JP7452410B2 - Shrinkage rate estimation device, shrinkage rate estimation method, program, recording medium, and extrusion molded product manufacturing method - Google Patents

Description

The present invention relates to a shrinkage rate estimation technique for estimating the shrinkage rate of an extruded product.

Japanese Unexamined Patent Publication No. 2020-44695 (Patent Document 1) discloses a technology that detects the torque generated in a rotating screw of a rubber extruder and estimates the viscosity of a rubber material based on the detected torque data. Are listed.

JP2020-44695A

For example, a cable, which is a typical extrusion molded product, has a structure in which a conducting wire is coated with a resin to ensure insulation, and the resin covering the conducting wire is formed by, for example, extrusion molding technology. Thereafter, the resin formed by extrusion molding is subjected to an annealing process, but it is known that the cable shrinks after the annealing process. For example, if the resin contracts in the longitudinal direction of the cable, there is a risk that the outer diameter of the cable will change to become thicker, or that the conductor (core wire) may be exposed from the end of the cable. For this reason, it is desired to reduce the shrinkage rate of the cable.

Regarding this point, at present, the shrinkage rate (dimensions after annealing treatment) of an extrusion molded product containing resin as a constituent material extruded from an extruder cannot be ascertained at the time of extrusion. For this reason, defects occur after the annealing process, resulting in a decrease in manufacturing yield and an increase in lead time. Therefore, from the viewpoint of improving the productivity of extrusion molded products, a technology that can estimate the shrinkage rate during extrusion is desired.

A shrinkage rate estimating device in one embodiment includes a shrinkage rate estimator that estimates the shrinkage rate of an extruded product based on the torque current of a motor included in the extruder and the extrusion conditions of the extruder.

A shrinkage rate estimation method in one embodiment includes a shrinkage rate estimation step of estimating the shrinkage rate of an extruded product based on the torque current of a motor provided in the extruder and the extrusion conditions of the extruder.

This shrinkage rate estimation method can be realized by using a program to cause a computer to execute a process of estimating the shrinkage rate of an extrusion molded product. For example, this program includes a shrinkage rate estimation process that estimates the shrinkage rate of the extruded product based on the torque current of a motor provided in the extruder and the extrusion conditions of the extruder. The program in one embodiment can be recorded on, for example, a computer-readable recording medium.

A method for manufacturing an extrusion molded product in one embodiment includes a shrinkage rate monitoring step of monitoring the shrinkage rate of the extrusion molded product in real time based on the torque current of a motor provided in the extruder and the extrusion conditions of the extruder. Further, the method for manufacturing an extrusion molded product in one embodiment includes a shrinkage rate estimation step of estimating the shrinkage rate of the extrusion molded product in real time based on the torque current of a motor provided in the extruder and the extrusion conditions of the extruder; The method includes an extrusion condition adjustment step of adjusting extrusion conditions based on the adjusted shrinkage rate, and a molding step of extrusion molding the resin under the adjusted extrusion conditions.

According to one embodiment, the shrinkage rate of the extrudate can be estimated during extrusion. Moreover, thereby, the productivity of extrusion molded products can be improved.

It is a schematic diagram explaining the extrusion molding process of covering the outer periphery of a conducting wire with resin. FIG. 3 is a schematic diagram showing how a conductive wire is covered with resin extruded from a die. It is a graph showing the measurement results (experimental data) of measuring the temperature of resin. It is a graph showing both the time dependence of viscosity calculated based on experimental data and the time dependence of torque current output from an extruder. FIG. 3 is a diagram illustrating the validity of the existence of a correlation between "torque current" and the shrinkage rate of an extruded product. It is a figure which shows the procedure of formulating the correlation between "torque current" and contraction rate. It is a schematic diagram explaining "strain rate." It is a diagram in which measured data is plotted. FIG. 2 is a diagram showing an example of a hardware configuration of a shrinkage rate estimating device. FIG. 2 is a functional block diagram showing the functional configuration of a shrinkage rate estimating device. It is a figure explaining the machine learning which determines a temperature coefficient and a viscosity index. It is a figure explaining the machine learning which determines the constant of (Formula VIII). It is a flowchart explaining the basic operation of a shrinkage rate estimating device. It is a flowchart explaining the basic operation of a shrinkage rate estimating device. It is a flowchart explaining the applied operation of the shrinkage rate estimating device. It is a flow chart explaining a part of manufacturing process of an extrusion molded product. It is a flow chart explaining a part of manufacturing process of an extrusion molded article.

In all the drawings for explaining the embodiments, the same members are designated by the same reference numerals in principle, and repeated explanation thereof will be omitted. Note that even in a plan view, hatching may be added to make the drawing easier to understand.

<Cable manufacturing method>
In this embodiment, a process of coating the outer periphery of a conducting wire with resin using extrusion molding technology will be described in a method of manufacturing a cable in which a conducting wire is coated with resin.

FIG. 1 is a schematic diagram illustrating an extrusion molding process for coating the outer periphery of a conducting wire with resin.

In FIG. 1, when raw material pellets 10, which are raw materials for a coating material, are put into an extruder 11 and kneaded, molten resin is extruded from a die 13 via a crosshead 12. The extruded resin coats the surface of the conducting wire 14 moving along the running line. Immediately after the resin coated on the surface of the conducting wire 14 is extruded from the die 13, it is air-cooled and then water-cooled in a water tank 15. In this way, the resin extruded from the die 13 is solidified during the cooling process by air cooling and water cooling. Here, the conducting wire 14 is made of twisted copper wire or the like. Further, the raw material pellets (plastic material) 10 are made of thermoplastic polyurethane resin or the like.

Thereafter, an annealing treatment is performed on an extrusion molded product containing resin as a constituent material formed by extrusion molding technology, but it is known that the extrusion molded product shrinks after the annealing treatment. Since shrinkage of an extruded product has a negative effect on the quality of the extruded product, it is desirable to reduce the shrinkage rate of the extruded product.

In this regard, for example, if it is possible to understand the shrinkage rate (dimensions after annealing treatment) of an extruded product in real time during extrusion molding, it is thought that it will be possible to improve manufacturing yield and reduce lead time. . That is, from the viewpoint of improving the productivity of extrusion molded products, a technology that can estimate the shrinkage rate in real time is desired.

<Basic idea of embodiment>
The basic idea of this embodiment is that in order to estimate the shrinkage rate of an extruded product in real time, instead of directly estimating the shrinkage rate itself, we focus on a physical quantity that has a correlation with the shrinkage rate and calculate this physical quantity. The idea is to indirectly estimate the shrinkage rate by estimating it. In particular, if a physical quantity that can be grasped in real time as a physical quantity that has a correlation with the shrinkage rate can be found, it is considered that the shrinkage rate can be estimated in real time based on this physical quantity.

