JP2023073624A - Molding machine, molding machine support device and molding system - Google Patents

Abstract

To provide a molding machine capable of suitably setting a numerical range for classification.SOLUTION: In a die cast machine 1, an operation part 15 receives the input of the set value of a defective indication rate. The defective indication rate is a ratio, when plural molding cycles are performed, in which defectives including molded articles produced by the molding cycle(s) in which the measured value of a physical amount reaches a value other than a prescribed numerical value range occupy in molded articles produced by the plural molding cycles or a ratio correlated with the ratio. A machine side transmission part 35 transmits the set value of the defective indication rate inputted into the operation part 15 to a support device 31. The machine side transmission part 35 receives information on the numerical value range corresponding to the set value of the defective indication rate from the support device 31. A control device 13 performs treatment of classifying the molded articles produced by the molding cycle(s) in which the measured value of the physical amount measured by a sensor 33 reaches the value other than the received numerical value range from the other molded articles.SELECTED DRAWING: Figure 1

Description

The present disclosure relates to molding machines, support devices that support the molding machines, and molding systems that include the molding machines. A molding machine fills a mold cavity with a molding material to obtain a molded product, and is, for example, a die casting machine or an injection molding machine.

A molding machine that monitors various physical quantities is known (for example, Patent Document 1). The various physical quantities include, for example, the temperature of the mold, the amount of molding material for one shot, the speed at which the molding material is filled into the mold, the pressure of the molding material in the mold, and the molding machine (or peripheral equipment) temperature, position, velocity, pressure, flow rate and power at each part. By monitoring such physical quantities, for example, it is possible to detect an abnormality in a molding machine, determine the quality of a molded product, or investigate the cause of a defective product. Patent Document 2 states that it is possible to determine whether a molded product is good or bad based on the monitoring of physical quantities, but that defective products may occur even if the values of the physical quantities are within the normal range.

JP 2011-140033 A JP 2007-196604 A Japanese Patent Application Laid-Open No. 2004-230901 JP-A-2001-293761

As described above, it is possible to determine the quality of a molded product by determining that the product is non-defective when the value of the physical quantity is within a predetermined numerical range. However, the numerical range (upper limit and lower limit) is set based on the operator's experience, for example. If the numerical range is narrower than an appropriate size, for example, there is a high probability that a non-defective product will be judged as a defective product and discarded. Also, if the numerical range is wider than the appropriate size, for example, the probability that a defective product will be determined as a non-defective product and the post-process will be performed will increase. Defective products are found in subsequent inspections in post-processes, but the post-processes are unnecessarily performed on the defective products. Thus, if the numerical range is not properly set, productivity will decrease. Therefore, it is desirable to provide a molding machine, a molding machine support device, and a molding system that can appropriately set a numerical range for sorting.

A molding machine according to an aspect of the present disclosure includes a machine body that repeats a molding cycle of filling a molding material into a cavity to produce a molded product, a sensor that measures a physical quantity related to the molding cycle, and a plurality of molding cycles. In the case where the measured value of the physical quantity is outside the predetermined numerical range, the proportion of defective products included in the molded products manufactured by the molding cycle, in the molded products manufactured by the plurality of molding cycles, or When a ratio correlated with a ratio is referred to as a defective product index rate, a set value receiving unit that receives an input of a set value of the defective product index rate; a machine-side transmitting unit that transmits, a machine-side receiving unit that receives information on the numerical range corresponding to the setting value transmitted by the machine-side transmitting unit from the support device, and the machine main body by repeating the molding cycle For a plurality of molded products to be manufactured, a molded product manufactured by a molding cycle in which the measured value of the physical quantity measured by the sensor is outside the numerical range received by the machine-side receiving unit. and a sorting section that sorts the molded products produced by the molding cycle of .

A support device for a molding machine according to an aspect of the present disclosure includes measured values of physical quantities related to a molding cycle in which a molding material is filled into a cavity to produce a molded product, and a molding cycle in which the measured values are obtained. a storage unit for storing a plurality of pieces of past data including information on whether the molded product is a non-defective product or a defective product; and the ratio of the past data in which the determination result is a defective product, or the ratio correlated with the ratio, is referred to as the defective product index rate, and the set value of the defective product index rate is set from the molding machine. a support-side receiving unit for receiving; and a computing unit that identifies the numerical range in which the defective product index rate for the plurality of past data stored in the storage unit is the set value received by the support-side receiving unit. and a support-side transmission unit that transmits information on the numerical range specified by the calculation unit to the molding machine.

A molding system according to an aspect of the present disclosure includes a machine body that repeats a molding cycle of filling a molding material into a cavity to produce a molded product, a sensor that measures a physical quantity related to the molding cycle, and a measured value of the physical quantity. , information on whether the molded product manufactured by the molding cycle in which the measured value is obtained is a non-defective product or a defective product, and a storage unit for storing a plurality of past data, respectively; When the molding cycle is performed, the number of defective products included in the molded product manufactured by the molding cycle in which the measured value of the physical quantity occupies the molded product manufactured by the plurality of molding cycles and has a value outside the predetermined numerical range. When a ratio or a ratio correlated to the ratio is referred to as a defective product index rate, a set value receiving unit that receives an input of a set value of the defective product index rate; Defective product index rate for data is targeted to a plurality of molded products manufactured by the machine main body by repeating the molding cycle, and a calculation unit that specifies a numerical range that is the set value input to the set value reception unit. The molded product manufactured by the molding cycle in which the measured value of the physical quantity measured by the sensor is outside the numerical range specified by the calculation unit is removed from the molded product manufactured by another molding cycle. and a sorting unit that performs a sorting process.

According to the above configuration, it is possible to appropriately set the numerical range for sorting.

1 is a side view showing the configuration of a die casting machine according to an embodiment of the present disclosure; FIG. FIG. 2 is a top view showing the configuration of a molding system including the die casting machine of FIG. 1; FIG. 3 is a block diagram for explaining the data accumulation operation of the molding system of FIG. 2; FIG. 3 is a block diagram for explaining the setting operation of the numerical range by the molding system of FIG. 2; FIG. 3 is a block diagram for explaining the sorting operation by the molding system of FIG. 2; FIG. 3 is a block diagram for explaining auxiliary operations by the molding system of FIG. 2; FIG. 3 is a schematic diagram showing a configuration example of data stored in the support device of the molding system of FIG. 2; FIG. 3 is a schematic diagram showing an example of setting a numerical range by the molding system of FIG. 2; FIG. 3 is a schematic diagram showing another setting example of the numerical range by the molding system of FIG. 2; FIG. 3 is a flow chart showing an example of a procedure for selecting a determination target by the support device of the molding system of FIG. 2; FIG.

Below, first, an outline of a molding system according to an embodiment of the present disclosure will be described, and then details of the molding system will be described.

(Overview of molding system)
FIG. 1 is a side view (partially including a cross-sectional view) showing the configuration of a die casting machine 1 included in a molding system SM1 (reference numeral is FIG. 2) according to an embodiment of the present disclosure. FIG. 1 is provided with an orthogonal coordinate system xyz for convenience. The z direction is the vertical direction and the +z side is upward.

A die casting machine 1 holds a die 101 . The mold 101 includes, for example, a fixed mold 103 and a movable mold 105 . The die casting machine 1 brings the movable die 105 closer to the stationary die 103 and brings it into contact with the fixed die 103 as indicated by the chain double-dashed line in FIG. 1 (the die is closed). Thereby, a cavity Ca having a shape similar to that of a molded product (in other words, a die-cast product or product) is formed between the fixed mold 103 and the movable mold 105 .

The die casting machine 1, for example, fills the cavity Ca with an uncured metal material (performs injection). The metal material filled in the cavity Ca is solidified by the mold 101 depriving it of heat. Thereby, a molded product is produced. After that, the die casting machine 1 separates the movable mold 105 from the fixed mold 103 (performs mold opening) in order to take out the molded product. The die casting machine 1 repeats, for example, a molding cycle in which the mold closing, injection and mold opening described above are performed in order.

FIG. 2 is a schematic top view showing the configuration of the molding system SM1.

The molding system SM1 has a take-out device 21 for taking out the molded product 107 from the opened mold 101 . Note that the take-out device 21 may be regarded as a device separate from the die casting machine 1 or may be regarded as a part of the die casting machine 1 . In the description of the present embodiment, for the sake of convenience, expressions based on the former way of understanding may be used.

The take-out device 21 places the taken-out molded product 107 on the conveyor 23, for example. The molded product 107 transported by the conveyor 23 is subjected to a post-process by a post-process device 29, for example. Post-processes include, for example, heat treatment, deburring, cutting, surface treatment and/or assembly. In cutting, for example, unnecessary parts such as biscuits are removed.

The molding system SM1 also has various sensors (not shown here) that measure various physical quantities related to the molding cycle. In other words, the physical quantity is, for example, a physical quantity whose value changes with the progress of the molding cycle and/or a physical quantity whose value differs between molding cycles. Specific examples of physical quantities include the temperature of the mold 101, the temperature of the metal material, the amount of the metal material in one shot, the speed at which the metal material is filled into the mold 101 (injection speed), and the metal material inside the mold 101. pressure (injection pressure or casting pressure), temperature or supply amount of substances other than metal materials (e.g. cooling water, air or mold release agent), and temperature in each part of the die casting machine 1 (or peripheral equipment) correlated with these, Position, velocity, pressure, flow rate and power are included.

In the following, for the sake of convenience, description or expression focusing on only one type of physical quantity may be given without any particular notice.

Physical quantities such as those described above correlate with the quality of the molded product 107 . Therefore, the take-out device 21 sorts the molded products 107 depending on whether the measured value of the physical quantity is within a predetermined numerical range. For example, when the measured value of the physical quantity is within the numerical range, the take-out device 21 places the molded product 107 on the conveyor 23 as described above. On the other hand, when the measured value of the physical quantity is out of the numerical range, the take-out device 21 arranges the molded product 107 in the defective product box 25 . As a result, the post-process is avoided for the molded product 107 that is highly likely to be defective.

