Injection molding system

Abstract

To shorten a trial shot period.SOLUTION: An injection molding machine repeatedly performs injection molding of a resin using a mold according to a molding cycle based on predetermined molding conditions. A measurement system outputs a plurality of measurement values corresponding to a plurality of physical quantities every time injection molding is performed. An adjustment device 1 stores the plurality of measurement values corresponding to the plurality of physical quantities in time series, and adjusts the molding conditions based on a plurality of time series data corresponding to the plurality of physical quantities, which are generated thereby. The molding conditions include a planned cooling time value related to a cooling time included in the molding cycle. The adjustment device 1 includes a first calculation unit 12 and an adjustment unit 13, and the first calculation unit 12 calculates a theoretical cooling time value using the plurality of time series data and a calculation formula. When a feasible condition is satisfied that the planned cooling time value is longer than the theoretical cooling time value by a threshold value or more, the adjustment unit 13 adjusts the molding conditions so that a trial shot period before the mold reaches a thermal equilibrium state is shortened.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to an injection molding system, and more particularly to an injection molding system that repeatedly performs injection molding of resin using a mold. [Background technology]

[0002] Patent Document 1 describes a mold temperature control device that measures the temperature of the mold and rapidly raises the mold temperature by not introducing a cooling medium into the mold until the measured temperature reaches a target temperature, thereby reducing the number of waste shots (molded products that have defects such as partial defects or non-uniformity due to a low mold temperature) at the start of mass production. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2001-18275 A Summary of the Invention [Problem to be solved by the invention]

[0004] In the above-mentioned mold temperature control device, when the mold temperature is increased, the cooling time required for the resin injected into the mold to cool and become a molded product that can be removed from the mold becomes longer, which can ultimately lengthen the throw-away shot period during which throw-away shots occur.

[0005] An object of the present disclosure is to provide an injection molding system that can shorten the trial injection period. [Means for solving the problem]

[0006] An injection molding system according to one aspect of the present disclosure includes a mold, an injection molding machine, a measurement system, and an adjustment device. The injection molding machine repeatedly performs injection molding of a resin using the mold according to a molding cycle based on predetermined molding conditions. The measurement system measures a plurality of physical quantities related to the injection molding each time the injection molding machine performs the injection molding, and outputs a plurality of measurement values ​​corresponding to the plurality of physical quantities. The adjustment device adjusts the molding conditions based at least on a plurality of time-series data corresponding to the plurality of physical quantities, which are generated by storing the plurality of measurement values ​​output by the measurement system in a time series. The molding cycle includes a cooling time. The cooling time is a time from when the resin is injected into the mold by the injection molding machine until the injected resin is cooled and can be removed from the mold. The molding conditions include a cooling time scheduled value. The cooling time scheduled value is a predetermined value of the cooling time. The adjustment device includes a calculation unit and an adjustment unit. The calculation unit calculates a theoretical cooling time value, which is a theoretical value of the cooling time, by using the plurality of time-series data and a calculation formula or information equivalent to the calculation formula. The adjustment unit adjusts the molding conditions so as to shorten the run-off period when a feasible condition is satisfied. The feasible condition is a condition that the planned cooling time value is longer than the theoretical cooling time value by a threshold value or more. The run-off period is a period before the mold reaches a thermal equilibrium state. Effect of the Invention

[0007] The injection molding system of the present disclosure has the effect of shortening the trial injection period. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a conceptual diagram of an injection molding system according to an embodiment of the present disclosure. [Diagram 2] FIG. 2 is a block diagram of an adjustment device constituting the above-mentioned injection molding system. [Diagram 3] FIG. 3 is a flowchart illustrating the operation of the injection molding system. [Figure 4] FIG. 4 is a flow chart for explaining a molding condition adjustment process (shortening the cooling time included in the molding cycle) by the adjustment device. [Diagram 5] FIG. 5 is a bar graph showing an example of adjustment by the molding condition adjustment process (shortening the dwell time during which pressure is maintained while cooling, which is included in the molding cycle). [Figure 6] FIG. 6 is a bar graph showing another example of the above adjustment (shortening the above dwell time and cooling time for performing cooling without dwell time, which are included in the molding cycle). [Figure 7] FIG. 7 is a bar graph showing another example of the above adjustment (shortening the above dwell time, the above cooling time and the above weighing time, which are included in the molding cycle). [Figure 8] FIG. 8 is a graph showing an example of the above adjustment (adjustment for bringing the predicted ascending curve closer to the target ascending curve while shortening the cooling time included in the molding cycle). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] The various physical quantities, various measuring instruments and their arrangements, various measured values, various time-series data, and calculation formulas given in the following description are merely examples and may be changed as appropriate.

[0010] (1) Overview An injection molding system 100 according to an embodiment of the present disclosure includes a mold 20, an injection molding machine 10, a measurement system 2, and an adjustment device 1, as shown in FIG.

[0011] (1-1) Mold The mold 20 is a mold for injection molding of resin. The resin is, for example, a thermoplastic resin such as polypropylene or polycarbonate, but may be a thermosetting resin such as melamine resin. The resin may contain a filler such as metal powder or glass fiber, and the material of the resin is not important. A measured amount of resin is injected into the mold 20 by the injection molding machine 10. The resin injected into the mold 20 is cooled until it can be removed from the mold 20 as a molded product.

[0012] (1-2) Injection molding machine The injection molding machine 10 performs injection molding of a resin using a mold 20. The injection molding machine 10 repeatedly executes injection molding according to a molding cycle based on predetermined molding conditions. The repeated execution is, for example, continuous execution, but may also be intermittent execution. The injection molding machine 10 is, for example, a vent-type molding machine or a DSI (Die Slide Injection Molding) molding machine, but is not limited thereto.

[0013] (1-2-1) Molding conditions The molding conditions are conditions related to injection molding, such as values ​​of time, temperature, pressure, etc., that are preset for each step of injection molding. The predetermined molding conditions are, for example, molding conditions used during mass production.

[0014] (1-2-1a) Mass production period The mass production period is the period after the trial run period described below, and is the period after the mold 20 reaches thermal equilibrium. The mass production period is the period during which "mold thermal equilibrium temperature - mold temperature ≦ predetermined temperature" is satisfied. In other words, the mass production period is the period during which the necessary conditions described below are not satisfied.

[0015] During mass production, the mold temperature is relatively high (either the mold thermal equilibrium temperature is reached or the difference between the mold thermal equilibrium temperature and the actual temperature is less than a specified temperature), so there is little possibility of defects in the molded product occurring due to a low mold temperature.

[0016] (1-3) Measurement system The measurement system 2 measures a plurality of physical quantities related to injection molding. The measurement system 2 measures a plurality of physical quantities related to injection molding every time the injection molding machine 10 executes injection molding, and outputs a plurality of measurement values ​​corresponding to the plurality of physical quantities.

