection process is controlled by the speed and position of the screw. Therefore, even if different materials are used, if the molding conditions are the same, the movement of the screw during the injection process will always be the same. However, if the viscosity of the material is different, the same screw Even with a single-flow operation, the weight of the resin flowing into the mold changes. This is because differences in viscosity cause changes in the pressure distribution upstream and downstream of the resin flow path, resulting in differences in the overall density distribution. The higher the viscosity of the material, the smaller the downstream pressure and the lower the density. Therefore, the filling weight of a high-viscosity material is smaller than that of a low-viscosity material.

[0065] In addition, in a normal injection molding machine, the screw operation during the pressure holding process is controlled by the pressure value detected by the plasticizing device. The pressure is often detected by a load cell 15 installed at the rear end of the screw as shown in Figure 1. Therefore, the screw operation during the pressure holding process is easily affected by the elastic modulus. For example, a material with a high elastic modulus has a large response stress associated with screw movement, so the screw movement amount for the set pressure value is small. As a result, the weight filled into the mold is also small.

[0066] As described above, the viscosity of the resin material has a large effect on the filling process, and the elastic modulus has a large effect on the dwelling process. In Comparative Example 1 of the conventional technology, since no estimation of material properties or molding condition control was performed, the viscosity and elastic modulus of the material in the hopper changed, causing fluctuations in both the injection process filling amount and the dwelling process filling amount. In Comparative Example 2 of the conventional technology, since only molding condition control was performed for the viscosity, the injection process filling amount was stable, but the fluctuations in the dwelling process filling amount could not be suppressed. In contrast, in Example 1, estimation and molding condition control were performed for both the viscosity and the elastic modulus, so stabilization of both the injection process filling amount and the dwelling process filling amount was achieved.

[0067] In the first embodiment, the molding conditions are controlled based on two material properties, namely, viscosity and elastic modulus. An example of the correction of the molding conditions will be described with reference to Figs.

[0068] Figure 9 shows an example of measuring the elastic modulus of a resin material using a rotational rheometer. Figure 9 shows the value of the elastic modulus [Pa] when the temperature [℃] is changed while the rotation frequency is constant at 1 [Hz] and the strain is constant at 0.5 [%]. As can be seen from this measurement result, the elastic modulus is temperature dependent. Therefore, in order to match the elastic modulus of two different materials, it is necessary to adjust the temperature conditions. For example, in the case of Figure 9, in order to match the elastic modulus of material B at 110℃, the temperature state of material A should be set to 118℃. Similarly, in an injection molding machine, it is possible to stabilize the elastic modulus by adjusting the heater temperature conditions (resin temperature) of the cylinder.

[0069] Figure 10 shows an example of measuring the viscosity of a resin material using a capillary rheometer. Figure 10 shows the viscosity [Pa·s] value when the melt temperature [°C] and shear rate [1 / s] are changed. As can be seen from this measurement result, viscosity is temperature-dependent and shear rate-dependent. Therefore, in order to match the viscosities of two different materials, it is necessary to adjust the temperature conditions or shear rate conditions. From the trends in Figure 10, if you want to lower the viscosity, you need to raise the temperature or increase the shear rate. In other words, it is thought that the viscosity can be stabilized by adjusting the resin temperature or injection speed in an injection molding machine.

[0070] As described above, the elastic modulus can be adjusted by the resin temperature, and the viscosity can be adjusted by the resin temperature and injection speed. Therefore, the adjustment of the elastic modulus and viscosity can be expressed by the following formulas (3) and (4), which have the setting parameters of the injection molding machine as variables. Elastic modulus: Δg = At ​​(3) Viscosity: Δμ=Bt+Cd (4)

[0071] Here, t is a variable corresponding to the resin temperature [℃], d is a variable corresponding to the injection speed [mm / sec], and A, B, and C are all constants. The constants A to C can be derived in advance for each material through material analysis, etc. Additionally, Δg and Δμ represent the amount of deviation between the target value and the actual value of the material properties. The target value is set from the actual value for a good product. Then, by solving these equations, the variables t and d are extracted. The extracted t and d become the correction amounts and are used for the next cycle. This is reflected in the shot molding conditions.

[0072] In this way, in the first embodiment, the molding conditions for the second injection molding are set using the relational expressions (3) and (4) that express the relationship between the adjustment amount of the molding conditions and the change in the parameters, which are obtained in advance for multiple material property-related parameters. The first embodiment is a method of controlling two objective variables, elastic modulus and viscosity, using two explanatory variables, resin temperature and injection speed, but it is possible to derive a solution even if there are three or more objective variables, as long as the number of explanatory variables is not greater than the number of objective variables. Note that the explanatory variables preferably include at least two material properties from among viscosity, elastic modulus, and shrinkage characteristics.

[0073] For example, the objective variables may be three, including the elastic modulus, viscosity, and shrinkage characteristics. Figure 11 shows the shrinkage characteristics of a material. Shrinkage characteristics are generally measured with a PVT measuring device, and are expressed as the specific volume [cm3] under pressure [MPa] and temperature [℃] environments. 3 / g]. As is clear from this figure, the shrinkage characteristics of the material can be adjusted by the resin temperature and pressure. Therefore, the adjustment of the shrinkage characteristics can be expressed as in formula (5). Contraction characteristic: Δρ=Ft+Gp (5)

[0074] Here, t is a variable corresponding to the resin temperature [℃], p is a variable corresponding to the pressure [MPa], and F and G are constants. The constants F and G can be calculated in advance for each material through material analysis, etc. Also, Δρ represents the amount of deviation between the target value and the actual value of the material property (shrinkage property).

[0075] If the three objective variables are elastic modulus, viscosity, and shrinkage characteristics, the explanatory variables contained in equations (3) to (5) are t, d, and p, so that the desired molding conditions can be adjusted by solving a multi-dimensional simultaneous equation.

[0076] However, there is a problem that the calculation accuracy decreases as the number of material properties that are the objective variables increases. As a result of intensive research, it has been found that two or more material properties are necessary to adjust, but it has also been made clear that injection molding is sufficient if at least one of the three material properties of viscosity, elastic modulus, and shrinkage property is included. In other words, by controlling at least the viscosity and elastic modulus, the elastic modulus and shrinkage property, or the shrinkage property and viscosity as the objective variables, a sufficiently stable molded product quality can be obtained. As mentioned above, the viscosity affects the resin filling amount in the injection process, and the elastic modulus affects the resin filling amount in the pressure holding process. Furthermore, the shrinkage property affects the amount of shrinkage of the molded product in the cooling process.

[0077] In this way, by controlling the three material properties of viscosity, elastic modulus, and shrinkage characteristics to be identical, it is possible to suppress the variation in material properties that has a large impact throughout the entire injection molding process, making it possible to stabilize quality.

