Quality estimation method, quality estimation device, and computer program

Abstract

According to the present invention: time-series physical quantity data related to the operation of an injection molding machine is acquired, the physical quantity data being obtainable in an injection molding step of a molded article by using the injection molding machine; the acquired physical quantity data is stored in a storage unit for each shot; quality data indicating the quality of the molded article obtained by injection molding when the acquired physical quantity data is acquired is stored in association with the physical quantity data; the quality of the molded article is calculated on the basis of physical quantity data acquired during estimation of the quality of the molded article and the stored physical quantity data and quality data in the storage unit; and prescribed processing is executed when the quality of the molded article becomes lower than prescribed quality.

Description

Quality estimation method, quality estimation device, and computer program

[0001] The present invention relates to a quality estimation method, a quality estimation device, and a computer program.

[0002] Patent Document 1, for example, discloses an injection molding machine that monitors the state of resin in an injection cylinder, detects the energy consumed for plasticizing the resin, and estimates the state of the resin in the injection cylinder based on the energy consumption to determine molding quality. Specifically, the injection molding machine compares the detected energy consumption with a reference amount of power, which is a standard amount of power consumed to produce a molded product of appropriate quality, and if the difference is equal to or greater than a predetermined value, determines that there is a problem with the quality of the molded product.

[0003] JP 2012-091424 A

[0004] However, in Patent Document 1, what is monitored to estimate the quality of the molded product is the upper and lower limit values ​​of the energy consumption, but the trend of these limits is not monitored. Although changes due to quality abnormalities of the molded product may appear in the trend of the monitored values, these changes cannot be captured, and therefore the quality abnormalities of the molded product may not be detected.

[0005] An object of the present disclosure is to provide a quality estimation method, a quality estimation device, and a computer program that can estimate the quality of a molded product by capturing the transition of time-series physical quantity data related to the operation of an injection molding machine.

[0006] A quality estimation method according to one aspect of the present disclosure acquires time-series physical quantity data relating to the operation of an injection molding machine, which is obtained during an injection molding process of a molded product using the injection molding machine, stores the acquired physical quantity data for each shot in a memory unit, associates quality data indicating the quality of the injection-molded molded product at the time the acquired physical quantity data was obtained with the physical quantity data and stores the quality data, calculates the quality of the molded product based on the physical quantity data acquired during quality estimation of the molded product and the physical quantity data and quality data stored in the memory unit, and executes a predetermined process if the quality of the molded product falls below a predetermined quality.

[0007] A quality estimation device according to one aspect of the present disclosure is a quality estimation device including a processing unit, wherein the processing unit acquires time-series physical quantity data relating to the operation of an injection molding machine obtained during an injection molding process of a molded product using the injection molding machine, stores the acquired physical quantity data for each shot in a memory unit, associates quality data indicating the quality of the injection-molded molded product at the time the acquired physical quantity data was obtained with the physical quantity data and stores it, calculates the quality of the molded product based on the physical quantity data acquired during quality estimation of the molded product and the physical quantity data and quality data stored in the memory unit, and executes a predetermined process if the quality of the molded product falls below a predetermined quality.

[0008] A computer program according to one aspect of the present disclosure acquires time-series physical quantity data relating to the operation of an injection molding machine, which is obtained during an injection molding process of a molded product using the injection molding machine; stores the acquired physical quantity data for each shot in a memory unit; stores quality data indicating the quality of the injection-molded molded product when the acquired physical quantity data is obtained in association with the physical quantity data; calculates the quality of the molded product based on the physical quantity data acquired during quality estimation of the molded product and the physical quantity data and quality data stored in the memory unit; and causes a computer to execute a process to execute a predetermined process if the quality of the molded product falls below a predetermined quality.

[0009] According to the present disclosure, it is possible to provide a quality estimation method, a quality estimation device, and a computer program that can estimate the quality of a molded product by capturing the transition of time-series physical quantity data related to the operation of an injection molding machine.

[0010] FIG. 1 is a schematic diagram showing an example of the configuration of an injection molding system according to embodiment 1. FIG. 2 is a flowchart showing a reference data collection process procedure according to embodiment 1. FIG. 3 is a flowchart showing a data collection process procedure according to embodiment 1. FIG. 4 is a conceptual diagram showing a data collection method according to embodiment 1. FIG. 5 is a conceptual diagram showing the contents of a file saved by the data collection method according to embodiment 1. FIG. 6 is a diagram showing an example of logging data items. FIG. 7 is a diagram showing an example of logging data items. FIG. 8 is a flowchart showing a quality estimation process procedure according to embodiment 1. FIG. 9 is a flowchart showing a quality estimation process procedure according to embodiment 2.

