JP7626272B2 - Drawdown stress estimation device, drawdown stress estimation method, and manufacturing method for extrusion molded products - Google Patents

Description

The present invention relates to a pull-down stress estimation technique for estimating the pull-down stress of resin.

JP 09-262887 A (Patent Document 1) describes a technique for predicting changes in specific volume and shrinkage rate by taking into account crystallization during the molding process of crystalline resins.

Japanese Patent Application Publication No. 9-262887

The cable has a structure in which the conductors are covered with resin to ensure insulation, and the resin covering the conductors is formed, for example, by extrusion molding technology. The resin formed by extrusion molding technology is then annealed, but it is known that the resin shrinks after annealing. For example, if the resin shrinks in the longitudinal direction of the cable, this can cause fluctuations in the outer diameter, making the cable larger, or can cause problems such as the conductors (core wires) being exposed from the ends of the cable. For this reason, it is desirable to reduce the shrinkage rate of the resin.

In this regard, technology has been developed to reduce the post-shrinkage (shrink-back) of resin that occurs after cable manufacturing. In particular, it has been found that the post-shrinkage of resin after extrusion molding can be reduced by appropriately controlling the extrusion conditions in extrusion molding. For this reason, a shrinkage rate estimation technology has been developed that estimates the shrinkage rate of resin based on the extrusion conditions.

This technology makes it possible to reduce the resin's shrinkage rate by appropriately setting the extrusion conditions, but it does not take into account the material properties of the resin (viscosity and crystallinity). Therefore, if the material properties of the resin change, the extrusion conditions must be optimized each time.

In other words, since the resin shrinkage rate is affected not only by the extrusion conditions but also by the material properties of the resin, it is desirable to develop technology that can reduce the resin shrinkage rate by taking into account not only the extrusion conditions but also the material properties of the resin.

In one embodiment, the pull-down stress estimation device includes a pull-down stress estimation unit that estimates the pull-down stress based on Equation 1 and Equation 5, which include constants related to the resin viscosity and the extrusion conditions of the resin.

The pull-down stress estimation method in one embodiment includes a pull-down stress estimation step for estimating the pull-down stress based on Equation 1 and Equation 5, which include constants related to the resin viscosity and extrusion conditions for the resin.

In one embodiment, the method for manufacturing an extrusion molded product uses an extruder. Here, the method for manufacturing an extrusion molded product includes a pull-down stress estimation process for estimating the pull-down stress applied when extruding a resin, and an extrusion condition change process for changing the extrusion conditions of the resin based on the pull-down stress, and the pull-down stress estimation process estimates the pull-down stress based on Equation 1 and Equation 5, which include a constant related to the viscosity of the resin and the extrusion conditions.

ここで、
σ：引落応力
η_０：粘度定数
α：粘度の温度係数
Ｔ：樹脂の温度
ｖ_ｆ：線速
Ｌ：ダイの出口から水槽までの距離
Ｄ：引落比
ｎ：粘度指数

Where:
σ: Drawdown stress η ₀ : Viscosity constant α: Temperature coefficient of viscosity T: Resin temperature v _f : Linear speed L: Distance from die outlet to water tank D: Drawdown ratio n: Viscosity index

ここで、
Ｓ_ｄ：ダイの出口の断面積
Ｓ_ｆ：成形物の断面積

Where:
S _d : Cross-sectional area of the die outlet S _f : Cross-sectional area of the molded product

According to one embodiment, the resin shrinkage rate can be reduced by taking into account not only the extrusion conditions but also the material properties of the resin.

5A to 5C are schematic diagrams illustrating an extrusion molding process for covering the outer periphery of a conductor wire with resin. 1 is a schematic diagram showing a state in which a conductor wire is covered with a resin extruded from a die. FIG. FIG. 2 is a schematic diagram illustrating “strain rate.” 1 is a table showing 16 types of experimental conditions (extrusion conditions: temperature, linear speed, rotation speed, outer diameter), the shrinkage rates measured under each of the 16 types of experimental conditions, and the "draw-down stress" estimated based on (Equation 1). 1 is a graph showing the relationship between "drawdown stress" and "shrinkage rate." FIG. 2 is a diagram illustrating an example of a hardware configuration of a shrinkage ratio estimation device. FIG. 2 is a functional block diagram showing a functional configuration of the shrinkage rate estimation device. FIG. 1 is a diagram illustrating a configuration for determining a viscosity constant, a temperature coefficient of viscosity, and a viscosity index by machine learning. FIG. 1 is a diagram illustrating a configuration for determining a response function by machine learning. 4 is a flowchart illustrating a basic operation of the shrinkage rate estimation device. 11 is a flowchart illustrating an application operation of the shrinkage ratio estimation device. 1 is a flowchart illustrating a method for manufacturing an extrusion molded product using a shrinkage rate estimation technique.

In all drawings used to explain the embodiments, the same components are generally given the same reference numerals, and repeated explanations will be omitted. In addition, hatching may be used even in plan views to make the drawings easier to understand.

<Cable manufacturing method>
In this embodiment, a process for covering the outer periphery of a conductor with resin using an extrusion molding technique will be described as part of a method for manufacturing a cable in which the conductor is covered with resin.