[0017] (1-3-1) Multiple physical quantities and multiple measured values The plurality of physical quantities are, for example, a mold temperature and a resin temperature, etc. The plurality of measured values ​​are, for example, a mold temperature measured value and a resin temperature measured value, etc.

[0018] (1-4) Adjustment device The adjustment device 1 adjusts molding conditions. The adjustment of molding conditions is, for example, adjustment of time, temperature, pressure, etc. The adjustment of molding conditions is particularly shortening the cooling time (at least one of the pressure holding time with cooling and the pressure-free cooling time) in order to shorten the throw-off period. As shown in Fig. 5, the adjustment of molding conditions may be to bring the planned cooling time closer to the theoretical cooling time T20 when a predetermined cooling time T2 (hereinafter, referred to as the "planned cooling time") included in the molding cycle is longer than the theoretical cooling time T20.

[0019] The adjustment device 1 stores, in time series, a plurality of measurement values ​​corresponding to a plurality of physical quantities output by the measurement system 2. Then, the adjustment device 1 adjusts molding conditions based at least on a plurality of time-series data corresponding to a plurality of physical quantities generated by storing the measurement values ​​in time series.

[0020] Storing in chronological order may mean, for example, storing measurement values ​​such as mold temperature measurement values ​​in association with a cycle number "i" indicating which molding cycle the measurement value is in. Alternatively, the measurement values ​​may be stored in association with current time information, or may be stored in chronological order starting from the oldest value without association with the cycle number or the like.

[0021] (1-4-1) Multiple time series data The time series data is data in which a plurality of measurement results corresponding to one physical quantity are arranged in a chronological order. The plurality of time series data includes mold temperature time series data and resin temperature time series data.

[0022] For example, if the current molding cycle is the nth molding cycle (cycle number n), the time series data is made up of n measurement values ​​corresponding to the n molding cycles from the 1st to the nth molding cycles (the 1st molding cycle to the nth molding cycle). The time series data indicates the change in physical quantity over time.

[0023] In the adjustment device 1, a plurality of time series data corresponding to a plurality of physical quantities are input to a trained model 131a of a neural network, and a plurality of calculation data are output from the trained model 131a. Then, the adjustment device 1 calculates an adjustment value based on the plurality of output calculation data, and adjusts the molding conditions based on the calculated adjustment value.

[0024] (1-4-2) Cooling time The molding cycle includes a cooling time T2, as shown in Fig. 5. The cooling time T2 is the time it takes for the resin injected into the mold 20 by the injection molding machine 10 to be cooled and become removable from the mold 20.

[0025] (1-4-3) Estimated cooling time The molding conditions include a cooling time estimate, which is a predetermined value for the cooling time T2.

[0026] (1-4-4) Calculation and adjustment section As shown in FIG. 2, the adjustment device 1 includes a calculation unit 12 and an adjustment unit 13.

[0027] The calculation unit 12 calculates a theoretical cooling time value, which is a theoretical value of the cooling time T2, by using a plurality of time series data and a calculation formula or information equivalent to the calculation formula. The information equivalent to the calculation formula is, for example, a data table regarding the correspondence between the values ​​of variables included in the calculation formula and the values ​​calculated by the calculation formula, or a machine learning trained model in which the values ​​of variables are input and the calculated values ​​are output.

[0028] When the feasible conditions are met, the adjustment unit 13 adjusts the molding conditions so that the trial shot period is at least shortened.

[0029] (1-4-4a) Possible conditions The possible condition is a condition regarding whether or not the cooling time T2 can be shortened. The possible condition is a condition that the scheduled cooling time is longer than the theoretical cooling time T20 by a predetermined time or more (for example, the scheduled cooling time is longer than the theoretical cooling time by a first threshold or more).

[0030] (1-4-4b) Throw-away period The run-off period is a period before the mold 20 reaches a thermal equilibrium state. The run-off period is a period during which "mold thermal equilibrium temperature - mold temperature>predetermined temperature" (e.g., "mold thermal equilibrium temperature predicted value - mold temperature measured value>second threshold value") is satisfied. In other words, the run-off period is a period during which the necessity condition described below is satisfied.

[0031] During the trial injection period, the mold temperature is relatively low (for example, lower than the mold thermal equilibrium temperature by a certain temperature or more), so the resin injection molding may be incomplete, which may result in defects in the molded product.

[0032] (1-5)Advantages In this manner, according to this embodiment, when the cooling time T2 can be shortened, the adjustment unit 13 adjusts the molding conditions, thereby making it possible to shorten at least the trial shot period.

[0033] By adjusting the molding conditions, the mass production period may be shortened together with the run-off period. However, during the run-off period, the mold temperature has not yet reached the mold thermal equilibrium temperature and there is a large room for it to rise, so it is often possible to shorten the cooling time T2, whereas during the mass production period, the mold temperature has already reached the mold thermal equilibrium temperature and there is little room for it to rise, so there are few cases where it is possible to shorten the cooling time T2. Therefore, at least the run-off period can be shortened.

[0034] (2) Details The calculation unit 12 described in the overview is referred to as the first calculation unit 12 in the following description.

[0035] (2-1) Details of multiple physical quantities As described above, the multiple physical quantities include the mold temperature and the resin temperature. The mold temperature is the temperature of the mold 20. More specifically, the mold temperature is the temperature of the surface of the mold 20 (the surface in contact with the outside air). The resin temperature is the temperature of the resin injected into the mold 20. More specifically, the resin temperature is the temperature of the portion of the resin injected into the mold 20 that is in contact with the inner surface of the mold 20 (the surface in contact with the resin), and may be considered to be equal to the temperature of the inner surface of the mold 20.

[0036] (2-2) Details of multiple measurements As described above, the plurality of measurement values ​​include the mold temperature measurement value and the resin temperature measurement value. The mold temperature measurement value is a measurement value corresponding to the mold temperature. The resin temperature measurement value is a measurement value corresponding to the resin temperature.

[0037] (2-3) Details of multiple time series data As described above, the multiple time series data include mold temperature time series data and resin temperature time series data. The mold temperature time series data is time series data corresponding to the mold temperature. The mold temperature time series data is data in which multiple mold temperature measurement values ​​corresponding to the mold temperature are arranged in time series. The resin temperature time series data is time series data corresponding to the resin temperature. The resin temperature time series data is data in which multiple resin temperature measurement values ​​corresponding to the resin temperature are arranged in time series.

[0038] (2-4) Judgment of feasible conditions by the Coordination Department The adjustment unit 13 judges whether the possible condition is satisfied. As described above, the possible condition is a condition regarding whether the cooling time T2 can be shortened, and is that the planned cooling time is longer than the theoretical cooling time T20 by a predetermined time or more ("planned cooling time-theoretical cooling time≧predetermined time"). As described above, the possible condition in this embodiment is that the planned cooling time is longer than the theoretical cooling time by a first threshold or more ("planned cooling time-theoretical cooling time≧first threshold").