[0011] A quality estimation method, a quality estimation device, and a computer program according to embodiments of the present disclosure will be described below with reference to the drawings. Note that the present disclosure is not limited to these examples, but is defined by the claims, and is intended to include all modifications within the meaning and scope equivalent to the claims. Furthermore, at least some of the embodiments described below may be combined in any desired manner.

[0012] 1 is a schematic diagram showing an example of the configuration of an injection molding system according to embodiment 1. The injection molding system according to embodiment 1 includes an injection molding machine 1, a logging device 6, and an information processing device (quality estimation device) 7.

[0013] <Injection Molding Machine 1 > The injection molding machine 1 includes a mold clamping device 2 that clamps a mold 21 , an injection device 3 that melts and injects molding material, a plurality of sensors 4 , and a control device 5 .

[0014] The mold clamping unit 2 includes a fixed platen 22 fixed on a bed 20, a mold clamping housing 23 slidably mounted on the bed 20, and a movable platen 24 that also slides on the bed 20. The fixed platen 22 and the mold clamping housing 23 are connected by a plurality of tie bars 25, for example, four tie bars 25. The movable platen 24 is slidably configured between the fixed platen 22 and the mold clamping housing 23. A mold clamping mechanism 26 is provided between the mold clamping housing 23 and the movable platen 24. The mold clamping mechanism 26 is configured, for example, by a toggle mechanism. Note that the mold clamping mechanism 26 may also be a direct pressure type mold clamping mechanism, i.e., a mold clamping cylinder. The fixed platen 22 and the movable platen 24 are provided with a fixed mold 28 and a movable mold 27, respectively, and the mold 21 is opened and closed by driving the mold clamping mechanism 26. The mold clamping unit 2 also includes an ejector pin for removing a molded product from the mold 21 and a drive motor for driving the ejector pin.

[0015] The injection device 3 is provided on a base 30. The injection device 3 includes a heating cylinder 31 having a nozzle 31a at its tip, and a screw 32 disposed within the heating cylinder 31 so as to be rotatable in the circumferential and axial directions. A heater for melting the molding material is provided inside or on the outer periphery of the heating cylinder 31. The screw 32 is driven in the rotational and axial directions by a drive device 35.

[0016] A hopper 33 into which molding material is poured is provided near the rear end of the heating cylinder 31. The injection molding machine 1 also includes a nozzle touch device 34 that moves the injection unit 3 in the front-to-rear direction (the left-to-right direction in FIG. 1 ). When the nozzle touch device 34 is driven, the injection unit 3 moves forward so that the nozzle 31 a of the heating cylinder 31 touches the contact portion of the fixed platen 22.

[0017] The multiple sensors 4 are elements and circuits that detect physical quantities related to the quality of the molded product. In other words, the multiple sensors 4 are elements and circuits that detect time-series physical quantities related to the operation of the injection molding machine 1, which are obtained during the injection molding process of the molded product using the injection molding machine 1.

[0018] The sensors 4 include sensors that are provided in the injection molding machine 1 as sensors necessary for controlling the operation of the injection molding machine 1, and sensors that are separately provided to estimate the state of the injection molding machine 1. All or some of the multiple sensors 4 are connected to a logging device 6, and the sensors 4 output signals indicating detected physical quantities to the logging device 6. An information processing device 7, which will be described later, acquires physical quantity data from the sensors 4 via the logging device 6. The physical quantity data is time-series sensor value data indicating the detected physical quantities. Some of the multiple sensors 4 are also connected to a control device 5, and the information processing device 7 can acquire the physical quantity data from the sensors 4 via the control device 5.

[0019] Physical quantities include temperature, position, speed, acceleration, current, voltage, pressure, time, image data, torque, force, strain, power consumption, weight, etc. These physical quantities can be measured using a thermometer, position sensor, speed sensor, acceleration sensor, ammeter, voltmeter, pressure gauge, timer, camera, torque sensor, wattmeter, weight scale, etc.