Figure 1 is a schematic diagram illustrating the extrusion molding process for covering the outer circumference of a conductor with resin.

In FIG. 1, raw material pellets 10, which are the raw material for the coating material, are fed into an extruder 11 and kneaded, and molten resin is extruded from a die 13 via a crosshead 12. The extruded resin coats the surface of a conductor 14 moving along a travel line. The resin coating the surface of the conductor 14 is then air-cooled immediately after being extruded from the die 13, and then water-cooled in a water tank 15. In this way, the resin extruded from the die 13 solidifies during the cooling process by air and water cooling. Here, the conductor 14 is composed of copper twisted wire, etc. The raw material pellets (plastic material) 10 are composed of a thermoplastic polyurethane resin, etc.

The resin formed by extrusion molding is then annealed, but it is known that the resin shrinks after annealing. Since resin shrinkage has a negative effect on the quality of the cable, it is desirable to reduce the resin shrinkage rate.

In this regard, there is shrinkage estimation technology that estimates the shrinkage rate of resin, but there is room for improvement in this technology. The following explains the room for improvement in this technology.

ROOM FOR IMPROVEMENT
For example, it is known that the shrinkage of the resin after molding can be reduced by appropriately controlling the extrusion conditions in the extrusion molding process (such as the temperature of the resin, the linear velocity of the conductor wire, and the rotation speed of the screw of the extruder.) For this reason, in the conventional shrinkage estimation technology, the shrinkage is estimated based on the input of the extrusion conditions.

However, the shrinkage rate of resin is affected not only by the extrusion conditions but also by the material properties of the resin (viscosity and crystallinity), so a shrinkage rate estimation technique based only on the extrusion conditions requires the extrusion conditions to be optimized each time the material properties change.

In this regard, for example, in Patent Document 1 listed in the Background Art, the shrinkage rate is estimated taking into account the crystallinity of the resin. However, the crystallinity is a parameter that must be determined by measurement, and it is difficult to apply the technology described in Patent Document 1 in real time, for example, in the cable manufacturing process.

Thus, the shrinkage rate of resin depends on both the extrusion conditions and the material properties, but current shrinkage rate estimation technology does not estimate the shrinkage rate by taking both the extrusion conditions and the material properties into account. This is because, when estimating the shrinkage rate itself, not only is it difficult to take both the extrusion conditions and the material properties into account, but it is also difficult to develop a shrinkage rate estimation technology that can be introduced in real time into the cable manufacturing process. Therefore, there is a demand for a shrinkage rate estimation technology that can take into account both the extrusion conditions and the material properties and that can be introduced into the cable manufacturing process.

In other words, there is currently room for improvement in terms of providing shrinkage estimation technology that can be introduced into the cable manufacturing process while taking into account both extrusion conditions and material properties.

Therefore, in this embodiment, we have implemented measures to address the room for improvement mentioned above. Below, we will explain the technical concept of this embodiment that incorporates these measures.

<Basic Concept of the Embodiment>
The basic idea of the present embodiment is to estimate the shrinkage rate of a resin not by directly estimating the shrinkage rate itself, but by focusing on a physical quantity that is correlated with the shrinkage rate and estimating this physical quantity, the shrinkage rate that is correlated with the physical quantity can be indirectly estimated.

This basic concept has the following advantages:

For example, to estimate the shrinkage rate itself with high accuracy, it is necessary to take into account both the extrusion conditions and the material properties of the resin. However, with shrinkage rate estimation technology that formulates the shrinkage rate itself, not only is it difficult to formulate the shrinkage rate itself by taking into account both the extrusion conditions and the material properties of the resin, but it also includes a parameter called "crystallinity" that needs to be measured. As a result, it is difficult to introduce technology that formulates the shrinkage rate itself in real time into the manufacturing process of extrusion molded products.

In contrast, according to the basic concept, there is no need to formulate the shrinkage rate itself, and if a physical quantity that is correlated with the shrinkage rate can be formulated, the shrinkage rate can be indirectly estimated from the formulated physical quantity. In this case, if it is easy to consider both the extrusion conditions and the material properties of the resin in the formulation of the physical quantity, and if the formulation can be done without including a parameter that requires measurement, such as "crystallinity", the shrinkage rate can be estimated with high accuracy and can be introduced in real time in the manufacturing process of extrusion molded products. In other words, if a physical quantity that does not include a parameter that requires measurement, such as "crystallinity", is found as a physical quantity that is correlated with the shrinkage rate, but can be formulated taking into account the extrusion conditions and material properties, the shrinkage rate can be estimated with high accuracy and can be introduced in real time in the manufacturing process of extrusion molded products.

The inventors conducted extensive research to find such a physical quantity, and as a result, they focused on a physical quantity called "drawdown stress." In the following, we will explain "drawdown stress."

<"Drawdown stress">
FIG. 2 is a schematic diagram showing how a conductor wire is covered with a resin extruded from a die.

In FIG. 2, the molten resin 20 extruded from the outlet of the die 13 is coated onto the surface of the conductor 14, which is moving at a constant linear speed. The molten resin 20 coated onto the surface of the conductor 14 is then cooled in a water tank 15 and crystallized. At this time, as shown in FIG. 2, the molten resin 20 extruded from the outlet of the die 13 is pulled by the conductor 14, which is moving along the travel line. As a result, the stress applied diagonally to the molten resin 20 from the time it is extruded from the outlet of the die 13 until it is coated onto the conductor 14 is the "drawdown stress σ."