[0039] If it is determined that the possible conditions are met, that is, if the cooling time T2 can be shortened, the adjustment unit 13 adjusts the molding conditions within a range that satisfies, for example, "(planned cooling time after shortening)-theoretical cooling time ≧ 0." If it is determined that the possible conditions are not met, that is, if the cooling time T2 cannot be shortened, the adjustment of the molding conditions is not performed.

[0040] (2-5) Details of adjustment part As shown in FIG. 2, the adjustment unit 13 includes a data output unit 131, a second calculation unit 132, and a reduction unit 133.

[0041] (2-5-1) Data output section The data output unit 131 includes a trained model 131a of a neural network.

[0042] (2-5-1a) Neural Network The neural network in this embodiment is, for example, a regression type neural network suitable for handling time series data. However, the neural network may be a neural network other than the regression type, or may be various machine learning (deep learning, etc.) algorithms that apply the neural network.

[0043] (2-5-1b) Trained model The trained model 131a receives a plurality of time-series data and outputs a plurality of calculation data. The calculation data is data for calculating an adjustment value (described later).

[0044] The plurality of calculation data include a predicted mold thermal equilibrium temperature value. The predicted mold thermal equilibrium temperature value is a predicted value of the mold thermal equilibrium temperature when the mold is in a thermal equilibrium state.

[0045] (2-5-1c) Thermal equilibrium state and mold thermal equilibrium temperature The thermal equilibrium state is a state in which the mold temperature rises as the low-temperature mold 20 repeatedly comes into contact with the high-temperature resin, the temperature difference between the mold temperature and the resin temperature becomes smaller, and a constant temperature is reached. The mold thermal equilibrium temperature is the constant temperature when the mold 20 reaches a thermal equilibrium state.

[0046] In this embodiment, the thermal equilibrium state is a state in which the temperature difference of the mold temperature during a predetermined number of consecutive molding cycles is equal to or less than a third threshold value. This makes it possible to determine whether the mold 20 has reached a thermal equilibrium state based on the mold temperature time series data.

[0047] In addition, the mold thermal equilibrium temperature in this embodiment is the average value of the mold temperature during a predetermined number of consecutive molding cycles in a thermal equilibrium state (i.e., when injection molding is performed continuously and the mold temperature fluctuation is within the third threshold value), which allows the mold thermal equilibrium temperature to be calculated based on the mold temperature time series data.

[0048] (2-5-2) Second calculation section The second calculation unit 132 calculates an adjustment value for the molding condition based on a plurality of pieces of calculation data output by the data output unit 131 when the necessity condition is satisfied.

[0049] (2-5-2a) Necessity condition The necessity condition is a condition as to whether or not it is necessary to shorten the cooling time T2, and further, a condition as to whether the current or next molding cycle belongs to a throw-away period in which the cooling time T2 needs to be shortened, or belongs to a mass production period in which the cooling time T2 does not need to be shortened.

[0050] The necessity condition is that the difference between the mold thermal equilibrium temperature and the mold temperature is equal to or greater than a predetermined temperature ("mold thermal equilibrium temperature-mold temperature≧predetermined temperature"). In this embodiment, the necessity condition is that the measured mold temperature is lower than the predicted mold thermal equilibrium temperature by a second threshold value or more.

[0051] (2-5-2b) Adjustment value The adjustment value is a value for adjusting the molding conditions. The adjustment value in this embodiment is, for example, a value for increasing the rate of increase in the mold temperature by shortening the cooling time T2 included in the molding cycle.

[0052] The mold temperature rise rate is the increase in mold temperature (℃ / cycle) between two consecutive molding cycles. For example, the mold temperature rise rate is the difference between the mold temperature measurement value in the previous molding cycle and the mold temperature measurement value in the current molding cycle (the increase rate based on the two actual measurements from the previous and current cycles).

[0053] Alternatively, the rate of rise of the mold temperature may be, for example, the difference between the measured mold temperature value in the current molding cycle and the predicted mold temperature value based on the predicted rate of rise in the next molding cycle (the predicted rate of rise based on the current actual value and the next predicted value).

[0054] (2-5-3) Judgment of Necessity Conditions by the Coordination Department If the possibility condition is satisfied, the adjustment unit 13 further determines whether or not the necessity condition is satisfied.

[0055] When it is determined that the possible condition is satisfied and the necessary condition is satisfied, that is, when the cooling time T2 can be shortened and the current or next molding cycle belongs to a throw-away period that requires the cooling time T2 to be shortened, the adjustment unit 13 adjusts the molding conditions. The adjustment of the molding conditions may be, for example, shortening the cooling time while aligning the predicted increase curve CV1 with the target increase curve CV2 (described later) within a range that satisfies "(cooling time T2 after shortening)-theoretical cooling time ≧0".

[0056] If it is determined that the possible conditions are met and the necessary conditions are not met, that is, even if it is possible to shorten the cooling time T2, if the current or next molding cycle belongs to a mass production period in which shortening the cooling time T2 is not necessary, the molding conditions will not be adjusted.

[0057] (2-5-4) Shortened section The shortening unit 133 shortens the waste shot period based on the adjustment value calculated by the second calculation unit 132. As a result, when the current or next molding cycle belongs to the waste shot period, the mold temperature increases at a higher rate (e.g., more steeply) than when it belongs to the mass production period.

[0058] In this way, it is possible to shorten the cooling time T2, and when the mold is not in a state of thermal equilibrium, the shortening section 133 can shorten the trial casting period by adjusting the molding conditions to increase the rate of increase in the mold temperature.

[0059] (2-5-4a) Shortening the cooling time based on the cooling time adjustment value The adjustment value includes a cooling time adjustment value. The cooling time adjustment value is an adjustment value for the planned cooling time value. The cooling time adjustment value is a value that does not make the planned cooling time after shortening based on the cooling time adjustment value (planned cooling time value after shortening) fall below the theoretical cooling time T20 (theoretical cooling time value). In other words, the cooling time adjustment value is an adjustment value that satisfies "(cooling time after shortening) - theoretical cooling time ≧ 0", and may be, for example, a value that satisfies "(cooling time after shortening) - theoretical cooling time = 0".

[0060] The shortening unit 133 shortens the expected cooling time value based on the cooling time adjustment value.

[0061] In this way, when it is possible to shorten the cooling time T2 and the mold 20 has not yet reached thermal equilibrium, the shortening section 133 can shorten the trial casting period by shortening the cooling time T2 and increasing the rate of rise of the mold temperature.