In the following description, for the sake of convenience, a molded article manufactured by a molding cycle in which the measured values of physical quantities are within a predetermined numerical range may be referred to as a "normal molded article". In addition, a molded product manufactured by a molding cycle in which the measured value of the physical quantity is outside a predetermined numerical range may be referred to as an "abnormal molded product". In addition, the terms "normal" and "abnormal" may be used in the same way as above. Unless otherwise specified, a plurality of molded articles refer to the same type (having the same shape, size and material).

FIG. 8 is a schematic diagram showing a setting example of numerical ranges.

In this figure, the horizontal axis indicates the order N of repeated molding cycles. The vertical axis indicates a predetermined physical quantity PQ. A plot of circles indicates the value of the physical quantity PQ in the molding cycle in which good products were produced. The cross plot shows the value of the physical quantity PQ in the molding cycle in which the defective product was produced. Here, values of the physical quantity PQ for 10 molding cycles from the N1th to the N10th in total are shown.

A line LL40 indicates the lower limit of the numerical range R40. A line LU40 indicates the upper limit of the numerical range R40. In the illustrated example, five physical quantities N1 (good product), N3 (defective product), N4 (good product), N7 (good product), and N10 (good product) fall within the numerical range. In the illustrated example, five physical quantities N2 (defective product), N5 (defective product), N6 (defective product), N8 (defective product), and N9 (defective product) are outside the numerical range. positioned.

As shown in this figure, even if the physical quantity is within the numerical range R40, the molded product may be defective (N3). In other words, a molded product under normal conditions is not necessarily a good product. Also, as shown in this figure, even if the physical quantity is located outside the numerical range R40, the molded product may be a non-defective product (N5). In other words, a molded product in the event of an abnormality is not necessarily a defective product.

In the illustrated example, if the numerical range is narrowed, for example, the probability that defective products will be sorted as normal molded products decreases, while the probability that non-defective products will be sorted as abnormal molded products increases. When the probability that non-defective products are sorted as abnormal molded products increases, the probability that non-defective products are discarded increases.

Conversely, if the numerical range is widened, for example, the probability that defective products will be sorted as normal molded products will increase, while the probability that good products will be sorted as abnormal molded products will decrease. When the probability that defective products are sorted as normal molded products increases, the probability that post-processes are performed on the defective products also increases.

Here, regardless of whether it is normal or abnormal, the ratio of defective products in abnormal conditions to any number of molded products (in other terms, all molded products) regardless of whether they are good or defective is called the "defect rate". shall be called Also, a ratio correlated with the defective rate is referred to as a “defective product index rate”. As the defective product index rate other than the defective rate, for example, the ratio of defective products under normal conditions to the molded products under normal conditions (good products and defective products) (hereinafter sometimes referred to as "defect content rate"), The percentage of defective products in an abnormal state (hereinafter sometimes referred to as "defect detection rate") to defective products in a time and abnormal state (all defective products from another point of view) can be mentioned.

From another point of view, the defective product index rate can be said to be a value obtained by dividing the number of defective products under normal conditions or the number of defective products under abnormal conditions by the number of a predetermined population. The population may be appropriately selected from all molded products, normal molded products, abnormal molded products, and all defective products. From another point of view, the defective index rate changes the numerical range for the same population (in other words, a predetermined number of molded products), and the number of defective products under normal conditions (from another viewpoint, It can be said that the ratio changes when the number of defective products) changes. Also, for example, when the same population is targeted, the sum of the defect detection rate and the ratio of normal defective items to all defective items is constant, so both may be regarded as equivalent.

In the example of FIG. 8, the defective product content rate is 20% (1/5×100). The defect rate is 40% (4/10×100). The defect detection rate is 80% (=4/5×100).

In addition, the ratio of non-defective products to abnormal molded products (non-defective products and defective products) will be referred to as "non-defective product content". Also, the non-defective item content rate or the ratio correlated with the non-defective item content rate is referred to as a "non-defective item index rate." As a non-defective product index rate other than the non-defective product content rate, for example, the ratio of non-defective products in normal and abnormal conditions (all molded products), and the ratio of non-defective products in normal and abnormal conditions (all non-defective products) The proportion of non-defective products in normal conditions can be mentioned.

From another point of view, the non-defective item index rate can be said to be a value obtained by dividing the number of normal non-defective items or the number of abnormal non-defective items by the number of a predetermined population. The population may be appropriately selected from all molded products, normal molded products, abnormal molded products, and all non-defective products. From another point of view, the non-defective product index rate changes the numerical range for the same population (in other words, a predetermined number of molded products), and the number of non-defective products under normal conditions It can be said that the rate of change when the number) changes.

In the example of FIG. 8, the non-defective product content is 20% (=1/5×100). The ratio of non-defective products to all molded products is 40% (=4/10×100). The ratio of non-defective products to all non-defective products is 80% (=4/5×100).

In order to deepen the understanding of the defective product index rate and the non-defective product index rate, FIG. 9 shows an example in which a numerical range R20 different from the numerical range R40 in FIG. 8 is set for the same physical quantity measurement results as in FIG. show. FIG. 9 is a diagram similar to FIG. 8, and lines LU20 and LL20 indicate the upper and lower limits of the numerical range R20.

In the example of FIG. 9, N1 (good product), N2 (defective product), N3 (defective product), N4 (good product), N5 (good product), N6 (defective product), N7 (good product) and N10 (good product). physical quantity falls within the numerical range R20. In the illustrated example, two physical quantities N8 (defective product) and N9 (defective product) are located outside the numerical range R20, which is the reverse of the above.

In the example of FIG. 9, the defective content is about 37.5% (3/8*100). The defect rate is 20% (2/10*100). The defect detection rate is 40% (=2/5×100).

Also, in FIG. 9, the non-defective product content is 0% (=0/5×100). The ratio of non-defective products to all molded products is approximately 50% (=5/10×100). The ratio of non-defective products to all non-defective products is 100% (=5/5×100).

In the present embodiment, the set value reception unit of the molding system SM1 receives input of the set value of the defective product index rate. More specifically, for example, an operation unit (described later) of the die casting machine 1 receives an input of a defective index rate value desired by the operator. Then, the molding system SM1 realizes the set value of the defective product index rate based on the data in which the value of the physical quantity in the past molding cycle is associated with the quality determination result of the molded product manufactured by the molding cycle. Calculate the numerical range (upper limit and lower limit).

Thus, by calculating the numerical range that achieves the set value of the defective index rate based on past data, the numerical range that achieves the desired defective index rate can be set regardless of the operator's experience. be able to. As a result, for example, it is easy to control wasteful costs caused by performing post-processes on defective products.

In this embodiment, when the numerical range is set as described above, the molding system SM1 may calculate the non-defective product index rate corresponding to the numerical range based on past data. The calculated non-defective product index rate may be used, for example, to verify the validity of the set value of the defective product index rate. For example, if the non-defective product content rate (the ratio of non-defective products to the too low).

(Details of molding system)
The molding system SM1 has, for example, the die casting machine 1, the take-out device 21, the conveyor 23, the defective product box 25, and the post-process device 29, as described above. In addition to these, the molding system SM1 has, for example, a marker 27 for marking the molded product 107 and a support device 31 for communicating with the die casting machine 1 .

The marking associates the molding cycle with the molded product, and in turn, associates the measurement values of the physical quantities in the molding cycle with the quality determination result of the molded product. The support device 31 includes, for example, a computer, and is responsible for storing past data, calculating the numerical range based on the set value of the defective index rate, and calculating the non-defective index rate based on the numerical range.

The molding system SM1 may be defined as including only the die casting machine 1 and the supporting device 31. In other words, devices other than the die casting machine 1 and the support device 31 may be regarded as separate devices from the molding system SM1. In the description of the present embodiment, for the sake of convenience, the molding system SM1 is based on an expression that includes the above-mentioned other devices.

Here, the outline of the molding system SM1 will be described in the following order.
・Die casting machine 1 (Fig. 1 and Fig. 2)
- Take-out device 21, conveyor 23 and defective product box 25 (Fig. 2)
・Marker 27 (Fig. 2)
・Post-process device 29 (Fig. 2)
- Support device 31 (Fig. 2)
・Physical quantity, numerical range and sensor ・Quality determination of molded product ・Configuration of signal processing system of molding system SM1 (Figs. 3 to 6)
・Example of configuration of past data (Fig. 7)
・Operation of molding system SM1 (Figs. 3 to 6)
・Specific example of setting method of numerical range (Fig. 8 and Fig. 9)
・Example of how to select the type of physical quantity to be judged (Fig. 10)
・Summary of embodiment

(Die casting machine)
The die casting machine 1 shown in FIGS. 1 and 2 injects an uncured metal material into the space (including the cavity Ca) formed by the mold 101, as described above. The uncured state is, for example, a liquid state or a solid-liquid coexistence state. The solid-liquid coexistence state is a semi-solid state in which solidification has progressed from a liquid state, or a semi-molten state in which melting has progressed from a solid state. Metals are, for example, aluminum alloys, zinc alloys or magnesium alloys. In addition, hereinafter, expressions may be made on the premise that the uncured metal material is molten metal (liquid metal material).

As already mentioned, the mold 101 includes, for example, a fixed mold 103 and a movable mold 105. As shown in FIG. In the drawings of the present disclosure, for convenience, the cross section of the fixed mold 103 or the movable mold 105 is indicated by one type of hatching. However, each mold may be of a direct carving type that is integrally formed as a whole, or may be of a nesting type that is configured by inserting a nest into a main mold. Moreover, the mold 101 may have a fixed core fixed to the fixed mold 103 or the movable mold 105 and/or a movable core sandwiched between the fixed mold 103 and the movable mold 105 .

The die casting machine 1 has, for example, a machine body 3 that performs various mechanical operations and a control unit 5 that controls the machine body 3 .