The inventors have focused on the fact that this "drawdown stress" is a physical quantity that can be formulated by taking into account both the extrusion conditions and the material properties, and have attempted to formulate it as shown below, which will be explained below.

<Formulation of "Drawdown Stress">
According to the study by the present inventors, the "drawdown stress" is expressed by the following formula (1).

Where:
σ: Drawdown stress η ₀ : Viscosity constant α: Temperature coefficient of viscosity T: Resin temperature v _f : Linear speed L: Distance from die outlet to water tank D: Drawdown ratio n: Viscosity index

The "withdrawal ratio D" included in (Formula 1) is expressed as (Formula 2) below.

Where:
_dw : diameter of die opening _dd : outer diameter of product (cable diameter)

Furthermore, the "viscosity constant η ₀ ," the "temperature coefficient α," and the "viscosity index n" included in (Equation 1) are included in (Equation 3) shown below.

Where:
η: Viscosity η ₀ : Viscosity constant α: Temperature coefficient of viscosity T: Resin temperature dγ/dt: Strain rate n: Viscosity index

<Explanation of strain rate>
Here, the "strain rate" included in (Equation 3) will be described.

Figure 3 is a schematic diagram explaining "strain rate."

In Fig. 3, the cross-sectional area of the outlet of the die 13 is indicated as "Sd". Molten resin 20 is extruded from the outlet of the die 13. At this time, the average flow velocity of the molten resin 20 extruded from the outlet of the die 13 is " _vd ". The molten resin 20 extruded from the outlet of the die 13 at the average flow velocity " _vd " is stretched by the linear velocity " _vf ". Here, " _Sf " shown in Fig. 13 is the cross-sectional area of a molded product made of a conductor coated with molten resin 20. Also, "L" shown in Fig. 3 is the distance from the outlet of the die 13 to the water tank 15.

In such a configuration, the "strain rate" is expressed as follows (Equation 4).

Where:
dγ/dt: strain rate v _d : average flow velocity of molten resin at the die outlet v _f : linear velocity L: distance from the die outlet to the water tank

That is, the "strain rate" is defined as a physical quantity obtained by dividing the difference between the average flow velocity " _vd " and the linear velocity " _vf " by the distance "L" from the outlet of the die 13 to the water tank 15. The "strain rate" defined in this way is zero, for example, if the average flow velocity " _vd " and the linear velocity " _vf " are equal. In other words, when the average flow velocity " _vd " and the linear velocity " _vf " are equal, it can be considered that no distortion is qualitatively applied to the molten resin 20, so it can be understood that the "strain rate", which is a physical quantity related to the distortion of the molten resin 20, is zero. In addition, it can be considered that the greater the difference between the average flow velocity " _vd " and the linear velocity " _vf ", the greater the distortion applied to the molten resin, so it is appropriate that the "strain rate" is expressed by (Equation 4).

<Qualitative understanding of the formulated "drawdown stress">
For example, (Formula 1) which formulates "drawdown stress σ" includes "viscosity constant η0", "temperature coefficient α" and "viscosity index n" which are included in (Formula 3) which expresses "viscosity η", and the relationship of "drawdown stress σ" ∝ "viscosity η" is derived from (Formula 1) and (Formula 3). In this way, (Formula 1) which formulates "drawdown stress" takes into account the material property of the resin viscosity, and since it is considered that qualitatively as the viscosity increases, the "drawdown stress" also increases, it can be said that the formulation by (Formula 1) is consistent with qualitative understanding.

Next, (Formula 1) includes the "line speed _vf ", "draw-down distance L" and "draw-down ratio D" of the conductor 14, which define the extrusion conditions. Therefore, it can be seen that (Formula 1) is a formula that takes into account not only the material property, namely the viscosity of the resin, but also the extrusion conditions.

Here, it is considered that the "drawing stress" increases as the "linear speed v _f " (e.g., 5 to 25 m/min) increases, and that the "drawing stress" decreases as the "drawing distance L" (e.g., 100 mm) increases. From this point of view, too, the formulation by (Equation 1) is consistent with the qualitative understanding.

...

<The usefulness of the formulated "drawdown stress">
The formula for the "drawdown stress" (Equation 1) has the following usefulness.

(1) (Equation 1) is a relational equation that takes into account both the material property of the resin viscosity and the extrusion conditions of the linear speed, the draw-down distance, and the draw-down ratio (corresponding to the screw rotation speed). This makes it possible to estimate the "draw-down stress" with a high degree of accuracy compared to formulations that only consider the material properties or the extrusion conditions. This means that if there is a high correlation between the "draw-down stress" and the "shrinkage rate" of the resin, then it is possible to estimate the "shrinkage rate" with a high degree of accuracy by taking into account both the material properties and the extrusion conditions. For this reason, the formulation using (Equation 1) is of great significance.