[0062] (2-6) Calculation formula The formula used by the first calculation unit 12 to calculate the value of the theoretical cooling time T20 (theoretical cooling time value) includes a first variable Tm, a second variable Tc, a first constant Tx, and at least one second constant. The measured mold temperature is substituted into the first variable Tm. The measured resin temperature is substituted into the second variable Tc. The first constant Tx is a constant corresponding to the ejection temperature. The ejection temperature is the temperature at which the resin injected into the mold 20 is cooled and becomes ejectable from the mold 20.

[0063] The removable temperature may be, for example, a heat distortion temperature or a solidification temperature. The resin cooled to the removable temperature does not have to be completely solidified, as long as it is solidified to an extent that it can be safely removed (without significant deformation or damage).

[0064] The at least one second constant corresponds to at least one of the wall thickness t of the injection-molded product, and the thermal diffusivity α, thermal conductivity, specific heat, density, glass transition temperature, latent heat of crystallization, and degree of temporary crystallinity of the resin.

[0065] The calculation formula is, for example, the formula "T2 = (t 2 / π 2 α)ln[8(Tc-Tm) / {π 2 (Tx-Tm)}]”. In this formula, “ln” indicates the natural logarithm.

[0066] By using such a calculation formula, the first calculation section 12 can calculate the theoretical cooling time value with high accuracy.

[0067] (2-7) Details of injection molding machine 1, the injection molding machine 10 includes a cylinder 10a, a screw 10b, a hopper 10c, and a plurality of heaters 10d. The mold 20 includes a plurality of water pipes 20a.

[0068] The cylinder 10a and the screw 10b are members for metering the resin to be injected into the mold 20. Metering means melting the resin to be used in the next molding cycle and measuring the amount. The hopper 10c is a member for storing the resin taken into the cylinder 10a by the screw 10b. The heater 10d is a device (temperature regulator) that adjusts the temperature of the resin taken into the cylinder 10a to a preset temperature.

[0069] The water pipe 20a is a pipe through which cooling water flows to cool the mold 20. Although the water pipe 20a in FIG.

[0070] (2-8) Details of the measurement system The measurement system 2 includes at least one type of measuring instrument among a temperature sensor and a flow meter. The measurement system 2 includes, for example, a first temperature sensor that measures the temperature of the mold 20 (mold temperature), a second temperature sensor that measures the temperature of the resin injected into the mold 20 (resin temperature), a third temperature sensor that measures the temperature of the outside air (outside air temperature), and a flow rate sensor that measures the flow rate of the cooling water flowing through the water pipe 20a (see FIG. 1) (water pipe flow rate).

[0071] The first temperature sensor is attached, for example, to the surface of the mold 20. The second temperature sensor is embedded, for example, in a portion of the inner surface of the mold 20 that comes into contact with the resin. The third temperature sensor is attached, for example, to an appropriate position of the injection molding machine 10.

[0072] The measurement system 2 measures the mold temperature with a first temperature sensor and outputs the mold temperature measurement value. The measurement system 2 also measures the resin temperature with a second temperature sensor and outputs the resin temperature measurement value. The measurement system 2 also measures the outside air temperature with a third temperature sensor and outputs the outside air temperature measurement value. Furthermore, the measurement system 2 measures the water pipe flow rate with a flow rate sensor and outputs the water pipe flow rate measurement value.

[0073] (2-9) Start of measurement at the start of each molding cycle Each time a molding cycle starts, the measurement system 2 begins measuring multiple physical quantities such as the mold temperature, resin temperature, outside air temperature, and water pipe flow rate using multiple measuring instruments such as the first to third temperature sensors and a flow rate sensor.

[0074] In this way, at the start of each molding cycle, the measurement system 2 initiates multiple measurements corresponding to the multiple physical quantities, and the adjustment device 1 stores multiple measurement values ​​corresponding to the multiple physical quantities, thereby generating multiple time series data corresponding to the multiple physical quantities.

[0075] (2-10) Other examples of multiple physical quantities and multiple measured values The multiple physical quantities may further include at least one of the cylinder temperature, the outside air temperature, the screw rotation speed, and the water tube flow rate. The cylinder temperature is the temperature of the cylinder 10a. The outside air temperature is the temperature of the outside air. The screw rotation speed is the number of rotations per unit time of the screw 10b. The water tube flow rate is the flow rate of the cooling water flowing through the water tube 20a per unit time.

[0076] The plurality of measurement values ​​may further include at least one of a cylinder temperature measurement value, an outside air temperature measurement value, a screw rotation speed measurement value, and a water tube flow rate measurement value. The cylinder temperature measurement value is a measurement value corresponding to the cylinder temperature. The outside air temperature measurement value is a measurement value corresponding to the outside air temperature. The screw rotation speed measurement value is a measurement value corresponding to the screw rotation speed. The water tube flow rate measurement value is a measurement value corresponding to the water tube flow rate.

[0077] The multiple time series data may further include at least one of cylinder temperature time series data, outside air temperature time series data, screw rotation speed time series data, and water tube flow rate time series data. The cylinder temperature time series data is time series data corresponding to cylinder temperature. The outside air temperature time series data is time series data corresponding to outside air temperature. The screw rotation speed time series data is time series data corresponding to screw rotation speed. The water tube flow rate time series data is time series data corresponding to water tube flow rate.

[0078] In this way, by the multiple physical quantities to be measured by the measurement system 2 including at least one of the cylinder temperature, outside air temperature, screw rotation speed and water pipe flow rate in addition to the mold temperature and resin temperature, the accuracy of adjustment of the molding conditions by the adjustment unit 13 can be improved.

[0079] Furthermore, the object of measurement by the measurement system 2 may include a physical quantity that is an object of adjustment by the adjustment device 1 or that can be an object of adjustment. That is, the physical quantities may further include at least one of the times of various processes included in the molding cycle (injection time T1, filling time T11, pressure holding time T12, cooling time T2, removal time T3, and weighing time T4) and back pressure. The back pressure is the pressure applied to the resin in the weighing process.

[0080] The plurality of measurement values ​​may further include one or more of an injection time measurement value, a filling time measurement value, a holding time measurement value, a cooling time measurement value, a removal time measurement value, and a back pressure measurement value. The plurality of time series data may further include one or more of an injection time time series data, a filling time time series data, a holding time time series data, a cooling time time series data, a removal time time series data, and a back pressure time series data.

[0081] In this way, the multiple physical quantities to be measured by the measurement system 2 include physical quantities that are to be adjusted by the adjustment device 1 (ejection time T1, etc.) or that can be to be adjusted (removal time T3, back pressure, etc.), thereby improving the adjustment accuracy.