This basic idea has the following advantages, for example.

For example, in order to estimate the shrinkage rate itself with high accuracy, it is necessary to consider both the extrusion conditions and the material properties of the resin. However, with the shrinkage rate estimation technology that formulates the shrinkage rate itself, it is not only difficult to formulate the shrinkage rate itself considering both extrusion conditions and resin material properties, but also the measurement of "crystallinity" is difficult. Also includes necessary parameters. As a result, it is difficult to implement the technology that formulates the shrinkage rate itself in real time in the manufacturing process of extrusion molded products.

On the other hand, according to the basic idea, there is no need to formulate the shrinkage rate itself; if a physical quantity that has a correlation with the shrinkage rate can be formulated, it is possible to indirectly estimate the shrinkage rate from the formulated physical quantity. can. At this time, when formulating the physical quantities, it is easy to consider both the extrusion conditions and the material properties of the resin, and if the formulation can be formulated without including the parameter that requires measurement of "crystallinity", it is possible to calculate the shrinkage rate. Not only can it be estimated with high accuracy, but it can also be introduced in real time in the manufacturing process of extrusion molded products. In other words, if a physical quantity that can be grasped in real time and that can be formulated in consideration of extrusion conditions and material properties as a physical quantity that has a correlation with the shrinkage rate can be found, the shrinkage rate can be estimated with high accuracy. It also becomes possible to introduce it in real time in the manufacturing process of extrusion molded products.

Therefore, as a result of intensive studies to find such a physical quantity, the inventor of the present invention focused on a physical quantity called "torque current", and therefore, the "torque current" will be explained below.

<“Torque current”>
An extruder is used in the extrusion molding process. In the extruder, raw material pellets, which are the raw material for the coating material, are kneaded with a rotating screw. Then, by extruding the kneaded molten resin from the exit of the die, the outer periphery of the conductive wire is coated with the resin. Here, the screw is rotated by a motor provided in the extruder. At this time, the load current flowing through the motor that rotates the screw is the "torque current." The present inventor has newly discovered that this "torque current" is a physical quantity that is correlated with the shrinkage rate of the extruded product. In particular, "torque current" is the current that flows through the motor that rotates the screw that kneads the resin, and extruders are configured so that abnormal rotation of the screw can be detected by constantly monitoring this "torque current." has been done. From this, "torque current" is a physical quantity that can be grasped in real time during the extrusion molding process. Therefore, if the "torque current" has a correlation with the shrinkage rate of the extruded product, it becomes possible to estimate the shrinkage rate of the extruded product in real time from the "torque current".

Here, it is not clear that there is a correlation between the "torque current" and the shrinkage rate of the extruded product. Therefore, below, first, it will be qualitatively explained that there is a correlation between the "torque current" and the shrinkage rate of the extruded product.

<Qualitative understanding of correlation>
<<Explanation of "drawing stress">>
In order to explain that there is a correlation between the "torque current" and the shrinkage rate of the extruded product, "drawdown stress" plays an important role. For this reason, "drawing stress" will be explained.

FIG. 2 is a schematic diagram showing how a conducting wire is covered with resin extruded from a die.

In FIG. 2, molten resin 20 extruded from the exit of die 13 coats the surface of conductive wire 14 moving at a constant linear speed. Then, the molten resin 20 coated on the surface of the conducting wire 14 is cooled in a water tank 15 and crystallized. At this time, as shown in FIG. 2, the molten resin 20 extruded from the exit of the die 13 is pulled by the conducting wire 14 moving along the running line. As a result, the stress applied to the molten resin 20 in an oblique direction after it is extruded from the exit of the die 13 until it is coated on the conductive wire 14 is the "draw-down stress σ."

The present inventor presumes that this "drawdown stress" has a correlation with the shrinkage rate of the extruded product. In this regard, the reason why the inventor of the present invention has come to estimate that there is a correlation between the "drop stress" and the shrinkage rate will be explained. The inventor of the present invention presumed that there is a correlation between "drawing stress" and shrinkage rate as a result of understanding the shrinkage mechanism described below.

Therefore, the contraction mechanism understood by the present inventor will be explained.

In extrusion molding technology, a molten resin extruded from a die is stretched to produce a product (extrusion molded product) with desired dimensions. At this time, the "drawing stress" applied to the extruded molten resin causes the polymer chains of the polymer that is the constituent material of the molten resin to elongate, and the molten resin is water-cooled in a state where the polymer chains are elongated. Thereafter, when the resin is exposed to a high temperature again through annealing treatment, the "draw-down stress" applied to the resin is eliminated, causing the resin to shrink. Shrinkage occurs in the resin due to the mechanism described above. Therefore, according to this mechanism, it can be seen that "drawdown stress" is a cause of shrinkage of extruded products containing resin as a constituent material. Taking this into consideration, the present inventor has come to conjecture that there is a correlation between "drawdown stress" and shrinkage rate.

<<Relationship between "drawing stress" and viscosity>>
Next, it will be explained that "drawing stress" has a correlation with viscosity. According to the above-mentioned mechanism, the "drawdown stress" applied to the extruded molten resin causes the polymer chains of the polymer that is the constituent material of the molten resin to elongate. Therefore, it can be considered that the "drop stress" is influenced by the material properties of the resin. In particular, since it is thought that the "down stress" is greatly influenced by the fluidity of the resin, it is assumed that the "down stress" has a correlation with the viscosity, which represents the fluidity of the resin. For example, since it is qualitatively understood that as the viscosity increases, the "drawing stress" also increases, it is reasonable to assume that there is a correlation between the "drawing stress" and the viscosity.

<<Relationship between viscosity and "torque current">>
Next, it will be explained that viscosity has a correlation with "torque current". For example, the resin is kneaded by rotating a screw with a motor. At this time, if the viscosity of the resin is high, the energy required to rotate the screw to knead the resin will be high. This means that a large load is placed on the motor that rotates the screw, which increases the "torque current" required to rotate the motor. On the other hand, if the viscosity of the resin is low, the load placed on the motor for kneading the resin will be low. This means that the "torque current" becomes smaller. Therefore, it can be considered reasonable that a correlation exists between viscosity and "torque current."

Below, experimental results showing that there is a correlation between viscosity and "torque current" will be explained. First, calculate the viscosity. Specifically, since the viscosity can be expressed by (Formula I) described later, the viscosity can be calculated based on this (Formula I). For example, based on the resin used in the experiment and the extrusion conditions of the extruder, the "viscosity constant η ₀ " included in (Formula I) is 9.11×10 ¹¹ (Pa·s ⁿ ), and the "temperature coefficient α ” is 8.42×10 ² (1/° C.), and “viscosity index n” is 0.225.

