JP2003145577A - Flow analyzing method, flow analyzer, and computer program and memory medium therefor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To solve the problem that enormous material physical property data are registered in a data base for use in the analysis of a flow but there is a problem in the measuring cost and accuracy of the molten material physical property data thereof. SOLUTION: The analysis of the flow is performed on the basis of the molten material physical property data obtained from an injection molding machine for actually molding a molded article.

Description

Detailed Description of the Invention

[0001]

TECHNICAL FIELD The present invention relates to a flow analysis method, a flow analysis device, and a flow analysis apparatus suitable for simulating a molding process of a molded product injection-molded by using a molten material and supporting measures against defects of the molded product. The present invention relates to a computer program and a storage medium.

[0002]

2. Description of the Related Art A flow analysis of a material when injection molding is performed using a molten material is performed using an analytical shape model, molding condition data and material physical property data. Here, the analytical shape model is a numerical model of the shape of a part in which a molten material such as a molded product or a runner flows in a mold for a flow analysis. Conventionally, a flow analysis has been performed using material physical properties registered in a database in advance as material physical property data (for example, refer to Patent Document 1).

[0003]

[Patent Document 1] Japanese Patent Laid-Open No. 2000-355033 (paragraph number [0040], FIG. 4)

[0004]

In order to register the material properties in the database, it was necessary to measure the melted material properties separately in advance with some kind of measuring instrument and register the material property data obtained thereby. . Therefore, a measuring device for measuring the physical properties of the molten material has to be used separately from the injection molding machine, which is very expensive.

Further, since there are lot-to-lot variations of materials used for injection molding and machine differences of injection molding machines, for example, machine differences in temperature and speed control, the material properties registered in the database in advance are used. In some cases, satisfactory analysis accuracy could not be obtained even if the flow analysis was performed according to the setting. The present invention has been made in view of the above circumstances, and a flow analysis method, a flow analysis apparatus, and a computer program and a storage medium therefor that more accurately predict the flow behavior of a material in a mold in a molding process of injection molding. The purpose is to provide.

[0006]

In order to solve the above problems, the flow analysis method of the present invention is based on the data obtained from the injection molding machine when performing the flow analysis of the molten material in the process of injection molding. The method is characterized by including a step of calculating physical property data and a step of performing a flow analysis using the calculated material physical property data.

The flow analysis apparatus of the present invention is a flow analysis apparatus for performing a flow analysis of a molten material in the process of injection molding, and a material property for calculating material property data based on data obtained from an injection molding machine. It is characterized by having a data calculation means and a flow analysis means for performing a flow analysis based on an analysis shape model, material physical property data and molding condition data.

The present invention also includes a computer program for executing each step of the flow analysis method using a computer, and a computer-readable storage medium storing the computer program.

[0009]

BEST MODE FOR CARRYING OUT THE INVENTION In the flow analysis using the present invention, the material physical property data is calculated based on the data obtained from the injection molding machine, and the flow analysis is performed using the calculated material physical property data. It enables highly accurate flow analysis without undue cost. Viscosity data is one of the important material property data for flow analysis. Viscosity is a material property data that is easily affected by temperature, shear rate, and molecular weight. However, the molecular weight of the material may differ depending on the production lot, and as a result, it may affect the shear rate dependence and temperature dependence of the viscosity. When the viscosity data obtained by using a viscosity measuring instrument such as a capillary viscometer is registered in a database and used as in the past, this viscosity data includes variations between material lots and machine differences of the injection molding machine used. Is never reflected. Therefore, the analysis accuracy of the flow analysis using the viscosity data registered in the database inevitably becomes unreliable.

By using the flow analysis of the present invention, it is possible to calculate the viscosity data based on the data obtained from the actually used injection molding machine by using the actually used materials. It is possible to perform flow analysis that reflects variations and machine differences of the injection molding machines used. Moreover, since no separate measuring device is required, it is advantageous in terms of cost. Of course, the same applies to material properties other than viscosity.

Embodiments of a flow analysis method and apparatus according to the present invention will be described below with reference to the accompanying drawings by taking as an example a case where a molten material is a resin and viscosity data is used as material physical property data. FIG. 1 is a block diagram showing an embodiment of the flow analysis apparatus of the present invention. In the present embodiment, (10
0) is an injection molding machine, (101) is a computer, (10)
2) is a keyboard, (103) is a mouse, (104) is a display, and (105) is an auxiliary storage device. In the auxiliary storage device (105), in addition to HD (hard disk),
A removable auxiliary storage device such as an FD (flexible magnetic disk), an MO (magneto-optical disk), a PD (optical disk), a DVD (digital multipurpose disk) or the like can also be used.