[0082] (2-11) Constants input to the adjustment section The adjustment unit 13 may adjust the molding conditions based on, in addition to the multiple time-series data, one or more constants (values ​​that do not change over time) such as the following: The one or more constants are, for example, one or more values ​​of the set temperature of the heater 10d, the weight of the mold 20, the weight of the molded product, the type of resin, and the diameter or radius of the water pipe 20a (water pipe diameter).

[0083] In addition, if the set temperature of the heater 10d can be changed during the repetition of the molding cycle (during the period from the start of production to the end of production), the set temperature may be considered as a type of variable, and the multiple time series data may further include set temperature time series data corresponding to the set temperature.

[0084] (2-12) Details of molding cycle As shown in Figs. 5 to 7, the molding cycle includes an injection time T1, a cooling time T2, a removal time T3, and a measuring time T4.

[0085] (2-12-1) Injection time The injection time T1 corresponds to the injection step, which is a step of injecting the resin measured in the previous molding cycle into the mold 20.

[0086] (2-12-2) Details of cooling time The cooling time T2 is a time corresponding to the cooling process. The cooling process is a process for cooling the resin injected into the mold 20 until it can be removed from the mold 20. The resin injected into the mold 20 is cooled until it reaches a temperature at which it can be removed. In detail, the molten resin in the mold 20 is cooled and solidified by the cooling water flowing through the water pipe 20a, and becomes a molded product that can be removed from the mold 20. The cooling time T2 is the time until the resin injected into the mold 20 is cooled and reaches a temperature at which it can be removed.

[0087] (2-12-3) Removal time The ejection time T3 is a time corresponding to the ejection step. The ejection step is performed after the cooling step, and is a step of ejecting the molded product formed by injection molding from the mold 20. More specifically, the ejection step is composed of mold opening for opening the mold 20, ejection for ejecting the molded product from the mold 20, ejection for ejecting the ejected molded product, and mold closing for closing the mold 20. In other words, the ejection step includes a series of steps from mold opening through ejection and ejection to mold closing, but in this embodiment, it is not necessary to particularly distinguish between the series of steps.

[0088] (2-12-4) Weighing time The metering time T4 corresponds to the metering step. The metering step is performed in parallel with the cooling step, and is a step for metering the resin to be injected into the mold 20 in the next molding cycle. The metering step is usually started in response to the end of the injection step and is ended before the end of the cooling step.

[0089] It should be noted that if the cooling step is completed and the removal step is started but the weighing step is not completed, removal is not performed in the removal step and the system remains in a standby state until the weighing step is completed.

[0090] Furthermore, if it is expected that the measurement step will not be completed before the end of the cooling step as a result of shortening the cooling time T2, the measurement time T4 included in the molding cycle may be shortened as shown in FIG.

[0091] (2-12-5) Details of molding conditions The molding conditions may further include a scheduled injection time value, a scheduled metering time value, and a scheduled removal time value in addition to the aforementioned scheduled cooling time value. The scheduled injection time value is a predetermined value of the injection time T1. The scheduled removal time value is a predetermined value of the removal time T3. The scheduled metering time value is a predetermined value of the metering time T4.

[0092] (2-12-6) Details of adjustment values The adjustment value may further include at least one of an injection time adjustment value, a removal time adjustment value, and a metering time adjustment value in addition to the cooling time adjustment value described above. The injection time adjustment value is an adjustment value for the scheduled injection time value. The removal time adjustment value is an adjustment value for the scheduled removal time value. The metering time adjustment value is an adjustment value for the scheduled metering time value.

[0093] However, in this embodiment, the adjustment of the removal time T3 may not be performed in particular. In other words, the shortening unit 133 may further shorten at least one scheduled time value corresponding to at least one adjustment value among the scheduled injection time value and the scheduled metering time value, in addition to the scheduled cooling time value.

[0094] In this way, by further shortening at least one of the injection time T1 and the metering time T4 in addition to the cooling time T2 (at least one of the time for cooling while maintaining pressure and the time for cooling without maintaining pressure), the shortening section 133 can further shorten the trial injection period.

[0095] (2-12-7) Details of the injection process: filling process and pressure holding process The injection process includes a filling process and a pressure holding process. The filling process is a process of filling the resin into the mold 20. The pressure holding process is a process of cooling the resin filled into the mold 20 while holding the pressure.

[0096] 5, the injection time T1 includes a filling time T11 and a pressure holding time T12. The filling time T11 is a time corresponding to the filling step. The pressure holding time T12 is a time corresponding to the pressure holding step.

[0097] The scheduled injection time value includes a scheduled filling time value and a scheduled pressure holding time value. The scheduled filling time value is a predetermined value of the filling time T11. The scheduled pressure holding time value is a predetermined value of the pressure holding time T12.

[0098] In this way, when the injection process is divided into the filling process and the pressure holding process, the theoretical cooling time is the time from when the resin filled into the mold 20 in the filling process starts to be cooled while being held in the pressure holding process until the temperature reaches a temperature at which the resin can be taken out (=first constant Tx). The pressure holding time T12 overlaps with a part (the beginning part) of the cooling time T2. In other words, it can be said that the cooling time T2 includes the pressure holding time T12.

[0099] (2-12-7a) Shortening of pressure retention time The molding conditions further include a condition related to the dwell time T12. The adjustment values ​​further include a dwell time adjustment value. The dwell time adjustment value is an adjustment value for the scheduled dwell time.

[0100] The shortening unit 133 shortens the pressure holding time T12 included in each of the injection time T1 and the cooling time T2, as shown in FIG. 5, based on the pressure holding time adjustment value.

[0101] In this way, the injection process includes a filling process and a pressure holding process, and in the pressure holding process, the resin filled in the filling process is cooled while being held under pressure. In this way, by shortening the pressure holding time T12, which is a part of the cooling time T2, the shortening unit 133 can shorten the trial injection period.

[0102] (2-12-7b) Shortening of pressure holding time and cooling time Alternatively, as shown in FIG. 6, the shortening section 133 may shorten the pressure holding time T12 included in each of the injection time T1 and the cooling time T2, and may further shorten the cooling time T2 excluding the pressure holding time T12.

[0103] In this way, the shortening section 133 shortens the pressure retention time T12 with cooling (in other words, the cooling time T2 with pressure retention), and also shortens the cooling time T2 without pressure retention, thereby enabling a further shortening of the waste shot period.

[0104] (2-12-7c) Reduction of pressure retention time, cooling time and weighing time The multiple measurement values ​​further include a screw rotation speed measurement value in addition to a mold temperature measurement value and a resin temperature measurement value.

[0105] The multiple time series data further includes screw rotation speed time series data in addition to mold temperature time series data and resin temperature time series data.

[0106] The calculation data further includes a predicted screw rotation speed value in addition to a predicted mold thermal equilibrium temperature value. The predicted screw rotation speed value is a predicted screw rotation speed value for completing the metering step by the end of the cooling step when the pressure holding time T12 included in each of the injection time T1 and the cooling time T2 is shortened and the cooling time T2 excluding the pressure holding time T12 is further shortened.