The machine main body 3 includes, for example, a mold clamping device 7 for opening and closing the mold 101 and for clamping the mold, an injection device 9 for injecting molten metal into the mold 101, and a fixed mold 103 or a movable mold 105 (FIG. 1). has an extruder 11 (FIG. 1) for extruding from a moving die 105). The configuration and operation of the machine body 3 (for example, the mold clamping device 7, the injection device 9, and the extrusion device 11) may be in various modes, and may be a known configuration.

For example, the mold clamping device 7 may perform mold opening/closing and mold clamping using a toggle mechanism (example shown in the figure), or may not have a toggle mechanism. In the latter aspect, mold opening and closing and mold clamping may be performed by separate drive sources. Further, for example, the drive system of the mold clamping device 7 may be an electric system, a hydraulic system (hydraulic system), or a hybrid system combining these.

The injection device 9 may be, for example, one for a cold chamber machine (example in FIG. 1), one for a hot chamber machine, or a hybrid type in which both are combined. may be Further, for example, the drive system of the injection device 9 may be an electric system, a hydraulic system (hydraulic system), or a hybrid system combining these.

The extruding device 11 may, for example, extrude a molded product from a movable mold 105 (example in FIG. 1), or may extrude a molded product from a fixed mold 103 . Further, for example, the extrusion device 11 may have an electric or hydraulic (hydraulic) drive source, or may utilize mold opening by the mold clamping device 7 (without a drive source). ).

The control unit 5 includes, for example, a control unit 13 that performs various calculations and outputs control commands, an operation unit 15 that receives operator input operations, and a display unit 17 that visually presents information to the operator. are doing. 1 and 2 show, as the control unit 5, an interface section (reference numerals omitted) including an operation section 15 and a display section 17. FIG. The control unit 5 may include a control panel (not shown) installed separately from the interface section. The position of the interface section is arbitrary. For example, the interface section may be provided on a fixed die plate (reference numerals omitted) of the mold clamping device 7 (example shown), or may be provided on a control panel installed separately from the machine main body 3. .

The control unit 13 may be configured by, for example, a computer. The computer includes, for example, a CPU (central processing unit), a ROM (read only memory), a RAM (random access memory), and an external storage device (not shown). Various functional units that perform various calculations are constructed by the CPU executing programs stored in the ROM and/or the external storage device. Note that the control unit 13 may include a logic circuit that performs only certain processing. The control unit 13 may be divided or dispersed as appropriate. For example, the control unit 13 includes a lower control unit for each of the mold clamping device 7, the injection device 9, and the extrusion device 11, and a higher control unit that performs control such as synchronizing a plurality of lower control units. may be configured.

The configuration of the operation unit 15 and the display unit 17 may be various configurations, and for example, may be a known configuration. For example, the operation unit 15 may include a touch panel that also serves as the display unit 17 and mechanical switches (reference numerals omitted). Also, for example, the display unit 17 may include a display (for example, a liquid crystal display or an organic EL display) that displays an arbitrary two-dimensional image. Moreover, the display unit 17 may have a lamp (for example, an LED) that presents information depending on the lighting state.

The display unit 17 is an example of a notification unit that notifies the operator. The die-casting machine 1 may have, for example, a device (for example, a speaker) that acoustically presents information as a notification unit other than the display unit 17 .

(Unloading device, conveyor and defective product box)
The take-out device 21 (FIG. 2) takes out the molded product from the mold 101 in synchronization with the molding cycle, for example, based on a signal from the die casting machine 1 . That is, the take-out device 21 contributes to the automation of take-out of molded products. However, unlike the present embodiment, the take-out device 21 may operate based on an operator's operation, or the take-out device 21 may not be provided and the molded product may be taken out manually.

The configuration of the take-out device 21 may be various configurations, for example, it may be similar to a known configuration. For example, the takeout device 21 grips a biscuit (not shown) of the molded product and conveys the molded product 107 . The take-out device 21 may be a device configured exclusively for taking out molded products, or may be a general-purpose articulated robot.

Different from the illustrated example, the sorting of normal molded products and abnormal molded products may be performed by a device other than the take-out device 21 . For example, the molded articles taken out by the take-out device 21 may be uniformly transported to a conveyor or a box. After that, a sorting robot may pick up the abnormal molded product from the conveyor or box and exclude it, or pick up the normal molded product and the abnormal molded product and transport them to different places. . Alternatively, a partition movable on the conveyor may guide the abnormal moldings to a different location than the normal moldings flow to.

The conveyor 23 and the defective product box 25 are only examples of sorting destinations for molded products. The destination of sorting may be in a form different from that shown in the drawing. For example, unlike the illustrated example, a box into which non-defective products are brought in and a defective product box 25 may be installed, or a conveyor on which non-defective products are placed and a conveyor on which defective products are placed. may be provided. Conveyor and box configurations may be of various configurations, for example, may be similar to known configurations.

In the illustrated example, the conveyor 23 is used not only as a sorting destination for the molded products in normal operation, but also for automatically conveying the molded products in normal operation to the marker 27 and/or the post-process device 29. ing. Unlike the illustrated example, this automatic transport may be performed by devices other than conveyors. For example, a general-purpose robot may pick up the normal molded product from the conveyor 23 or the box and transport it. Also, the molded product under normal conditions may not be automatically transported, but may be transported by a conveyor or a robot that operates at timing according to the operator's operation, or may be transported manually.

The operation of automatically conveying the normal molded product to the marker 27 and/or the post-process device 29 may be performed as one mode of sorting, not as an operation after sorting. For example, a robot (not shown) picks up a normal molded product from all molded products (a plurality of molded products in which normal molded products and abnormal molded products are mixed), and markers 27 and / or It may be transported to the post-process device 29 .

A device (conveyor 23 or a robot (not shown)) that automatically conveys the molded product to the marker 27 carries out the molded product in synchronism with the molding cycle based on the signal from the die casting machine 1, similar to the take-out device 21, for example. It may be transported to marker 27 . In this case, the time difference between when each molding cycle is performed and when the molded product produced by each molding cycle is conveyed to the marker 27 is constant. This time difference may be used to identify one or the other of the molded article marked by the marker 27 and the molding cycle that produced the molded article.

(marker)
The mark formed on the molded product by the marker 27 is composed of, for example, an arrangement of letters, numbers and/or symbols (hereinafter referred to as "character string"), and links each molded product and each molding cycle. Indicates information that can be attached. The information may be, for example, a character string arbitrarily assigned to each molding cycle, or the time when each molding cycle was performed. In addition, below, these information shall be called "identification information" for convenience. The marker 27 may also be used to form information other than identification information.

The marker 27 may automatically mark the molded product in synchronization with the molding cycle based on a signal from the die casting machine 1, for example. However, the marker 27 may perform marking based on an operator's operation. It is also possible to mark manually without using the marker 27 .

The marker 27 may have, for example, the same configuration as various markers used in various technical fields. For example, the marker 27 may be a device (stamping machine) that engraves (forms unevenness) on the molded product, or a device (printer) that applies paint to the molded product. The stamping machine may be, for example, a stamping machine that applies pressure to the molded product, or a laser stamping machine that irradiates the molded product with laser light.

In the example of FIG. 2 , the marker 27 marks the molded product 107 being conveyed to the conveyor 23 . However, as understood from the description of the conveyor 23 and the robot that replaces it, the configuration of the marker 27 is not limited to such. For example, a robot may place a molded product on the table of the marker 27 and mark the molded product on the table.

The marker 27 may be omitted if the molding cycle and the result of quality determination can be linked for the same molded product. For example, if the length of time from the execution of the molding cycle to the determination of quality is constant, tying is possible without marking. However, in the description of the present embodiment, expressions may be made on the premise that marking is performed.

(Post-process equipment)
An example of the post-process performed by the post-process device 29 has already been described. The illustrated post-process apparatus 29 may be regarded as an example of one of a plurality of post-process apparatuses corresponding to various post-processes, and such a plurality of post-process apparatuses as a whole may be combined into one. It may be understood that the post-process equipment is schematically shown as a block. The configuration of the post-process device 29 may be various configurations, and may be similar to a known configuration, for example. The post-process device 29 may automatically post-process the molded product conveyed from the die casting machine 1, or perform the post-process at a timing according to the operator's operation (that is, not automatically). good too. In the former aspect, the post-process device 29 may perform the post-process in synchronization with the molding cycle based on the signal from the die casting machine 1, or may perform the post-process out of synchronization with the molding cycle.

In the illustrated example, the post-process by the post-process device 29 is performed after the marking by the marker 27 . As a result, for example, the molding cycle can be linked to the molded product to be post-processed. However, if such mark-based tying is unnecessary, the marking may be performed after a post-process. In such cases, there are cases where the stringing itself is not necessary for the post-process, and where the molding cycle and the post-process are synchronized (in other words, the time difference between the two is constant). and a case where it can be linked to. However, in the description of the present embodiment, for the sake of convenience, expressions may be made on the premise that marking is performed before the post-process.

(support device)
The support device 31 may be configured by a computer, for example, as described above. The computer includes, for example, a CPU, a ROM, a RAM, and an external storage device (not shown). Various functional units (computing unit 39 to be described later) that perform various computations are constructed by the CPU executing programs stored in the ROM and/or the external storage device. Note that the support device 31 may include a logic circuit that performs only certain processing. The support device 31 may be integrated in one place in terms of hardware, or may be distributed and arranged in a plurality of places.

In relation to the above, one supporting device 31 may be provided for one die casting machine 1 or one supporting device 31 may be provided for a plurality of die casting machines 1 . From another point of view, the support device 31 may communicate with only one die casting machine 1 or may communicate with a plurality of die casting machines 1 . Further, in the latter aspect, the plurality of die casting machines 1 corresponding to one support device 31 may have the same configuration or may have different configurations.