[0020] The multiple sensors 4 include, for example, a speed sensor that detects the speed of the screw 32, a speed sensor that detects the speed of the movable platen 24, and a speed sensor that detects the speed of the ejector pin. The multiple sensors 4 include, for example, a torque sensor that detects the torque of the motor that drives the screw 32, a torque sensor that detects the torque of the motor that drives the movable platen 24, and a torque sensor that detects the torque of the motor that drives the ejector pin. The multiple sensors 4 include, for example, a pressure sensor that detects the pressure inside the screw 32 or the heating cylinder 31, and a pressure sensor that detects the pressure applied to the mold 21. The multiple sensors 4 include, for example, a load cell that detects the pressure applied to the screw 32 in the longitudinal direction. The multiple sensors 4 include, for example, a position sensor that detects the position of the screw 32, a position sensor that detects the position of the movable platen 24, and a position sensor that detects the position of the ejector pin. The multiple sensors 4 include, for example, a rotational speed sensor that detects the rotational speed of the motor that drives the screw 32, a rotational speed sensor that detects the rotational speed of the motor that drives the movable platen 24, and a rotational speed sensor that detects the rotational speed of the motor that drives the ejector pin. The multiple sensors 4 include a load sensor that detects the clamping force applied by the clamping device 2. The multiple sensors 4 include a temperature sensor that detects the temperature of the hopper 33, a temperature sensor that detects the temperature at one or more locations on the heating cylinder 31, and a temperature sensor that detects the temperature at one or more locations on the nozzle 31 a.

[0021] The sensor 4 also includes any other detector capable of detecting a physical quantity that contributes to estimating the quality of the molded product.

[0022] The control device 5 is a computer that controls the operation of the injection molding machine 1. Molding conditions for operating the injection molding machine 1 are set in the control device 5. The control device 5 outputs command signals to the injection molding machine 1 based on various set values ​​indicated by the molding conditions and the detected values ​​of the sensor 4, and operates the injection molding machine 1.

[0023] The control device 5 also includes a communication unit and an operation panel (not shown) for transmitting and receiving information to and from the information processing device 7. Specifically, the control device 5 transmits data related to the molding conditions set in the injection molding machine 1 to the information processing device 7. The data related to the molding conditions is, for example, the name of the molding conditions for identifying the molding conditions set in the injection molding machine 1. The data related to the molding conditions may be the content of the molding conditions themselves. The data related to the molding conditions is not particularly limited as long as it reflects the content of the molding conditions. Furthermore, the control device 5 outputs a signal related to a command value based on the molding conditions to the logging device 6 during the injection molding process.

[0024] Furthermore, the control device 5 receives an estimation result regarding the quality of the molded product transmitted from the information processing device 7, and displays the received estimation result. The control device 5 also outputs an alert in accordance with the estimation result of the quality of the molded product. The control device 5 also receives information transmitted from the information processing device 7 indicating how to change the setting values ​​related to the molding conditions, and displays the method for changing the setting values.

[0025] The logging device 6 is, for example, a programmable logic controller (PLC). The logging device 6 samples analog signals output from the multiple sensors 4 at predetermined intervals, performs AD conversion, and stores the results in its internal memory as physical quantity data indicating time-series physical quantities. The logging device 6 also samples command value signals output from the control device 5 at predetermined intervals, performs AD conversion, and stores the results in its internal memory as time-series command value data. For example, the logging device 6 stores the physical quantity data and command value data as a CSV file. The logging device 6 transfers the logged physical quantity data and command value data files to the information processing device 7 for each injection molding cycle. The physical quantity data is data related to the operation of the injection molding machine 1 and the quality of the molded product, obtained during the injection molding process using the injection molding machine 1.

[0026] <Information Processing Device 7> The information processing device 7 is a computer that estimates the quality or degree of defect of a molded product manufactured by the injection molding machine 1. Furthermore, when the quality of the molded product falls below a predetermined quality level, the information processing device 7 issues an alert and executes a process of suggesting how to change the set values ​​of the molding conditions. When the quality of the molded product falls below a predetermined quality level, the information processing device 7 executes a process of issuing an alarm and suggesting changes to the set values ​​of the molding conditions. The information processing device 7 includes, as its hardware configuration, a processing unit 71, a storage unit 72, an operation unit 73, an acquisition unit 74, and a display unit 75. The information processing device 7 may be a server device connected to a network. Furthermore, the information processing device 7 may be configured to perform distributed processing using multiple computers, may be implemented by multiple virtual machines installed on a single server, or may be implemented using a cloud server.

[0027] The processing unit 71 is a processor having arithmetic circuits such as a CPU (Central Processing Unit), a multi-core CPU, a GPU (Graphics Processing Unit), a GPGPU (General-purpose computing on graphics processing units), a TPU (Tensor Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), and an NPU (Neural Processing Unit), internal storage devices such as a ROM (Read Only Memory) and a RAM (Random Access Memory), an I / O terminal, a timer, etc. The processing unit 71 implements the quality estimation method according to the first embodiment by executing a computer program (program product) 72a stored in a storage unit 72 (described later). Note that each functional unit of the information processing device 7 may be realized by software, or part or all of it may be realized by hardware.