(2) Next, the formula (Equation 1) for formulating the "drawing stress" does not include the degree of crystallinity. This is because, as shown in FIG. 2, the resin extruded from the die 13 (for example, the temperature of the resin is 180°C to 200°C) is molten resin 20, which is cooled and crystallized in the water tank 15. Therefore, before reaching the water tank 15, the resin is in a molten state and there is no need to consider the degree of crystallinity. In other words, the "drawing stress" is significant in that it does not include the degree of crystallinity as a parameter. In other words, the formula (Equation 1) for formulating the "drawing stress" with a focus on the "drawing stress" does not include the parameter "degree of crystallinity" that requires measurement, and therefore it can be said to be significant in that it can be easily introduced in real time in the manufacturing process of extrusion molded products.

However, the above-mentioned usefulness is premised on the assumption that there is a high correlation between "drawdown stress" and "shrinkage rate". This is because, if there is no high correlation between "drawdown stress" and "shrinkage rate", even if "drawdown stress" can be estimated with high accuracy using (Equation 1), it does not lead to the ability to estimate "shrinkage rate" with high accuracy. Therefore, the correlation between "drawdown stress" and "shrinkage rate" becomes important. In this regard, the present inventor has newly discovered that there is a high correlation between "drawdown stress" and "shrinkage rate".

<Reasons for inferring a correlation>
First, the reason why the inventor came to presume that there is a correlation between "drawdown stress" and "shrinkage rate" will be explained. The inventor presumed that there is a correlation between "drawdown stress" and "shrinkage rate" as a result of grasping the shrinkage mechanism shown below.

Here, we explain the shrinkage mechanism that the inventors have discovered.

In extrusion molding technology, molten resin extruded from a die is stretched to produce a product of the desired dimensions. At this time, the "draw stress" applied to the extruded molten resin stretches the polymer chains of the polymer that constitutes the molten resin, and the molten resin is water-cooled in the stretched state. When the resin is then exposed to high temperatures again through annealing, the "draw stress" applied to the resin is eliminated, causing the resin to shrink. The resin shrinks due to the above mechanism. Therefore, according to this mechanism, it can be seen that the "draw stress" is one of the causes of resin shrinkage. Taking this into consideration, the inventor has come to surmise that there is a correlation between "draw stress" and "shrinkage rate".

Below, we will explain the verification results that support the correctness of the inventor's findings. In other words, we will explain the verification results that support the existence of a high correlation between "pull-down stress" and "shrinkage rate."

<Results of correlation verification>
In order to verify the correlation between "draw-down stress" and "shrinkage rate", an extrusion experiment is carried out using, for example, an extrusion molding system having the configuration shown in FIG. 1. Specifically, in the extrusion experiment, a thermoplastic polyurethane resin is used, and the extrusion conditions are the temperature of the resin, the linear speed of the conductor wire, and the rotation speed of the screw. A plurality of samples obtained by carrying out the extrusion experiment under each extrusion condition are each cut to 500 mm, and then each of the plurality of samples is subjected to an annealing treatment at 130° C. for 3 hours. The amount of shrinkage of each of the plurality of samples is evaluated by measuring the amount of shrinkage of the resin after the annealing treatment.

On the other hand, the "viscosity constant η0", "temperature coefficient α", and "viscosity index n" are determined from the viscosities measured for each of the samples using (Formula 3), and then these determined constants are substituted into (Formula 1). Specifically, the temperature is changed from 185°C to 210°C, and the viscosity is measured with a capillary rheometer when the strain rate is changed from 6.08 (1/s) to 6080 (1/s), and based on these measurement results, the "viscosity constant η0", "temperature coefficient α", and "viscosity index n" are determined from (Formula 3). The constants determined in this way are substituted into (Formula 1), and each extrusion condition (temperature, linear speed, screw rotation speed) is substituted into (Formula 1) to estimate the "drawdown stress". At this time, the "drawdown ratio D" included in (Formula 1) is related to the screw rotation speed, but in reality, it is determined based on (Formula 2) based on the diameter of the die opening and the outer diameter of the sample obtained in the experiment.

The number of samples corresponds to the number of three lots with different material properties (viscosity properties) applied to the 16 types of experimental conditions (Experiment No. 1 to Experiment No. 16) shown in Figure 4. In other words, the number of samples consists of 16 x 3 = 48 types of samples.

Figure 4 is a table showing 16 types of experimental conditions (extrusion conditions: temperature, linear speed, rotation speed, outer diameter), the shrinkage rate measured under each of the 16 types of experimental conditions, and the "pull-down stress" estimated based on (Equation 1). The 16 types of experimental conditions shown in Figure 4 are, for example, 16 types of conditions optimized by the "Box-Behnken method." This "Box-Behnken method" is a method that can find experimental conditions that are sufficient to obtain highly accurate predictions and can minimize the number of experiments, and the 16 types of experimental conditions shown in Figure 4 are the minimum necessary conditions found by the "Box-Behnken method."

Next, we will explain the experimental results based on the 16 x 3 = 48 types of samples mentioned above.

Figure 5 is a graph showing the relationship between "pulling stress" and "shrinkage rate." In Figure 5, the horizontal axis shows the "pulling stress" estimated based on (Equation 1), while the vertical axis shows the "shrinkage rate" measured in an experiment. In Figure 5, "Sample A," "Sample B," and "Sample C" correspond to three different lots with different material properties (viscosity properties), and experiments were conducted under 16 different experimental conditions for each of "Sample A," "Sample B," and "Sample C." As a result, there are 3 x 16 = 48 measurement points in Figure 5.