[0107] The molding conditions further include a condition regarding the metering time T4. The adjustment values ​​further include a metering time adjustment value.

[0108] The shortening section 133 shortens the pressure holding time T12 included in each of the injection time T1 and the cooling time T2, and further shortens the cooling time T2 excluding the pressure holding time T12. In the case where the weighing process is not completed by the end of the cooling process, the shortening section 133 may shorten the weighing time T4 included in the molding cycle based on the predicted screw rotation speed value so that the weighing process is completed by the end of the cooling process, as shown in FIG. 7.

[0109] In this way, if the metering is not completed within the cooling time T2, the shortening unit 133 shortens the metering time T4 based on the predicted screw rotation speed so that the metering is completed within the cooling time T2, thereby further shortening the trial shot period.

[0110] (2-12-8) Projected ascent curve and target ascent curve The calculation data further includes a predicted rise rate of the mold temperature. The adjustment value is a value that shortens the scheduled cooling time based on the cooling time adjustment value while aligning the rise prediction curve CV1 based on the predicted rise rate with the rise target curve CV2, as shown in Fig. 8.

[0111] As described above, the mold temperature rise rate is the mold temperature rise value per molding cycle (°C / cycle). The predicted mold temperature rise rate value is, for example, the difference between the mold temperature measurement value in the current molding cycle and the predicted mold temperature value in the next molding cycle.

[0112] The predicted mold temperature value rises, for example, as shown by the rise prediction curve CV1 shown by the solid line in Fig. 8. That is, in a first period from the initial temperature (50°C) until the first temperature (for example, 58°C: a temperature 1°C lower than the mold thermal equilibrium temperature 59°C) in the vicinity of the mold thermal equilibrium temperature (59°C) is reached, the predicted mold temperature value rises at a first rise rate (for example, 4°C / cycle). Then, in a second period from the first temperature (58°C) until the temperature reaches or exceeds the mold thermal equilibrium temperature (59°C), the predicted mold temperature value rises at a second rise rate (for example, 1°C / cycle) smaller than the first rise rate (4°C / cycle). The rise prediction curve CV1 is a curve (broken line) that shows the time change of such a predicted mold temperature value.

[0113] The target mold temperature value rises, for example, as shown by the rising target curve CV2 indicated by the dashed line in Fig. 8. That is, in a first period from the initial temperature (50°C) until the first temperature (approximately 58°C) is reached, the target mold temperature value rises at a first rise rate (for example, 4°C / cycle) like the predicted mold temperature value. Then, in a second period from the first temperature (approximately 58°C) until the temperature reaches or exceeds the mold thermal equilibrium temperature (59°C), the rate of rise of the target mold temperature value monotonically decreases from the first rise rate to 0. The rising target curve CV2 is a curve (monotonically increasing curve) that shows the time change of such a target mold temperature value.

[0114] In this way, by using an adjustment value that shortens the cooling time T2 while aligning the predicted rise curve CV1 with the target rise curve CV2, the shortening section 133 can shorten the cooling time T2 while controlling the rise in mold temperature.

[0115] The rising curve CV0 shown by the dotted line in Fig. 8 is an example (broken line) of a curve showing the rise in the mold temperature when the molding conditions are manually adjusted. Although it is possible to raise the mold temperature as shown by the rising curve CV0 by manual adjustment and shorten the dry-off period, the adjustment requires time and effort, and it is not easy to raise the mold temperature along the target rise curve CV2.

[0116] (2-12-9) Example of an upward trend forecast curve As described above, the rise prediction curve CV1 is a curve that shows a temperature change in which the predicted mold temperature value rises at a first rise rate in the first period and at a second rise rate in the second period. The first period is the period from the initial temperature to the first temperature. The first temperature is a temperature close to the mold thermal equilibrium temperature. The first rise rate is a rise rate based on the theoretical cooling time value. The second period is the period from the first temperature to the mold thermal equilibrium temperature or higher. The second rise rate is a rise rate smaller than the first rise rate.

[0117] The first period may be a throw-away period after the adjustment of the molding conditions by the adjustment unit 13 (for example, after the shortening unit 133 shortens the cooling time T2), and the second period may be a leading part of the mass production period. The leading part of the mass production period is a part of the mass production period that corresponds to the period until the mold temperature reaches the mold thermal equilibrium temperature.

[0118] In this way, by raising the mold temperature to the first temperature at a first rate of increase (e.g., a rapid increase) and then raising it from the first temperature to the mold thermal equilibrium temperature at a second rate of increase (<the first rate of increase) (e.g., a gradual increase), it is possible to shorten the cooling time T2 while suppressing the phenomenon that occurs when the mold temperature is rapidly raised to the mold thermal equilibrium temperature, in which the mold temperature exceeds the mold thermal equilibrium temperature and then drops to the mold thermal equilibrium temperature.

[0119] (2-13) Generating a trained model The injection molding system 100 further includes a model generation unit 134. The model generation unit 134 executes a learning process of a neural network (described above) based on a plurality of time-series data, thereby generating a trained model 131a.

[0120] The learning process is, for example, supervised learning based on a set (teacher data) of multiple time-series data and multiple actual measurement data corresponding to multiple calculation data, but may be unsupervised learning that does not use teacher data.

[0121] The model generation unit 134 may further generate a second trained model 132a, which will be described in a modified example, by executing a learning process of a neural network based on a plurality of calculation data and the adjustment value.

[0122] This allows the model generation unit 134 to generate the trained model 131a within the adjustment device 1. However, the trained model 131a may be one that is generated externally.

[0123] (3) Specific examples Next, a specific example of the injection molding system 100 will be described. Note that, in the following, the description of the previously mentioned items will be omitted or simplified.

[0124] 1, an injection molding system 100 in this specific example includes an injection molding machine 10, a mold 20, and a controller 30. The controller 30 controls the injection molding machine 10 and the mold 20. The controller 30 includes an adjustment device 1 and a measurement system 2. The measurement system 2 outputs a plurality of measurement values ​​including a mold temperature measurement value and a resin temperature measurement value to the adjustment device 1.

[0125] 2, the adjustment device 1 includes a storage unit 11, a first calculation unit 12, and an adjustment unit 13. The adjustment unit 13 includes a data output unit 131, a second calculation unit 132, a reduction unit 133, and a model generation unit .

[0126] The memory unit 11 stores the multiple measurement values ​​output by the measurement system 2 in chronological order, whereby multiple time series data including mold temperature time series data and resin temperature time series data are generated in the memory unit 11.

[0127] The multiple pieces of time-series data generated in the storage unit 11 are input to the model generation unit 134. The model generation unit 134 executes a learning process of a neural network to generate a trained model 131a.