[0028] The storage unit 72 is a non-volatile memory such as a hard disk, an EEPROM (Electrically Erasable Programmable ROM), or a flash memory. The storage unit 72 stores a computer program 72a for causing a computer to execute processes such as estimating the quality of a molded product. The storage unit 72 also stores time-series physical quantity data obtained from the injection molding machine 1 for each shot. The storage unit 72 stores a folder (hereinafter referred to as the temporary storage folder 72b) for temporarily storing files of physical quantity data acquired for each shot via the logging device 6, and a folder (hereinafter referred to as the sorting folder 72c) for sorting the temporarily stored files according to molding conditions and data collection periods.

[0029] The computer program 72a according to the first embodiment may be recorded on a recording medium 8 in a computer-readable manner. The storage unit 72 stores the computer program 72a read from the recording medium 8 by a reading device. The recording medium 8 is a semiconductor memory such as a flash memory. The recording medium 8 may also be an optical disc such as a CD (Compact Disc)-ROM, a DVD (Digital Versatile Disc)-ROM, or a BD (Blu-ray (registered trademark) Disc). The recording medium 8 may also be a magnetic disc such as a flexible disk or a hard disk, a magneto-optical disc, or the like. Furthermore, the computer program 72a according to the first embodiment may be downloaded from an external server connected to a communication network and stored in the storage unit 72.

[0030] The operation unit 73 is an input device such as a touch panel, soft keys, hard keys, a keyboard, or a mouse.

[0031] The acquisition unit 74 is a communication circuit that acquires physical quantity data and command value data based on molding conditions output from the logging device 6. The acquisition unit 74 also communicates with the control device 5 to acquire data related to molding conditions and other data necessary for estimating the quality of the molded product.

[0032] The display unit 75 is a liquid crystal panel, an organic EL display, electronic paper, a plasma display, etc. The display unit 75 displays various information according to the image data provided from the processing unit 71.

[0033] 2 is a flowchart showing the reference data collection process procedure according to the first embodiment. The processing unit 71 of the information processing device 7 collects time-series physical quantity data and command value data relating to the operation of the injection molding machine 1, which are obtained by detection by the multiple sensors 4 during the injection molding process of a molded product using the injection molding machine 1 (step S111). The physical quantity data is information for estimating the quality of the molded product. The process of step S111 is repeatedly executed, and physical quantity data spanning multiple injection molding cycles is collected.

[0034] FIG. 3 is a flowchart showing the data collection processing procedure according to the first embodiment, FIG. 4 is a conceptual diagram showing the data collection method according to the first embodiment, FIG. 5 is a conceptual diagram showing the contents of a file saved by the data collection method according to the first embodiment, and FIGS. 6 and 7 are diagrams showing examples of logging data items.

[0035] When the injection molding machine 1 starts a molding process, the logging device 6 starts logging time-series physical quantity data and command value data obtained by detection by the sensors 4 (step S131). That is, the logging device 6 starts a process of saving signals indicating physical quantities output from the multiple sensors 4 as time-series physical quantity data. The specific content of the physical quantity data will be described later. The logging device 6 also starts a process of saving command value signals for operating the injection molding machine 1 as time-series command value data, along with the physical quantity data.

[0036] Next, the logging device 6 determines whether one injection molding cycle has been completed (step S132). If it is determined that one injection molding cycle has not been completed (step S132: NO), the logging device 6 continues logging the physical quantity data. If it is determined that one injection molding cycle has been completed (step S132: YES), the logging device 6 ends logging the physical quantity data and command value data (step S133).

[0037] Then, the logging device 6 transfers the time-series physical quantity data for one shot to the information processing device 7 (step S134).

[0038] The information processing device 7 receives the file of physical quantity data and command value data transferred from the logging device 6 and saves the file including the received physical quantity data and command value data in the temporary storage folder 72b (step S151). In detail, as shown in Fig. 4, when saving the file including the physical quantity data and command value data in the temporary storage folder 72b, the information processing device 7 starts saving the physical quantity data and command value data as a file with a first extension, and when saving of the physical quantity data and command value data is completed, changes the extension of the file stored in the temporary storage folder 72b from the first extension to a second extension. For example, the second extension is "csv," and the first extension is a name different from the second extension.

[0039] The file name of the file containing the time-series physical quantity data and command value data for one shot is not particularly limited, but it is preferable to include the shot number. The physical quantity data and command value data are saved in, for example, a CSV format, and the data items, as shown in Figure 5, include a serial number "No." indicating the logging point, the date of logging, the time of logging, the elapsed time from the previous logging point to the current logging point (unit: μseconds, for example), and various command values ​​and monitor values ​​(physical quantities) output from the control device 5 to the injection molding machine 1, which are associated with each other and recorded.