It is desirable that the injection molding machine (100) be an electric injection molding machine whose speed can be easily controlled. Figure 15
Shows an outline of an injection mechanism section of an electric injection molding machine to which injection pressure control is applied. In FIG. 15, (201) is a nozzle, (202) is a cylinder, (203) is a screw, (204) is a hopper that supplies resin pellets into the cylinder, (205) is a front plate that constitutes an injection mechanism section, ( 206) is a rear plate. A plurality of guide bars (207) are provided between the front plate (205) and the rear plate (206), and the pressure plate (208) is guided by these guide bars (207) so that the pressure plate (208) moves forward and backward (left and right in the figure). ) Is arranged to be movable.

A base of a screw (203) is rotatably attached to the pressure plate (208), and a pulley is attached to the base, and a drive pulley and a timing belt are attached by a screw rotation servomotor (M1). Screw (20
3) is rotationally driven. In addition, the pressure plate (2
A ball nut (210) is attached to the ball nut (210) via a pressure sensor (load cell) (209), and a ball screw (211) is screwed into the ball nut (210). The ball screw (211) is driven by the injection servo motor (M2) to drive the pulley, the timing belt,
It is designed to be rotationally driven via a passive pulley.

During the injection process, the injection servo motor (M
2) is driven, the ball screw (211) rotates, the nut (210) and the pressure plate (208) screwed to the ball screw (211) advance (leftward in the figure),
The screw (208) also moves forward and the molten resin in the cylinder (202) is injected. The injection molding machine (100) of the present embodiment creates molding machine data creation means (data for creating temperature data such as temperature, pressure and movement of each part of the injection molding machine so that the data can be taken out of the injection molding machine (100). 118). When the viscosity data is used as the material physical property data, the molding machine data creating means preferably includes at least air shot flow rate / pressure data creating means.

The air shot flow rate / pressure data generating means is, for example, as shown in the above-mentioned Patent Document 1, the injection flow rate when the molten material is blank-shot (air shot) without attaching a die, and the injection flow rate at that time. It is a means for detecting the resin pressure generated and creating data on the injection flow rate and the resin pressure. The injection flow rate can be obtained by multiplying the cylinder cross-sectional area and the injection speed in an electric injection molding machine capable of precise speed control. The resin pressure is the pressure detected by the load cell (209) when the molten material is injected as shown in FIG. 15, that is, the injection pressure received at the rear end of the screw (203).

The auxiliary storage device (105) includes a molding machine data storage means (106) and a material physical property data storage means (10).
8), CAD data storage means (109), analysis condition storage means (110), analysis shape model storage means (111),
The flow analysis result storage means (112) is a computer (1
It is included as a file managed by the operating system 01).

The molding machine data storage means (106) stores the data extracted from the molding machine data creating means and the separately input data concerning the injection molding machine (100). When the viscosity data is used as the material physical property data, at least the air shot flow rate / pressure data created by the air shot flow rate / pressure data creation means is separately input to the molding machine data storage means (106). It is preferable to store the nozzle shape data.

The nozzle shape data is numerical data of the nozzle shape of the molding machine that has performed the air shot. The material physical property data storage means (108) stores resin physical property data, such as thermal conductivity and specific heat, necessary for the viscosity and other flow analysis created by the material physical property data calculation means (114) described later.
It is a means of storing density and the like.

The CAD data storage means (109) stores the CAD data created in advance and / or the data created by the CAD data creating means described later. The analysis condition storage means (110) stores the molding conditions. Analytical shape model storage means (1
11) stores previously created analysis shape model data for numerical analysis of a molded product and / or stores data created by an analysis shape model creating means (116) described later.

The flow analysis result storage means (112) stores data created by the flow analysis means (117) described later. In the computer (101), a molding machine data reading means (113) consisting of a CPU and a subroutine expanded on a memory, a material physical property data calculating means (114), a CAD data creating means (115), and an analytical shape model creating means (116). , Flow analysis means (117)
Etc. are included.

The molding machine data reading means (113) externally reads molding machine data such as air shot flow rate / pressure data created by the molding machine data creation means (118) and / or the auxiliary storage device (105). This is a means for reading the molding machine data stored in the molding machine data storage means (106). The material property data calculation means (114) is a means for creating material property data used for flow analysis. Below, an example of the method of creating viscosity data using the material physical property data calculation means (114) is shown.