[0078] In this embodiment, since the molding conditions after the change can be fed back to the injection molding machine in the shortest cycle, even if the material properties of the resin material change during mass production, the occurrence of defective products can be minimized. Furthermore, in this embodiment, since multiple material properties can be estimated simultaneously by calculating the collected process data, the dimensional variation of molded products caused by multiple factors can be reduced. In addition, the estimated material properties include at least the viscosity, the elastic modulus, and the shrinkage property. In this embodiment, the calculation process is limited to the resin filling amount in the injection process, the mass of the compensation flow in the pressure holding process, and the shrinkage amount of the molded product in the cooling process, so that the calculation efficiency can be optimized. <Example 2> A method for estimating the viscosity of a resin material from process data obtained during one molding cycle will be described. In this embodiment, the upstream pressure P 1 and the downstream pressure P obtained from a second pressure sensor provided in the resin flow path in the mold. 2 More specifically, in this embodiment, when the temperature sensor value obtained from the temperature sensor that detects the temperature of the resin material provided near the second pressure sensor is equal to or higher than the glass transition temperature Tg, the viscosity is estimated based on the relationship of P 1 and P 2 The viscosity is estimated based on the relationship:

[0079] Viscosity can be calculated according to Hagen-Poiseuille's law using equations (6) and (7). Viscosity: μ[Pa s]=(πa 4 ΔP) / (SQL) ···(6) ΔP=P 1 -P 2 (7)

[0080] Here, Q is the flow rate of the molten resin [m 3 / s], L is the flow path length [m], a is the flow path radius [m], P 1 is the upstream pressure [Pa], P 2 is the downstream pressure [Pa].

[0081] In injection molding, the flow path length L and flow path radius a are fixed values ​​depending on the specifications of the mold and injection molding machine. The flow rate Q is also fixed by the molding conditions (injection speed, etc.). In other words, the upstream pressure P 1 and downstream pressure P 2By measuring the difference (ΔP) between these values, the viscosity fluctuation of the resin used can be understood. In other words, ΔP is a value proportional to the viscosity in the injection molding process under consideration, and is a parameter related to viscosity. Therefore, in this embodiment, by controlling the molding conditions based on ΔP, control of molding conditions based on viscosity is achieved. However, it is a prerequisite that ΔP is measured when the molten resin is flowing. Therefore, in injection molding, it is necessary to measure ΔP when the resin is in a molten state and during the injection process and the pressure holding process.

[0082] Upstream pressure P 1 The first pressure sensor measures the downstream pressure P 2 The position of the second pressure sensor that measures the pressure may be any position on the resin flow path, as long as the first pressure sensor is upstream of the second pressure sensor. For example, the first pressure sensor may be installed in the cylinder or nozzle of the plasticizer, or a member that extends the flow path may be sandwiched between the mold and the nozzle, and the pressure may be measured inside the member. Also, the detection value of a load cell that is originally provided at the rear end of the screw of the plasticizer may be used as the first pressure sensor. On the other hand, the second pressure sensor may be installed at any position, such as the sprue bush of the mold, the hot runner manifold, the hot runner tip, the runner, or the cavity.

[0083] Fig. 12(a) is a diagram showing the arrangement of sensors in experimental configuration 2. In experimental configuration 2, a first pressure sensor 72 is installed in the nozzle of the plasticizing device 11, and a second pressure sensor 62 is installed near the gate in the mold to measure the viscosity-related parameter ΔP. At this time, a resin temperature sensor 63 is installed near the second pressure sensor to also measure the resin temperature. Fig. 12(b) shows the measurement waveform for one cycle measured in this manner.

[0084] When ΔP(x) at any timing x is expressed by the following equation (8), ΔP(x)=P 1 (x)-P 2 (x) ...(8) The viscosity-related parameter ΔP is expressed by equation (9).

number

[0085] Here, T S is the measurement start time, T E is the end time of the measurement. In other words, ΔP is the average pressure difference from the start time of the measurement to the end time of the measurement.

[0086] The viscosity-related parameter ΔP must be measured while the resin is in a molten state and during the injection and dwell steps, and is therefore calculated as the average pressure difference during any time period from the start of injection until the resin temperature reaches the glass transition temperature Tg (between 0.0 s and 4.5 s in FIG. 12(b)). The measurement time period may be set at any time within the above time period, and may be, for example, during the injection step (0.0 s to 1.5 s in FIG. 12(b)), during the dwell step (1.5 s to 4.5 s), throughout the entire range (0.0 s to 4.5s).

[0087] However, when deciding the measurement time period, it is preferable to take into consideration the time dependency and shear rate dependency of viscosity. Figure 13 is a schematic diagram of the time dependency of viscosity. When a shear rate is applied to molten resin, it takes a certain amount of time for the viscosity to reach equilibrium. It has also been shown that the time to reach equilibrium varies depending on the shear rate conditions. As described above, in injection molding, which involves high-speed shear, it is necessary to determine the measurement time period after determining the timing at which equilibrium is reached.

[0088] For example, in the injection process (0.0s to 1.5s) in Figure 12(b), P 1 and P 2 increases over time On the other hand, during the pressure holding process (1.5s to 4.5s), the pressure value is stable and close to equilibrium. 2 Therefore, it is considered preferable to measure ΔP during the first half of the pressure holding process.

[0089] After careful consideration, it was determined that a pressure fluctuation of 5MPa / sec or less is considered to be in equilibrium. It was found that the error in viscosity measurement was small. Therefore, in the injection process and the pressure holding process, the first pressure sensor value P 1 and the second pressure sensor value P 2 The viscosity is estimated based on the value when the amount of change over time in each of the above values ​​is within 5 MPa / sec. More specifically, it is considered preferable to start measurement after the start of the pressure dwell step and when the pressure fluctuation is within 5 MPa / sec, and to end measurement when the pressure fluctuation becomes 5 MPa / sec or more or when the pressure dwell step is completed, and to obtain the average pressure.

[0090] Figure 14 shows the measurement results of the correlation between differential pressure (viscosity parameter) ΔP and MVR (Melt Volume Rate: ISO 1133 200℃ / 5kg) when injection molding was performed using various types of HIPS materials under experimental configuration 2. It can be confirmed that there is a strong correlation between ΔP and the viscosity (MVR) of the resin material.

[0091] The method of this embodiment is applied to the estimation of the viscosity of the resin material in the first embodiment, and the molding conditions can be changed based on the obtained estimated viscosity value.