In a mode in which the support device 31 communicates with a plurality of die casting machines 1, the plurality of die casting machines 1 use molds 101 having the same configuration (from another point of view, the same type of molded product is produced). It may or may not be operated in such a manner. A plurality of die casting machines 1 communicating with the same support device 31 may be installed in the same factory or may be installed in different factories.

The distance between the supporting device 31 and the die casting machine 1 is arbitrary. For example, the support device 31 may be arranged adjacent to the die casting machine 1 . Conversely, the support device 31 may be installed at a location away from the die casting machine 1 in the factory where the die casting machine 1 is installed, or at a location separate from the factory where the die casting machine 1 is installed. may be installed. Moreover, the support device 31 may be provided in a manner that can be regarded as a part of one die casting machine 1 . For example, the support device 31 and the control unit 13 (at least part of it) may be housed in the same housing.

The configuration for transmitting and receiving signals between the support device 31 and the die casting machine 1 is arbitrary. For example, the support device 31 and the die casting machine 1 (control unit 13) may be directly connected to each other by a cable, may perform short-range wireless communication, or may be connected to a network (for example, a LAN (Local Area Network)). ) or the Internet). Further, the support device 31 and the control unit 13 (at least a part thereof) may share the same hardware resource (CPU, etc.). In other words, unlike the description of the present embodiment, the support device 31 and the control unit 13 may not communicate with each other.

(physical quantity, numerical range and sensor)
Examples of various physical quantities that change as the molding cycle progresses have already been described. The molding system SM1 may set a numerical range for one or more arbitrary physical quantities among various physical quantities, and use it for sorting normal molded products and abnormal molded products. In addition, the physical quantity used for sorting may be, for example, one or more predetermined points in the molding cycle, or a representative value (e.g., average value) during part or all of the molding cycle. , maximum or minimum. Numerical ranges for sorting may be set separately for physical quantities of the same type (physical quantities detected by the same sensor from another point of view) at different points in time. In this case, physical quantities at different points in time may be regarded as different types of physical quantities.

When the value of the physical quantity is outside the numerical range corresponding to the normal molded product, the value of the physical quantity is greater than the upper limit of the numerical range, and the value of the physical quantity is greater than the lower limit of the numerical range. There are small cases. Depending on the type of physical quantity, for example, the probability that the value of the physical quantity exceeds the upper limit is extremely low, or even if the value of the physical quantity increases, the quality of the molded product may be little affected. In such a case, the upper limit of the numerical range may not be set, or whether or not the value of the physical quantity is greater than the upper limit of the numerical range may not be determined. Although the upper limit has been described, the same applies to the lower limit.

When two or more physical quantities are used for sorting, the determination result of whether or not the measured values of the two or more physical quantities are outside the numerical range may be appropriately used for sorting. For example, when the measured value of at least one physical quantity out of the measured values of two or more physical quantities is out of the numerical range, the molded product may be sorted as the abnormal molded product. Further, for example, when the number of types of physical quantities whose measured values are outside the numerical range is equal to or greater than a predetermined number, the molded product may be sorted as an abnormal molded product. In other words, when the number of types of physical quantities whose measured values are outside the numerical range is less than a predetermined number, the molded product may be sorted as a normal molded product. In addition, for a specific type of physical quantity, if the measured value is out of the numerical range, the molded product is sorted as an abnormal molded product. If the number of types of physical quantities that are outside is equal to or greater than a predetermined number, the molded product may be sorted as an abnormal molded product.

As can be understood from the above description, for example, focusing on one type of physical quantity, ``a molded product manufactured by a molding cycle in which the measured value of the physical quantity has a value outside the numerical range is replaced by another molding cycle. When it says "sorted from articles made by", the former articles may not be sorted from the latter articles. Therefore, the above is, for example, "sorting molded articles from molded articles made by other molding cycles with at least one necessary condition that they were made by a molding cycle in which the measured value of the physical quantity was out of the numerical range. It can be rephrased as "to do".

As will be understood from the description of physical quantities, the molding system SM1 may have various sensors that detect one or more various physical quantities. Types of sensors include, for example, temperature sensors, position sensors, speed sensors, acceleration sensors, load sensors, pressure sensors, flow sensors, current sensors, and voltage sensors. The configuration of each sensor may be a known one. Also, one sensor may be used for detecting two or more physical quantities. For example, position, velocity and acceleration may be detected by one type of sensor since they are interconvertible by differentiation or integration. Also, a value calculated from detection values of two or more sensors may be treated as a detection value of one sensor. That is, two or more sensors may be regarded as one sensor. For example, when statistical values of temperatures detected by two or more temperature sensors are used, the two or more temperature sensors may be regarded as one sensor.

Also, as understood from the description of physical quantities, various sensors may be provided at appropriate positions. For example, various sensors may be provided at various locations such as the die 101 , the die casting machine 1 , and peripheral equipment of the die casting machine 1 . Peripheral equipment includes, for example, a supply device (not shown) for supplying molten metal to the die casting machine 1, a spray device for spraying a mold release agent on the mold 101 (see FIG. 1, reference numerals omitted), the above-described take-out device 21, and a supply device (not shown) that supplies cooling water to the mold 101 . However, these peripheral equipment may be regarded as part of the die casting machine 1 .

(Quality judgment of molded products)
In this embodiment, for example, at least two kinds of pass/fail judgments are performed as follows.

The first pass/fail determination is performed on a plurality of molded products including normal molded products and abnormal molded products. The results of the first pass/fail judgment are, for example, the calculation of a numerical range based on the set value of the defective index rate, the calculation of the non-defective index rate based on the numerical range, and the selection of the type of physical quantity to be judged (described later). It is sometimes called statistical processing.). The first pass/fail judgment is made, for example, on a prototype of the molded product. From another point of view, the first pass/fail judgment is performed on the molded product when the molding cycle is executed while changing the molding conditions appropriately for the purpose of searching for the optimum molding conditions.

The second pass/fail judgment is a pass/fail judgment only for molded products in normal condition after sorting. The result of this pass/fail determination is used, for example, to determine whether or not the molded product under normal conditions can be shipped, and is not used for the statistical processing described above. The second pass/fail determination is made, for example, on a molded product that is manufactured for the purpose of being actually shipped. From another point of view, the second pass/fail judgment is a pass/fail judgment for a molded product when molding cycles are repeated under basically constant molding conditions. However, the molding conditions may be appropriately adjusted by the operator and/or the control section 13 in the course of repeating the molding cycle.

When the data containing the result of the second pass/fail judgment is added to the data containing the result of the first pass/fail judgment, for example, while the data of the result of the judgment that the value of the physical quantity is out of the numerical range and the result of the judgment of failure is not added, The data of the result of determination that the value of the physical quantity is within the numerical range and that it is defective is added. As a result, for example, when the set value of the defective product index rate is reset, the numerical range corresponding to the set value becomes narrower as the amount of added data increases. As a result, the validity of the statistical processing is lowered. Therefore, the data including the result of the second pass/fail judgment is basically not used for statistical processing. However, data including the result of the second pass/fail judgment may be used for statistical processing based on some kind of reasoning and processing.

When the first quality judgment is performed, unlike the above description, for example, the take-out device 21 does not sort the molded products based on the values of the physical quantities, and places all the molded products on the conveyor 23. . The molded product placed on the conveyor 23 is marked with a marker 27 and post-processed by a post-process device 29 . The quality determination of the molded product is performed after it is placed on the conveyor 23, for example.

When the second pass/fail determination is made, the take-out device 21 sorts the molded products based on the values of the physical quantities, as described above. A normal molded product placed on the conveyor 23 is marked by a marker 27 and post-processed by a post-process device 29 . The quality determination of the molded product is performed after the molded product is placed on the conveyor 23 in the same manner as the first quality determination.

As can be understood from the above, although the first pass/fail judgment and the second pass/fail judgment differ in the presence or absence of sorting in the preceding stage, the judgments themselves may be made at the same time and by the same method. However, there may be a difference in timing and/or method between the two. For example, the first pass/fail determination may be performed before the post-process, while the second pass/fail determination may be performed after the post-process.

It should be noted that the second pass/fail judgment does not necessarily need to associate the molding cycle with the pass/fail judgment result. Therefore, when the second pass/fail judgment is performed, the marking for the purpose of linking may not be performed. Also, the prototype does not necessarily have to be subjected to the post-process. In other words, when the first pass/fail judgment is performed, the post-process may not be performed.

In the description of the present embodiment, for the sake of convenience, it is assumed that the first quality determination and the second quality determination are generally performed in the same manner, except for the presence or absence of sorting by the take-out device 21 and specific molding conditions. In some cases, the first pass/fail judgment and the second pass/fail judgment are not particularly distinguished.

The quality determination of the molded product may be performed at an appropriate time after the molded product is removed from the mold 101 . For example, the determination of the quality of the molded product may be made at an appropriate time during the period from when the molded product is removed from the mold 101 to when it is conveyed to the marker 27 , or when the molded product is located at the marker 27 . It may be performed at any time during the period from the marker 27 until it is conveyed to the post-process device 29, or it may be performed at the post-process device 29. Alternatively, it may be carried out after being unloaded from the post-process device 29 .

In the description of the present embodiment, mainly, an aspect in which quality determination is performed after the molded product is conveyed to the post-process device 29 will be taken as an example. In this case, the device that performs pass/fail judgment may be regarded as an example of the post-process device 29 . That is, the post-process device 29 shown in FIG. 2 may be regarded as a device for performing pass/fail judgment. In the following description, the post-process device 29 may be referred to as a pass/fail determination device.

Also, the quality determination of the molded product may be performed by various methods, for example, the same method as a known method may be used. For example, a computer may perform quality determination based on an image of a molded product. Imaging of the molded article may be performed using visible light or radiation (for example, X-rays). Further, the image may be an image of the surface, or may be a tomographic image obtained by computed tomography (CT). Alternatively, for example, the dimension of the molded product may be measured by a contact or non-contact measuring device, and the computer may determine the quality based on the measured dimension. The quality judgment may be based on whether the dimensional error of the surface shape or the size of the cavity is within a predetermined allowable range, may be based on pattern matching, or may be based on AI (artificial intelligence) technology. may be used. Furthermore, the pass/fail judgment can also be performed visually.

