JPH0336016A - System for monitoring production by molder - Google Patents

Abstract

PURPOSE:To make it possible to easily discriminate good molding conditions from poor molding conditions and conforming molded item from non-conforming molded item by a method wherein a plurality of physical quantities concerning molding conditions are detected as molding condition data and successively compared with reference data for controlling conditions so as to control for obtaining favorable molding conditions and, in addition, with reference data for discriminating good and poor. CONSTITUTION:Predetermined physical quantities concerning molding conditions are detected by a plurality of data detecting means affixed to the predetermined locations of a molder 1, with which resin is molded by the predetermined molding method so as to obtain a molded item, and outputted as molding condition data. In a discriminating means of condition controlling data, respective molding condition data, which are inputted for a certain period of time from the respective data detecting means, are successively and one by one compared with respective pre-set reference data for controlling conditions and condition controlling signals for controlling the physical quantities of the molder so as to obtain respective favorable molding conditions on the basis of respective comparison results are outputted. In a discriminating means of good and poor data, molding condition data, which are inputted for a certain period of time from the respective data detecting means, are successively and one by one compared with respective pre-set reference data for discriminating good and poor data and, by synthetically judging respective comparison results, conforming molded items are discriminated from non-conforming molded items.

Description

[Detailed Description of the Invention] [Field of Industrial Application] The present invention is a molding machine that manufactures molded products by molding resin using a predetermined molding method, and in particular monitors molding condition data to improve the molding conditions. The present invention relates to a molding machine production monitoring system that can control and easily determine whether a molded product is good or bad.

[Conventional technology]

Conventionally, molding machines that employ various molding methods have been used to mold resin to produce molded products. For example, an injection molding machine that uses the injection molding method, a blow molding machine that uses the blow molding method, an injection blow molding machine that uses the injection blow molding method, a vacuum forming machine that uses the vacuum forming method,
Powder molding machines that employ a powder molding method, stretch blow molding machines that employ a stretch blow molding method, and the like have been used. Among these, recently, stretch blow molding machines have been particularly widely adopted because molded products with excellent transparency, rigidity, and impact resistance and low moisture permeability can be obtained. This stretch blow molding machine is
For example, in blow molding of polypropylene or PET, a parison is stretched in the axial direction at an appropriate temperature and then blow molded to obtain a molded product such as a transparent bottle. , devices have been developed that perform shaping after stretching with appropriate auxiliary tools.

[GIm to be Solved by the Invention] By the way, in such a molding machine, the shape including the wall thickness of the molded product obtained by molding is considerably influenced by the molding conditions during molding. For this reason, it is necessary to monitor the data regarding the molding conditions, monitor the molding conditions, and take measures to control the molding conditions in the event of unfavorable conditions, but this type of equipment has not yet been developed. The reality is that there is not. Conventionally, the setting value is 7f as the molding condition that can achieve $1li21+
However, it is not possible to determine to what extent it is actually controlled. Moreover, whether a molded product is a good product or a defective product is determined by simple measurement on the molding line or measurement by sampling.

However, although the former method allows for 100% measurement, there are only a few check items, and the latter method has many check items and, although it can achieve high measurement accuracy, it is not possible to perform a 100% check. If the value is high, it is difficult to distinguish between good and defective products.

The present invention was made to solve the above-mentioned problems, and it is possible to monitor molding condition data, control molding conditions well, and easily determine whether a molded product is good or bad. The purpose is to provide a molding machine production monitoring system.

[Means for Solving the Problems] In order to achieve the above-mentioned object, in the present invention, a molding machine is installed at a predetermined part of a molding machine for molding resin by a predetermined molding method to obtain a molded product, and the A plurality of data detection means detect predetermined physical quantities and output them as molding condition data, input molding condition data for a certain period of time from each data detection means, and input the respective data to each preset condition flA. a condition control data determining means for sequentially comparing with reference data for 's, and outputting a condition control signal for controlling physical quantities of the molding machine so that favorable molding conditions can be obtained respectively based on the individual comparison results; , inputs molding condition data for a certain period of time from each data detection means, sequentially compares the individual data with each preset standard data for determining good/bad, and synthesizes the individual comparison results. and a pass/fail data discrimination means for determining whether the molded product is good or bad by making a judgment based on the quality of the molded product.