[0040] Examples of the various command values ​​and monitored physical quantities stored in the file include data such as those shown in Figures 6 and 7. The "Command / Monitor Items" in the left column indicate the command values ​​output to the injection molding machine 1 and the detected physical quantities. In each column, "Injection" and "Measurement" indicate command values ​​and monitored values ​​related to the operation of the screw 32, "Platen" indicates command values ​​and monitored values ​​related to the operation of the clamping unit 2, and "Eject" indicates the known position and monitored values ​​related to the operation of the ejector pin for removing the molded product from the mold 21. Checked items indicate that there are command values ​​or monitored values ​​to be recorded.

[0041] Next, the processing unit 71 of the information processing device 7 constantly monitors whether or not a file is stored in the temporary storage folder 72b, and determines whether or not a file with the second extension exists in the temporary storage folder 72b (step S152). If it is determined that a file with the second extension does not exist in the temporary storage folder (step S152: NO), the processing unit 71 continues to monitor the files stored in the temporary storage folder 72b.

[0042] If it is determined that a file with the second extension exists in the temporary storage folder (step S152: YES), the processing unit 71 acquires current molding condition data from the injection molding machine 1 (step S153). The molding condition data includes data indicating the molding conditions limited to the injection molding machine 1, the molding condition names assigned to the molding conditions, and other data expressing the molding conditions. The molding conditions set in the injection molding machine 1 vary depending on the molded product, and the content of the physical quantity data collected from the injection molding machine 1 also changes when the molding conditions vary. The information processing device 7 acquires the molding condition data in order to store the physical quantity data sorted by molding condition.

[0043] Next, the processing unit 71 determines whether a classification folder 72c has been created as a folder for saving the physical quantity data in the temporary storage folder 72b, the folder name of which includes a character string reflecting the molding conditions and the collection period of the physical quantity data (step S154).

[0044] If it is determined that the classification folder 72c has not been created (step S154: NO), the processing unit 71 creates a folder for saving the physical quantity data, the folder name of which includes a string reflecting the molding conditions and the collection period of the physical quantity data (step S155). For example, the folder name may be "Molding Condition Name / YYYY / MM / DD / Collection Start Time-Collection End Time." The "Molding Condition Name" is the name given to the molding conditions set in the injection molding machine 1. "YYYY," "MM," and "DD" indicate the year, month, and day on which the physical quantity data was collected. The "Collection Start Time" and "Collection End Time" indicate the times (start time and end time) when the physical quantity data to be saved in the folder was collected. The time interval between the collection start time and the collection end time is not particularly limited. The collection end time may be set, for example, as follows: In a first example, the processing unit 71 determines that the timing when the molding conditions are changed is the collection end time. In a second example, if 30 minutes or more have passed since the most recent shot, the processing unit 71 sets the point in time when 30 minutes have passed as the collection end time. In a third example, the processing unit 71 sets a predetermined collection period, such as 30 minutes. In the first and third examples, since the collection end time is not determined while collecting physical quantity data, it is advisable to use a pseudonym for the folder name. For example, the processing unit 71 may use a pseudonymous folder name of "current," or may leave only the collection end time blank. There are no particular limitations on how the pseudonym is assigned.

[0045] Although the example in which the molding condition name is included in the name of the classification folder 72c has been described, the name may also include characters that reflect the molding conditions set in the injection molding machine 1. For example, instead of the molding condition name, characters that represent the content of the molding conditions may be used. In short, it is sufficient if the molding conditions set in the injection molding machine 1 can be identified.

[0046] If it is determined in step S154 that the classification folder 72c has been created (step S154: YES), or after completing the processing of step S155, the processing unit 71 moves the files with the second extension saved in the temporary storage folder 72b to the classification folder 72c that corresponds to the molding conditions and data collection period (step S156), and ends the processing. In other words, the processing unit 71 moves and stores the physical quantity data obtained when injection molding is performed under the molding conditions included in the folder name of the classification folder 72c during the collection period included in the folder name of the classification folder 72c, for each shot. The processing of step S156 is an example of a process of storing the acquired physical quantity data for each shot in the storage unit 72 in association with the molding conditions set in the injection molding machine 1.

[0047] 2, the processing unit 71 acquires quality data indicating the quality of the molded product manufactured by the injection molding machine 1 (step S112). The method of acquiring the quality data is not particularly limited; an operator may visually judge the quality of the molded product and input the judgment result into the information processing device 7, or a computer may be configured to judge the quality of the molded product using a camera, a position sensor, a weight sensor, etc.