Here, in the case of the viscosity of the resin extruded from the extruder to the outside and stretched, "strain rate" is used for (dγ/dt) included in (Formula I). On the other hand, in the case of the viscosity of the resin being kneaded inside the extruder, the "shear rate" is used for (dγ/dt) included in (Formula I).

If the "shear rate" is assumed to be constant inside the extruder and regarded as a constant, then the viscosity η can be calculated from the temperature T of the resin based on (Formula I).

Therefore, the temperature of the resin extruded from the extruder is measured. Specifically, a thermocouple was inserted into a hole made at the tip of the extruder to measure the temperature of the resin. FIG. 3 is a graph showing the measurement results (experimental data) of the temperature of the resin.

Next, the viscosity is calculated by substituting the experimental data shown in FIG. 3 into (Equation I). FIG. 4 is a graph showing both the time dependence of viscosity calculated based on experimental data (shown in black) and the time dependence of torque current output from the extruder (shown in gray).

As shown in FIG. 4, when paying attention to the peak positions surrounded by circles, it can be seen that there is a correlation between the calculated viscosity value and the torque current value. From the above experimental results, it is considered reasonable that there is a correlation between viscosity and "torque current."

The above can be summarized as shown in FIG. FIG. 5 is a diagram illustrating the validity of the existence of a correlation between the "torque current" and the shrinkage rate of the extruded product. In FIG. 5, from the above qualitative explanation, it is first inferred that there is a correlation (first correlation) between the "drawdown stress" and the shrinkage rate. It is assumed that there is a correlation (second correlation) between "drawing stress" and viscosity, and there is also a correlation (third correlation) between viscosity and "torque current". It is assumed that there is. Therefore, when these first correlation, second correlation, and third correlation are comprehensively considered, it is found that there is a correlation between the "torque current" and the shrinkage rate of the extruded product. Guessed. That is, considering the first correlation, the second correlation, and the third correlation, it can be inferred that the "torque current" and the shrinkage rate are correlated with each other through the viscosity and the "drawing stress". Can be done. In this way, it is qualitatively understood that there is a correlation between the "torque current" and the shrinkage rate of the extruded product.

<Formulation of correlation>
Furthermore, since the present inventor has gone one step beyond a qualitative understanding of the correlation between "torque current" and the shrinkage rate of an extruded product, and is attempting to formulate the correlation, this point will be explained.

FIG. 6 is a diagram showing a procedure for formulating the correlation between "torque current" and contraction rate.

As shown in FIG. 6, as a first step, the correlation between viscosity and "torque current" is formulated. Then, as a second step, the correlation between the "drawing stress" and the "torque current" is formulated, and then, as a third step, the correlation between the shrinkage rate and the "torque current" is formulated.

In the following, it will be explained that the correlation between the contraction rate and the "torque current" can be finally formulated according to the procedure shown in FIG.

<<First stage: Formulation of the correlation between viscosity and "torque current">>
Generally, viscosity is expressed by the following formula (I).

here,
t: Time η: Viscosity η ₀ : Viscosity constant α: Temperature coefficient T: Resin temperature dγ/dt: Strain rate n: Viscosity index

<<<Explanation of strain rate>>>
Here, the "strain rate" included in (Formula I) will be explained.

FIG. 7 is a schematic diagram illustrating "strain rate".

In FIG. 7, the cross-sectional area of the exit of the die 13 is indicated by "S _d ". Molten resin 20 is extruded from the outlet of this die 13. At this time, the average flow velocity of the molten resin 20 extruded from the outlet of the die 13 is "v _d ". The molten resin 20 extruded from the outlet of the die 13 at an average flow velocity "v _d " is stretched by the linear velocity "v _f ". Here, “S _f ” shown in FIG. 7 is the cross-sectional area of the molded product made of the conducting wire coated with the molten resin 20. Moreover, "L" shown in FIG. 7 is the distance from the exit of the die 13 to the water tank 15.

In such a configuration, the "strain rate" is expressed by (Equation II) shown below.

here,
dγ/dt: Strain rate v _d : Average flow velocity of molten resin at the exit of the die v _f : Linear velocity L: Distance from the exit of the die to the water tank

That is, the "strain velocity" is defined as a physical quantity obtained by dividing the difference between the average flow velocity "v _d " and the linear velocity "v _f " by the distance "L" from the outlet of the die 13 to the water tank 15. The “strain rate” defined in this way becomes zero if, for example, the average flow velocity “v _d ” and the linear velocity “v _f ” are equal. In other words, if the average flow velocity "v _d " and the linear velocity "v _f " are equal, it can be qualitatively considered that no distortion is applied to the molten resin 20. Therefore, " It is understandable that the strain rate is zero. Furthermore, since it can be considered that the larger the difference between the average flow velocity "v _d " and the linear velocity "v _f ", the greater the strain applied to the molten resin, the "strain rate" is expressed by (Formula II). That is reasonable.

<<<Assumption of linearity>>>
Next, in formulating the correlation between the viscosity and the "torque current" expressed by the above-mentioned (Equation I), linearity between the viscosity and the "torque current" is assumed. This assumption can be said to be valid because it matches the qualitative understanding that, for example, as the viscosity increases, the "torque current" also increases. Based on this assumption, the viscosity is expressed by (Formula III) shown below.

here,
t: Time η: Viscosity a: Constant τ: Torque current b: Constant

According to the inventor's study, when the "torque current" is changed, the average flow velocity (v _d ), linear velocity (v _f ) of the molten resin at the exit of the die, and the distance from the exit of the die to the water tank (L ), the temperature (T), temperature coefficient (α), and viscosity index (n) of the resin are almost constant, while the viscosity constant (η ₀ ) of the resin mainly changes, as a new finding. .

Based on this knowledge, the linearity between viscosity and "torque current" expressed by (Formula III) is approximately equivalent to expressing the viscosity constant (η ₀ ) by (Formula IV) shown below.

here,
t: Time η ₀ : Viscosity constant a ₀ : Constant τ : Torque current b ₀ : Constant

As described above, the correlation between viscosity and "torque current" can be formulated.

<<Second stage: Formulation of the correlation between "pulling stress" and "torque current">>
Next, the formulation of the correlation between "drop stress" and "torque current" will be explained.

