JP2021070210A - Control device, injection molding machine, and control method - Google Patents

Abstract

To provide a control device for controlling an operation of an injection molding machine, which suppresses defects in a molded product formed by injection molding.SOLUTION: A control device 120 that controls an operation of an in-line screw type injection molding machine equipped with a cylinder and a screw includes an estimating unit 122 that estimates a viscosity of a resin in a molten state in the cylinder based on an output waveform of a measured value of a rotational torque during a measuring period by the screw.SELECTED DRAWING: Figure 2

Description

The present invention relates to a control device, an injection molding machine, and a control method.

Patent Document 1 below discloses a technique for changing or stopping the screw rotation operation when a screw rotation torque equal to or higher than an allowable upper limit value is detected during measurement with a screw in an injection molding machine.

Japanese Patent No. 4237237

However, in the prior art, for example, when a recycled material is used, the viscosity of the resin ejected from the cylinder may vary due to the variation in the particle size of the pellet-shaped resin charged into the cylinder. is there. In addition, there is a risk that the viscosity of the raw material itself will vary between lots or within the lot. Such variations in the viscosity of the resin may cause defects in the molded product formed by injection molding (for example, insufficient filling of the resin, overfilling of the resin, etc.).

The control device of one embodiment is a control device that controls the operation of an in-line screw type injection molding machine including a cylinder and a screw, and is based on the output waveform of the measured value of the rotational torque during the measurement period by the screw. It is provided with an estimation unit for estimating the viscosity of the resin in a molten state.

According to one embodiment, it is possible to suppress defects in the molded product formed by injection molding.

The figure which shows the schematic structure of the injection molding machine which concerns on one Embodiment The figure which shows the functional structure of the control device which concerns on one Embodiment. The figure which shows an example of the output waveform of the measured value of the rotational torque of a screw measured by the measuring apparatus which concerns on one Embodiment. A flowchart showing a first example of a processing procedure by a control device according to an embodiment. A flowchart showing a second example of the processing procedure by the control device according to the embodiment. A flowchart showing a third example of the processing procedure by the control device according to the embodiment.

Hereinafter, one embodiment will be described with reference to the drawings.

(Rough configuration of injection molding machine 100)
FIG. 1 is a diagram showing a schematic configuration of an injection molding machine 100 according to an embodiment. The injection molding machine 100 shown in FIG. 1 is an in-line screw type injection molding machine. As shown in FIG. 1, the injection molding machine 100 includes an injection molding unit 110, a control device 120, and a measuring device 130.

The injection molding unit 110 includes a cylinder 111, a screw 112, a heater 113, a hopper 114, and a drive device 115.

The cylinder 111 is an elongated tubular member. The resin 140 of the cylinder 111 is melted inside the cylinder. At the tip of the cylinder 111, a nozzle portion 111A for injecting the resin 140 liquefied by melting into the mold is provided.

The hopper 114 is provided near the rear end of the cylinder 111. The hopper 114 sends the pellet-shaped resin 140 charged from the upper opening of the hopper 114 into the cylinder 111 through the lower opening of the hopper 114. As the resin 140, a resin material having plasticity is used.

The screw 112 is provided inside the cylinder 111 so as to be forward and backward and rotatable. The screw 112 is rotated by the drive of the drive device 115 to shear and compress the resin 140 charged into the cylinder 111 from the hopper 114 while being conveyed toward the tip of the cylinder 111. As a result, the screw 112 can melt the resin 140. Further, the screw 112 can rotate to feed the liquefied resin 140 to the tip end portion of the cylinder 111 and store the resin 140. At this time, the screw 112 gradually retracts to measure the resin 140 stored in the tip of the cylinder 111. Then, the screw 112 advances by driving the drive device 115, so that the resin 140 stored in the tip end portion of the cylinder 111 can be injected into the mold from the nozzle portion 111A of the cylinder 111. In this document, the "weighing period by the screw 112" means that a predetermined amount of resin 140 is stored in the tip of the cylinder 111 from the start of rotation of the screw 112 to the stop of rotation of the screw 112. Up to) period.

The heater 113 is provided on the outer peripheral surface of the cylinder 111 and heats the resin 140 inside the cylinder 111. As a result, the heater 113 can keep the melted and liquefied resin 140 warm by being sheared and compressed by the screw 112, and can prevent the liquefied resin 140 from solidifying.