[0048] The processing unit 71 then stores quality data indicating the quality of the injection-molded product when the saved physical quantity data was obtained, in association with the file of the physical quantity data (step S113). For example, the processing unit 71 saves a quality data file in which the shot number and the quality data are associated in the classification folder 72c. Note that the method of associating each file saved in the classification folder 72c with the quality data is just an example, and the method of associating the data is not particularly limited. The quality data may be recorded in the file of the physical quantity data, or may be recorded as the properties or other attribute information of the file.

[0049] 8 is a flowchart showing the processing procedure for quality estimation according to embodiment 1. The processing unit 71 of the information processing device 7 collects time-series physical quantity data related to the operation of the injection molding machine 1, which is obtained by detection by the multiple sensors 4 during the injection molding process of a molded product using the injection molding machine 1 (step S171).

[0050] Then, the processing unit 71 reads out from the storage unit 72 reference data for non-defective products that are under the same molding conditions as when the collected physical quantity data was obtained (step S172). The non-defective reference data is physical quantity data, among the files stored in the classification folder 72c, whose quality indicated by the quality data is equal to or exceeds a specific standard indicating a non-defective product.

[0051] Next, the processing unit 71 compares the time-series waveforms indicated by the physical quantity data acquired during the quality estimation of the molded product with the time-series waveforms indicated by the read reference data, and calculates the difference between the time-series waveforms as the quality of the molded product (step S173). The difference is, for example, the square sum error of the time-series waveforms. More preferably, the processing unit 71 compares the time-series waveforms for a period in which the processes constituting the injection molding cycle are common. By referring to the molding conditions, the processing unit 71 can identify the time of each process constituting the injection molding process in one cycle. The processing unit 71 can extract the time-series waveforms corresponding to the identified time of each process from the time-series waveforms in one cycle. By comparing the time-series waveforms for the same process, the processing unit 71 can more accurately estimate the quality of the molded product.

[0052] Next, the processing unit 71 determines whether the calculated quality is below a predetermined quality (step S174). If it is determined that the quality of the molded product is below the predetermined quality (step S174: YES), it executes an alarm notification process (predetermined process) (step S175). That is, the processing unit 71 notifies the operator that the quality of the molded product has deteriorated by sound, lighting, or the like. The alert method is not particularly limited, and the processing unit 71 may send a signal notifying the alert to the control device 5. Alternatively, the processing unit 71 may be configured to send a signal notifying the alert to a terminal carried by the operator.

[0053] Next, the processing unit 71 identifies a method for changing the set values ​​of the molding conditions based on the physical quantity data acquired during the quality estimation and the physical quantity data stored in the storage unit 72 (step S176), and displays the identified method for changing the set values ​​on the display unit 75 (step S177). For example, it is preferable to compare the time-series waveform of the physical quantity data detected during the quality control with the time-series waveform of the reference data for each item of the detected physical quantities, identify physical quantities with large differences, and display on the display unit 75 or via the control device 5 that the physical quantities are larger or smaller than the reference data. Note that the processing unit 71 may be configured to transmit the method for changing the set values ​​of the molding conditions to the control device 5 and display it on the display of the control device 5.

[0054] The process shown in FIG. 8 is a process for estimating the quality of one molded product based on one shot's worth of physical quantity data. However, the processing unit 71 can repeatedly execute the process shown in FIG. 8 during the molding process, thereby monitoring the quality of molded products mass-produced through repeated injection molding cycles.

[0055] As described above, according to the injection molding system of the present embodiment 1, the physical quantity data obtained for each shot in the injection molding process can be stored in association with the molding conditions and the data collection period. By associating the physical quantity data with the molding conditions and the data collection period, it is possible to make the physical quantity data easier to utilize.

[0056] In addition, by creating a separate folder 72c with a folder name indicating a character string related to the molding conditions and the data collection period, and storing files of physical quantity data corresponding to the separate folder 72c, it becomes easier to search and refer to the physical quantity data that is the result of injection molding performed in the past, and it becomes easier to utilize the physical quantity data more efficiently.

[0057] For example, by comparing physical quantity data obtained during quality control with past physical quantity data collected under the same conditions and during a similar period, similar physical quantity data can be identified. If past physical quantity data is associated with the quality data of a molded product, the quality of the molded product can be estimated by comparing the physical quantity data.

[0058] Furthermore, the information processing device 7 of this embodiment 1 can more accurately identify similar physical quantity data and estimate the quality of the molded product by comparing time series waveforms of parts that are common to the processes that make up the injection molding cycle, among the time series waveforms indicated by the physical quantity data.

[0059] In addition, since the command values ​​are associated with the monitor values ​​and saved in a file, it is possible to identify a file when the molding conditions and physical quantity data were similar and the quality data was good, and based on the command values ​​at that time, it is also possible to estimate how to change the setting values ​​based on the current molding conditions.