[0092] In the above example, the viscosity estimate is calculated based on the upstream pressure P 1 and downstream pressure P 2 Difference P 1 -P 2 The difference ΔP is calculated based on P 2 -P 1 or |P 1 -P 2 | may also be used. 1 and P 2 If we estimate the viscosity based on the difference or the relationship according to the difference, P 1 -P 2 Other relationships may be used. For example, αP 1 -βP 2 (α, β are predetermined coefficients greater than 0) and P 1 / P 2 etc. P1 and P 2 The viscosity can be estimated based on the difference between the viscosity of the liquid and the viscosity of the liquid. 1 -P 2 yaP 1 / P 2 Contains the ingredients The viscosity may be estimated using such values.

[0093] <Example 3> A method for estimating the elastic modulus of a resin material from process data obtained during one molding cycle will be described. In this embodiment, the elastic modulus is estimated based on the relationship between a pressure sensor value obtained from a pressure sensor provided in a resin flow path in a mold 1 and a screw pressure value of an injection molding machine 10. More specifically, the elastic modulus is estimated based on the relationship between the pressure P in the resin path in the mold when the temperature of the resin material falls to the glass transition temperature Tg+10°C or lower in the pressure holding step during injection molding. 3 and the screw pressure value Ps of the plasticizing unit of the injection molding machine 10, the elastic modulus is estimated based on the relationship.

[0094] In this disclosure, the term "elastic modulus" is used as a general term for elastic constant, elastic modulus, Young's modulus (longitudinal elastic modulus, bending elastic modulus), rigidity modulus (transverse elastic modulus, torsional elastic modulus, shear elastic modulus), Poisson's ratio, and bulk modulus. The elastic modulus of a resin material used in injection molding is evaluated by performing dynamic viscoelasticity measurement using a rotational rheometer or the like, and the storage elastic modulus is used as the elastic term of the material. The elastic modulus is measured as the value of the response stress against the strain (amount of displacement), and is expressed in units of [Pa] or [Bar].

[0095] As mentioned above, the elastic modulus of the material has a large effect on the dwelling process. It has been revealed that the elastic modulus near the glass transition temperature (Tg) of the material has a particularly strong effect. Figure 15 is a graph showing the relationship between the elastic modulus of the HIPS material at Tg (=110°C) and the injection volume of the injection molding machine. The elastic modulus at Tg can be derived by extracting the measurement results shown in Figure 9 (Example 1) using a rotational rheometer. Figure 15 shows that there is a strong correlation between the elastic modulus at Tg and the injection volume.

[0096] The ejection volume Vi in FIG. 15 is calculated by formula (10). Injection capacity: Vi=(Lm-Lc)π(D / 2) 2 (10)

[0097] Lm is the metering position [mm], Lc is the packing completion position [mm], and D is the screw inner diameter [mm]. Since the metering position Lm and the screw inner diameter D are fixed regardless of the state of the material, the change in the injection volume Vi occurs due to the change in the packing completion position Lc.

[0098] Since a change in injection volume means a change in the mass of the molded product, this suggests that the elastic modulus at Tg affects the dimensions of the molded product.

[0099] An example of estimating the Tg elastic modulus will be described below with reference to Experimental Example 3. Experimental Example 3 uses a pressure sensor 62 provided in the resin flow path in the mold 1 in Fig. 12(a) and a temperature sensor 63 provided in the vicinity thereof for detecting the temperature of the resin material.

[0100] As a result of careful investigation, it became clear that there is a relationship between the elastic modulus of the resin material at Tg and the decay tendency of the pressure inside the mold. In particular, the pressure inside the mold P when the molded product temperature inside the mold is cooled to Tg + 10℃ 3 There is a negative correlation between the elastic modulus at Tg and the pressure inside the mold when the molded product temperature is cooled to Tg. 3 There was a stronger negative correlation between the elastic modulus at Tg and the

[0101] In this embodiment, the elastic modulus at Tg is estimated based on the formula (11). That is, the pressure sensor value P 3 The ratio of the injection molding machine screw pressure Ps to Ps / P 3 is a parameter related to the elastic modulus. Therefore, in this embodiment, Ps / P 3 By controlling the molding conditions based on the elastic modulus at Tg, control of the molding conditions based on the elastic modulus at Tg can be achieved. Elastic modulus (at Tg) ∝ Ps(x) / P 3 (x) ...(11) x: The point at which the molded product temperature reaches Tg

[0102] As mentioned above, the pressure inside the mold when the molded product temperature inside the mold is cooled to Tg+10℃ is P 3 Since there is a negative correlation between the elastic modulus at Tg and the elastic modulus at Tg, the point at which the molded article temperature drops to a temperature of Tg+10°C or lower may be used as x. Any temperature may be used as long as it is Tg+10°C or lower, and for example, the point at which the molded article is cooled to Tg may be used as x.

[0103] In the example of Figure 12(b), the molded product temperature reaches Tg at X = 4.5 s, so the pressure value P 3 (4.5) = 28 MPa. In addition, the screw pressure is Ps(4.5) = 40 MPa, so the elastic modulus related parameter Ps / P 3 is 1.54MPa.

[0104] Figure 16 shows the elastic modulus-related parameter Ps / P when various types of HIPS materials were used for injection molding in Experimental Example 3. 3 The correlation between the elastic modulus at Tg and the ratio Ps / P 3 It can be seen that there is a strong correlation between the elastic modulus at Tg and

[0105] The method of this embodiment is applied to the estimation of the elastic modulus of the resin material in the first embodiment, and the molding conditions can be changed based on the obtained estimated value.

[0106] In the above example, the elastic modulus is estimated based on the ratio of the screw pressure Ps to the pressure value P3, but a relationship other than Ps / P3 may be used as long as the elastic modulus is estimated based on the relationship or ratio between P3 and Ps. For example, αPs / P 3 , (Ps+β) / P 3 , Ps / (P 3 The elastic modulus may be estimated using the reciprocal of these. α, β, and γ are predetermined coefficients. In addition, P can be calculated by modifying the formula. s / P 3 Or P3 The viscosity may be estimated using a value that includes the component / Ps.

[0107] <Example 4> Another method for estimating the elastic modulus of a resin material from process data obtained during one molding cycle will be described. In Example 3, a method for estimating the elastic modulus at Tg was described, but in Example 4, a method for estimating the elastic modulus at molten state will be described. In this example, the elastic modulus is estimated based on the relationship between a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold 1 and the screw position of the injection molding machine 10. More specifically, the amount of change in the screw position ΔLs and the amount of change in pressure in the resin path in the mold ΔP during the injection process during injection molding are 4 The elastic modulus is estimated based on the relationship between

[0108] The elastic modulus of a resin material when it is completely melted follows Hooke's law, which expresses the amount of displacement relative to the load together with the spring constant, as shown in equation (12). F = Kx (12)

[0109] Here, x is the spring displacement, F is the reaction force (load) of the spring, and K is the spring constant.