The correlation between "drawing stress" and viscosity is expressed by the following (Equation V).

here,
t: time σ: drawing stress η: viscosity dγ/dt: strain rate η ₀ : viscosity constant α: temperature coefficient T: resin temperature n: viscosity index

For example, (Equation V) that formulates "drawing stress σ" includes "viscosity η" and expresses the relationship of "drawing stress σ" ∝ "viscosity η". In this way, the formulation of "drawdown stress" (Equation V) takes into account the material properties of resin viscosity and the extrusion conditions including temperature and strain rate. Qualitatively, as the viscosity increases, "drawdown stress" '' is also considered to be large, so it can be said that the formulation by (Formula V) is consistent with qualitative understanding.

The formula (Formula V) that formulates "dropping stress" has the following usefulness.

(1) (Equation V) is a relational expression that takes into consideration both the material property of the resin viscosity and the extrusion conditions of the resin temperature and strain rate. This makes it possible to estimate the "drop stress" with high accuracy compared to formulations that only consider material properties or formulations that only consider extrusion conditions. This means that if there is a high correlation between the "drawdown stress" and the "shrinkage rate" of an extruded product, it is possible to estimate the "shrinkage rate" with high accuracy by considering both material properties and extrusion conditions. means. From this, the formulation by (Equation V) has great significance.

(2) Next, "crystallinity" is not included in the formula (Formula V) in which "pulling stress" is formulated. 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 a molten resin 20, and this molten resin 20 is cooled in a water tank 15 and crystallized. become Therefore, before reaching the water tank 15, the resin is in a molten state and there is no need to consider "crystallinity". That is, "drawing stress" has great significance in that "crystallinity" is not included as a parameter. In other words, focusing on the "pull-down stress", the formula (Equation V) for the "pull-down stress" does not include the parameter "crystallinity" that needs to be measured, so it is difficult to manufacture extruded products. It can be said that it has great significance in that it can be easily introduced in real time in the process.

Next, by substituting the relationship in (Formula IV) to the viscosity constant (η ₀ ) included in (Formula V) representing "drawing stress", (Formula VI) shown below is obtained.

here,
t: time σ: drawing stress _a0 : constant τ: torque current _b0 : constant α: temperature coefficient T: temperature of resin dγ/dt: strain rate n: viscosity index

In the manner described above, the correlation between "pulling stress" and "torque current" can be formulated.

<<Third stage: Formulating the correlation between contraction rate and "torque current">>
Next, the formulation of the correlation between contraction rate and "torque current" will be explained.

As mentioned above, it is estimated that the shrinkage rate has a correlation with the "pulling stress". Therefore, the present inventor proposes to assume linearity in the correlation between shrinkage rate and "drawdown stress." For example, according to the contraction mechanism, "drawdown stress" causes the polymer chains of the polymer that is the constituent material of the molten resin to elongate. It is thought that the degree of this elongation increases as the "pulling stress" increases. Considering that when the resin is exposed to high temperatures through annealing treatment, the "draw-down stress" applied to the resin is resolved, causing the resin to shrink.As the degree of elongation increases, the shrinkage rate increases. It will be understood as it gets bigger. In other words, it is thought that the larger the "drawdown stress" is, the higher the shrinkage rate of an extrusion molded product containing resin as a constituent material, so it is not possible to assume linearity between the "drawdown stress" and the shrinkage rate of an extrusion molded product. It seems logical.

Therefore, assuming this linearity, the correlation between the "drawdown stress" and the shrinkage rate will be expressed by (Equation VII) shown below.

here,
t: Time ε: Shrinkage rate A: Constant σ: Drop stress C: Constant

Then, by substituting the "drawing stress" expressed by (Formula VI) into (Formula VII), (Formula VIII) shown below is obtained.

here,
t: Time ε: Shrinkage rate A ₀ = Aa ₀ : Constant τ: Drop stress B ₀ = Ab ₀ : Constant α: Temperature coefficient T: Temperature of resin dγ/dt: Strain rate n: Viscosity constant C: Constant

As described above, the correlation between contraction rate and "torque current" can be formulated. According to (Formula VIII) formulated in this way, if the constant A ₀ , constant B ₀ , constant C, temperature coefficient α, and viscosity constant n are known, the resin temperature (T) and strain rate (dγ /dt) and the "torque current", it is possible to estimate the shrinkage rate (ε) of the extruded product.

<Correlation verification results>
Below, verification results that support the correctness of the inventor's insight that there is a correlation between the shrinkage rate of an extruded product and the "torque current" will be explained. In other words, verification results that support the existence of a high correlation between contraction rate and "torque current" will be explained.

In order to verify the correlation between shrinkage rate and "torque current," an extrusion experiment is performed 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 temperature and strain rate of the resin are adopted as the extrusion conditions.

Specifically, a crosshead was attached to an extruder equipped with a full-flight screw with an outer diameter of 40 mm, and a die with a hole diameter of 2.25 mm was used to produce an extruded product (cable) with an outer diameter of 1.5 mm. A string-like sample consisting of the following was produced at a linear speed of 20 m/min. At this time, the temperature of the crosshead and die (corresponding to the temperature of the resin) was changed to 185°C, 190°C, and 195°C, and the "torque current" during extrusion was recorded every second with a data logger. This makes it possible to obtain data on string-like samples whose viscosity is changed by changing the temperature of the resin. The shrinkage rate was actually measured using the string-like sample thus obtained.

Specifically, string-like samples were taken every 600 seconds during extrusion and cut into approximately 500 mm. Then, the length of the cut string sample was measured after annealing at 130°C for 3 hours, and the shrinkage rate was measured by dividing the length after annealing by the initial length. did. In the manner described above, it is possible to obtain measured data showing the relationship between contraction rate and "torque current."

FIG. 8 is a graph plotting the measured data.

In FIG. 8, the horizontal axis indicates "torque current" (A), while the vertical axis indicates contraction rate (%). The O marks shown in FIG. 8 are data when the resin temperature is 185°C, the diamond marks are data when the resin temperature is 190°C, and the × marks are data when the resin temperature is 195°C.

As shown in FIG. 8, the correlation coefficient (R) between "torque current" and contraction rate is "0.89", and 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 "torque current" and contraction rate. In particular, it can be seen that the actually measured data has a generally linear relationship as shown by the broken line, which shows that the formulation of the correlation between the contraction rate and "torque current" by (Equation VIII) is appropriate. .

The above experimental results support the existence of a high correlation between "torque current" and contraction rate; This means that the inventor's assumption that this would be the case has been confirmed to be correct. Therefore, the technical idea of estimating the shrinkage rate of an extruded product based on the "torque current" formulated by (Equation VIII) is that it takes into account both material properties and extrusion conditions, and It can be seen that this is extremely useful in that it can be introduced in real time in the manufacturing process of products.