As a result of examining the graph shown in Figure 5, the correlation coefficient between "pulling stress" and "shrinkage rate" was "0.8057". Considering that the closer the correlation coefficient is to 1, the higher the correlation, it can be seen that there is a high correlation between "pulling stress" and "shrinkage rate".

The above experimental results support the existence of a high correlation between "drawdown stress" and "shrinkage rate", confirming the correctness of the inventor's assumption that a high correlation exists between "drawdown stress" and "shrinkage rate". Therefore, it can be seen that the technical idea of estimating the "shrinkage rate" of a resin based on the "drawdown stress" formulated in (Equation 1) is useful in that it takes into account both the material properties and extrusion conditions, and can be easily introduced in real time into the manufacturing process of extrusion molded products.

<Configuration of the shrinkage ratio estimation device>
A shrinkage rate estimation device that embodies the above-mentioned technical idea will be described below.

<<Hardware configuration>>
First, the hardware configuration of the shrinkage ratio estimation device according to this embodiment will be described.

Figure 6 is a diagram showing an example of the hardware configuration of the contraction ratio estimation device 100 in this embodiment. Note that the configuration shown in Figure 6 merely shows an example of the hardware configuration of the contraction ratio estimation device 100, and the hardware configuration of the contraction ratio estimation device 100 is not limited to the configuration shown in Figure 6, and may be other configurations.

In FIG. 6, the shrinkage rate estimation device 100 includes a CPU (Central Processing Unit) 101 that executes a program. This CPU 101 is electrically connected to, for example, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, and a hard disk drive 112 via a bus 113, and is configured to control these hardware devices.

The CPU 101 is also connected to input devices and output devices via the bus 113. Examples of input devices include the keyboard 105, the mouse 106, the communication board 107, and the scanner 111. Examples of output devices include the display 104, the communication board 107, and the printer 110. The CPU 101 may also be connected to, for example, a removable disk device 108 and a CD/DVD-ROM device 109.

The contraction ratio estimation device 100 may be connected to a network, for example. For example, when the contraction ratio estimation device 100 is connected to other external devices via a network, the communication board 107 constituting a part of the contraction ratio estimation device 100 is connected to a LAN (local area network), a WAN (wide area network), or the Internet.

RAM 103 is an example of a volatile memory, and the recording media ROM 102, removable disk device 108, CD/DVD-ROM device 109, and hard disk device 112 are examples of non-volatile memory. These volatile and non-volatile memories constitute the storage device of the shrinkage rate estimation device 100.

The hard disk device 112 stores, for example, an operating system (OS) 201, a group of programs 202, and a group of files 203. The programs included in the group of programs 202 are executed by the CPU 101 using the operating system 201. The RAM 103 also temporarily stores at least some of the programs of the operating system 201 and application programs executed by the CPU 101, as well as various data required for processing by the CPU 101.

The ROM 102 stores a BIOS (Basic Input Output System) program, and the hard disk drive 112 stores a boot program. When the shrinkage rate estimation device 100 is started, the BIOS program stored in the ROM 102 and the boot program stored in the hard disk drive 112 are executed, and the operating system 201 is started by the BIOS program and the boot program.

The program group 202 stores programs that realize the functions of the shrinkage rate estimation device 100, and these programs are read and executed by the CPU 101. In addition, the file group 203 stores information, data, signal values, variable values, and parameters that indicate the results of processing by the CPU 101 as each item of a file.

The files are recorded on a recording medium such as the hard disk drive 112 or memory. The information, data, signal values, variable values, and parameters recorded on the recording medium such as the hard disk drive 112 or memory are read by the CPU 101 into the main memory or cache memory, and are used for the operations of the CPU 101, such as extraction, search, reference, comparison, calculation, processing, editing, output, printing, and display. For example, during the above-mentioned operations of the CPU 101, the information, data, signal values, variable values, and parameters are primarily stored in the main memory, registers, cache memory, buffer memory, etc.

The functions of the shrinkage rate estimation device 100 may be realized by firmware stored in ROM 102, or may be realized by software alone, by hardware alone such as elements, devices, boards, and wiring, a combination of software and hardware, or even a combination with firmware. The firmware and software are recorded as programs on a recording medium such as the hard disk drive 112, a removable disk, a CD-ROM, or a DVD-ROM. The programs are read and executed by the CPU 101. In other words, the programs cause the computer to function as the shrinkage rate estimation device 100.

In this way, the contraction rate estimation device 100 is a computer equipped with a CPU 101 as a processing device, a hard disk drive 112 and memory as storage devices, a keyboard 105, a mouse 106, and a communication board 107 as input devices, and a display 104, a printer 110, and a communication board 107 as output devices. The functions of the contraction rate estimation device 100 are realized by utilizing the processing device, the storage device, the input device, and the output device.

<<Function block configuration>>
Next, the functional block configuration of the shrinkage ratio estimation device 100 will be described.

Figure 7 is a functional block diagram showing the functional configuration of the shrinkage rate estimation device.