A single molded article 107 produced in one molding cycle may include two or more articles. In such a case, the quality determination may be performed with the molded product 107 as one unit. However, the quality determination may be performed for each of two or more products included in one molded product 107 . In this case, for example, if at least one product is defective, it may be determined that a defective product has been produced (however, in this case, it can be regarded as a determination for each molded product 107), and for each product may be used as one determination result for statistical processing for calculating a non-defective product index rate or the like. In addition, in the description of the present embodiment, for the sake of convenience, expressions may be made on the premise that one determination result is obtained for one molded product 107 .

(Configuration of signal processing system of forming system)
3 to 6 are block diagrams showing the configuration of the signal processing system of the shaping system SM1. 3 to 6 also serve as diagrams for explaining the operation of the molding system SM1, and the arrows indicating signals between blocks are different from each other. In the description here, basically, any one of FIGS. 3 to 6 may be referred to.

The molding system SM1 has the die casting machine 1, the take-out device 21, the marker 27, the post-process device 29 and the support device 31 as described above.

The die-casting machine 1 has, for example, a sensor 33 , a machine-side transmitter 35 and a machine-side receiver 37 in addition to the control section 13 , the operation section 15 and the display section 17 already described. The sensor 33 is a sensor (described above) that detects a physical quantity that changes with the molding cycle. Here, one of the one or more sensors 33 is shown representatively. The machine-side transmission unit 35 transmits a signal (information and/or data from another point of view; hereinafter the same) to the outside of the die casting machine 1 . The machine-side receiving section 37 receives a signal from the outside of the die casting machine 1 .

The method of communication between the machine-side transmitter 35 and the machine-side receiver 37 may be appropriate, and may be wired and/or wireless, for example. Communication partners of the machine-side transmitting unit 35 and the machine-side receiving unit 37 are, for example, the conveyor 23 (not shown here), the pick-up device 21, the marker 27, the post-process device 29, and the support device 31. As already mentioned, the communication between the machine-side transmitter 35 and the machine-side receiver 37 and the support device 31 may be direct or indirect via a network (e.g., LAN and/or Internet). It may be a specific one.

The support device 31 includes, for example, a calculation unit 39 that performs various calculations, a storage unit 41 that stores data, a support-side transmission unit 43 that transmits signals to the outside of the support device 31, and a signal from the outside of the support device 31. and a support-side receiving unit 45 for receiving . The storage unit 41 stores, for example, a plurality of pieces of past data in which values of physical quantities and results of pass/fail judgment are associated with each other. The calculation unit 39 performs statistical processing based on a plurality of past data stored in the storage unit 41, for example.

The communication method of the support-side transmitting unit 43 and the support-side receiving unit 45 may be set appropriately, and may be wired and/or wireless, for example. The communication partners of the support-side transmission unit 43 and the support-side reception unit 45 are, for example, the die casting machine 1 and the post-process device 29 (good/bad judgment device). As can be understood from the above description, the communication between the support-side transmitting unit 43 and the support-side receiving unit 45 may be direct or indirect through a network (for example, LAN and/or Internet). It may be a specific one.

(Example of past data structure)
FIG. 7 is a schematic diagram conceptually showing a configuration example of the database DB1 stored in the storage unit 41 of the support device 31. As shown in FIG.

The database DB1 has a plurality of past data DT1 (represented by a plurality of rows in the table in the drawing). Each past data DT1 has one or more physical quantity values in one molding cycle, and information on the result of quality determination of the molded product produced in the one molding cycle. The former is represented by columns of "physical quantity 1", "physical quantity 2" and "physical quantity 3". The latter is expressed by the column of "judgment result". The database DB1 is used for statistical processing such as calculation of the numerical range of the physical quantity corresponding to the set value of the defective index rate, calculation of the non-defective index rate corresponding to the numerical range, and selection of the physical quantity to be judged (described later). used.

The past data DT1 may contain identification information. The content of this identification information is the same as the content of the identification information marked on the molded product by the marker 27, for example. However, the marked identification information is for storing in the database DB1 the molding cycle (the value of its physical quantity) and the information on the quality determination result of the molded product in association with each other. not from Therefore, the past data DT1 may not include the content of the marked identification information. Just to be sure, the past data DT1 may include identification information (identification information having content unrelated to the content of the marked identification information) for distinguishing a plurality of past data DT1 from each other in data processing. do not have.

One database DB1 is constructed, for example, when the single die casting machine 1 repeatedly molds the same type of molded product. The single database DB1 is used by the single die casting machine 1. However, one database DB1 is constructed when the same type of molded product is molded by a plurality of die casting machines 1 having the same configuration, and/or is constructed by a plurality of die casting machines 1 having the same configuration. It may be used when forming molded articles of the same type. From another point of view, the number of die casting machines 1 used for constructing the database DB1 and the number of die casting machines 1 using the database DB1 may be the same or different.

When the same type of molded product is molded by a plurality of die casting machines 1 having the same configuration and one database DB1 is constructed and used, for example, the number of past data DT1 can be increased. Variation in calculation results due to the small number can be reduced. When the database DB1 is constructed and used by a single die casting machine 1, for example, there are differences between individuals of the die 101, differences between individuals of the die casting machine 1, devices of the configuration of the peripheral equipment of the die casting machine 1, or Variations in calculation results due to differences between individuals and differences in the external environment can be reduced. Therefore, any aspect may be selected as appropriate.

Although not shown, the storage unit 41 may have a plurality of databases DB1. Then, the support device 31 selects the database DB1 according to the type of the molded product and/or the type of the die casting machine 1, and accumulates the past data DT1 or reads out the past data DT1 from the selected database DB1. (statistical processing) may be performed.

More specifically, for example, although not shown, the storage unit 41 may have a database that stores information specifying the database DB1 and the database DB1 in association with each other. The information specifying the database DB1 may be, for example, a combination of information specifying the type of molded product and information specifying the type of the die casting machine 1 . Alternatively, the information specifying the database DB1 may be identification information appropriately assigned to each combination of the type of molded product and the type of the die casting machine 1 . Then, the support device 31 receives both the past data DT1 and the information specifying the database DB1, accumulates the past data DT1 in the corresponding database DB1, or requests statistical processing and specifies the database DB1. Statistical processing may be performed based on the corresponding database DB1.

However, in the description of this embodiment, for the sake of convenience, the description of the operation of the support device 31 selecting one database DB1 from a plurality of databases DB1 is basically omitted. In some cases, the support device 31 is expressed as if it has only one database DB1.

When a plurality of prototypes are manufactured, one database DB1 may contain past data DT1 for all the prototypes, or may contain past data DT1 for some of the prototypes. As can be understood from the above explanation about basically not using the second pass/fail judgment result for statistical processing, if the values of the physical quantities in the database DB1 are biased toward peculiar values, based on the database DB1 Validity of the calculated non-defective product index rate value is lowered. Therefore, the conditions of the prototype are set so that the values of the physical quantities are distributed over a predetermined range in the database DB1, and the past data DT1 for constructing the database DB1 is extracted from the past data DT1 of all the prototypes. You can The distribution at this time may be an appropriate distribution form such as uniform distribution or normal distribution.

(Operation of molding system)
The operation of the molding system SM1 can be classified, for example, as follows. In the description here, the operation of the molding system SM1 will be briefly described in the following order.
・Action to accumulate past data DT1 ・Action to set numerical range for sorting based on past data DT1 ・Action to sort based on set numerical range ・Action to assist setting of numerical range (good product index rate operation to calculate)

(Accumulation of past data)
FIG. 3 schematically shows the operation of accumulating the past data DT1. FIG. 3 may be regarded as showing the operation when performing the above-mentioned first pass/fail judgment (pass/fail judgment for the molded product in the normal state and the molded product in the abnormal state). Then, it may be understood that it shows the operation when molding the prototype.

When the die casting machine 1 performs a molding cycle, physical quantities associated with the molding cycle are detected as indicated by arrows from the sensor 33 to the controller 13 . The physical quantity measurement value information DT<b>5 is transmitted from the machine-side transmission unit 35 and received by the support-side reception unit 45 of the support device 31 . At this time, identification information DT7 including information specifying the molding cycle in which the measured value included in the information DT5 was obtained is attached to the information DT5 on the measured value of the physical quantity.

The identification information DT7 is information specifying the molding cycle described in the above description of the marker 27. FIG. The identification information DT7 may be, for example, a character string arbitrarily assigned to the molding cycle by the control unit 13, or information on the time when the molding cycle was performed, as described above. The identification information DT7 may be generated by the control section 13, for example, and transmitted to the marker 27 via the machine-side transmission section 35 as well.

The marker 27 that has received the identification information DT7 marks the molded product with the identification information DT7. At this time, an appropriate measure may be taken so that the molding cycle indicated by the identification information DT7 and the molding cycle in which the molded article marked with the identification information DT7 is formed coincide with each other. For example, as already mentioned, the pick-up device 21 and the conveyor 23 (and the marker 27) operate synchronously with the die-casting machine 1 based on signals from the die-casting machine 1, and when a certain time has passed since the molding cycle, The molded product may be conveyed to the marker 27 immediately. Then, the marker 27 may mark the molded article conveyed to the marker 27 with the identification information DT7 when a certain period of time has elapsed after receiving the identification information DT7.

The molded product marked with the identification information DT7 by the marker 27 is judged as good or bad by a quality judgment device as an example or a part of the post-process device 29 . Then, the information DT9 of the determination result is received by the support side receiving section 45 of the support device 31 with the identification information DT7 attached. The post-process device 29 may, for example, read the identification information DT7 marked on the molded product by an imager, although not shown.