For example, if we take an insulating resin that covers a conducting wire as an extruded product, being able to estimate the shrinkage rate of the insulating resin in real time means that we can sequentially grasp the shrinkage rate in the longitudinal direction of the insulating resin extruded from an extruder. It means that you can.

<Configuration of shrinkage rate estimation device>
Below, a shrinkage rate estimating device that embodies the above-mentioned technical idea will be described.

<<Hardware configuration>>
First, the hardware configuration of the shrinkage rate estimating device in this embodiment will be described.

FIG. 9 is a diagram showing an example of the hardware configuration of the shrinkage rate estimating device 100 in this embodiment. The configuration shown in FIG. 9 merely shows an example of the hardware configuration of the shrinkage rate estimating device 100, and the hardware configuration of the shrinkage rate estimating device 100 is not limited to the configuration shown in FIG. Other configurations are also possible.

In FIG. 9, the shrinkage rate estimating device 100 includes a CPU (Central Processing Unit) 101 that executes a program. The CPU 101 is electrically connected to, for example, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, and a hard disk device 112 via a bus 113, and controls these hardware devices. It is configured as follows.

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

The shrinkage rate estimating device 100 may be connected to a network, for example. For example, when the shrinkage rate estimating device 100 is connected to other external devices via a network, the communication board 107 that constitutes a part of the shrinkage rate estimating device 100 is connected to a LAN (Local Area Network), WAN (Wide Area Network), network) or the Internet.

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

The hard disk device 112 stores, for example, an operating system (OS) 201, a program group 202, and a file group 203. The programs included in the program group 202 are executed by the CPU 101 while using the operating system 201. Further, the RAM 103 temporarily stores at least a portion of the operating system 201 programs and application programs to be executed by the CPU 101, and also stores various data necessary 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 estimating 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 implement the functions of the shrinkage rate estimating device 100, and this program is read and executed by the CPU 101. Further, the file group 203 stores information, data, signal values, variable values, and parameters indicating the results of processing by the CPU 101 as each item of the file.

The file is recorded on a recording medium such as the hard disk device 112 or memory. Information, data, signal values, variable values, and parameters recorded on recording media such as the hard disk device 112 and memory are read by the CPU 101 to the main memory and cache memory, and are extracted, searched, referenced, compared, calculated, processed, and It is used for operations of the CPU 101, such as editing, outputting, printing, and displaying. For example, during the operation of the CPU 101 described above, information, data, signal values, variable values, and parameters are temporarily stored in main memory, registers, cache memory, buffer memory, and the like.

The functions of the shrinkage rate estimating device 100 may be realized by firmware stored in the ROM 102, or may be realized only by software, only by hardware such as elements, devices, boards, and wiring, or by the combination of software and hardware. It may be implemented in combination, or even in combination with firmware. The firmware and software are recorded as programs on a recording medium such as a hard disk device 112, a removable disk, a CD-ROM, a DVD-ROM, and the like. The program is read and executed by the CPU 101. That is, the program causes the computer to function as the shrinkage rate estimating device 100.

In this way, the shrinkage rate estimating device 100 includes a CPU 101 as a processing device, a hard disk device 112 and a memory as a storage device, a keyboard 105, a mouse 106, a communication board 107 as an input device, a display 104 as an output device, and a printer 110 as an input device. , a computer equipped with a communication board 107. The functions of the shrinkage rate estimating device 100 are realized using a processing device, a storage device, an input device, and an output device.

<<Functional block configuration>>
Next, the functional block configuration of the shrinkage rate estimating device 100 will be explained.

FIG. 10 is a functional block diagram showing the functional configuration of the shrinkage rate estimating device.

In FIG. 10, the shrinkage rate estimation device 100 according to the present embodiment includes a first known data group input section 301, a second known data group input section 302, a first constant determination section 303, and a second constant determination section 304. , a shrinkage rate estimating section 305 , a determining section 306 , a matching condition searching section 307 , an output section 308 , and a data storage section 309 .

The first known data group input unit 301 is configured to input a first known data group, for example. Here, the "first known data group" is a data group that associates the combination of resin temperature and strain rate with viscosity, and is defined as a data group for which the resin temperature, strain rate, and viscosity are known. be done. These "first known data groups" are input to the first known data group input section 301 and then stored in the data storage section 309.

The second known data group input unit 302 is configured to input a second known data group, for example. Here, the "second known data group" is a data group that associates the combination of torque current and extrusion conditions with the shrinkage rate of the extruded product. is defined as a data group for which the Specifically, in this embodiment, the extrusion conditions consist of a combination of resin temperature and strain rate, so the "second known data group" refers to the combination of torque current, resin temperature, and strain rate. A data group that associates a combination with the shrinkage rate of an extruded product, and is defined as a data group in which the torque current, resin temperature, strain rate, and shrinkage rate of the extruded product are known. These "second known data groups" are input to the second known data group input section 302 and then stored in the data storage section 309.

Next, the first constant determination unit 303 determines the “temperature coefficient α” and the “viscosity index” included in (formula I) based on the first known data group stored in the data storage unit 309 and (formula I). n''. Specifically, for example, as shown in FIG. 11, the first constant determination unit 303 uses the first known data group as teacher data to create a neural network whose inputs are the temperature and strain rate of the resin and whose output is the viscosity. It is configured to determine the temperature coefficient and viscosity index by learning. At this time, the strain rate is determined by using (Formula II), for example, the average flow velocity (v _d ) and linear velocity (v _f ) of the molten resin at the exit of the die, and the distance from the exit of the die to the water tank (L ). Note that the first constant determining unit 303 is configured not only to determine the temperature coefficient and viscosity index using the machine learning described above, but also to determine the temperature coefficient and viscosity index by using the least squares method on the first known data group, for example. The temperature coefficient and the viscosity index may be determined by applying typical statistical analysis techniques. The temperature coefficient and viscosity index determined in this way are stored in the data storage section 309.

Next, the second constant determination unit 304 substitutes the second known data group stored in the data storage unit 309 and the temperature coefficient and viscosity index determined by the first constant determination unit 303 into (Formula VIII). Based on this, the constant A ₀ , the constant B ₀ and the constant C included in (Formula VIII) are determined. Specifically, for example, as shown in FIG. 12, the second constant determination unit 304 uses the second known data group as teacher data and inputs the extrusion conditions (resin temperature and strain rate) and "torque current". The constant A ₀ , the constant B ₀ , and the constant C are determined by training a neural network whose output is the shrinkage rate of the extruded product. At this time, the strain rate is determined by using (Formula II), for example, the average flow velocity (v _d ) and linear velocity (v _f ) of the molten resin at the exit of the die, and the distance from the exit of the die to the water tank (L ).