The drive device 115 drives each part of the injection molding part 110. For example, the drive device 115 uses a servomotor (not shown) to rotate and move the screw 112 forward and backward.

The measuring device 130 measures the rotational torque of the screw 112. For example, the measuring device 130 measures the rotational torque of the screw 112 at each predetermined sampling cycle, and outputs the measured value of the rotational torque to the control device 120. Further, the measuring device 130 can display the measured value of the rotational torque on a display device such as a liquid crystal panel (not shown) together with other information.

The control device 120 controls the operation of the injection molding unit 110. For example, the control device 120 controls the rotation (rotational speed, etc.) and injection (injection speed, injection pressure, etc.) of the screw 112 by controlling the drive device 115 that rotates and injects the screw 112. Further, for example, the control device 120 controls the heating operation of the heater 113.

In particular, the control device 120 of the present embodiment can estimate the viscosity of the resin 140 in a molten state in the cylinder 111 according to the output waveform of the measured value of the rotational torque during the measurement period by the screw 112. Further, the control device 120 of the present embodiment sets the operation of the injection molding unit 110 (for example, the rotation speed of the screw 112, the injection speed, the injection pressure, and the output temperature of the heater 113) according to the estimated viscosity of the resin 140. Alternatively, by changing the temperature inside the cylinder 111) and the like), it is possible to suppress defects in the molded product formed by the injection molding machine 100. Alternatively, the control device 120 of the present embodiment can temporarily stop the operation of the injection molding unit 110 when the estimated viscosity of the resin 140 is out of the permissible range.

(Functional configuration of control device 120)
FIG. 2 is a diagram showing a functional configuration of the control device 120 according to the embodiment. As shown in FIG. 2, the control device 120 includes an acquisition unit 121, an estimation unit 122, a change unit 123, a control unit 124, and a storage unit 125.

The acquisition unit 121 acquires the measured value of the rotational torque of the screw 112 measured by the measuring device 130. For example, the acquisition unit 121 continuously acquires the measured value of the rotational torque of the screw 112 in response to the measuring device 130 continuously outputting the measured value of the rotational torque of the screw 112.

The estimation unit 122 estimates the viscosity of the resin 140 in a molten state in the cylinder 111 based on the output waveform of the measured value of the rotational torque during the measurement period by the screw 112 acquired by the acquisition unit 121.

As a first example, the estimation unit 122 estimates the viscosity of the resin 140 by analyzing the output waveform of the measured value of the rotational torque during the measurement period by the screw 112 by statistical processing using the MT (Mahalanobis Taguchi) method. ..

As a second example, the estimation unit 122 estimates the viscosity of the resin 140 by analyzing the output waveform of the measured value of the rotational torque during the measurement period by the screw 112 using AI (Artificial Intelligence).

For example, the viscosity of the resin 140 estimated by the estimation unit 122 is relative to the reference value, such as "viscosity is higher than the reference value" and "viscosity is lower than the reference value". You may. Further, for example, the viscosity of the resin 140 estimated by the estimation unit 122 may be an absolute value representing the viscosity of the resin 140 in numerical values or levels.

When the viscosity of the resin 140 estimated by the estimation unit 122 is out of the predetermined allowable range (that is, when the viscosity deviates from the normal viscosity range), the change unit 123 sets the operation of the injection molding unit 110 (that is, when it deviates from the normal viscosity range). For example, the rotation speed of the screw 112, the injection speed, the injection pressure, the output temperature of the heater 113 (or the temperature inside the cylinder 111), etc.) are changed. For example, the changing unit 123 acquires the operation setting of the viscosity range corresponding to the viscosity of the resin 140 estimated by the estimating unit 122 from the storage unit 125 as the changed operation setting.

The control unit 124 controls the operation of the injection molding unit 110. For example, when the operation setting of the injection molding unit 110 is changed by the changing unit 123, the control unit 124 controls the operation of the injection molding unit 110 based on the changed operation setting by the changing unit 123. Further, for example, in the control unit 124, when the viscosity of the resin 140 estimated by the estimation unit 122 is out of a predetermined allowable range (that is, when it deviates from the normal viscosity range), the injection molding unit 110 Operation can be stopped.

The storage unit 125 stores various information. For example, the storage unit 125 has an appropriate operation setting (for example, rotation speed of screw 112, injection speed, injection pressure, output temperature of heater 113 (or temperature in cylinder 111)) for each of a plurality of viscosity ranges. Etc.) are memorized.