[0110] In injection molding, it can be considered that x corresponds to the screw movement amount during injection, F corresponds to the generated stress (pressure inside the mold), and K corresponds to the elastic modulus when melted. Figure 17 is a plot of the screw positions in Experimental Example 3 in Figure 12. The screw movement amount ΔLs during the injection process can be calculated using formula (13). ΔLs=L m -L vp (13)

[0111] Here, Lm is the metering position [mm], and Lvp is the VP switching position [mm]. The amount of change in the pressure inside the mold during the same time period (between injection processes) is ΔP 4 Let us assume that.

[0112] In this example, the elastic modulus when melted is estimated based on equation (14). That is, ΔP 4 Proportion ΔP 4 / ΔLs is used as a parameter related to the elastic modulus (when melted). Therefore, in this embodiment, ΔP 4 By controlling the molding conditions based on / ΔLs, control of the molding conditions based on the elastic modulus when molten can be achieved. Elastic modulus (when melted) ∝ ΔP 4 / ΔLs (14)

[0113] Figure 18 shows the elastic modulus-related parameter ΔP when various types of HIPS materials were used for injection molding in Experimental Example 3. 4 The correlation between / ΔLs and the elastic modulus of each material when melted is shown in Fig. 1. 4 It can be seen that there is a strong correlation between / ΔLs and the melt elastic modulus.

[0114] The method of this embodiment is applied to the estimation of the elastic modulus of the resin material in the first embodiment, and the molding conditions can be changed based on the obtained estimated value.

[0115] In the above example, the elastic modulus is estimated based on the change in pressure inside the mold ΔP relative to the screw movement ΔLs. 4 Based on ΔLs and ΔP 4 If the elastic modulus is estimated based on the relationship or ratio of ΔP 4 Relationships other than αΔP may be used. 4 / ΔLs, (ΔP 4 +Β) / ΔLs, ΔP 4 The elastic modulus may be estimated using / (ΔLs+γ) or the reciprocal of these. Note that α, β, and γ are predetermined coefficients. In addition, the elastic modulus can be estimated by transforming the formula to ΔP 4 / ΔLs or ΔLs / ΔP 4 The viscosity may be estimated using a value that includes the components:

[0116] <Example 5> A method for estimating the shrinkage characteristics of a resin material from process data obtained during one molding cycle will be described. In this embodiment, the shrinkage characteristics are estimated based on the relationship between the pressure sensor value obtained from a pressure sensor installed in the resin flow path in the mold 1 and the injection volume. More specifically, the shrinkage characteristics are estimated based on the relationship between the pressure sensor value obtained from a pressure sensor installed in the resin flow path in the mold 1 and the injection volume when the gate of the mold is sealed in the dwelling process and the cooling process during injection molding. 5 and the pressure inside the mold when the molded product becomes below the deflection temperature under load P 6 The shrinkage characteristics are estimated based on the relationship between the injection volume Vi and

[0117] Resin shrinkage during injection molding is mainly related to two factors: "thermal expansion" and "state change." Thermal expansion is the characteristic where the volume of the resin changes with a change in temperature, and state change is the volume change that occurs when the resin is in a molten state and a solidified state.

[0118] The shrinkage characteristics of such materials are often expressed in a diagram called the PVT curve, as shown in Figure 11, which shows the relationship between pressure [MPa], temperature [℃], and specific volume [cm 3 / g]. This characteristic is mainly measured using a dedicated measuring device called a PVT measuring device. Generally, in injection molding, the resin material changes from a high-temperature, high-pressure state to a low-temperature, low-pressure state, so by reading the difference in specific volume at that time, the shrinkage behavior inside the mold can be predicted.

[0119] Specific volume is the volume per unit weight. However, in injection molding, there are periods of time when weight changes occur as resin flows into the mold. Therefore, to estimate changes in specific volume from process data, it is necessary to analyze data from after the flow of resin into the mold stops.

[0120] Experimental Example 4, which shows an example of shrinkage characteristic estimation, will be described. In Experimental Example 4, a pressure sensor 62 provided in the resin flow path inside the mold 1 in FIG. 12(a) and a temperature sensor 63 provided nearby to detect the temperature of the resin material are used. Since the runner of this mold is a cold runner, the time it takes for the gate to solidify (gate sealing time) was investigated in advance. In the case of Experimental Example 4, the gate sealing time was 5.0 seconds after the start of injection. In other words, after 5.0 seconds During this period, there is no resin flow into the mold and no change in resin weight. Therefore, the process data measured during this period is not affected by fluctuations in resin weight.

[0121] Figure 19 summarizes the relationship between resin temperature and pressure after 5.0 seconds in Experimental Example 4. The vertical axis is pressure [MPa] and the horizontal axis is resin temperature [°C], and the plotted data is roughly linear. This is similar to the linear slope of the PVT characteristics shown in Figure 11. In other words, it is believed that pressure fluctuations when the weight remains constant represent changes in the molded product volume (specific volume).

[0122] In this embodiment, the shrinkage characteristic (specific volume difference) is estimated based on the formula (15). That is, the pressure sensor value P 5 and the pressure sensor value P when the molded product falls below the load deflection temperature 6 The pressure difference is divided by the injection volume Vi (P 5 -P 6 ) / Vi is used as a parameter related to the shrinkage characteristics (specific volume difference). The injection volume Vi is calculated using formula (10). The reason for dividing by the injection volume Vi is to accommodate fluctuations in the filling weight for each molding due to changes in viscosity and elastic modulus. Thus, in this embodiment, (P 5 -P 6 By controlling the molding conditions based on (V) / Vi, control of the molding conditions based on the shrinkage characteristics (specific volume difference) is achieved. Shrinkage characteristics (specific volume difference) ∝ (P 5 -P 6 ) / Vi···(15)

[0123] Figure 20 shows the shrinkage characteristic related parameters (P 5 -P 6 The correlation between ) / Vi and the specific volume difference of each material was measured. The specific volume difference was calculated from the difference between the specific volume at a temperature of 110°C (glass transition temperature) and a pressure of 20 MPa and the specific volume at a temperature of 50°C and a pressure of 20 MPa, which were determined by PVT measurement. As a result, (P 5 -P 6 It can be seen that ) / Vi has a strong correlation with the specific volume difference, that is, the shrinkage characteristics.