[0128] The generated plurality of time series data are input to the first calculation unit 12. The first calculation unit 12 calculates a theoretical cooling time value based on the plurality of time series data, and outputs the calculated theoretical cooling time value to the adjustment unit 13.

[0129] The adjustment unit 13 judges whether the feasible condition "planned cooling time value - theoretical cooling time value ≧ first threshold value" is satisfied based on the planned cooling time value constituting the molding conditions and the calculated theoretical cooling time value.

[0130] The data output unit 131 includes the trained model 131a generated by the model generation unit 134. When it is determined that the feasibility conditions are satisfied, the data output unit 131 inputs the generated mold temperature time series data and resin temperature time series data, and the calculated theoretical cooling time value, to the trained model 131a. The trained model 131a outputs a predicted mold thermal equilibrium temperature value and a predicted rise rate value.

[0131] The adjustment unit 13 determines whether the necessity condition "mold thermal equilibrium temperature predicted value - mold temperature measured value ≦ second threshold value" is satisfied based on the mold thermal equilibrium temperature predicted value output by the trained model 131a and the mold temperature measured value included in the mold temperature time series data.

[0132] If it is determined that the necessity condition is met, the second calculation unit 132 calculates a cooling time adjustment value that shortens the cooling time T2 while aligning the rise prediction curve CV1 with the rise target curve CV2 based on the mold thermal equilibrium temperature prediction value and the rise rate prediction value output from the trained model 131a.

[0133] The shortening unit 133 adjusts the expected cooling time value constituting the molding conditions based on the calculated cooling time adjustment value.

[0134] (4) Means for implementing the adjustment device The adjustment device 1 has a processor and a memory. The memory stores programs and various information, and the processor operates based on the various programs (described later) and various information stored in the memory. This realizes the functions of the adjustment device 1 (the storage unit 11, the first calculation unit 12, and the adjustment unit 13).

[0135] The various information includes, for example, a value of the cooling time T2 (scheduled cooling time value) constituting the molding conditions, a plurality of time series data, and the trained model 131a. The first calculation unit 12 is realized by a theoretical cooling time calculation program that calculates the theoretical cooling time T20. The adjustment unit 13 is realized by a feasibility determination program that makes a determination regarding a possible condition, a necessity determination program that makes a determination regarding a necessary condition, a calculation data output program that outputs calculation data using the trained model 131a, an adjustment value calculation program that calculates an adjustment value, and an adjustment program that adjusts the molding conditions.

[0136] (5) Example of operation The injection molding system 100 operates, for example, according to the flowchart of Fig. 3. The operation of Fig. 3 starts when the injection molding system 100 is started.

[0137] When the injection molding system 100 is started, the adjustment device 1 executes a molding condition adjustment process for adjusting molding conditions (step S1). The molding condition adjustment process will be described with reference to the flowchart of FIG.

[0138] After the adjustment of the molding conditions is completed, the injection molding machine 10 fills the resin into the mold 20 under the control of the controller 30 based on the filling-related conditions (such as the expected filling time) among the molding conditions (step S2).

[0139] When the filling is completed, the injection molding machine 10 starts cooling based on the cooling-related conditions (expected cooling time value, etc.) among the molding conditions under the control of the controller 30 (step S3).

[0140] In response to the start of cooling, the injection molding machine 10 performs pressure dwell based on the conditions related to pressure dwell (expected pressure dwell time value, etc.) among the molding conditions under the control of the controller 30 (step S4).

[0141] When the pressure dwell is completed, the injection molding machine 10 performs measurement based on the measurement-related conditions (measurement time schedule value, etc.) among the molding conditions under the control of the controller 30 (step S5).

[0142] After the measurement is completed, under the control of the controller 30, the injection molding machine 10 ends the cooling when a time corresponding to the planned pressure holding time and the planned cooling time has elapsed since the start of cooling in step S3 (step S6).

[0143] After the cooling is completed, the injection molding machine 10, under the control of the controller 30, removes the molded product from the mold 20 based on the removal-related conditions (such as the expected removal time) among the molding conditions (step S7).

[0144] When the removal of the molded product is completed, the controller 30 judges whether the current molding cycle including the above seven operations corresponding to steps S1 to S7 is the last molding cycle among the multiple molding cycles scheduled (step S8). If it is judged that the current molding cycle is not the last molding cycle (No in step S8), the operation returns to step S1.

[0145] If it is determined in step S8 that the current molding cycle is the last molding cycle (Yes), the operation is ended.

[0146] The molding condition adjustment process in step S1 is executed, for example, according to the flowchart of FIG.

[0147] The first calculation unit 12 constituting the adjustment device 1 acquires a plurality of time series data from the storage unit 11 (step S101).

[0148] Next, the first calculation unit 12 calculates the theoretical cooling time T20 based on the multiple pieces of time-series data acquired in step S101, and acquires the theoretical cooling time value (step S102).

[0149] Next, the adjustment unit 13 judges whether or not the possible condition that the planned cooling time is longer than the theoretical cooling time by at least a first threshold is satisfied (step S103). If the planned cooling time constituting the molding conditions is longer than the theoretical cooling time acquired in step S102 by at least the first threshold, it is judged that the possible condition is satisfied. If the difference between the planned cooling time and the theoretical cooling time (planned cooling time - theoretical cooling time) does not satisfy the first threshold, it is judged that the possible condition is not satisfied. If it is judged that the possible condition is not satisfied (No in step S103), the process returns to the upper flowchart (step S2 in FIG. 3).

[0150] If it is determined in step S103 that the feasibility condition is met (Yes), the data output unit 131 inputs a plurality of pieces of time-series data to the trained model 131a (step S104).

[0151] Next, the data output unit 131 outputs a plurality of pieces of calculation data from the trained model 131a (step S105). The plurality of pieces of calculation data to be output includes a mold thermal equilibrium temperature prediction value.

[0152] Next, the adjustment unit 13 judges whether or not the necessity condition that the measured mold temperature value is lower than the predicted mold thermal equilibrium temperature value by a second threshold value or more is satisfied (step S106). If the most recent measured mold temperature value included in the mold temperature time series data is lower than the predicted mold thermal equilibrium temperature value output in step S105 by a second threshold value or more, it is judged that the necessity condition is satisfied. If the difference between the most recent measured mold temperature value and the predicted mold thermal equilibrium temperature value (predicted mold thermal equilibrium temperature value - most recent measured mold temperature value) does not satisfy the second threshold value, it is judged that the necessity condition is not satisfied. If it is judged that the necessity condition is not satisfied (No in step S106), the process returns to the upper flowchart (step S2 in FIG. 3).

[0153] If it is determined in step S106 that the necessity condition is satisfied (Yes), the second calculation unit 132 calculates an adjustment value based on the multiple pieces of calculation data output from the data output unit 131 in step S105 (step S107). Here, for example, a cooling time adjustment value is calculated.