In FIG. 7, the contraction rate estimation device 100 in this embodiment has an input unit 301, a constant determination unit 302, a contraction rate estimation unit 303, a judgment unit 305, a matching condition search unit 306, an output unit 307, and a data storage unit 308.

The input unit 301 is configured to input, for example, a known data group or the data group shown in FIG. 5. Here, the "known data group" is a data group that associates a combination of the resin temperature and strain rate with the viscosity, and is defined as a data group in which the resin temperature, strain rate, and viscosity are known. The data group shown in FIG. 5 is defined as a data group that associates "drawdown stress" with "shrinkage rate." These "known data groups" and "data group shown in FIG. 5" are input to the input unit 301 and then stored in the data storage unit 308.

Next, the constant determination unit 302 is configured to determine the "viscosity constant η0", "temperature coefficient α", and "viscosity index n" included in (Equation 3) based on the group of known data stored in the data storage unit 308. Specifically, as shown in FIG. 8, for example, the constant determination unit 302 is configured to determine the viscosity constant, the temperature coefficient of viscosity, and the viscosity index by using the group of known data as training data and training a neural network with the resin temperature and strain rate as input and the viscosity as output. The viscosity constant, the viscosity temperature coefficient, and the viscosity index determined in this manner are stored in the data storage unit 308.

The shrinkage rate estimation unit 303 is configured to estimate the shrinkage rate of the resin based on the "drawing stress" applied when the resin is extruded. In other words, the shrinkage rate estimation unit 303 is configured to indirectly estimate the shrinkage rate based on the "drawing stress" that has a correlation with the shrinkage rate. For example, the shrinkage rate estimation unit 303 is configured to estimate the "drawing stress" based on a constant related to the viscosity of the resin and the extrusion conditions of the resin, and includes a draw stress estimation unit 304.

The drawing stress estimating unit 304 is configured to estimate the "drawing stress" based on (Formula 1) and (Formula 2). For example, the drawing stress estimating unit 304 is configured to estimate the "drawing stress _" by further substituting the extrusion conditions ("temperature T of resin", "linear speed v _f ", "distance L from the die outlet to the water tank", and "drawing ratio D" defined by (Formula 2)) into (Formula 1) into which the "viscosity constant η 0 ", "temperature coefficient α" and "viscosity index n" determined by the constant determining unit 302 are substituted. The "drawing stress" estimated in this manner is stored in the data storage unit 308.

The shrinkage rate estimation unit 303 is configured to estimate the shrinkage rate of the resin based on the "drawing stress" estimated by the drawing stress estimation unit 304. For example, since there is a correlation between the "drawing stress" and the shrinkage rate represented by the data group shown in FIG. 5, the shrinkage rate estimation unit 303 is configured to estimate the shrinkage rate from the "drawing stress" using this correlation. As a specific example, as shown in FIG. 9, the shrinkage rate estimation unit 303 is configured to generate a response function by learning a neural network with the input being the "drawing stress" and the output being the shrinkage rate, using the data group shown in FIG. 5 stored in the data storage unit 308 as training data, and to estimate the shrinkage rate from the "drawing stress" whose correspondence with the shrinkage rate is unknown, using this response function.

Here, the response function is defined as a function that outputs the shrinkage rate corresponding to the input "pulling stress" when the "pulling stress" is input.

Next, the determination unit 305 is configured to determine whether the shrinkage rate estimated by the shrinkage rate estimation unit 303 is equal to or less than a preset "threshold value."

When the determination unit 305 determines that the shrinkage rate estimated by the shrinkage rate estimation unit 303 is not equal to or less than a preset "threshold value," the matching condition search unit 306 is configured to change the extrusion conditions included in (Formula 1) to re-estimate the "drawdown stress," and to search for extrusion conditions (matching conditions) that result in the shrinkage rate corresponding to the re-estimated "drawdown stress" being equal to or less than the "threshold value."

The output unit 307 is configured to output, for example, the shrinkage rate estimated by the shrinkage rate estimation unit 303 and the extrusion conditions searched for by the matching condition search unit 306.

The shrinkage rate estimation device 100 in this embodiment is configured as described above.

<Operation of the shrinkage ratio estimation device (shrinkage ratio estimation method)>
Next, the operation of the shrinkage ratio estimation device 100 in this embodiment will be described.

＜＜Basic operation＞＞
FIG. 10 is a flowchart illustrating the basic operation of the shrinkage ratio estimation device.

In FIG. 10, first, when a known data group is input to the input unit 301 (S101), the input known data group is stored in the data storage unit 308. Next, the constant determination unit 302 determines the constants ("viscosity constant η ₀ ", "temperature coefficient α" and "viscosity index n") related to the material properties (viscosity) included in (Equation 3) based on the known data group stored in the data storage unit 308 (S102). Then, the drawing stress estimation unit 304 estimates the "drawing stress" from (Equation 1) by substituting the constants determined by the constant determination unit 302 (S103) and further inputting the extrusion conditions (S104). Next, the shrinkage rate estimation unit 303 estimates the shrinkage rate of the resin from the "drawing stress" estimated by the drawing stress estimation unit 304 based on the response function (S105). Then, the shrinkage rate estimated by the shrinkage rate estimation unit 303 is output from the output unit 307. In this manner, the basic operation is performed in the shrinkage rate estimation device 100. As a result, the shrinkage rate estimation device 100 can estimate the shrinkage rate of the resin.