[0124] As a modification of this embodiment, the shrinkage characteristic (specific volume difference) may be estimated based on the formula (16). That is, when the pressure value at the gate seal is P5 and the pressure sensor value when the molded product becomes equal to or lower than the load deflection temperature is P6, the pressure difference is expressed as the weight W of the molded product. A Divided by (P 5 -P 6 ) / W A may be used as a parameter related to the shrinkage characteristic (specific volume difference). The same effect can be obtained by estimating the shrinkage characteristic (specific volume difference) in this way. Contraction characteristic ∝ (P 5 -P 6 ) / W A (16)

[0125] The method of this embodiment is applied to the estimation of the shrinkage characteristics of the resin material in the first embodiment, and the molding conditions can be changed based on the obtained estimated values.

[0126] In the above example, we estimate the shrinkage properties as (P 5 -P 6 ) / Vi or (P 5 -P 6 ) / W A Based on the above, P 5 , P 6 , and Vi or W A Other relationships may be used, provided that the shrinkage characteristics are estimated based on the relationship or ratio of P 5 -P6 αP 5 -P 6 yaP 5 -βP 6 Alternatively, you can use a value obtained by adding a constant to at least one of the numerator and denominator. 5 -P 6 And (P 5 -P 6 ) / Vi, (P 5 -P 6 ) / W A Using values ​​that include the components of viscosity may be estimated.

[0127] <Example 6> In the present embodiment, the relationship between the material properties and the molding conditions is obtained with high accuracy by analysis based on a prior measurement, and the material properties can be estimated with high accuracy. An example of the prior measurement is a measurement in a test run before mass production.

[0128] In the first embodiment, an example was described in which the molding conditions (explanatory variables) for obtaining the target material properties (objective variables) were derived using formulas (3), (4), and (5). However, in order to obtain explanatory variables with high accuracy, the constants included in formulas (3) to (5) must be realistic. Therefore, in the sixth embodiment, a procedure for deriving the constants that are realistic will be described.

[0129] In this embodiment, an analysis step is performed before the first injection molding to obtain the relationship between the material properties and the molding conditions, and the molding conditions are set using the obtained relationship. The analysis step can be performed, for example, in a pre-test run. The pre-test run is performed after the production of the mold is completed and the mass production environment, such as the molding machine and temperature controller, is determined, and the test environment is the same as the mass production environment. In addition, a mold and an injection molding machine equipped with a sensor as shown in FIG. 12(a) are used. However, the analysis step may be performed using a test device other than the device used for mass production.

[0130] In the analysis step, injection molding is performed under a number of different conditions. The molding conditions follow the explanatory variables in equations (3) to (5). In other words, since the explanatory variables consist of t (resin temperature), d (injection speed), and p (pressure), molding is performed with these set to a number of different values. Typically, molding is performed by varying the explanatory variables between two and three levels. In the analysis step, the material properties when molding is performed under different conditions are measured, and the measurement results are used to determine the relationship between the material properties and molding conditions.

[0131] Figure 21 shows the settings for Experimental Example 5, where molding conditions were varied in a preliminary test run. HIPS material was used as the resin material, and molding was performed under the environment shown in Figure 12(a). The resin temperature conditions were 200°C to 230°C, and the injection speed was set to 20mm / s to 40mm / s. In Experimental Example 5, the pressure was adjusted by changing the VP position, and was changed within the range of 8mm to 12mm.

[0132] 22(a) to 22(c) show the estimated results of material properties obtained in Experimental Example 5. The estimated values ​​of elastic modulus, viscosity, and shrinkage properties were obtained by the methods described in Examples 2 to 5. As can be seen from these results, each material property shows an approximately linear change with respect to the molding conditions. In other words, the constants included in Equations (3) to (5) can be extracted from the linear approximation formula.

[0133] As described above, by conducting test runs in the same environment as mass production, it is possible to construct a relational equation between the material properties and molding conditions that matches the actual situation. Using this equation during mass production will result in higher molding quality. Note that although the relationship between the material properties and molding conditions is used in the form of a relational equation here, it is also possible to save and use the above relationship in the form of a LUT (Look Up Table). stomach.

[0134] The preliminary analysis may be performed at any timing before the relationship between the material properties and molding conditions obtained by the analysis is used for control. In other words, "previous" may be any timing before the first injection operation. For example, the above analysis may be performed not only during a preliminary test run but also during mass production operation. This is because there is a possibility that differences in material properties may occur between the material used in the test run and the material used during mass production. In the present disclosure, the relationship between the material properties and the molding conditions is continuously updated based on the molding results of the injection molding operation. The continuous update may be performed after each injection molding operation, after multiple injection molding operations, or at any other timing. In the present disclosure, the estimation of material properties is performed even during mass production. Since the molding conditions are continuously changed (modified), it is possible to continue to add plot points to the diagram shown in Fig. 24. Therefore, the linear equation can be updated to a more accurate one with a larger number of measurement points.

[0135] <Example 7> The accuracy of the control process of the injection molding machine shown in Examples 1 to 6 may decrease due to various factors. For example, there may be a shortage of sensors for collecting process data due to mold specifications, or a case where a sensor cannot be installed at a desired position. In such a situation, an error occurs in the calculation for estimating material properties and the calculation for correcting conditions. In addition, although a linear tendency was observed in the molding conditions and material properties in Example 6, nonlinear behavior may occur for various reasons. In such a situation, the calculation accuracy of estimating material properties and correcting molding conditions decreases.

[0136] In this embodiment, such a problem is solved by using machine learning. Machine learning is capable of processing and analyzing on a scale that exceeds the level of human thinking, so if a large amount of information can be collected, it becomes possible to predict situations with high accuracy.

[0137] In this embodiment, the material property calculation unit 53 and the control amount calculation unit 55 shown in FIG. 2 are implemented using a prediction model constructed based on machine learning. Therefore, this embodiment further includes a learning step in which injection molding is performed under a plurality of different conditions, the material properties at that time are measured, and a model of the relationship between the material properties and the molding conditions is learned. The prediction model learning process used in the material property calculation unit 53 is performed using learning data in which the process data and the material properties at the time of injection molding are paired. The learning data is acquired by performing pre-injection molding (before the first injection molding) under a plurality of different molding conditions and acquiring the process data and the material properties at that time. The pair of the process data and the material properties thus obtained is treated as the learning data. In addition, the learning process of the prediction model used in the control amount calculation unit 55 is performed using learning data in which the material property estimate value and the molding condition are paired. The learning data is acquired by performing pre-injection molding (before the first injection molding) under a plurality of different molding conditions and acquiring the material property estimate value and the molding condition at that time. The thus obtained pair of estimated material properties and molding conditions is used as learning data.

[0138] By applying a machine learning algorithm using these learning data, it is possible to learn a prediction model for the material property calculation unit 53 and the control amount calculation unit 55. For the machine learning model, a supervised learning regression analysis can be used, and examples of the machine learning model that can be used include linear regression, SVM regression, random forest, neural network, and deep neural network.