[0060] Furthermore, by comparing the physical quantity data, if the quality of the molded product falls below a predetermined quality, an alert can be output to notify the operator of a molding abnormality.

[0061] Furthermore, when a file of logged physical quantity data is transferred to the information processing device 7 and saved in the temporary storage folder 72b, and then sorted into the classification folder 72c, changing the file extension allows the file to be reliably moved. Specifically, it is possible to determine whether or not the physical quantity data is being transferred based on the file extension, and after confirming that the file transfer has been completed, the file can be moved from the temporary storage folder 72b to the classification folder 72c.

[0062] In the first embodiment, an example has been described in which command value data is logged together with physical quantity data, but it is also possible to configure the system so that only physical quantity data is logged and saved to estimate the quality of the molded product.

[0063] (Embodiment 2) An injection molding system according to embodiment 2 differs from embodiment 1 in the quality estimation processing procedure. Other configurations of the injection molding system are similar to those of the injection molding system according to embodiment 1, so similar parts are denoted by the same reference numerals and detailed description thereof will be omitted.

[0064] Fig. 9 is a flowchart showing the processing procedure for quality estimation according to embodiment 2. The processing in steps S271 to S272 and steps S274 to S277 shown in Fig. 9 is similar to the processing in steps S171 to S172 and steps S174 to S177 in embodiment 1, and only the processing for quality estimation is different.

[0065] The processing unit 71 of the information processing device 7 according to the second embodiment determines the quality of the molded product by comparing the increase / decrease or periodic change in the feature quantity based on the physical quantity data acquired during the quality control collected in step S271 with the increase / decrease or periodic change in the feature quantity based on the reference data (step S273). For example, the processing unit 71 calculates the similarity of the increase / decrease or periodic change in the feature quantity as the quality of the molded product. The higher the similarity with the reference data for a non-defective product, the higher the quality of the molded product, and the lower the similarity, the lower the quality of the molded product.

[0066] According to the injection molding system of the second embodiment configured as described above, the quality of a molded product can be estimated by utilizing past physical quantity data, similar to the first embodiment.

[0067] Means for solving the problems of the present disclosure are appended below. (Supplementary Note 1) A quality estimation method comprising: acquiring time-series physical quantity data relating to the operation of an injection molding machine obtained during an injection molding process of a molded product using the injection molding machine; storing the acquired physical quantity data in a memory unit for each shot; storing quality data indicating the quality of the injection-molded molded product when the acquired physical quantity data is obtained in association with the physical quantity data; calculating the quality of the molded product based on the physical quantity data acquired during quality estimation and the physical quantity data and quality data stored in the memory unit; and executing a predetermined process if the quality of the molded product falls below a predetermined quality. (Supplementary Note 2) The quality estimation method according to Supplementary Note 1, wherein the quality of the molded product is calculated based on the difference between the time-series waveforms indicated by the physical quantity data acquired during quality estimation and the time-series waveforms indicated by the physical quantity data stored in the memory unit. (Supplementary Note 3) The quality estimation method according to Supplementary Note 1 or Supplementary Note 2, wherein the quality of the molded product is calculated based on the difference between the time-series waveforms indicated by multiple physical quantity data for which processes constituting an injection molding cycle are common. (Supplementary Note 4) The quality estimation method according to any one of Supplementary Notes 1 to 3, wherein the physical quantity data is stored in the storage unit in association with molding conditions set in the injection molding machine, and the quality of the molded product is calculated based on a difference in time-series waveforms indicated by a plurality of physical quantity data having common molding conditions. (Supplementary Note 5) The quality estimation method according to any one of Supplementary Notes 1 to 4, wherein a folder is created having a folder name including a character string reflecting the molding conditions set in the injection molding machine and a collection period for the physical quantity data, and physical quantity data obtained when injection molding is performed under the molding conditions included in the folder name during the collection period included in the folder name, is saved in the folder for each shot. (Supplementary Note 6) The quality estimation method according to any one of Supplementary Notes 1 to 5, wherein the physical quantity data is stored as a file in which the date and time of injection molding, time information for specifying the detection point of the physical quantity data, the acquired physical quantity data, and a command value related to the operation of the injection molding machine when the physical quantity data was acquired are associated with each other.(Supplementary Note 7) The quality estimation method according to any one of Supplementary Notes 1 to 6, wherein a method for changing set values ​​related to molding conditions is identified based on physical quantity data acquired during quality estimation and the physical quantity data stored in the storage unit. (Supplementary Note 8) The quality estimation method according to any one of Supplementary Notes 1 to 7, wherein the predetermined processing includes processing related to alarm notification. (Supplementary Note 9) The quality estimation method according to any one of Supplementary Notes 1 to 8, wherein the quality of the molded product is estimated by comparing an increase / decrease or periodic change in a feature calculated based on the physical quantity data acquired during quality estimation with an increase / decrease or periodic change in a feature calculated based on the physical quantity data stored in the storage unit.