Note that the second constant determining unit 304 is configured not only to determine the constant A ₀ , the constant B 0 , and the constant C using the machine learning described above, but also, for example, to determine the constant A 0 , the constant B ₀ , and the constant C using the machine learning described above. The constant A ₀ , the constant B ₀ , and the constant C may be determined by applying a statistical analysis technique represented by the least squares method. The constant A ₀ , constant B ₀ and constant C determined in this way are stored in the data storage unit 309.

In the above, among the five constants included in (Formula VIII), the temperature coefficient and the viscosity index are determined by the first constant determination unit 303 based on the first known data group, and the constant A ₀ , the constant B ₀ and the constant C A configuration in which is determined by the second constant determination unit 304 based on the second known data group is described.

However, the configuration for determining the five constants included in (Formula VIII) is not limited to this, and can also be realized by the configuration shown below. That is, a configuration may be considered in which the second constant determination unit 304 determines all five constants included in (Formula VIII) based on the second known data group. In this case, there is an advantage that there is no need to measure the viscosity itself included in the first known data group using a rheometer or the like. When determining the five constants using this configuration, it is desirable to use machine learning, which is better at fitting nonlinear functions than fitting using the least squares method, from the viewpoint of increasing fitting accuracy.

Next, the shrinkage rate estimating unit 305 is configured to estimate the shrinkage rate of the extruded product based on the "torque current" of the motor provided in the extruder and the extrusion conditions of the extruder. Specifically, the shrinkage rate estimating unit 305 substitutes the temperature coefficient and viscosity index determined by the first constant determining unit 303 and the constant A ₀ , constant B ₀ and constant C determined by the second constant determining unit. It is configured to estimate the shrinkage rate of the extruded product from the extrusion conditions consisting of temperature and strain rate and "torque current" based on (Equation VIII).

Subsequently, the determining unit 306 is configured to determine whether the shrinkage rate estimated by the shrinkage rate estimating unit 305 is equal to or less than a preset “threshold value”.

If the determining unit 306 determines that the shrinkage rate estimated by the shrinkage rate estimating unit 305 is not equal to or less than a preset “threshold value,” the matching condition search unit 307 calculates the value included in (Formula VIII). The shrinkage rate of the extruded product is re-estimated by changing the extrusion conditions (temperature and strain rate of the resin), and the extrusion conditions (compatible conditions) under which the re-estimated shrinkage rate is below the "threshold" are searched. It is configured.

The output unit 308 is configured to output, for example, the shrinkage rate estimated by the shrinkage rate estimation unit 305 and the extrusion conditions searched for by the compatible condition search unit 307.

As described above, the shrinkage rate estimating device 100 in this embodiment is configured.

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

＜＜Basic operation＞＞
FIGS. 13 and 14 are flowcharts illustrating the basic operation of the shrinkage rate estimating device.

In FIG. 13, first, when a first known data group is input to the first known data input section 301 (S101), the input first known data group is stored in the data storage section 309.

Next, the first constant determination unit 303 determines the temperature coefficient and viscosity index regarding the material property (viscosity) included in (Formula I) based on the first known data group stored in the data storage unit 309. (S102).

On the other hand, when the second known data group is input to the second known data group input section 302 (S103), the input second known data group is stored in the data storage section 309. Next, the second constant determination unit 304 substitutes the second known data group stored in the data storage unit 309 and the temperature coefficient and viscosity index determined by the first constant determination unit 303 into (Formula VIII). Based on this, constant A ₀ , constant B ₀ and constant C included in (Formula VIII) are determined (S104). In this way, a relational expression between "torque current" and contraction rate can be obtained.

In FIG. 14, when the extrusion conditions (resin temperature and strain rate) and "torque current" are input (S201), the shrinkage rate estimating unit 305 calculates the temperature coefficient and viscosity index determined by the first constant determining unit 303. The shrinkage rate of the extrusion molded product is estimated based on (Equation VIII) in which the constant A ₀ , constant B ₀ and constant C determined by the second constant determination unit 304 are substituted (S202). The shrinkage rate estimated by the shrinkage rate estimation section 305 is output from the output section 308. In this way, the basic operation of the shrinkage rate estimating device 100 is performed. Thereby, according to the shrinkage rate estimating device 100, the shrinkage rate can be estimated in real time based on the "torque current."

<<Application operation>>
Furthermore, in addition to the basic operations described above, the shrinkage rate estimating device 100 can also perform the following applied operations. FIG. 15 is a flowchart illustrating the applied operation of the shrinkage rate estimating device. In FIG. 15, when the shrinkage rate of the extruded product is estimated by performing the above-mentioned basic operations (S301), the determining unit 306 determines that the shrinkage rate estimated by the shrinkage rate estimating unit 305 is set in advance. It is determined whether or not the value is less than or equal to the "threshold value" set (S302). When the shrinkage rate estimated by the shrinkage rate estimation unit 305 is less than or equal to the “threshold value”, the output unit 308 outputs a message that the shrinkage rate is less than or equal to the “threshold value” (S305). On the other hand, if the shrinkage rate estimated by the shrinkage rate estimation unit 305 is not less than the “threshold value”, the compatible condition search unit 307 changes the extrusion conditions (resin temperature and strain rate) included in (Formula VIII). The shrinkage rate of the extruded product is then re-estimated, and an extrusion condition (suitable condition) under which the re-estimated shrinkage rate is equal to or less than the "threshold" is searched for (S303). Then, the extrusion conditions searched by the compatible condition search unit 307 are output from the output unit 308 (S304). In this way, the applied operation of the shrinkage rate estimating device 100 is performed. Thereby, according to the shrinkage rate estimating device 100, even if the shrinkage rate estimated by the shrinkage rate estimation unit 305 does not satisfy the predetermined condition, the extrusion conditions for the shrinkage rate to satisfy the predetermined condition are presented. can.

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

<Modified example>
When the shrinkage rate estimating device 100 performs not only the basic operation but also the applied operation, the shrinkage rate estimating unit 305 needs to be configured to estimate the shrinkage rate based on (Formula VIII). This is because (Formula VIII) includes "torque current" and extrusion conditions (resin temperature and strain rate) as variables for estimating the shrinkage rate, so it is not possible to estimate the shrinkage rate by changing the extrusion conditions. This is because it becomes possible.