Further, for example, the storage unit 125 stores in advance the data used for the analysis process by the estimation unit 122. For example, when the estimation unit 122 estimates the viscosity of the resin 140 by statistical processing using the MT method, the storage unit 125 uses the storage unit 125 as a reference for determining normality and abnormality in the normal state (no defect occurs in the molded product). When), the data group (unit space) of the inclination a is stored in advance. “Slope a” represents the slope of the approximate quadratic curve with respect to the output waveform of the measured value of the rotational torque during the measurement period by the screw 112. In this case, it is preferable that the storage unit 125 stores the data group of the inclination a at the normal time for each material of the resin 140.

Further, for example, when the estimation unit 122 estimates the viscosity of the resin 140 using AI, the storage unit 125 serves as a reference for determining normality and abnormality in the normal state (when no defect occurs in the molded product). The data group of the measured values of the rotational torque during the measurement period by the screw 112 (that is, from the start of rotation of the screw 112 to the stop of rotation of the screw 112) is stored in advance as teacher data. In this case, it is preferable that the storage unit 125 stores the teacher data for each material of the resin 140.

(Example of output waveform of measured value of rotational torque of screw 112)
FIG. 3 is a diagram showing an example of an output waveform of a measured value of the rotational torque of the screw 112 measured by the measuring device 130 according to the embodiment. In FIG. 3, the measured value of the rotational torque of the screw 112 is represented by a solid line, and the injection pressure by the screw 112 is represented by a dotted line.

In FIG. 3, the timing t1 is the timing at which the previous injection by the screw 112 was performed. Therefore, as shown in FIG. 3, at the timing t1, the injection pressure by the screw 112 is sharply increased.

Further, in FIG. 3, the timing t2 is the rotation start timing of the screw 112 for the next weighing, and the timing t3 is the rotation end timing of the screw 112 for the next weighing. That is, the period of timing t2 to t3 is the measurement period by the screw 112.

During the weighing period by the screw 112, the screw 112 gradually retracts while melting the resin 140 by rotating the screw 112. Therefore, as shown in FIG. 3, during the weighing period by the screw 112, the output waveform of the measured value of the rotational torque of the screw 112 is inclined upward as a whole. It has been found by the inventors of the present invention that the viscosity of the resin 140 changes (that is, has a causal relationship with the viscosity of the resin 140) according to the inclination of the output waveform of the measured value of the rotational torque. .. The slope of the output waveform of the measured value of the rotational torque is related to the load applied to the screw 112 when the screw 112 shears and melts the resin 140. When the inclination is large, the load applied to the screw 112 for melting the resin 140 is larger, and the viscosity of the melted resin 140 tends to be high. On the contrary, when the inclination is small, the resin 140 is melted more easily, and the viscosity of the melted resin 140 tends to be low.

(First example of the processing procedure by the control device 120)
FIG. 4 is a flowchart showing a first example of the processing procedure by the control device 120 according to the embodiment.

First, the acquisition unit 121 acquires the measured value of the rotational torque during the measurement period by the screw 112, which is measured by the measuring device 130 (step S401).

Next, the estimation unit 122 increases the slope of the approximate quadratic curve of the rotational torque measurement value in the measurement period by the screw 112 based on the output waveform of the rotational torque measurement value in the measurement period by the screw 112 acquired in step S401. Calculate a (step S402).

Next, the estimation unit 122 performs statistical processing using the MT method on the data group of the normal inclination a stored in the storage unit 125 (however, it corresponds to the material of the resin 140 currently in use). , The Mahalanobis distance d is calculated (step S403).

Next, the estimation unit 122 determines whether or not the distance d calculated in step S403 is less than a predetermined threshold value A (step S404).

When it is determined in step S404 that the distance d is less than a predetermined threshold value A (step S404: Yes), the control unit 124 operates the injection molding unit 110 without changing the operation setting of the injection molding unit 110. (Step S405). Then, the control device 120 ends a series of processes shown in FIG.

On the other hand, when it is determined in step S404 that the distance d is not less than the predetermined threshold value A (step S404: No), the control device 120 performs a predetermined error processing (step S406). The “predetermined abnormality processing” is, for example, issuing a warning, stopping the operation of the injection molding unit 110, changing the operation setting of the injection molding unit 110 by the changing unit 123, and the like. Then, the control device 120 ends a series of processes shown in FIG.