[Function] Therefore, in the molding machine production monitoring system of the present invention,
When a molding machine performs molding, a plurality of physical quantities related to molding conditions that may affect the shape of a molded product are detected as molding condition data. Then, each molding condition data for a certain period of time is sequentially compared with each condition control reference data, and if it is determined that the data is not good, appropriate molding conditions are set so that good molding conditions can be obtained. The physical quantities lvJga are dynamically adjusted to control the molding conditions. In addition, each molding condition data for a certain period of time is sequentially compared with each standard data for determining good/bad, and the individual comparison results are comprehensively realized to determine whether the molded product is good or bad. Ru.

[Example] Hereinafter, an example of the present invention will be described with reference to the drawings.

FIG. 1 is a diagram showing an example of the overall configuration when a molding machine production monitoring system according to the present invention is applied to a stretched PET molding machine. In FIG. 1, a stretched PET molding machine 1 includes a blow mold 2, a temperature control section 3, an injection mold (or preform mold) 4, a discharge section 5, a rotor 6, and an injection cylinder 7. , a hopper 8, an injection control unit 9, and a temperature control unit 10.

On the other hand, the molding machine production monitoring system includes a plurality of (five in the figure) sensors 11 to 15 serving as data detection means, a production monitoring device main body 16, and an air exhaust machine 17. Here, each of the sensors 11 to 15 detects a predetermined physical quantity related to molding conditions that may affect the shape of the molded product, including the wall thickness, and outputs this as molding condition data. That is, the sensor (consisting of a blow pressure sensor) 11 is attached to the blow mold 2 of the stretched PET molding machine 1, detects the blow pressure, and outputs blow pressure data. A sensor (consisting of a temperature sensor) 12 is attached to the temperature control section 3 of the stretched PET molding machine 1, and detects the heater temperature and outputs heater temperature data. A sensor (consisting of a temperature sensor) 13 is attached to the injection mold 4 of the stretched PET molding machine 1 to detect the mold temperature and output mold temperature data. A sensor (consisting of an injection pressure sensor) 14 is attached to the injection cylinder 7 of the stretched PET molding tool 1, detects the injection pressure, and outputs injection pressure data. The sensor (consisting of a temperature sensor) 15 is connected to the hopper 8 of the stretched PET molding machine 1.
It is attached to the hopper, detects the hopper temperature, and outputs hopper temperature data. In addition, air exhaust machine 1
7 is for discharging defective molded products from the molding line by air pressure.

Furthermore, the production monitoring device main body 16, as shown in FIG. 2 as an example of its configuration, includes an input/output interface section 16A, a data input processing section 16B, a data analysis processing section 16C, an external storage device 16D, a display 16E, printer 16
It consists of F.

Here, the input/output interface section 16A is made of stretched PET.
It provides a data input/output interface between the molding machine 1 side and the production monitoring device main body 16 side. The data input processing unit 16B also receives analog waveform data (actually 1/1
00 seconds of digital data) for a certain period of time,
This data is processed using a moving average method or the like.

Furthermore, the data analysis processing unit 16C includes a CPU that performs analysis processing of molding condition data, a program memory that stores the following program, and a data memory that stores reference data for condition $IJIil and standard data for determining good/defective. It consists of

(a) Input molding condition data for a certain period of time from the data input processing section 16B, sequentially compare each piece of data with each condition control reference data stored in advance in the data memory, and compare the individual pieces of data sequentially with each condition control reference data stored in advance in the data memory. Stretch PET molding machine 1 to obtain good molding conditions based on the results.
A condition control data discrimination program that outputs condition control signals to control physical quantities.

(b) Input molding condition data for a certain period of time from the data input processing section 16B, sequentially compare each piece of data with each standard data for good/bad judgment stored in the data memory in advance, and A good/bad data discrimination program that comprehensively evaluates the comparison results and determines whether a molded product is good or bad.

(c) A defective product discharge processing program that outputs a discharge control signal to the air discharge machine 17 for discharging the defective molded product from the molding line when the molded product is determined to be defective according to (b) above.

(d) An update data filing program that files the latest molding condition data for a certain period of time in the external storage device 16D.

(e) When a molded product is determined to be defective in accordance with (b) above, a storage request data filing program that files molding condition data for a certain period of time before that in the external storage device 16D.

(f) A failure cause analysis program that analyzes the progress of molding conditions when a product is determined to be defective in accordance with (e) above.

(g) Molding condition data from the data manual processing section 16B and processing results from the data analysis processing section 16C, etc.
A display processing program that displays output on the display 16E.

(h) Forming condition data from the i-data manual processing section 16B and processing results from the data analysis processing section 16C, etc.
A print processing program that causes the printer 16F to print.