Here, for example, it is conceivable to fix the extrusion conditions of the extruder and perform only the operation of estimating the shrinkage rate of the extruded product under the fixed extrusion conditions. In other words, it is conceivable that the shrinkage rate estimating device 100 performs only the basic operations. In this case, the shrinkage rate estimating unit 305 can be configured to estimate the shrinkage rate based on a relational expression that simplifies (Equation VIII). This is because when the extrusion conditions are fixed, the term (e ^{− αT} |dγ/dt| ⁿ ) becomes a constant term. This relational expression is expressed by (Formula IX) shown below.

here,
t: Time ε: Contraction rate A ₁ : Constant τ: Torque current B ₁ : Constant

In this case, the first known data group and the first constant determining section become unnecessary. Furthermore, as the second known data group, it is sufficient to obtain a data group in which the "torque current" changes under a fixed extrusion condition, which facilitates data acquisition. The second constant determining unit 304 can be configured to determine the constant A ₁ and the constant B ₁ by applying the least squares method to the second known data group, for example. In this way, according to this modification, the shrinkage rate of the extruded product can be estimated from the "torque current" while simplifying the configuration of the shrinkage rate estimating device 100.

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

For example, in the shrinkage rate estimating apparatus 100 comprising a computer shown in FIG. 9, the shrinkage rate estimating program according to this embodiment can be introduced as one of the program group 202 stored in the hard disk drive 112. The shrinkage rate estimation method according to the present embodiment can be realized by causing the computer serving as the shrinkage rate estimation device 100 to execute this shrinkage rate estimation program.

A 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. Examples of recording media include 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. is included.

<Effects of the embodiment>
According to the technical idea of this embodiment, instead of directly estimating the shrinkage rate of an extruded product, we focus on "torque current" which has been newly found to have a correlation with the shrinkage rate. The shrinkage rate is indirectly estimated based on this "torque current." This not only allows for highly accurate estimation of shrinkage by easily taking into account both material properties and extrusion conditions, but also eliminates the need to consider a parameter that requires measurement, such as "crystallinity," which can be understood in real time. Since it uses possible "torque current", it has great technical significance in that it can provide a shrinkage rate estimation technology that can be introduced in real time in the manufacturing process of extrusion molded products.

<Manufacturing method of extrusion molded product>
For example, until now, there was no shrinkage rate estimation technology that could be introduced in real time in the manufacturing process of extrusion molded products, so it is possible to reduce the shrinkage rate by adjusting extrusion conditions based on the experience of workers. was being carried out. Regarding this point, according to the technical idea of this embodiment, it is possible to introduce objectively accurate shrinkage rate estimation technology into the manufacturing process (manufacturing line) of extruded products without relying on the experience of workers. can. As a result, according to the present embodiment, it is possible to reduce the amount of discarded resin materials and extruded products (for example, cables) and improve production efficiency. In other words, the technical idea of this embodiment is to make it possible to introduce the shrinkage rate estimation technology into the extrusion product production line in real time, thereby achieving the remarkable effect of improving the production yield of extrusion products. be able to. Therefore, below, a manufacturing process of an extrusion molded product using the technical idea of this embodiment will be explained.

<<Specific example 1>>
For example, in Specific Example 1, a method for producing an extruded product will be described which includes a shrinkage rate monitoring step of monitoring the shrinkage rate of the extruded product in real time based on the torque current of a motor provided in an extruder.

FIG. 16 is a flowchart illustrating a part of the manufacturing process of the extrusion molded product.

In FIG. 16, first, the extrusion conditions in the extruder are initialized (S401), the resin is kneaded under the initially set extrusion conditions, and the molten resin is extruded from the exit of the die. The kneading of the resin at this time is performed by rotating a screw using a motor provided in the extruder.

Here, in order to detect abnormal rotation of the screw, the "torque current" for driving the motor is constantly monitored. In specific example 1, the shrinkage rate of the extruded product is estimated in real time based on this "torque current", and it is determined whether the estimated shrinkage rate of the extruded product is within a predetermined threshold range. (S402) Then, if the estimated shrinkage rate of the extruded product is within the threshold range, it is determined that the shrinkage rate is "OK" (S403), and the operation of the extruder is started. Continue to monitor the shrinkage rate of the extrusion. On the other hand, if the estimated shrinkage rate of the extruded product is outside the threshold range, the shrinkage rate is determined to be "NG" (S403), and the operation of the extruder is stopped (S404). . This makes it possible to prevent the production of defective products.

<<Specific example 2>>
In specific example 2, extrusion conditions are adjusted based on the results of estimating the shrinkage rate of the extruded product in real time based on the torque current of the motor provided in the extruder, and the extrusion molded product is manufactured under the adjusted extrusion conditions. The method for manufacturing the molded product will be explained.

FIG. 17 is a flowchart illustrating a part of the manufacturing process of an extrusion molded product.

In FIG. 17, first, extrusion conditions are initialized (S501). Next, the shrinkage rate estimation technique in this embodiment is used. Specifically, for example, five constants consisting of "temperature coefficient α", "viscosity index n", "constant A ₀ ", "constant B ₀ ", and "constant C" are determined (Formula VIII) is prepared. Then, the shrinkage rate of the extruded product is estimated by substituting the "torque current" monitored in real time and the initially set extrusion conditions into this (Equation VIII) (S502). At this time, the above-mentioned basic operation and applied operation are performed.

As a result, if the estimated shrinkage rate is below the "threshold", the initially set extrusion conditions are maintained. On the other hand, if the estimated shrinkage rate is not below the threshold, the conditions are changed to the compatible conditions (extrusion conditions) presented in the applied operation (S503).

Then, extrusion molding of the resin is performed under the maintained extrusion conditions or the changed extrusion conditions (S504). Thereafter, an annealing process is performed on the resin (S505), and after a predetermined period of time (one day to two days later), the shrinkage rate is measured (S506). At this time, if the shrinkage rate is below a predetermined value (OK) (S507), an extrusion molded product is manufactured as a non-defective product. On the other hand, if the shrinkage rate is not less than the predetermined value (NG), the constants included in (Formula VIII) are re-determined, taking into consideration this NG data (S508). For example, the constants included in (Formula VIII) are re-determined by adding the above-mentioned NG data and retraining the neural network. In this way, the method for manufacturing an extrusion molded product according to the present embodiment is realized.

According to the method for manufacturing an extrusion molded product in this embodiment, the shrinkage rate estimation technology is introduced into the production line to estimate the shrinkage rate of the extrusion molded product in real time, thereby improving the manufacturing yield of the extrusion molded product. can be done. Furthermore, if the estimated shrinkage rate is "OK" but the final measured shrinkage rate is "NG", the constants included in (Formula VIII) can be redetermined based on this NG data. Accordingly, the accuracy of estimating the shrinkage rate can be improved.

The invention made by the present inventor has been specifically explained based on the embodiments thereof, but the present invention is not limited to the embodiments described above, and can be modified in various ways without departing from the gist thereof. Needless to say.