A pressure Pair (hereinafter referred to as an air shot pressure) for detecting a reaction force of the molten resin obtained by an air shot for injecting the molten resin without attaching a die, a flow rate q at that time,
And the shear viscosity of the molten resin can be obtained from the molding machine nozzle shape data. FIG. 5 shows a waveform of the air shot pressure Pair. As shown in FIG. 5, the final pressure of the air shot pressure Pair is set to the nozzle rear end pressure Pair-last.
And

Next, a method for obtaining the shear viscosity from the air shot pressure Pair will be described. First, in the flow analysis, the data of the shear viscosity itself is not necessary, and the viscosity coefficient of the viscosity formula representing an arbitrary viscosity model may be obtained. Here, the three-constant viscosity model shown in equation (1) is used as the shear viscosity equation. η = A × γ ^B × exp (C × T) (1) where η is viscosity, γ is shear rate, T is temperature, A, B,
C is a viscosity coefficient.

FIG. 6 shows an example of nozzle shape data and a calculation method using the same. The nozzle shape is preferably assumed to be a combination of circular pipes (C1, ~ Cn) having different diameters (D1, ~ Dn) and lengths (L1, ~ Ln). The pressure loss DPi generated in each circular pipe is
It may be obtained by the pressure loss calculation method assuming the Newtonian fluid shown in (2).

DPi = (8.0 × Li × q × η) / (π × ri ⁴ ) ri = 0.5 × Di (however, i = 1, to n) (2) where q is a resin The flow rate and η are the viscosities represented by the above formula (1). Here, the shear rate required for the equation (1) may be obtained by the shear rate calculation method assuming the Newtonian fluid shown in the equation (3).

Γ = (8.0 × q) / (π × Di ³ ) ... (3) Next, the pressure Pend at the rear end of the nozzle is expressed by the equation (4). Pend = atmospheric pressure + DP1 + DP2 + ... + DPn (4) Finally, the nozzle rear end pressure Pend represented by the equation (4).
The viscosity coefficients A, B and C are determined so that becomes the above-mentioned Pair-last. The method for determining the viscosity coefficients A, B, C is as follows: Genetic Algorithms; G
It can be determined using an optimization method such as A).
The created viscosity data is stored in the material physical property data storage means (10
It is stored in 8) and, if necessary, it is read out from this to a memory and used.

The CAD data creating means (115) is a means for creating the shape of a molded product on a computer, and is an ID
It is a technology installed in many CAD such as EAS (manufactured by SDRC; trade name), CATIA (manufactured by Dassult, trade name), UniGraphics (manufactured by UGS, trade name). The created CAD data is stored in the CAD data storage means (109) or is read out from the CAD data storage means (109) and used.

The analysis shape model creating means (116) uses C
With respect to the CAD data created by the AD data creating means (115), for example, as shown in FIG. 7, a neutral surface is created from the CAD data, a two-dimensional shell element is automatically created, and / or a three-dimensional solid element is created. Automatically creates an analysis shape model consisting of. As described above, the method of creating the analysis shape model from the CAD data is used in many CAD as described above.
Is a technology installed in. The created analytical shape model data is stored in the analytical shape model storage means (111) and, if necessary, is read out from the memory to be used.

The flow analysis means (117) is an analysis shape model and material physical property data storage means (108) created by the analysis shape model creation means (116), and an analysis condition storage means (1).
10) is a means for obtaining the pressure and temperature at the time of flow, the flow velocity vector, etc., based on the material properties and analysis conditions read from the memory from 10).
This is a technology installed in flow analysis software such as injection molding such as LDFLOW (MOLDFLOW, trade name). The analysis shape model, material physical property data, molding condition data, etc. may be read into the memory from the auxiliary storage device (105), but the data already developed in the memory may be used as it is. .

The flow of work using each of the above means is shown in the flow chart of FIG. First, CAD data creating means (1
According to 15), CAD data of the shape of the molded product is created (step 201). Then, the analysis shape model creating means (116) creates a two-dimensional or three-dimensional analysis shape model based on the CAD data (step 20).
2). Next, the viscosity data (step 203) created by the material physical property data calculating means (114) by the flow analysis means (117) and other material physical property data and analysis conditions registered in advance in the database are read (step 204). A flow analysis is performed on the above analysis shape model (step 205).