<<Applied operations>>
Furthermore, in the shrinkage rate estimation device 100, in addition to the basic operation described above, the following applied operation can also be performed. FIG. 11 is a flowchart explaining the applied operation of the shrinkage rate estimation device. In FIG. 11, when the shrinkage rate of the resin is estimated by performing the basic operation described above (S201), the judgment unit 305 judges whether or not the shrinkage rate estimated by the shrinkage rate estimation unit 303 is equal to or less than a preset "threshold value" (S202). If the shrinkage rate estimated by the shrinkage rate estimation unit 303 is equal to or less than the "threshold value", the output unit 307 outputs a message indicating that the shrinkage rate is equal to or less than the "threshold value" (S205). On the other hand, if the shrinkage rate estimated by the shrinkage rate estimation unit 303 is not equal to or less than the "threshold value", the matching condition search unit 306 changes the extrusion conditions included in (Equation 1) to re-estimate the "drawing stress", and searches for extrusion conditions (matching conditions) that make the shrinkage rate corresponding to the re-estimated "drawing stress" equal to or less than the "threshold value" (S203). Then, the extrusion conditions found by the matching condition search unit 306 are output from the output unit 307 (S204).

In this manner, the applied operation is performed in the shrinkage ratio estimation device 100. As a result, the shrinkage ratio estimation device 100 can present extrusion conditions for the shrinkage ratio to satisfy the specified conditions even if the shrinkage ratio estimated by the shrinkage ratio estimation unit 303 does not satisfy the specified conditions.

By operating the shrinkage rate estimation device 100 in the manner described above, the shrinkage rate estimation method of this embodiment is realized.

<Shrinkage rate estimation program>
The shrinkage ratio estimation method performed by the above-described shrinkage ratio estimation device 100 can be realized by a shrinkage ratio estimation program that causes a computer to execute a shrinkage ratio estimation process.

For example, in the contraction ratio estimation device 100 consisting of a computer shown in FIG. 6, the contraction ratio estimation program in this embodiment can be introduced as one of the program group 202 stored in the hard disk device 112. Then, by having the computer that is the contraction ratio estimation device 100 execute this contraction ratio estimation program, the contraction ratio estimation method in this embodiment can be realized.

The shrinkage rate estimation program that causes a computer to execute each process for creating data related to the shrinkage rate estimation process can be recorded on a computer-readable recording medium and distributed. Recording media include, for example, magnetic storage media such as hard disks and flexible disks, optical storage media such as CD-ROMs and DVD-ROMs, and hardware devices such as non-volatile memories such as ROMs and EEPROMs.

<Effects of the embodiment>
According to the technical idea of this embodiment, the shrinkage rate of the resin is not directly estimated, but the shrinkage rate is indirectly estimated based on the "drawdown stress" which is correlated with the shrinkage rate. This not only makes it possible to estimate the shrinkage rate with high accuracy by easily considering both the material properties and the extrusion conditions, but also makes it unnecessary to consider the parameter "crystallinity" which requires measurement, and therefore has great technical significance in that it provides a shrinkage rate estimation technique which can be introduced in real time in the manufacturing process of extrusion molded products.

For example, until now, there was no shrinkage estimation technology that could be introduced in real time in the manufacturing process of extrusion molded products, so the shrinkage was reduced by adjusting the extrusion conditions based on the experience of the workers. In this regard, according to the technical idea of this embodiment, it is possible to introduce an objectively accurate shrinkage estimation technology into the manufacturing process (manufacturing line) of extrusion molded products without relying on the experience of the workers. As a result, according to this embodiment, it is possible to reduce the amount of waste of resin materials and extrusion molded products (e.g., cables) and improve production efficiency. In other words, the technical idea of this embodiment makes it possible to introduce the shrinkage estimation technology into the manufacturing line of extrusion molded products, and as a result, it is possible to obtain a remarkable effect of improving the manufacturing yield of extrusion molded products. Therefore, the manufacturing process of extrusion molded products using the technical idea of this embodiment will be described below.

<Method of manufacturing extrusion molded product>
Fig. 12 is a flow chart for explaining a method for manufacturing an extrusion molded product using the shrinkage estimation technique of this embodiment. In Fig. 12, first, the extrusion conditions are initialized (S301). Next, the shrinkage estimation technique of this embodiment is used. Specifically, (Formula 1) is prepared in which constants related to material properties are substituted, and the extrusion conditions initialized for this (Formula 1) are substituted to estimate the "drawdown stress", and the shrinkage is estimated based on this "drawdown stress" (S302). At this time, the basic operation and applied operation described above are performed.

As a result, if the estimated shrinkage rate is equal to or less than the "threshold", the initially set extrusion conditions are maintained. On the other hand, if the estimated shrinkage rate is not equal to or less than the "threshold", the conditions are changed to the suitable conditions (extrusion conditions) presented in the applied operation (S303).