As described above, the support-side receiving unit 45 of the support device 31 receives the physical quantity measurement value information DT5 to which the identification information DT7 is attached and the quality determination result information DT9 to which the identification information DT7 is attached. . Then, the calculation unit 39 associates the information DT5 and the information DT9 with the same identification information DT7 (generates the past data DT1) and adds them to the database DB1. Thus, past data DT1 is accumulated.

(Set numerical range)
FIG. 4 schematically shows the operation of setting the numerical range used for sorting.

As indicated by an arrow from the operation unit 15 to the control unit 13 in the die casting machine 1 , for example, the control unit 13 receives input of the set value of the defective index rate via the operation unit 15 . That is, the operator inputs an arbitrary value as the set value of the defective product index rate. The input setting value information DT11 is transmitted from the machine-side transmission section 35 of the die-casting machine 1 to the support-side reception section 45 of the support device 31 and is acquired by the calculation section 39 .

Unlike the illustrated example, the set value of the defective product index rate may be input to the control unit 13 via the machine-side receiving unit 37 from an external input device (for example, a personal computer; hereinafter the same). Also, the setting value of the defective index rate may be input via an operation unit (not shown) included in the support device 31, or may be input to the support-side receiving unit 45 from an external input device. That is, the set value of the defective product index rate may be acquired by the calculation unit 39 without using the die casting machine 1 .

The calculation unit 39 identifies a numerical range that realizes the acquired setting value of the defective product index rate by referring to the database DB1 stored in the storage unit 41 . Information DT13 on the specified numerical range is transmitted from the support-side transmission unit 43 to the machine-side reception unit 37 of the die casting machine 1, and is acquired by the control unit 13 as well.

(sorting)
FIG. 5 schematically shows the sorting operation.

As described with reference to FIG. 4, the control unit 13 holds numerical range information DT13. Further, as indicated by an arrow from the sensor 33 to the control unit 13, the control unit 13 acquires measured values of physical quantities for each molding cycle. Then, the control unit 13 determines whether or not the acquired measured value of the physical quantity is out of the numerical range for each molding cycle, and outputs a different signal to the extraction device 21 according to the determination result. Then, the take-out device 21 sorts according to the received signal.

In addition, as already mentioned, based on the determination results of each of the plurality of types of physical quantities, it may be further determined whether the molded product is normal or abnormal, and this determination is also controlled. Section 13 may perform. The signal that differs according to the determination result as to whether the measured value of the physical quantity is out of the numerical range may be read as a signal indicating whether the molded product is normal or abnormal.

(Calculation of non-defective product index rate)
FIG. 6 schematically shows the operation of calculating the non-defective product index rate. FIG. 6 also shows some of the operations shown in FIG.

As described with reference to FIG. 4, the setting value of the defective product index rate (the information DT11) input to the operation unit 15 of the die casting machine 1 is sent via the machine side transmission unit 35 and the support side reception unit 45. , is obtained by the calculation unit 39 of the support device 31 . The calculation unit 39 calculates a numerical range that realizes the set value of the defective index rate, as described above. Further, the calculation unit 39 calculates the non-defective item index rate value based on the calculated numerical range and the database DB1 stored in the storage unit 41 . Information DT<b>15 on the calculated non-defective product index rate value is transmitted from the support-side transmission unit 43 to the machine-side reception unit 37 , and is acquired by the control unit 13 . As indicated by an arrow from the control unit 13 to the display unit 17, the value of the non-defective product index rate is displayed on the display unit 17, for example.

Although not particularly shown, the value of the non-defective product index rate calculated as described above is displayed, and at the same time, the control unit 13 displays a display inquiring whether sorting based on the set value of the input defective product index rate may be performed. may be caused to be performed by the display unit 17 . Then, the control unit 13 may accept an operation to approve the sorting based on the set value of the defective product index rate and an operation to reset the set value of the defective product index rate to the operation unit 15 . When the latter operation is performed, the numerical range setting and non-defective item index rate calculation described with reference to FIGS. 4 and 6 may be performed again.

As the information DT15 related to the non-defective product index rate value, the support device 31 provides information on the corresponding rank when the non-defective product index rate value is ranked, instead of or in addition to the information on the non-defective product index rate value itself. Alternatively, information on the determination result of whether the set value of the defective product index rate based on the value of the non-defective product index rate is appropriate may be sent. Alternatively, the control unit 13 may perform the above-described ranking classification or suitability determination based on the value of the non-defective product index rate received. Then, the display unit 17 may display the rank or determination result as described above instead of or in addition to the non-defective product index rate value itself.

(Specific example of how to set the numerical range)
Various specific procedures may be used to identify the numerical range that achieves the set value of the defective index rate. An example of a specific procedure will be described with reference to FIGS. 8 and 9. FIG.

First, a reference value indicated by line RL is set. The reference value is, for example, a representative value (e.g., average value or median value) of the physical quantity of non-defective product data. Next, an upper limit value and a lower limit value that make the difference d1 (only the absolute value) from the reference value equal to each other and that can realize the set value of the defective index rate are calculated. .

Any suitable method may be used to calculate the upper limit value and the lower limit value that can achieve the set value of the defective product index rate. For example, by repeating the process of setting temporary upper and lower limit values and calculating the defective index rate while decreasing or increasing the difference d1, the upper limit value and the lower limit value that can realize the set value of the defective index rate. may be calculated. Also, for example, the values of the physical quantities of defective products are arranged in descending order of the difference d3 from the reference value, and the set value of the defective product detection rate (ratio of defective products in normal and abnormal conditions to defective products in normal and abnormal conditions) A value between the corresponding order difference d3 and the next order difference d3 may be specified as the difference d1 from the reference value of the upper and lower limits.

For example, when the order difference d3 corresponding to the setting value of the defective product detection rate and the next order difference d3 are the same, this same difference d3 is the reference value for the upper limit and the lower limit. Alternatively, the difference d3 next to the same difference d3 may be used as the difference d1 between the upper limit value and the lower limit value from the reference value. Thus, the upper limit value or lower limit value for realizing the set value of the defective index rate may have an error corresponding to a small number of samples equal to or greater than one.

The above procedure may be modified as appropriate. For example, the reference value may be calculated based on the physical quantity values of defective products or the physical quantity values of all molded products, instead of being calculated based on the physical quantity values of non-defective products. Upper and lower limits may be specified without calculating the reference value. For example, setting a temporary numerical range having a temporary width (2×d1), and moving the temporary numerical range in the direction of the vertical axis PQ, the position of the temporary numerical range that can achieve the set value of the defective index rate. The process of determining whether or not there exists may be repeated while decreasing or increasing the width (2×d1).

There are multiple numerical ranges that can achieve the same defective index rate. For example, in FIG. 9, two defective products (N9 and N8) with large physical quantity values are excluded and the defect detection rate is 40%. The defect detection rate can be 40% by excluding the defective product (N2) with the smallest value, or 40% by excluding two defective products (N2 and N3) with small physical quantity values. A plurality of numerical ranges can be identified depending on the method of identifying numerical ranges. In such a case, an appropriate method may be used to specify a numerical range to be actually used for sorting from a plurality of numerical ranges. For example, the non-defective product content ratio (ratio of non-defective products to the molded products in the abnormal state) when using each numerical range may be calculated, and the numerical range with the smallest non-defective product content ratio may be selected.

(Example of how to select the type of physical quantity to be judged)
The types of physical quantities used for sorting may be selected as appropriate.

For example, the types of physical quantities used for sorting may be selected by the manufacturer of molding system SM1. From another point of view, the information specifying the types of physical quantities used for sorting may be stored in advance in the ROM or external storage device of the die casting machine 1 and/or the support device 31 . Also, for example, the type of physical quantity used for sorting may be selected by the operator of the die casting machine 1 . From another point of view, information specifying the type of physical quantity used for sorting may be input via the operation unit 15 or the like and stored in the die casting machine 1 and/or the external storage device of the support device 31 .

Further, for example, the type of physical quantity used for sorting may be selected by the control unit 13 of the die casting machine 1 or the calculation unit 39 of the support device 31 based on the database DB1. At this time, the control unit 13 or the calculation unit 39 may select the type of physical quantity according to a predetermined algorithm, or may select the type of physical quantity using AI technology. Below, an example of the procedure when the calculation unit 39 selects the type of physical quantity according to a predetermined algorithm is shown.

FIG. 10 is a flow chart showing an example of a procedure of processing for selecting the type of physical quantity (hereinafter sometimes referred to as “determination target”) used for sorting executed by the calculation unit 39 . This process may be performed, for example, at any time after the past data DT1 are accumulated to construct the database DB1 and before the sorting operation using the database DB1 is executed.

In FIG. 10, for ease of explanation, the defective product detection rate (ratio of defective products in defective products to defective products) is taken as an example of the defective product index rate, and the non-defective product content rate ( ratio of non-defective products to molded products) is taken as an example. In the following description, words such as "large" or "small" may be read as opposite words such as "small" or "large" depending on the type of index rate.

At step ST1, the calculation unit 39 selects an arbitrary physical quantity from among a plurality of types of physical quantity. It should be noted that the plurality of types of physical quantities are measured by the die casting machine 1, and the measured values are included in the past data DT1.

In step ST2, the calculation unit 39 sets a provisional value (virtual value) as the setting value of the defective product index rate. This virtual value may be preset by the manufacturer of the support device 31 or may be set by the operator of the die casting machine 1, for example. In other words, it may be stored in advance in the ROM of the support device 31 or an external storage device, or may be input via the operation unit 15 . Also, the virtual value may be set for each type of physical quantity.

In step ST3, the calculation unit 39 refers to the database DB1 to specify a numerical range that realizes the above tentative set values, and calculates a non-defective product index rate when using the specified numerical range. The calculation procedure at this time may be the same as the above-described procedure until the non-defective product index rate is calculated from the set value of the defective product index rate.