[0139] The prediction model of the material property calculation unit 53 takes process data as input and outputs the material property of the resin material in the process. The controlled variable calculation unit 55 takes the material property estimate as input and outputs the molding conditions (adjustment amount) for obtaining the target material property. A prediction model is trained in which the material property is input and the molding conditions for obtaining the material property are output.

[0140] In addition, it is preferable that the machine learning prediction model is updated during mass production. Since machine learning tends to be more accurate with a larger number of learning data, the control system can be improved by continuously learning through online learning and rewriting the prediction model even during mass production. This embodiment may further include an update step of acquiring learning data for each cycle during mass production, continuously learning through online learning using the data, and updating the prediction model. Note that learning is not required for each cycle, and the re-learning interval is not particularly limited as long as the model is updated using data obtained by injection molding after the learning model has been learned (generated) once as learning data.

[0141] <Example 8> A quality determination method using the technology of the present disclosure will be described.

[0142] In the control flow shown in Figure 3, steps ST8 and ST9 determine whether the material properties are within the allowable values. If the properties are determined to be outside the allowable values, the system issues a warning and determines whether the molding is pass or fail. Steps ST8 and ST9 can be considered as judgment steps that determine whether an injection molded product is pass or fail based on whether multiple parameters related to multiple material properties are within preset appropriate ranges.

[0143] To determine pass / fail, it is necessary to determine a threshold value in advance. The threshold value can be derived experimentally, or by analyzing the relationship between material properties and molding quality using analysis software. There is also a method of setting the threshold value based on past production results.

[0144] It is preferable to perform pass / fail judgment for each estimated material property. For example, if the elastic modulus judgment is passed but the viscosity judgment is failed, the molding quality may be rejected. Basically, if even one of the material properties is unsatisfactory, the molding quality should also be rejected.

[0145] In addition, it is preferable that the material properties to be judged as pass / fail include at least the elastic modulus, viscosity, and shrinkage property. In this case, by expressing the input values ​​(estimated values) of the elastic modulus, viscosity, and shrinkage property using the threshold values ​​and the parameters shown in Examples 2 to 5, it becomes possible to estimate the material properties with high accuracy and judge pass / fail based on them.

[0146] <Example 9> A material property monitoring system utilizing the techniques of the present disclosure will be described.

[0147] 1 to 3, it is possible to fully automatically control the injection molding machine 10. However, by having an operator check various pieces of information obtained during the control process, it is possible to utilize the information for analyzing phenomena and improving work efficiency.

[0148] This embodiment further includes a display step of displaying a plurality of parameters related to a plurality of material properties on a monitor. For example, if the estimated material properties are displayed in real time on a monitor attached to the injection molding machine 10 and the control device 51, it becomes possible to manage the physical properties of the delivered material. Furthermore, it becomes possible to utilize the material properties in element research.

[0149] The above information may be confirmed at a remote location by placing a monitor at a location different from the installation location of the injection molding machine 10. If mass production results can be managed remotely, information from multiple locations can be organized simultaneously.

[0150] In addition, it is preferable that the information is automatically stored in a server or the like for a certain period of time and can be freely extracted afterwards. Therefore, it is preferable that this embodiment further includes a storage step of storing a plurality of parameters related to a plurality of material properties in a storage medium.

[0151] It would also be better if the operator could rewrite the molding conditions themselves based on the measurement results, rather than using fully automatic control.

[0152] <Example 10> The control cycle, i.e., the change in molding conditions, can be set arbitrarily, for example, for each resin lot or each start-up of production.

[0153] In the configuration shown in Figures 1 to 3, the injection molding machine is controlled every one cycle. However, since material properties change significantly when the production lot of the resin material is changed, sufficient effect can be obtained by only controlling at that cycle. However, it is also possible to control the molding conditions at a cycle longer than one cycle and shorter than the cycle when the production lot is changed. In this way, it is preferable to have a function that allows the operator to set the control cycle himself.