On the other hand, the external storage device 16D stores molding condition data. Further, the display 16E displays molding condition data from the data input processing section 16B, processing results from the data analysis processing section 16C, and the like. Further, the printer 16F prints the molding condition data from the data input processing section 16B and the processing results from the data analysis processing section 16C.

Next, the operation of the molding machine production monitoring system configured as above will be explained using FIGS. 3 and 4.

In FIGS. 1 and 2, each sensor 11 to 15 measures a predetermined physical quantity related to the molding conditions, that is, the sensor 11 measures the blow pressure of the blow mold 2 of the stretched PET molding machine 1, and the sensor 12 measures the temperature of the stretched PET molding machine 1. The temperature of the heater in the control section 3 is determined by the sensor 13, the mold temperature of the injection mold 4 of the stretched PET molding machine 1 is determined by the sensor 14, the injection pressure of the injection cylinder 7 of the stretched PET molding machine 1 is determined by the sensor 14, and the temperature of the stretched PET molding machine 1 is determined by the sensor 15. The temperatures of the hoppers 8 are detected, and the detected data, such as blow pressure data, heater temperature data, mold temperature data, injection pressure data, and hopper temperature data, are input to the production monitoring device main body 16 as molding condition data.

On the other hand, in the production monitoring device main body 16, the above-mentioned molding condition data is inputted to the data manual processing section 16B through the human output interface section 16A.

Then, in the data input processing section 16B, the analog waveform data, which is the molding condition data, is input for a certain period of time as shown in FIG. 4(a), and the data is processed by the moving average method etc. as shown in FIG. The molding process is as follows. In other words, the reason for converting digital data to analog waveform data here is that since molding conditions change over time, their basic values also change over time, so it is useless to simply compare instantaneous values. This is because analog waveform data is effective for comparison with standard data that has certain rules. The molding condition data subjected to the molding process is input to the data analysis processing section 16C, and analyzed by the CPU according to the program stored in the program memory. That is, first, the molding condition data for a certain period of time from the data input processing section 16B are sequentially compared with respective condition control reference data stored in advance in the data memory. In this case, the reference data for condition control consists of an upper limit value and a lower limit value as shown in Fig. 4(c), and it is determined whether the molding condition data is within the range of the corresponding upper limit value and lower limit value or not. are compared sequentially. As a result, if the molding condition data is not within the range between the upper limit and the lower limit, condition control signals are output for controlling the physical quantities of the stretched PET molding machine 1 so as to obtain good molding conditions. For example, the heater temperature of the temperature control section 3 of the stretched PET molding machine 1 is
When it is not within the range of the upper and lower limits, a condition control signal is output to control the heater temperature of the temperature control section 3 of the stretched PET molding Fa1 so that the heater temperature is within the range of the upper and lower limits. be done. In addition, when the blow pressure of the blow mold 2 of the stretched PET molding machine 1 is not within the range of the upper limit value and the lower limit value, the stretched PET molding machine 1 A condition control signal for controlling the blow pressure of the blow mold 2 is output.

This condition control signal is then sent to the input/output interface section 1.
6A to the corresponding control unit and the stretching P
The physical quantities of the ET molding machine 1 will be controlled.

Next, the molding condition data for a certain period of time from the data input processing section 16B is sequentially compared with each standard data for determining good/bad, which is stored in advance in the data memory. In this case, the standard data for good/bad discrimination also consists of an upper limit value and a lower limit value as described above, and each piece of data is sequentially compared to see if the molding condition data is within the range of the corresponding upper limit value and lower limit value. Ru. The comparison results of the individual data are then comprehensively determined to determine whether the molded product is good or defective. For example, even if blow pressure data, mold temperature data, injection pressure data, and hopper temperature data are all within the range of the upper and lower limits, if the heater temperature data is not within the range of the upper and lower limits. , the molded product is determined to be defective.
. When the molded product is determined to be defective, a discharge control signal for discharging the defective molded product from the molding line is given to the air discharge machine 17 through the human output interface section 16A, and the defective molded product is removed from the molding line. The product will be discharged from the molding line.

Furthermore, when a molded product is determined to be defective, the molding condition data for a certain period of time before that is filed in the external storage device 16D (data storage request), and the molding conditions data at the time when the molded product was determined to be defective are filed in the external storage device 16D. The process is analyzed (in order to develop software that automatically distinguishes between good and defective products and automatically controls molding conditions, it is necessary to clarify the causal relationship between the occurrence of defective products and molding conditions. Improvements in software also require a more severe causal relationship.The pursuit of this causal relationship is referred to here as analysis.) The results of the above processing by the data analysis processing section 16C are output and displayed on the display 16E, and are also printed out by the printer 16F.