In this embodiment, the molding machine data such as the air shot flow rate / pressure data created by the molding machine data creating means (118) may be imported into the computer (101) by any method. For example, the molding machine (100) and the computer (101) may be directly connected by a cable or the like to exchange data, or the data may be exchanged via a network. In addition, the data created by the molding machine data creating means (118)
Alternatively, the data may be temporarily stored in an external recording medium such as D or MO, and read out by the molding machine data reading means (113) for use. In particular, it is preferable from the viewpoint of operability that the molding machine data is read directly from the molding machine (100) to the computer (101) by using the molding machine data reading means (113). Here, to directly take in molding machine data means that the molding machine (100) transmits the molding machine data through a cable, a network or the like in response to a data transmission request transmitted from the molding machine data reading means (113). Is automatically read by the molding machine data reading means (113).

The molding machine data reading means (113)
FIG. 14 shows an example mounted on the user graphical interface displayed on the computer screen. In the example shown in FIG. 14, when the viscosity data acquisition button is clicked, the air shot flow rate / pressure data is directly acquired from the molding machine (100) and is input in advance and stored in the molding machine data storage means (106). The viscosity data is calculated by the material physical property data calculating means (114) by the above-mentioned method together with the nozzle shape data thus obtained, and is automatically stored in the material physical property data storing means (108).
The above operation can be performed with only one click of the user graphical interface.

Another embodiment is shown in FIG. The second embodiment shown in FIG. 2 is the same as the embodiment shown in FIG. 1 except that the data is obtained from the molding machine via the network. Further, the auxiliary storage device (105) is connected to the server (13
0) or other computer (not shown), and various data may be exchanged via the network.

Further, as in the third embodiment shown in FIG.
The fiber orientation analysis means (12
1) It is also preferable to further include a warp analysis means (122), and to carry out the fiber orientation analysis and the warp analysis after performing the flow analysis. Here, the fiber orientation analysis means (121) is means for analyzing the fiber orientation during the flow based on the result obtained by the flow analysis means (117). Sled analysis means (121)
Is a flow analysis means (117) and a fiber orientation analysis means (12
It is a means for predicting the warpage of a molded product based on the result obtained in 1).

In FIG. 3, the fiber orientation analysis result storage means (119) is a means for storing the result obtained by the fiber orientation analysis means (121). The warp analysis result storage means (120) is a means for storing the result obtained by the warp analysis means (122). Below, FIG. 8 shows a specific simulation example according to each embodiment of the present invention.

FIG. 8 is a logarithmic graph of the viscosity data prepared by the material physical property data preparation means. The resin used is modified PPO (polyphenylene oxide plastic resin). The viscosity coefficient for the viscosity equation of equation (1) is [A = 1.1840E + 06] and [B
= -5.3810E-01] and [C = -1.8420E-02].

On the other hand, FIG. 9 is a logarithmic graph showing the viscosity data registered in advance in the database. The resin used is the same as in FIG. The viscosity coefficient for the viscosity equation of the equation (1) is [A = 2.0050E + 06], [B
= -5.8770E-01] and [C = -1.5170E-02]. Figure 10 is 100mm x 30mm used for accuracy verification
× This is an analytical model of a flat plate mold having a wall thickness of 2 mm.

FIG. 11 is a graph comparing the actual measurement and the analysis result when the flow analysis is performed on the viscosity data shown in FIG. 8 and the viscosity data shown in FIG. 9 using the analysis model of FIG. is there. FIG. 12 is an analysis model of the box mold used for accuracy verification. FIG. 13 is a graph comparing the actual measurement and the analysis result when the flow analysis is performed on the viscosity data shown in FIG. 8 and the viscosity data shown in FIG. 9 using the analysis model of FIG.

As described above, not only the material physical property data can be easily obtained from the injection molding machine, but also the material physical property data obtained from the injection molding machine is used for the flow analysis to perform a more accurate simulation. You can In addition, the flow analysis method as described above is performed by a computer and software (program) loaded in the computer.
It is realized by. Such software is distributed through a tangible storage medium such as a flexible magnetic disk or a CD-ROM, or a transmission means such as a wireless or wired network.

[0040]

According to the present invention, the material property data of the molten material to be actually molded from the injection molding machine is acquired when necessary without registering a vast amount of material property data used for flow analysis in the database in advance. Then, the flow analysis can be performed. Furthermore, since the material property data of the material actually used is acquired from the injection molding machine that actually molds the molded product, it becomes possible to more accurately predict the flow behavior in the mold during injection molding.

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of a first exemplary embodiment of the present invention.

FIG. 2 is a block diagram showing a configuration of a second exemplary embodiment of the present invention.