[0154] <Additional Notes> The present disclosure includes the following configurations. [Configuration 1] A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; A collection step of collecting a plurality of process data measured during the first injection molding from a plurality of sensors provided in the manufacturing apparatus; An acquisition step of acquiring a plurality of parameters related to a plurality of material properties of a resin material used in the injection molding based on the process data; A control step of setting molding conditions for a second injection molding after the first injection molding based on the plurality of parameters; 1. A method for controlling an injection molding machine, comprising: [Configuration 2] In the control step, molding conditions for the second injection molding are set by using simultaneous equations including a relational expression between an adjustment amount of the molding condition and a change in the parameter, the relational expression being calculated in advance for each of the plurality of parameters. 2. A method for controlling an injection molding machine according to claim 1, [Configuration 3] The plurality of material properties include at least two of the following material properties: viscosity, elastic modulus, and shrinkage property. 3. The control method according to claim 1 or 2. [Configuration 4] The plurality of parameters related to the material properties are A first pressure sensor value P in a resin flow path in a plasticizing section of the injection molding machine when the temperature of the resin material in the mold is equal to or higher than the glass transition temperature Tg in the injection process and the pressure holding process. 1 and a second pressure sensor value P in the resin flow path in the mold. 2 Difference P 1 -P 2 A viscosity-related parameter, the viscosity being a value according to The pressure sensor value P of the resin material in the mold when the temperature of the resin material in the mold drops to the glass transition temperature Tg + 10℃ or lower during the pressure holding process. 3 The ratio of the screw pressure value Ps of the injection molding machine to Ps / P 3 or the change amount ΔP of the pressure sensor value in the mold relative to the change amount ΔLs of the screw position of the injection molding machine in the injection process 4 Proportion ΔP 4 A parameter related to the elastic modulus, which is a value according to / ΔLs; Pressure sensor value P in the resin flow path inside the mold when the mold gate is sealed during the pressure holding and cooling processes 5 and the pressure sensor value P in the resin flow path inside the mold when the molded product falls below its deflection temperature under load. 6 The injection volume Vi or the weight of the molded product W A Divided by (P 5 -P 6 ) / Vi or (P 5 -P 6 ) / W A A parameter related to the shrinkage characteristics, the value of which is a function of Contains at least two parameters from 4. The control method according to any one of configurations 1 to 3. [Configuration 5] Further comprising an analysis step of performing injection molding under a plurality of different conditions prior to the first injection molding, measuring material properties at each step, and determining a relationship between the material properties and the molding conditions; In the control step, the relationship obtained in the analysis step is used to control the plurality of parameters. Setting the molding conditions based on the meter; 5. The control method according to any one of configurations 1 to 4. [Configuration 6] and continuously updating the relationship based on a molding result of the injection molding. 6. The control method according to claim 5, [Configuration 7] Further comprising a learning step of performing injection molding under a plurality of different conditions prior to the first injection molding, measuring material properties at that time, and learning a model of the relationship between material properties and molding conditions; In the control step, the molding conditions are set based on the plurality of parameters using the model. 7. The control method according to any one of configurations 1 to 6, [Configuration 8] updating the model based on results of the second injection molding. 8. The control method according to claim 7, [Configuration 9] Further comprising a step of determining whether the injection molded product is good or bad based on whether a plurality of parameters related to the plurality of material properties are within a preset appropriate range. 9. The control method according to any one of configurations 1 to 8, [Configuration 10] and displaying a plurality of parameters related to the plurality of material properties on a monitor. 10. The control method according to any one of configurations 1 to 9, [Configuration 11] and further comprising a step of storing the plurality of parameters related to the plurality of material properties in a storage medium. 11. The control method according to any one of configurations 1 to 10. [Configuration 12] The collecting step, the acquiring step, and the controlling step are performed every time a production lot of the resin material is changed. 12. The control method according to any one of configurations 1 to 11, [Configuration 13] The collecting step, the acquiring step, and the controlling step are performed every time the manufacturing apparatus is started up. 13. The control method according to any one of configurations 1 to 12, [Configuration 14] A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a first pressure sensor value obtained from a first pressure sensor provided in a plasticizing section of the injection molding machine, a second pressure sensor value obtained from a second pressure sensor provided in a resin flow path in a mold, and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the second pressure sensor for detecting the temperature of the resin material; A first pressure sensor value P when the temperature sensor value is equal to or higher than the glass transition temperature Tg of the resin material during the injection process and the pressure holding process during injection molding. 1 and the second pressure sensor value P 2 A control step of setting molding conditions for injection molding based on the relationship between the above and the above. A control method comprising: [Configuration 15] The above relationship is P 1 and P 2 This is a relationship that depends on the difference between 15. The control method according to claim 14, [Configuration 16] The above relationship is P 1 and P 2 This is a relationship according to the difference between 16. The control method according to configuration 14 or 15. [Configuration 17] In the control step, molding conditions for injection molding are set based on the first pressure sensor value and the second pressure sensor value when the amounts of change over time of the first pressure sensor value and the second pressure sensor value both become within 5 MPa / sec during the injection and pressure holding steps. 17. The control method according to any one of configurations 14 to 16, [Configuration 18] A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold, a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting the temperature of the resin material, and a screw pressure value of the injection molding machine; The pressure sensor value P when the temperature sensor value falls to the glass transition temperature Tg+10°C or lower of the resin material during the pressure holding process during injection molding. 3 and a control step of setting molding conditions for injection molding based on the relationship between the pressure value Ps of the screw of the injection molding machine and the pressure value Ps of the screw of the injection molding machine. A control method comprising: [Configuration 19] The above relationship is P 3 and Ps ratio, 19. The control method according to claim 18, [Configuration 20] A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting pressure sensor values ​​obtained from a pressure sensor provided in a resin flow path in the mold and a screw position of the injection molding machine; The change amount ΔLs of the screw position and the change amount ΔP of the pressure sensor value during the injection process during injection molding 4 A control step of setting molding conditions for injection molding based on the relationship between the A control method comprising: [Configuration 21] The above relationship is ΔP 4 and ΔLs, 21. The control method according to claim 20, [Configuration 22] A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting a temperature of the resin material; Pressure sensor value P when the gate of the mold is sealed during the dwelling and cooling processes during injection molding 5 and the pressure sensor value P when the molded product falls below the load deflection temperature 6 and a control step of setting molding conditions for injection molding based on the relationship between the injection volume Vi and the A control method comprising: [Configuration 23] The above relationship is P 5 and P 6 The relationship is based on the difference between the two and the ratio of Vi. 23. The control method according to claim 22, [Configuration 24] The above relationship is P 5 and P 6 The relationship is based on the difference between the two and the ratio of Vi. 24. The control method according to claim 22 or 23. [Configuration 25] A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting a temperature of the resin material; The pressure sensor value P when the gate of the mold is sealed during the dwelling and cooling processes during injection molding 5 and the pressure sensor value P when the molded product becomes equal to or lower than the load deflection temperature. 6 and the weight of the molded product W A A control step of setting molding conditions for injection molding based on the relationship between the A control method comprising: [Configuration 26] The above relationship is P 5 and P 6 Differences between W and A The relationship is based on the ratio of 26. The control method according to claim 25, [Configuration 27] The above relationship is P 5 and P 6 Difference and W A The relationship is based on the ratio of 27. The control method according to claim 25 or 26, [Configuration 28] Providing a manufacturing apparatus including an injection molding machine and a mold attached to the injection molding machine; Injecting a resin material into the mold by the injection molding machine; removing the injection molded article from the mold; Including, The manufacturing apparatus is controlled by the control method according to any one of configurations 1 to 27; A method for producing an injection molded product comprising the steps of: [Configuration 29] The resin material is a recycled resin material. 29. A method for producing an injection molded product according to claim 28, [Configuration 30] A manufacturing apparatus including an injection molding machine and a mold attached to the injection molding machine; A control device; Equipped with The control device controls the manufacturing device by the control method according to any one of configurations 1 to 27. A system characterized by: [Explanation of symbols]

[0155] 1: Mold 10: Injection molding machine 11: Plasticizing device 12: Mold clamping device 51: Control device 52: Data detection unit 53: Material property calculation unit 54: Comparison section 55: Control amount calculation section 61: Die sensor 62: Second pressure sensor 63: Resin temperature sensor 71: Cylinder sensor 72: First pressure sensor 81: Measuring device

Claims

1. A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; A collection step of collecting a plurality of process data measured during the first injection molding from a plurality of sensors provided in the manufacturing apparatus; An acquisition step of acquiring a plurality of parameters related to a plurality of material properties of a resin material used in the injection molding based on the process data; A control step of setting molding conditions for a second injection molding after the first injection molding based on the plurality of parameters; 1. A method for controlling an injection molding machine, comprising:

2. In the control step, molding conditions for the second injection molding are set by using simultaneous equations including a relational expression between an adjustment amount of the molding condition and a change in the parameter, the relational expression being calculated in advance for each of the plurality of parameters.

2. The method for controlling an injection molding machine according to claim 1.

3. The plurality of material properties include at least two of the following material properties: viscosity, elastic modulus, and shrinkage property.