In step ST4, the calculation unit 39 determines whether the calculated non-defective product content rate is smaller than a predetermined threshold. The threshold value may be preset by the manufacturer of the support device 31 or may be set by the operator of the die casting machine 1, for example. In other words, it may be stored in advance in the ROM of the support device 31 or an external storage device, or may be input via the operation unit 15 . Also, the threshold may be set for each type of physical quantity.

Here, the reason why the non-defective product content rate is high is that the set value of the defect index rate is too strict (in other words, the set value of the defective product detection rate is too high, or the numerical range corresponding to the set value is narrow). too much), or the correlation between the physical quantity and the quality of the molded product is low. Therefore, for example, when the temporary set value of the defective product detection rate set in step ST2 is set to a moderately low value, the non-defective product content rate being equal to or higher than the threshold value in step ST4 means that the currently selected physical quantity It means that the correlation between (the physical quantity selected in step ST1) and the quality of the molded product is low.

Accordingly, when the determination in step ST4 is affirmative, the calculation unit 39 proceeds to step ST5 and designates the currently selected physical quantity as the physical quantity to be determined (physical quantity used for sorting). On the other hand, if a negative determination is made in step ST4, step ST5 is skipped.

In step ST6, the calculation unit 39 determines whether or not the processes of steps ST1 to ST5 have been performed for all physical quantities. Then, in the case of a negative determination, the calculation unit 39 returns to step ST1 and performs similar processing for other physical quantities. Moreover, in the case of an affirmative determination, the calculation unit 39 terminates the processing.

Information on the type of physical quantity specified in step ST5 is transmitted from the support-side transmitter 43 of the support device 31 to the machine-side receiver 37 of the die casting machine 1 as designation information DT17, for example, as indicated by the dotted line in FIG. may be Then, the control unit 13 may perform the sorting using the measured value of the physical quantity of the type designated by the designation information DT17. Further, when receiving an input of a set value of the defective product index rate via the operation unit 15, the control unit 13 presents the type of physical quantity specified by the specification information DT17 through the display unit 17, and Input of the set value of the defective index rate may be accepted only for the type of physical quantity.

The temporary set value of the defective product index rate in step ST2 and the specific size of the threshold value of the non-defective product index rate in step ST4 may be set as appropriate. To give an example from the standpoint of excluding physical quantities with extremely low correlation, the provisional set value of the defective product detection rate may be set to 50%, and the threshold value of the non-defective product content rate may be set to 50%. Even if half of the defective products can be excluded as abnormal molded products, if half of the abnormal molded products are non-defective, the physical quantity cannot be said to be appropriate for sorting. . Further, to give an example from the viewpoint of selecting a physical quantity with a higher correlation, the temporary set value of the defective product detection rate may be set to 90%, and the threshold value of the non-defective product content rate may be set to 1%.

In the process of FIG. 10, the value of the pass/fail index rate is checked for only one provisional set value (step ST2) for one type of physical quantity. However, the non-defective item index rate value may be checked for a plurality of temporary set values. In this case, for example, from a plurality of temporary setting values for the defective product detection rate, a temporary setting value that makes the non-defective product content rate less than the threshold is specified, and when the specified temporary setting value is equal to or greater than a predetermined allowable value, Specify the physical quantity as the physical quantity for sorting, or specify the physical quantity as the physical quantity for sorting when the absolute value of the change rate of the decrease in the non-defective product content ratio increases as the temporary set value increases. You can

(Summary of embodiment)
As described above, the molding machine (die casting machine 1) according to the present embodiment includes the machine main body 3, the sensor 33, the set value reception section (operation section 15), the machine side transmission section 35, and the machine side reception section 37. and a sorting unit (control unit 13). The machine body 3 repeats a molding cycle in which the molding material is filled into the cavity Ca to produce a molded product. The sensor 33 measures physical quantities related to the molding cycle. The operation unit 15 accepts input of a set value of the defective product index rate. The defective product index rate is determined when a plurality (in other words, an arbitrary predetermined number) of molding cycles (does not have to be continuous molding cycles) are performed, and the measured value of the physical quantity is outside the predetermined numerical range. It can be defined as the ratio of defective products included in the molded products produced by the molding cycle having the value to the molded products produced by the plurality of molding cycles, or the ratio correlated to the ratio. The machine-side transmission unit 35 transmits the set value of the defective product index rate input to the operation unit 15 to the support device 31 . The machine-side transmission unit 35 receives from the support device 31 the information on the numerical range corresponding to the setting value of the defective product index rate transmitted by the machine-side transmission unit 35 . The control unit 13 targets a plurality of molded products manufactured by the machine main body 3 by repeating the molding cycle, and determines whether the measured values of the physical quantities measured by the sensor 33 are outside the numerical range received by the machine-side receiving unit 37. A process for sorting out the molded products manufactured by one molding cycle from the molded products manufactured by other molding cycles is performed.

From another point of view, the support device 31 according to this embodiment has a storage unit 41 , a support-side reception unit 45 , a calculation unit 39 , and a support-side transmission unit 43 . The storage unit 41 stores a plurality (in other words, an arbitrary predetermined number) of past data DT1. Each past data DT1 includes measured values of physical quantities related to a molding cycle in which a molding material is filled into a cavity Ca to produce a molded product, and molded products produced by the molding cycle in which the measured values are obtained are non-defective products and defective products. and information of the determination result as to which one. The support-side receiving unit 45 receives the set value of the defective product index rate from the molding machine (the die casting machine 1). The defective product index rate is the ratio of the past data DT1 in which the measured value is outside a predetermined numerical range and the determination result is defective, or the ratio correlated with the ratio, among the plurality of past data DT1. can be defined. The calculation unit 39 specifies a numerical range in which the defective index rate for the plurality of past data DT1 stored in the storage unit 41 is the set value of the defective index rate received by the support-side receiving unit 45 . The support-side transmission unit 43 transmits the numerical range information DT13 specified by the calculation unit 39 to the die casting machine 1 .

From yet another viewpoint, the molding system SM1 includes the machine body 3, the sensor 33, the storage unit 41, the set value reception unit (operation unit 15), the calculation unit 39, and the sorting unit (control unit 13 and/or and a take-out device 21). The machine body 3 repeats a molding cycle in which the molding material is filled into the cavity Ca to produce a molded product. The sensor 33 measures physical quantities related to the molding cycle. The storage unit 41 stores a plurality of past data DT1. Each piece of past data DT1 includes a measured value of a physical quantity and information on the determination result as to whether the molded product manufactured by the molding cycle in which the measured value was obtained is a non-defective product or a defective product. The operation unit 15 accepts input of a set value of the defective product index rate. The defective product index rate is the molding cycle in which the measured value of the physical quantity in the molded product manufactured by the plurality of molding cycles becomes a value outside the predetermined numerical range when a plurality of molding cycles is performed. It can be defined as the percentage of defective items in an article, or the percentage that correlates to that percentage. The calculation unit 39 identifies a numerical range in which the defective product index rates for the plurality of past data DT1 stored in the storage unit 41 are set values input to the operation unit 15 . The control unit 13 and/or the take-out device 21 controls that the measured values of the physical quantities measured by the sensor 33 are within the numerical range specified by the calculation unit 39 for a plurality of molded products manufactured by the machine body 3 by repeating the molding cycle. A process of sorting the molded products produced by the molding cycle having the outside value from the molded products produced by the other molding cycles is performed.

Therefore, for example, as described above, it is possible to set a numerical range that achieves a desired defective product index rate regardless of the operator's experience, and by extension, post-processing is performed on defective products, Controlling the resulting wasteful costs is facilitated.

In the die-casting machine 1, the machine-side receiving section 37 receives information DT15 related to the non-defective-product index rate value corresponding to the numerical range corresponding to the set value of the defective-product index rate transmitted by the machine-side transmitting section 35 from the support device 31. You can The non-defective product index rate can be defined as the ratio of non-defective products among the molded products produced by the molding cycle in which the measured value of the physical quantity is out of the numerical range, or the ratio correlated with this ratio. The die-casting machine 1 may further include a notification unit for notifying the operator of the information DT15 related to the non-defective product index rate received by the machine-side receiving unit 37 .

From another point of view, in the support device 31 , the calculation unit 39 uses the numerical range specified based on the setting value of the defective product index rate received by the support-side receiving unit 45 to determine the plurality of values stored in the storage unit 41 . may specify the value of the non-defective product index rate for the past data DT1. The non-defective product index rate can be defined as the ratio of the past data DT1 in which the determination result is a non-defective product to the past data DT1 in which the measured value of the physical quantity is a value outside the numerical range, or the ratio correlated with this ratio. The support-side transmission unit 43 may transmit information DT15 related to the non-defective product index rate specified by the calculation unit 39 to the die casting machine 1 .

In this case, for example, as described above, it is facilitated to verify the validity of the set value of the defective index rate. For example, if the non-defective product content rate is too high, it can be determined that the set value of the defective product index rate is too strict (eg, the defective product content rate is too low). Further, for example, as understood from the description of FIG. 10, the operator can also consider whether or not the type of physical quantity used for sorting is appropriate. In response to such an effect, the die casting machine 1 may be capable of accepting selection of the type of physical quantity used for sorting via the operation section 15, as already described.

The die casting machine 1 may have multiple sensors 33 that measure multiple types of physical quantities. The machine-side receiving section 37 may receive designation information DT17 that designates one or more types of physical quantities among a plurality of types. The sorting unit (control unit 13) may sort the molded products based on the numerical range only for the type of physical quantity designated by the designation information DT17 among the plurality of types of physical quantity.

From another point of view, in the support device 31, the plurality of past data DT1 may each include measurement values of a plurality of types of physical quantities and information on the quality determination result of the molding cycle from which the measurement values were obtained. The calculation unit 39 may select one or more types from among the plurality of types of physical quantities based on the plurality of past data DT1. The support-side transmission unit 43 may transmit designation information DT17 indicating one or more types selected by the calculation unit 39 to the die casting machine 1 .