FIG. 3 is a block diagram showing a configuration of a third exemplary embodiment of the present invention.

FIG. 4 is a flowchart of an embodiment of the present invention.

FIG. 5 is air shot data obtained from an electric injection molding machine.

6 is a numerical calculation method for obtaining the pressure at the rear end portion of the nozzle necessary for converting the viscosity data from the air shot data of FIG.

FIG. 7 is a CAD shape and analysis shape model diagram.

FIG. 8 is a logarithmic graph showing the viscosity data created by the material physical property data calculating means (114).

FIG. 9 is a logarithmic graph of viscosity data registered in advance in a database.

FIG. 10 is an analytical shape model diagram for a flat plate of 100 mm × 30 mm × thickness of 2 mm.

FIG. 11 is a graph comparing the actual measurement and the analysis result when a flow analysis is performed on the viscosity data shown in FIG. 8 and the viscosity data shown in FIG. 9 using the analysis model of FIG. 10.

FIG. 12 is an analysis shape model diagram for a box of 100 mm × 70 mm × 50 mm.

13 is a graph comparing the actual measurement and the analysis result when the flow analysis is performed on the viscosity data shown in FIG. 8 and the viscosity data shown in FIG. 9 using the analysis model of FIG.

FIG. 14 shows a method of embodying the molding machine data reading means 113 by a graphical user interface.

FIG. 15 is a diagram showing an outline of an injection mechanism section of a typical electric injection molding machine.

[Explanation of symbols]

101 computer 102 keyboard 103 mouse 104 display 105 auxiliary storage 106 molding machine data storage means 108 Material Physical Property Data Storage Means 109 CAD data storage means 110 analysis condition storage means 111 analysis shape model storage means 112 flow analysis result storage means 113 Molding machine data reading means 114 Material Physical Property Data Calculation Means 115 CAD data creating means 116 Analytical shape model creating means 117 Flow analysis means 118 Molding machine data creation means 119 Fiber orientation analysis result storage means 120 Sled analysis result storage means 121 Fiber orientation analysis means 122 Sled analysis means 201 nozzle 202 cylinder 203 screw 204 hopper 205 front plate 206 rear plate 207 Guide bar 208 Pressure plate 209 Pressure sensor (load cell) 210 ball nut 211 ball screw Servo motor for M1 screw rotation M2 injection servo motor

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Katsuya Sakaba             1-1 1-1 Sonoyama, Otsu City, Shiga Prefecture Toray Co., Ltd.             Ceremony company Shiga business site (72) Inventor Kenichi Konishi             1-1 1-1 Sonoyama, Otsu City, Shiga Prefecture Toray Co., Ltd.             Ceremony company Shiga business site (72) Inventor Yasuo Suga             1-1 1-1 Sonoyama, Otsu City, Shiga Prefecture Toray Co., Ltd.             Ceremony company Shiga business site (72) Inventor Shusaku Nishiyama             4-1, Kamiodanaka, Nakahara-ku, Kawasaki-shi, Kanagawa             No. 1 within Fujitsu Limited (72) Inventor ▲ Taka ▼ Ikushi History             4-1, Kamiodanaka, Nakahara-ku, Kawasaki-shi, Kanagawa             No. 1 within Fujitsu Limited F-term (reference) 4F206 JA07 JL09 JP11

Claims (8)

[Claims] 1. When performing a flow analysis of a molten material in the process of injection molding, a step of calculating material physical property data based on data obtained from an injection molding machine, and a flow analysis using the calculated material physical property data. And a step of performing a flow analysis method. 2. The flow analysis method according to claim 1, wherein the material physical property data calculated based on the data obtained from the injection molding machine is viscosity data. 3. The flow analysis method according to claim 1, wherein when the material property data is calculated based on the data obtained from the injection molding machine, the data is fetched from the injection molding machine. 4. A flow analysis device for performing a flow analysis of a molten material in a process of injection molding, comprising material physical property data calculating means for calculating material physical property data based on data obtained from an injection molding machine, and an analysis shape. A flow analysis device comprising: a flow analysis means for performing a flow analysis based on a model, material property data, and molding condition data. 5. The flow analysis apparatus according to claim 4, wherein the material physical property data calculated based on the data obtained from the injection molding machine is viscosity data. 6. The flow analysis apparatus according to claim 4, further comprising molding machine data reading means for fetching data from the injection molding machine. 7. A computer program for executing each step in the flow analysis method according to claim 1 by using a computer. 8. A computer-readable storage medium storing the computer program according to claim 7.