Then, the resin is extruded under the maintained or changed extrusion conditions (S304). The resin is then annealed (S305), and after a predetermined period of time (1 to 2 days), the shrinkage rate is measured (S306). If the shrinkage rate is equal to or less than the predetermined value (OK), a non-defective cable is manufactured (S307). On the other hand, if the shrinkage rate is not equal to or less than the predetermined value (NG), a response function that outputs the shrinkage rate from the input "pull-down stress" is reconstructed based on this NG data (S308). That is, the response function is reconstructed by adding the above-mentioned NG data and re-training the neural network that takes the "pull-down stress" as the input and the shrinkage rate as the output. In this way, the cable manufacturing method of this embodiment is realized.

According to the manufacturing method of the extrusion molded product in this embodiment, the shrinkage rate estimation technology is introduced into the manufacturing line to estimate the shrinkage rate of the resin in advance, thereby improving the manufacturing yield of the extrusion molded product. Furthermore, if the estimated shrinkage rate is "OK" but the final measured shrinkage rate is "NG," the response function can be reconstructed based on this NG data to improve the estimation accuracy of the shrinkage rate.

The invention made by the inventor has been specifically described above based on the embodiment thereof, but it goes without saying that the invention is not limited to the above embodiment and can be modified in various ways without departing from the gist of the invention.

The technical ideas in the above embodiments are applicable to a wide variety of resins, including plastics and rubbers, and are not limited to, for example, thermoplastic polyurethane resin. In addition, the technical ideas in the above embodiments are applicable to a wide variety of extrusion forms, regardless of tube extrusion, wire extrusion, or die shape.

REFERENCE SIGNS LIST 10 Raw material pellets 11 Extruder 12 Crosshead 13 Die 14 Conductive wire 15 Water tank 20 Molten resin 100 Shrinkage ratio estimation device 101 CPU
102 ROM
103 RAM
104 Display 105 Keyboard 106 Mouse 107 Communication board 108 Removable disk device 109 CD/DVD-ROM device 110 Printer 111 Scanner 112 Hard disk device 201 Operating system 202 Program group 203 File group 301 Input section 302 Constant determination section 303 Shrinkage rate estimation section 304 Pull-down stress estimation section 305 Judgment section 306 Compatible condition search section 307 Output section 308 Data storage section

Claims (5)

A drawing stress estimation device that estimates drawing stress applied when extruding a resin, comprising:
The drawing stress estimation device includes a drawing stress estimation unit that estimates the drawing stress based on Equation 1 and Equation 5, which include a constant related to the viscosity of the resin and an extrusion condition of the resin.

Where:
σ: Drawdown stress η ₀ : Viscosity constant α: Temperature coefficient of viscosity T: Resin temperature v _f : Linear speed L: Distance from die outlet to water tank D: Drawdown ratio n: Viscosity index

Where:
S _d : Cross-sectional area of the die outlet S _f : Cross-sectional area of the molded product The pull-down stress estimation device according to claim 1,
The viscosity constant, the temperature coefficient of viscosity, and the viscosity index included in the formula 1 are calculated based on the viscosity measurement results and the formula 3 shown below.

Where:
η: Viscosity η ₀ : Viscosity constant α: Temperature coefficient of viscosity T: Resin temperature dγ/dt: Strain rate n: Viscosity index The pull-down stress estimation device according to claim 2,
The pull-down stress estimation device comprises:
a known data group input unit for inputting a known data group that associates the combination of the temperature and the strain rate with the viscosity;
a constant determination unit that determines the viscosity constant, the temperature coefficient of viscosity, and the viscosity index by learning a neural network that uses the known data group as teacher data and has the temperature and the strain rate as inputs and the viscosity as output;
having
The drawing stress estimation unit estimates the drawing stress from the extrusion conditions based on the formula 1 in which the viscosity constant, the temperature coefficient of the viscosity, and the viscosity index determined by the constant determination unit are substituted. A method for estimating a drawing stress applied when a resin is extruded, comprising the steps of:
The drawing stress estimation method includes a drawing stress estimation step of estimating the drawing stress based on Equation 1 and Equation 5, which include a constant related to the viscosity of the resin and an extrusion condition of the resin.

Where:
σ: Drawdown stress η ₀ : Viscosity constant α: Temperature coefficient of viscosity T: Resin temperature v _f : Linear speed L: Distance from die outlet to water tank D: Drawdown ratio n: Viscosity index

Where:
S _d : Cross-sectional area of the die outlet S _f : Cross-sectional area of the molded product A method for producing an extrusion molded product by extruding a resin using an extruder, comprising the steps of:
a drawing stress estimating step of estimating a drawing stress applied when the resin is extruded;
and changing an extrusion condition for changing an extrusion condition of the resin based on the pull-down stress,
The method for manufacturing an extrusion molded product, wherein the drawing stress estimating step estimates the drawing stress based on Equation 1 and Equation 5, which include a constant related to the viscosity of the resin and the extrusion conditions.

Where:
σ: Drawdown stress η ₀ : Viscosity constant α: Temperature coefficient of viscosity T: Resin temperature v _f : Linear speed L: Distance from die outlet to water tank D: Drawdown ratio n: Viscosity index

Where:
S _d : Cross-sectional area of the die outlet S _f : Cross-sectional area of the molded product

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