In this case, for example, the operator does not have to select the type of physical quantity used for sorting based on empirical rules. As a result, the operator's burden is reduced. Situations in which the operator's burden is reduced include, for example, a case where a new type of physical quantity (a new sensor from another point of view) is introduced as a measurement target. Moreover, even if the type of physical quantity highly correlated with the quality of the molded product varies depending on the type of the mold 101, the type of the die casting machine 1, and the operating state of the die casting machine 1, the burden on the operator can be reduced.

The calculation unit 39 determines the type of physical quantity in which the non-defective product index rate corresponding to the numerical range when the defective product index rate is a predetermined virtual value is located on the side where the non-defective product content rate is low with respect to a predetermined threshold value. may be included in the one or more types specified by the specification information DT17.

In this case, for example, a simple algorithm using the non-defective product index rate can be used to determine the degree of correlation between the physical quantity and the quality of the molded product, and select the physical quantity to be used for sorting. In addition, in a mode in which the molding system SM1 has a function of presenting the value of the non-defective product index rate corresponding to the set value of the defective product index rate to the operator, part of the function is used to determine whether the types of physical quantities are appropriate. Available.

In the above embodiments, the die casting machine 1 is an example of a molding machine. A metal material is an example of a molding material. The control unit 13 that transmits a signal for causing the take-out device 21 that performs sorting to perform sorting is an example of a sorting unit that performs sorting processing. Note that the take-out device 21 may be regarded as an example of the sorting section of the molding system.

The operation unit 15 is an example of a setting value reception unit that receives input of a setting value of the defective product index rate. The control unit 13 that acquires the set value of the defective index rate via the operation unit 15 may be regarded as an example of the set value receiving unit. In the description of the operation of setting the numerical range with reference to FIG. 4, it has been described that the set value of the defective product index rate may be input without going through the operation unit 15 . As can be understood from this description, the machine-side receiving unit 37 that receives information related to setting values from the outside can be regarded as an example of a setting value receiving unit of a die casting machine, and support for receiving information related to setting values from the outside can be understood. The side receiving unit 45 or the operation unit (not shown) of the support device 31 may be regarded as an example of the set value receiving unit of the molding system.

The technology according to the present disclosure is not limited to the above embodiments, and may be implemented in various forms.

For example, molding machines are not limited to die casting machines. For example, the molding machine may be another metal molding machine, an injection molding machine that molds resin, or a molding machine that molds a material obtained by mixing wood flour with thermoplastic resin or the like. There may be. Further, the molding machine is not limited to horizontal clamping and horizontal injection, and may be, for example, vertical clamping and vertical injection, vertical clamping and horizontal injection, or horizontal clamping and vertical injection.

As mentioned in the embodiment, the molding system does not have to be capable of distinguishing between the molding machine and the support device. For example, at least one of a storage unit that stores a plurality of past data and a computing unit that specifies numerical ranges and the like for a plurality of past data may be housed in a housing together with the control unit of the molding machine. and hardware resources (CPU, ROM, RAM, and external storage device).

The division of roles between the die casting machine and the supporting device may differ from the embodiment. For example, in the embodiment, the die casting machine determines whether the measured value of the physical quantity is within the numerical range, but the determination may be performed by a support device.

Inventions that do not include the requirement of setting a numerical range based on the set value of the defective index rate may be extracted from the present disclosure. For example, an invention focused on selecting the type of physical quantity to be determined as shown in FIG. 10 may be extracted. In such an invention, the numerical range may be set, for example, by an operator based on experience, or the numerical range is calculated by the molding system or support device so that the non-defective product content is equal to or less than a predetermined set value. may

DESCRIPTION OF SYMBOLS 1... Die casting machine (molding machine), 3... Machine main body, 5... Control part 13... Cooling part, 15... Spray apparatus, 59... Temperature sensor (sensor), 101... Mold (mold).

Claims (10)

a machine body that repeats the molding cycle of filling the molding material into the cavity to produce a molded product;
a sensor that measures a physical quantity related to the molding cycle;
When a plurality of molding cycles are performed, the molded product manufactured by the molding cycle in which the measured value of the physical quantity is a value outside the predetermined numerical range is a molded product manufactured by the plurality of molding cycles. a set value receiving unit that receives an input of a set value of the defective product index rate when the ratio of the defective product index rate or the ratio that correlates to the ratio is referred to as the defective product index rate;
a machine-side transmission unit that transmits the setting value input to the setting value reception unit to a support device;
a machine-side receiving unit that receives, from the support device, information on the numerical range corresponding to the setting value transmitted by the machine-side transmitting unit;
Molding in which the measured value of the physical quantity measured by the sensor is a value outside the numerical range received by the machine-side receiving unit for a plurality of molded products manufactured by the machine body by repeating the molding cycle. a sorting unit that performs a process of sorting the molded products produced by the cycle from the molded products produced by other molding cycles;
A molding machine having a The defective product index rate is
The ratio of defective products to the molded products produced by the molding cycle in which the measured value of the physical quantity is a value within the numerical range,
Percentage of defective products among the molded products manufactured by the plurality of molding cycles, including defective products manufactured by molding cycles in which the measured value of the physical quantity is outside the numerical range, or by the plurality of molding cycles 2. The molding machine according to claim 1, which is a ratio of defective products among manufactured defective products, which are included in molded products manufactured by a molding cycle in which the measured value of the physical quantity is a value outside the numerical range. When the ratio of non-defective products in the molded product produced by the molding cycle in which the measured value of the physical quantity is outside the numerical range, or the ratio correlated to the ratio, is referred to as the non-defective product index rate,
The machine-side receiving unit receives from the support device information related to the value of the non-defective product index rate corresponding to the numerical range corresponding to the setting value transmitted by the machine-side transmitting unit,
3. The molding machine according to claim 1, further comprising a notification unit for notifying an operator of the information related to the non-defective product index rate received by the machine-side receiving unit. The non-defective product index rate is
Percentage of non-defective products in molded products produced by a molding cycle in which the measured value of the physical quantity is a value outside the numerical range,
Percentage of non-defective products among the molded products manufactured by the plurality of molding cycles, which are included in the molded products manufactured by the molding cycles in which the measured value of the physical quantity is within the numerical range, or manufactured by the plurality of molding cycles 4. The molding machine according to claim 3, wherein the ratio of non-defective products among the non-defective products produced by the molding cycle in which the measured value of the physical quantity falls within the numerical range. Having a plurality of sensors for measuring a plurality of types of physical quantities,
The machine-side receiving unit receives designation information designating one or more types of the plurality of types of physical quantities,
5. The sorting unit according to any one of claims 1 to 4, wherein the sorting unit sorts the molded products based on the numerical range only for physical quantities of the type specified by the specified information among the plurality of types of physical quantities. Molding machine. Measured values of physical quantities related to a molding cycle in which a molded product is produced by filling a molding material into a cavity, and whether the molded product produced by the molding cycle in which the measured values are obtained is a non-defective product or a defective product. a storage unit that stores a plurality of pieces of past data each including information on determination results;
The percentage of the past data in which the measured value is outside the numerical range and the determination result is defective, or the percentage correlated with the percentage, in the plurality of past data is referred to as the defective index rate. a support-side receiving unit that receives the set value of the defective product index rate from the molding machine;
a computing unit that identifies the numerical range in which the defective product index rate for the plurality of past data stored in the storage unit is the set value received by the support-side receiving unit;
a support-side transmission unit that transmits information on the numerical range specified by the calculation unit to the molding machine;
A support device for a molding machine having When the ratio of the past data in which the determination result is a non-defective product to the past data in which the measured value is a value outside the numerical range, or the ratio correlated with the ratio, is referred to as the non-defective product index rate,
The calculation unit calculates the non-defective product index rate values for the plurality of past data stored in the storage unit using the numerical range specified based on the set value received by the support-side reception unit. identify,
7. The molding machine support device according to claim 6, wherein the support-side transmission unit transmits information related to the non-defective product index rate specified by the calculation unit to the molding machine. The plurality of past data includes measured values of the plurality of types of physical quantities and information on the determination result of the molding cycle in which the measured values were obtained,
The calculation unit selects one or more types of the plurality of types of physical quantities based on the plurality of past data,
The support device for a molding machine according to claim 6 or 7, wherein the support-side transmission unit transmits designation information indicating the one or more types selected by the calculation unit to the molding machine. The ratio of the past data in which the determination result is a non-defective item to the past data in which the measured value is a value outside the numerical range is referred to as the non-defective item content rate, and the non-defective item content rate or the percentage correlated with the non-defective item content rate is referred to as the non-defective item content rate. When referring to the index rate,
The calculation unit is configured such that the value of the non-defective product index rate corresponding to the numerical range when the defective product index rate is a predetermined virtual value is positioned on the side where the non-defective product content rate is lower than a predetermined threshold value. 9. The support device for a molding machine according to claim 8, wherein the one or more types of physical quantities to be processed are included in the one or more types. a machine body that repeats the molding cycle of filling the molding material into the cavity to produce a molded product;
a sensor that measures a physical quantity related to the molding cycle;
storing a plurality of pieces of past data each including a measured value of the physical quantity and information of a judgment result as to whether the molded product manufactured by the molding cycle in which the measured value is obtained is a non-defective product or a defective product; a storage unit;
When a plurality of molding cycles are performed, the molded product manufactured by the molding cycle in which the measured value of the physical quantity occupies the molded product manufactured by the plurality of molding cycles is a value outside the predetermined numerical range. a setting value receiving unit that receives an input of a setting value for the defective product index rate when the ratio of non-defective products or a ratio that correlates with the ratio is referred to as the defective product index ratio;
a calculation unit that specifies a numerical range in which the defective product index rate for the plurality of past data stored in the storage unit is the set value input to the set value reception unit;
For a plurality of molded products manufactured by the machine main body by repeating the molding cycle, the measured value of the physical quantity measured by the sensor becomes a value outside the numerical range specified by the calculation unit. a sorting unit that performs a process of sorting the manufactured molded product from the molded products manufactured by other molding cycles;
A molding system having a

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