2. The control method according to claim 1 .

4. The plurality of parameters related to the material properties are A first pressure sensor value P in a resin flow path in a plasticizing section of the injection molding machine when the temperature of the resin material in the mold is equal to or higher than the glass transition temperature Tg in the injection process and the pressure holding process. １ and a second pressure sensor value P in the resin flow path in the mold. ２ Difference P １ -P ２ A viscosity-related parameter, the viscosity being a value according to The pressure sensor value P of the resin material in the mold when the temperature of the resin material in the mold drops to the glass transition temperature Tg + 10 ° C. or lower during the pressure holding process ３ The ratio of the screw pressure value Ps of the injection molding machine to the ３ or the change amount ΔP of the pressure sensor value in the mold relative to the change amount ΔLs of the screw position of the injection molding machine in the injection process ４ The ratio ΔP ４ A parameter related to the elastic modulus, which is a value according to / ΔLs; Pressure sensor value P in the resin flow path in the mold when the mold gate is sealed during the pressure holding process and the cooling process ５ and the pressure sensor value P in the resin flow path in the mold when the molded product becomes equal to or lower than the deflection temperature under load. ６ The injection volume Vi or the weight of the molded product W Ａ Divided by (P ５ -P ６ ) / Vi or (P ５ -P ６ ) / W Ａ A parameter related to the shrinkage characteristics, the value of which is a function of The parameter includes at least two of the following:

2. The control method according to claim 1 .

5. Further comprising an analysis step of performing injection molding under a plurality of different conditions prior to the first injection molding, measuring material properties at each step, and determining a relationship between the material properties and the molding conditions; In the control step, the molding conditions are set based on the plurality of parameters using the relationship obtained in the analysis step.

2. The control method according to claim 1 .

6. and continuously updating the relationship based on a molding result of the injection molding.

6. The control method according to claim 5.

7. The method further includes a learning step of performing injection molding under a plurality of different conditions prior to the first injection molding, measuring material properties at the time, and learning a model of the relationship between material properties and molding conditions. fruit, In the control step, the molding conditions are set based on the plurality of parameters using the model.

2. The control method according to claim 1 .

8. updating the model based on results of the second injection molding.

8. The control method according to claim 7.

9. The method further includes a step of determining whether the injection molded product is good or bad based on whether a plurality of parameters related to the plurality of material properties are within a predetermined appropriate range.

2. The control method according to claim 1 .

10. and displaying a plurality of parameters related to the plurality of material properties on a monitor.

2. The control method according to claim 1 .

11. and further comprising a step of storing the plurality of parameters related to the plurality of material properties in a storage medium.

2. The control method according to claim 1 .

12. The collecting step, the acquiring step, and the controlling step are performed every time a production lot of the resin material is changed.

2. The control method according to claim 1 .

13. The collecting step, the acquiring step, and the controlling step are performed every time the manufacturing apparatus is started up.

2. The control method according to claim 1 .

14. A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a first pressure sensor value obtained from a first pressure sensor provided in a plasticizing section of the injection molding machine, a second pressure sensor value obtained from a second pressure sensor provided in a resin flow path in a mold, and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the second pressure sensor for detecting the temperature of the resin material; A first pressure sensor value P when the temperature sensor value is equal to or higher than the glass transition temperature Tg of the resin material during the injection process and the pressure holding process during injection molding. １ and the second pressure sensor value P ２ A control step of setting molding conditions for injection molding based on the relationship between the above and the above. A control method comprising:

15. The relationship is P １ and P ２ This is a relationship that depends on the difference between 15. The control method according to claim 14.

16. The relationship is P １ and P ２ This is a relationship according to the difference between 15. The control method according to claim 14.

17. In the control step, molding conditions for injection molding are set based on the first pressure sensor value and the second pressure sensor value when the amounts of change over time of the first pressure sensor value and the second pressure sensor value both become within 5 MPa / sec in the injection and pressure holding steps.

15. The control method according to claim 14.

18. A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold, a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting a temperature of the resin material, and a screw pressure value of the injection molding machine; The pressure sensor value P when the temperature sensor value falls to the glass transition temperature Tg+10° C. of the resin material during the pressure holding step in injection molding. ３ and a control step of setting molding conditions for injection molding based on the relationship between the pressure value Ps of the screw of the injection molding machine and the pressure value Ps of the screw of the injection molding machine. A control method comprising:

19. The relationship is P ３ and Ps ratio, 20. The method of claim 18.

20. A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting pressure sensor values ​​obtained from a pressure sensor provided in a resin flow path in the mold and a screw position of the injection molding machine; The change amount ΔLs of the screw position and the change amount ΔP of the pressure sensor value during the injection process during injection molding ４ A control step of setting molding conditions for injection molding based on the relationship between the A control method comprising:

21. The relationship is ΔP ４ and ΔLs, 21. The control method according to claim 20.

22. A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting a temperature of the resin material; The pressure sensor value P when the gate of the mold is sealed during the pressure holding process and the cooling process during injection molding ５ and the pressure sensor value P when the molded product falls below the load deflection temperature ６ and a control step of setting molding conditions for injection molding based on the relationship between the injection volume Vi and the A control method comprising:

23. The relationship is P ５ and P ６ The relationship is based on the difference between the two and the ratio of Vi.

23. The method of claim 22.

24. The relationship is P ５ and P ６ and the ratio of Vi, 23. The method of claim 22.

25. A manufacturing apparatus control method executed by a control device, comprising: the manufacturing apparatus includes an injection molding machine and a mold attached to the injection molding machine; a collection step of collecting a pressure sensor value obtained from a pressure sensor provided in a resin flow path in the mold and a temperature sensor value obtained from a temperature sensor provided in the vicinity of the pressure sensor for detecting a temperature of the resin material; The pressure sensor value P when the gate of the mold is sealed during the pressure holding process and the cooling process during injection molding ５ and the pressure sensor value P when the molded product becomes equal to or lower than the load deflection temperature. ６ and the weight of the molded product W Ａ A control step of setting molding conditions for injection molding based on the relationship between the A control method comprising:

26. The relationship is P ５ and P ６ Differences between Ａ The relationship is based on the ratio of 26. The control method according to claim 25.

27. The relationship is P ５ and P ６ Difference and W Ａ The relationship is based on the ratio of 26. The control method according to claim 25.

28. Providing a manufacturing apparatus including an injection molding machine and a mold attached to the injection molding machine; Injecting a resin material into the mold by the injection molding machine; removing the injection molded article from the mold; Including, The manufacturing apparatus is controlled by a control method according to any one of claims 1 to 27. A method for producing an injection molded product comprising the steps of:

29. The resin material is a recycled resin material.

29. The method for producing an injection molded article according to claim 28.

30. A manufacturing apparatus including an injection molding machine and a mold attached to the injection molding machine; A control device; Equipped with The control device controls the manufacturing device by a control method according to any one of claims 1 to 27. A system characterized by:

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