(Second example of the processing procedure by the control device 120)
FIG. 5 is a flowchart showing a second example of the processing procedure by the control device 120 according to the embodiment.

First, the acquisition unit 121 acquires the measured value of the rotational torque during the measurement period by the screw 112, which is measured by the measuring device 130 (step S501).

Next, the estimation unit 122 increases the slope of the approximate quadratic curve of the rotational torque measurement value in the measurement period by the screw 112 based on the output waveform of the rotational torque measurement value in the measurement period by the screw 112 acquired in step S501. Calculate a (step S502).

Next, the estimation unit 122 performs statistical processing using the MT method on the data group of the normal inclination a stored in the storage unit 125 (however, it corresponds to the material of the resin 140 currently in use). , The Mahalanobis distance d is calculated (step S503).

Next, the estimation unit 122 determines whether or not the distance d calculated in step S503 is less than a predetermined threshold value A (step S504).

When it is determined in step S504 that the distance d is less than a predetermined threshold value A (step S504: Yes), the control unit 124 operates the injection molding unit 110 without changing the operation setting of the injection molding unit 110. (Step S509). Then, the control device 120 ends a series of processes shown in FIG.

On the other hand, when it is determined in step S504 that the distance d is not less than the predetermined threshold value A (step S504: No), whether the slope a calculated by the estimation unit 122 in step S502 is larger than the predetermined threshold value B. It is determined whether or not (step S505).

When it is determined in step S505 that the slope a is larger than the predetermined threshold value B (step S505: Yes), the estimation unit 122 determines that "the viscosity of the resin 140 is higher than the reference value" (step S507). .. Then, the control device 120 performs a predetermined abnormality processing (step S508). After that, the control device 120 ends a series of processes shown in FIG.

On the other hand, when it is determined in step S505 that the slope a is not larger than the predetermined threshold value B (step S505: No), the estimation unit 122 determines that "the viscosity of the resin 140 is lower than the reference value" (step S505: No). Step S507). Then, the control device 120 performs a predetermined abnormality processing (step S508). After that, the control device 120 ends a series of processes shown in FIG.

Here, the concept of determination in steps S504 to S506 and S507 is supplemented. When No is determined in step S504, it is known that the viscosity of the molten resin 140 is abnormal, but it is possible to determine whether the viscosity is high and abnormal, or the viscosity is low and abnormal. Absent.

The threshold value B in step S505 is the slope a when the distance d <threshold value A holds in step S504. That is, the inclination a in the state determined to be normal may be sufficient. The distance d is preferably closer to 0.

In step S506, since the inclination is smaller than the inclination in the normal state (the viscosity tends to be low) and it is not normal, it can be determined that the viscosity is low and abnormal.

Further, in step S507, since the inclination is larger than the inclination in the normal state (the viscosity tends to be high) and it is not normal, it can be determined that the viscosity is high and abnormal.

Therefore, in step S508, a more appropriate abnormality treatment can be performed according to the viscosity of the resin 140.

(Third example of the processing procedure by the control device 120)
FIG. 6 is a flowchart showing a third example of the processing procedure by the control device 120 according to the embodiment.

First, the acquisition unit 121 acquires the measured value of the rotational torque during the measurement period by the screw 112, which is measured by the measuring device 130 (step S601).

Next, the estimation unit 122 transmits the data group of the measured values of the rotational torque during the measurement period by the screw 112 in the normal state (however, the data group corresponding to the material of the resin 140 currently in use) from the storage unit 125 as teacher data. (Step S602).

Then, the estimation unit 122 uses AI to determine the characteristics (for example, inclination, period, amplitude, etc.) of the output waveform based on the measured value of the rotational torque in the measurement period by the screw 112 acquired in step S601 in step S602. The molten state of the resin 140 is evaluated by comparing with the read-out teacher data (step S603).

Subsequently, the estimation unit 122 determines whether or not the evaluation result in step S603 is “good” (step S604).

If it is determined to be "good" in step S604 (step S604: Yes), the control unit 124 continues the operation of the injection molding unit 110 without changing the operation setting of the injection molding unit 110 (step S604). S605). Then, the control device 120 ends a series of processes shown in FIG.

On the other hand, if it is determined in step S604 that it is not "good" (step S604: No), the control device 120 performs a predetermined abnormality processing (step S606). Then, the control device 120 ends a series of processes shown in FIG.