For example, the "torque current" of the motor installed in an extruder differs depending on the type of motor and the shape of the screw, but if you determine the value under the standard extrusion conditions (molding conditions), the relative value can be used to determine the value of the extruded product. It is possible to understand increases and decreases in shrinkage rate. Therefore, as long as the standard conditions of the extruder are understood, the technical idea in the embodiment can be applied to any type of extruder. However, since the full-flight screw has a simple screw structure, it is easy to apply the technical idea in the above embodiment.

The technical idea in the embodiments described above is applicable to a wide variety of resins including plastics and rubbers, and is not limited to thermoplastic polyurethane resins, for example. Furthermore, the technical idea in the embodiments described above is applicable to a wide range of extrusion forms regardless of tube extrusion, wire extrusion, or die shape. Furthermore, the extrusion molded product (product) manufactured by the method for manufacturing an extrusion molded product to which the technical concept of the embodiment is applied can be of any shape or type, such as a sheet, irregular shape, or cable (electric wire).

10 Raw material pellets 11 Extruder 12 Crosshead 13 Die 14 Conductive wire 15 Water tank 20 Molten resin 100 Shrinkage rate 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 First known data group input section 302 Second known data group Input section 303 First constant determination section 304 Second constant determination section 305 Shrinkage rate estimation section 306 Judgment section 307 Compatibility condition search section 308 Output section 309 Data storage section

Claims (15)

A shrinkage rate estimating device for estimating the shrinkage rate of an extruded product containing resin as a constituent material extruded from an extruder,
The shrinkage rate estimating device includes a shrinkage rate estimator that estimates the shrinkage rate of the extruded product based on a torque current of a motor included in the extruder and extrusion conditions of the extruder. The shrinkage rate estimating device according to claim 1,
The shrinkage rate estimating unit is a shrinkage rate estimating device that estimates the shrinkage rate of the extrusion molded product based on Equation 1 shown below.

here,
t: Time ε(t): Shrinkage rate A ₀ : Constant τ(t): Torque current B ₀ : Constant α: Temperature coefficient T: Resin temperature dγ/dt: Strain rate n: Viscosity index C: Constant The shrinkage rate estimating device according to claim 2,
In the shrinkage rate estimating device, the strain rate is expressed by Equation 2 shown below.

here,
dγ/dt: Strain rate v _d : Average flow velocity of molten resin at the exit of the die v _f : Linear velocity L: Distance from the exit of the die to the water tank The shrinkage rate estimating device according to claim 3,
The shrinkage rate estimating device, wherein the temperature coefficient and the viscosity index included in the equation 1 are included in the equation 3 shown below.

here,
t: Time η: Viscosity η ₀ : Viscosity constant α: Temperature coefficient T: Resin temperature dγ/dt: Strain rate n: Viscosity index The shrinkage rate estimating device according to claim 4,
The shrinkage rate estimating device includes:
a first known data group input unit that inputs a first known data group that associates the combination of the temperature and the strain rate with the viscosity;
a first constant determining unit that determines the temperature coefficient of the viscosity and the viscosity index based on the first known data group input from the first known data group input unit and the formula 3;
a second known data group input unit that inputs a second known data group that associates the combination of the torque current, the temperature, and the strain rate with the shrinkage rate of the extruded product;
Based on the second known data group input from the second known data group input section and the formula 1 in which the temperature coefficient of the viscosity and the viscosity index determined by the first constant determining section are substituted, a second constant determining unit that determines constant A ₀ , constant B ₀ and constant C included in Formula 1;
has
The shrinkage rate estimating unit is configured to calculate the temperature coefficient and the viscosity index determined by the first constant determining unit, the constant A ₀ , the constant B ₀ and the constant C determined by the second constant determining unit. A shrinkage rate estimating device that estimates the shrinkage rate of the extrusion molded product from the extrusion conditions including the temperature and the strain rate and the torque current based on the formula 1 in which . The shrinkage rate estimating device according to claim 5,
The first constant determination unit determines the temperature coefficient and the viscosity by using the first known data group as training data and training a neural network whose inputs are the temperature and the strain rate and whose output is the viscosity. Shrinkage rate estimator that determines the index. The shrinkage rate estimating device according to claim 5,
The shrinkage rate estimating device, wherein the second constant determining unit determines the constant A ₀ , the constant B ₀ , and the constant C by applying a least squares method to the second known data group. The shrinkage rate estimating device according to claim 5,
The second constant determining unit uses the second known data group as training data to train a neural network whose inputs are the extrusion conditions and the torque current, and whose output is the shrinkage rate of the extruded product. , the constant A ₀ , the constant B ₀ and the constant C. A shrinkage rate estimating device for estimating the shrinkage rate of an extruded product containing resin as a constituent material extruded from an extruder,
The shrinkage rate estimating device includes a shrinkage rate estimator that estimates the shrinkage rate of the extruded product based on a torque current of a motor included in the extruder. The shrinkage rate estimating device according to claim 9,
The shrinkage rate estimating unit is a shrinkage rate estimating device that estimates the shrinkage rate of the extrusion molded product based on Equation 4 shown below.

here,
t: Time ε: Contraction rate A ₁ : Constant τ: Torque current B ₁ : Constant A shrinkage rate estimation method for estimating the shrinkage rate of an extruded product containing resin extruded from an extruder as a constituent material, the method comprising:
The shrinkage rate estimating method includes a shrinkage rate estimating step of estimating the shrinkage rate of the extruded product based on the torque current of a motor provided in the extruder and extrusion conditions of the extruder. A program that causes a computer to execute a process of estimating the shrinkage rate of an extruded product containing resin extruded from an extruder as a constituent material, the program comprising:
The program includes a shrinkage rate estimation process for estimating the shrinkage rate of the extruded product based on a torque current of a motor provided in the extruder and extrusion conditions of the extruder. A computer-readable recording medium recording the program according to claim 12. A method for producing an extrusion molded product containing a resin extruded from an extruder as a constituent material, the method comprising:
The method for manufacturing an extrusion molded product includes a shrinkage rate monitoring step of monitoring the shrinkage rate of the extrusion molded product in real time based on the torque current of a motor provided in the extruder. A method for producing an extrusion molded product containing a resin extruded from an extruder as a constituent material, the method comprising:
a shrinkage rate estimation step of estimating the shrinkage rate of the extruded product in real time based on the torque current of a motor provided in the extruder and the extrusion conditions of the extruder;
an extrusion condition adjustment step of adjusting the extrusion conditions based on the estimated shrinkage rate;
a molding step of extruding the resin under the adjusted extrusion conditions;
A method for producing an extruded product, comprising:

Images