In the above, in the production monitoring device main body 16, the latest molding condition data for a certain period of time is filed in the external storage device 16D (filing is to save the molding condition data, but the capacity of the storage device is limited. Because there are
It is necessary to delete the oldest data and write the latest data)
. Further, the molding condition data from the data input processing section 16B is output and displayed on the display 16E, and is also printed out by the printer 16F.

As described above, the stretched PET hollow molding production monitoring system of this embodiment can provide the following various effects.

(a) The difference between whether a molded product is good or defective is due to the difference in molding conditions, but in this example, the molding conditions are determined and whether the molded product is good or defective is determined. This makes it possible to automatically check all products on the molding line for highly accurate discrimination.

(b) In the past, it was difficult to control the molding conditions 24 hours a day, even if it was done by an experienced person.
In this embodiment, it is possible to control molding conditions well while checking non-control data on a second-by-second basis.

(c) When controlling the molding conditions in a stretched PET molding machine, it is necessary to control while estimating the actual conditions, which requires skill, but in this example, the actual molding conditions are monitored as digital data. Therefore, no skill in guessing is required.

In the above embodiments, the present invention was applied to a stretched PET molding machine, but the present invention is not limited to this and can be similarly applied to other molding machines.

In addition, in the above example, a case is described in which blow pressure, heater temperature, mold temperature, injection pressure, and hopper temperature are detected as predetermined physical quantities related to molding conditions that may affect the shape of the molded product, including the wall thickness. However, the molding conditions are not limited to these, and include, for example, the following conditions.

(a) Injection molding conditions: injection pressure, injection timing, mold temperature, etc.

(b) Temperature control conditions: heater temperature, oil temperature, preform temperature, etc.

(C) Blow conditions: blow pressure, blow timing, etc.

(d) Other conditions: hopper temperature (resin temperature), air temperature (room temperature), etc.

Furthermore, in the above embodiments, the program functions (d) to (h) are not necessarily essential to the present invention.

[Effects of the Invention] As explained above, according to the present invention, molding condition data can be monitored to satisfactorily control molding conditions, and
A molding machine production monitoring system that can easily determine whether a molded product is good or bad can be provided.

[Brief explanation of drawings]

FIG. 1 shows an extension of the molding machine production monitoring system according to the present invention.
FIG. 2 is a block diagram showing an example of the configuration of the production monitoring device main body in this embodiment, and FIG. 3 is a block diagram showing an example of the structure of the production monitoring device in the same embodiment. The flowchart, FIG. 4, is a diagram for explaining the operation in the same embodiment. 1... Stretched PET molding machine, 2... Blow mold, 3...
... Warm W#, 4... Injection mold (or preform mold), 5... Discharge section, 6... Rotor 7... Injection cylinder 8... Hopper 9... Injection control Unit, 10...Temperature control unit, 11-15...
・Sensor 16...Production monitoring device body, 16A...
- Human output interface section, 16B...Data human processing section, 16C...Data analysis processing section, 160...External storage device! , 16E...Display, 16F...
・Printer 17...Air discharge machine.

Claims (3)

[Claims] (1) In a production monitoring system for a molding machine that molds resin to obtain a molded product using a predetermined molding method, the system is installed at a predetermined part of the molding machine and detects predetermined physical quantities related to molding conditions to obtain molding condition data. inputting molding condition data for a certain period of time from each of the data detection means and sequentially comparing the individual data with preset reference data for each condition control; and condition control data determining means for outputting condition control signals for controlling the physical quantities of the molding machine so that good molding conditions can be obtained based on the respective comparison results; Input molding condition data for a certain period of time, sequentially compare the individual data with each preset standard data for determining good/bad, and comprehensively judge the individual comparison results to determine the quality of the molded product. A molding machine production monitoring system comprising: a good/bad data discrimination means for determining good or bad data; and a molding machine production monitoring system. (2) In the molding machine production monitoring system according to claim (1), when the defective molded product is determined to be defective by the good/defective data determining means, the defective product discharge is performed to discharge the defective molded product from the molding line. A molding machine production monitoring system characterized by comprising an additional means. (3) A stretch molding machine is used as the molding machine, and injection pressure, blow pressure, heater temperature, etc. are detected as predetermined physical quantities related to molding conditions. The molding machine production monitoring system described in item 2).