[0068] DESCRIPTION OF SYMBOLS 1: Injection molding machine 2: Clamping device 3: Injection device 4: Sensor 5: Control device 6: Logging device 7: Information processing device 8: Recording medium 20: Bed 21: Mold 22: Fixed platen 23: Clamping housing 24: Movable platen 25: Tie bar 26: Clamping mechanism 27: Movable mold 28: Fixed mold 30: Base 31: Heating cylinder 31a: Nozzle 32: Screw 33: Hopper 34: Nozzle touch device 35: Drive device 71: Processing unit 72: Memory unit 72a: Computer program 72b: Temporary storage folder 72c: Sorting folder 73: Operation unit 74: Acquisition unit 75: Display unit

Claims

1. A quality estimation method comprising the steps of: acquiring time-series physical quantity data related to the operation of an injection molding machine obtained in an injection molding process of a molded product using the injection molding machine; storing the acquired physical quantity data in a memory unit for each shot; storing quality data indicating the quality of a molded product injection-molded at the time the acquired physical quantity data was obtained in association with the physical quantity data; calculating the quality of the molded product based on the physical quantity data acquired during quality estimation of the molded product and the physical quantity data and quality data stored in the memory unit; and executing a specified process when the quality of the molded product falls below a specified quality.

2. A quality estimation method as described in claim 1, which calculates the quality of a molded product based on the difference between a time series waveform indicated by physical quantity data acquired during quality estimation and a time series waveform indicated by physical quantity data stored in the memory unit.

3. A quality estimation method according to claim 1 or 2, which calculates the quality of a molded product based on the difference in time-series waveforms indicated by a plurality of physical quantity data that share a common process that constitutes an injection molding cycle.

4. A quality estimation method according to any one of claims 1 to 3, further comprising the steps of: storing the physical quantity data in the memory unit in association with molding conditions set in the injection molding machine; and calculating the quality of the molded product based on the difference in time-series waveforms indicated by a plurality of physical quantity data having common molding conditions.

5. A quality estimation method according to any one of claims 1 to 4, comprising the steps of: creating a folder having a folder name including a character string reflecting the molding conditions set in the injection molding machine and a collection period for the physical quantity data; and saving in the folder, for each shot, physical quantity data obtained when injection molding is performed under the molding conditions included in the folder name during the collection period included in the folder name.

6. The quality estimation method according to any one of claims 1 to 5, wherein the physical quantity data is stored as a file in which the date and time when the injection molding was performed, time information for specifying the point in time when the physical quantity data was detected, the acquired physical quantity data, and command values ​​related to the operation of the injection molding machine when the physical quantity data was acquired are associated with each other.

7. A quality estimation method according to any one of claims 1 to 6, further comprising identifying a method for changing set values ​​related to molding conditions based on physical quantity data acquired during quality estimation and physical quantity data stored in the memory unit.

8. The quality estimation method according to any one of claims 1 to 7, wherein the predetermined processing includes processing related to alarm notification.

9. A quality estimation method according to any one of claims 1 to 8, in which the quality of a molded product is estimated by comparing an increase / decrease or periodic change in a feature calculated based on physical quantity data acquired during quality estimation with an increase / decrease or periodic change in a feature calculated based on physical quantity data stored in the memory unit.

10. A quality estimation device having a processing unit, wherein the processing unit: acquires time-series physical quantity data related to the operation of an injection molding machine obtained in an injection molding process of a molded product using the injection molding machine; stores the acquired physical quantity data in a memory unit for each shot; stores quality data indicating the quality of a molded product injection-molded when the acquired physical quantity data is obtained in association with the physical quantity data; calculates the quality of the molded product based on the physical quantity data acquired during quality estimation of the molded product and the physical quantity data and quality data stored in the memory unit; and executes a specified process when the quality of the molded product falls below a specified quality.

11. A computer program for causing a computer to execute the following processes: acquiring time-series physical quantity data related to the operation of an injection molding machine obtained during an injection molding process of a molded product using the injection molding machine; storing the acquired physical quantity data in a memory unit for each shot; storing quality data indicating the quality of a molded product injection-molded when the acquired physical quantity data was obtained in association with the physical quantity data; calculating the quality of the molded product based on the physical quantity data acquired during quality estimation of the molded product and the physical quantity data and quality data stored in the memory unit; and executing a specified process when the quality of the molded product falls below a specified quality.

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