As described above, the control device 120 according to the embodiment estimates the viscosity of the resin 140 in the molten state in the cylinder 111 based on the output waveform of the measured value of the rotational torque during the measurement period by the screw 112. The unit 122 is provided.

As a result, the control device 120 according to the embodiment can take measures such as changing the viscosity of the resin 140 to be appropriate according to the estimated viscosity of the resin 140. Therefore, according to the control device 120 according to the embodiment, it is possible to suppress defects in the molded product formed by injection molding.

Further, in the control device 120 according to one embodiment, the estimation unit 122 analyzes the output waveform of the measured value of the rotational torque during the measurement period by the screw 112 by statistical processing using the MT method, thereby performing the inside of the cylinder 111. The viscosity of the molten resin 140 can be estimated.

As a result, the control device 120 according to the embodiment estimates the viscosity of the resin 140 in the molten state in the cylinder 111 with high accuracy based on the latest measurement data and the past measurement data (unit space). be able to.

Further, in the control device 120 according to one embodiment, the estimation unit 122 uses AI to analyze the output waveform of the measured value of the rotational torque during the measurement period by the screw 112, so that the estimation unit 122 is in a molten state in the cylinder 111. The viscosity of the resin 140 can be estimated.

As a result, the control device 120 according to the embodiment estimates the viscosity of the resin 140 in the molten state in the cylinder 111 with high accuracy based on the latest measurement data and the past measurement data (teacher data). be able to.

Further, the control device 120 according to the embodiment further includes a changing unit 123 for changing the operation setting of the injection molding machine 100 when the viscosity of the resin 140 estimated by the estimating unit 122 is out of a predetermined allowable range. ..

As a result, the control device 120 according to the embodiment can autonomously change the operation setting of the injection molding machine 100 so as to suppress defects in the molded product formed by injection molding.

Further, the control device 120 according to the embodiment further includes a control unit 124 that stops the operation of the injection molding machine 100 when the viscosity of the resin 140 estimated by the estimation unit 122 is out of a predetermined allowable range.

As a result, the control device 120 according to the embodiment can automatically stop the operation of the injection molding machine 100 so as not to cause a defect in the molded product formed by injection molding.

Although one embodiment of the present invention has been described in detail above, the present invention is not limited to these embodiments, and various modifications or modifications are made within the scope of the gist of the present invention described in the claims. It can be changed.

For example, in one embodiment, the viscosity of the resin 140 is estimated by statistical processing by the MT method, but the viscosity is not limited to this, and the viscosity of the resin 140 may be estimated by using statistical processing by another method. ..

100 Injection molding machine 110 Injection molding unit 111 Cylinder 112 Screw 113 Heater 114 Hopper 115 Drive device 120 Control device 121 Acquisition unit 122 Estimate unit 123 Change unit 124 Control unit 125 Storage unit 130 Measuring device 140 Resin

Claims (8)

A control device that controls the operation of an in-line screw type injection molding machine equipped with a cylinder and a screw.
A control device including an estimation unit that estimates the viscosity of the resin in a molten state in the cylinder based on the output waveform of the measured value of the rotational torque during the measurement period by the screw. The estimation unit
The control device according to claim 1, wherein the viscosity is estimated by analyzing the output waveform by a predetermined statistical process. The estimation unit
The control device according to claim 2, wherein the viscosity is estimated by analyzing the output waveform by the statistical processing by the MT (Mahalanobis Taguchi) method. The estimation unit
The control device according to claim 1, wherein the viscosity is estimated by analyzing the output waveform using AI (Artificial Intelligence). Any one of claims 1 to 4, further comprising a changing part for changing the operation setting of the injection molding machine when the viscosity estimated by the estimating part is out of a predetermined allowable range. The control device described in. The invention according to any one of claims 1 to 5, further comprising a control unit for stopping the operation of the injection molding machine when the viscosity estimated by the estimation unit is out of a predetermined allowable range. The control device described. With the cylinder
With the screw
A measuring device that measures the rotational torque of the screw and
An injection molding machine comprising the control device according to any one of claims 1 to 6. A control method for controlling the operation of an in-line screw type injection molding machine equipped with a cylinder and a screw.
A control method comprising an estimation step of estimating the viscosity of the resin in a molten state in the cylinder based on the output waveform of the measured value of the rotational torque during the measurement period by the screw.

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