[0154] Next, the shortening unit 133 adjusts the molding conditions based on the adjustment value calculated in step S107 (step S108). Here, for example, the cooling time T2 is shortened based on the cooling time adjustment value. After that, the process returns to the upper flowchart (step S2 in FIG. 3).

[0155] (6) Variations (6-1) Modification of the second calculation unit The trained model 131a described in the embodiment is the first trained model 131a in this modified example.

[0156] The second calculation unit 132 includes a second trained model 132a of a neural network. The second trained model 132a receives a plurality of pieces of calculation data and outputs an adjustment value.

[0157] According to this modified example, the second calculation unit 132 includes a second trained model 132a that receives multiple calculation data and outputs an adjustment value, making it possible to output an adjustment value using the trained model.

[0158] (6-2) Variations of trained models In this modified example, the trained model 131a of the neural network described in the embodiment is a first trained model by machine learning other than the neural network. Also, in this modified example, the trained model 132a of the neural network described in the modified example of the second calculation unit is a second trained model by machine learning other than the neural network. The machine learning other than the neural network is, for example, a decision tree, a random forest, or a support vector machine (SVM), but is not limited thereto.

[0159] (6-3) Modifications of the memory unit The storage unit 11 may be located outside the adjustment device 1. The storage unit 11 may be provided in, for example, the measurement system 2, or may be provided in an element in the controller 30 other than the adjustment device 1 and the measurement system 2. Furthermore, the storage unit 11 may be located outside the controller 30 (for example, a cloud server, etc.), and its location does not matter as long as the processor of the adjustment device 1 can access it.

[0160] (7) Summary The injection molding system (100) according to the first embodiment includes a mold (20), an injection molding machine (10), a measurement system (2), and an adjustment device (1). The injection molding machine (10) repeatedly performs injection molding of a resin using the mold (20) according to a molding cycle based on predetermined molding conditions. The measurement system (2) measures a plurality of physical quantities related to the injection molding every time the injection molding machine (10) performs injection molding, and outputs a plurality of measurement values ​​corresponding to the plurality of physical quantities. The adjustment device (1) adjusts the molding conditions based at least on a plurality of time-series data corresponding to the plurality of physical quantities, which are generated by storing the plurality of measurement values ​​output by the measurement system (2) in a chronological order. The molding cycle includes a cooling time (T2). The cooling time (T2) is the time from when the resin is injected into the mold (20) by the injection molding machine (10) until the injected resin is cooled and can be removed from the mold (20). The molding conditions include a cooling time estimate. The planned cooling time value is a predetermined value of the cooling time (T2). The adjustment device (1) includes a calculation unit (12) and an adjustment unit (13). The calculation unit (12) calculates a theoretical cooling time value, which is a theoretical value of the cooling time (T2), using multiple time series data and a calculation formula or information equivalent to the calculation formula. The adjustment unit (13) adjusts the molding conditions so that the run-off period is shortened when a feasible condition is satisfied. The feasible condition is a condition that the planned cooling time value is longer than the theoretical cooling time value by a threshold value or more. The run-off period is the period before the mold (20) reaches a thermal equilibrium state.

[0161] According to this embodiment, when the cooling time (T2) can be shortened, the molding conditions can be adjusted to shorten the trial casting period.

[0162] The mass production period may be shortened together with the run-off period. However, during the run-off period, the mold temperature has not yet reached the mold thermal equilibrium temperature and there is a large room for it to rise, so it is often possible to shorten the cooling time (T2), whereas during the mass production period, the mold temperature has already reached the mold thermal equilibrium temperature and there is little room for it to rise, so there are few cases where it is possible to shorten the cooling time (T2). Therefore, at least the run-off period can be shortened.

[0163] In the injection molding system (100) according to the second aspect, in the first aspect, the calculation unit (12) is a first calculation unit (12). The physical quantities include a mold temperature and a resin temperature. The mold temperature is the temperature of the mold (20). The resin temperature is the temperature of the resin injected into the mold (20). The measurement values ​​include a mold temperature measurement value and a resin temperature measurement value. The mold temperature measurement value is a measurement value corresponding to the mold temperature. The resin temperature measurement value is a measurement value corresponding to the resin temperature. The time series data includes mold temperature time series data and resin temperature time series data. The mold temperature time series data is time series data corresponding to the mold temperature. The resin temperature time series data is time series data corresponding to the resin temperature. The threshold is a first threshold. The adjustment unit (13) further includes a data output unit (131), a second calculation unit (132), and a shortening unit (133). The data output unit (131) includes a machine learning trained model (131a). The trained model (131a) receives a plurality of time series data and outputs a plurality of calculation data. The calculation data includes a predicted mold thermal equilibrium temperature value. The predicted mold thermal equilibrium temperature value is a predicted value of the mold thermal equilibrium temperature when the mold reaches a thermal equilibrium state. The second calculation unit (132) calculates an adjustment value for the molding conditions based on the plurality of calculation data when a necessity condition is satisfied. The adjustment value is a value for increasing the rate of increase of the mold temperature. The necessity condition is that the measured mold temperature value is lower than the predicted mold thermal equilibrium temperature value by a second threshold value or more. The shortening unit (133) shortens the trial shot period based on the adjustment value.

[0164] According to this embodiment, it is possible to shorten the cooling time (T2), and when the mold (20) is not in a thermal equilibrium state, the molding conditions can be adjusted to increase the rate of increase in the mold temperature, thereby shortening the trial casting period.

[0165] In the injection molding system (100) according to the third aspect, in the second aspect, the adjustment value includes a cooling time adjustment value. The cooling time adjustment value is an adjustment value for a scheduled cooling time value. The shortening unit (133) shortens the scheduled cooling time value based on the cooling time adjustment value.

[0166] According to this embodiment, it is possible to shorten the cooling time (T2), and when the die (20) is not in a state of thermal equilibrium, the cooling time (T2) can be shortened to increase the rate of rise in the die temperature, thereby shortening the trial casting period.

[0167] In the injection molding system (100) according to the fourth aspect, in the third aspect, the calculation formula includes a first variable (Tm), a second variable (Tc), a first constant (Tx), and at least one second constant. A measured mold temperature is substituted for the first variable (Tm). A measured resin temperature is substituted for the second variable (Tc). The first constant (Tx) is a constant corresponding to a demoldable temperature. The demoldable temperature is a temperature at which the resin injected into the mold (20) is cooled and can be demolded from the mold (20). The at least one second constant corresponds to at least one of the wall thickness (t) of the molded product by injection molding, and the thermal diffusivity (α), thermal conductivity, specific heat, density, glass transition temperature, latent heat of crystallization, and temporary crystallinity of the resin.

[0168] According to this aspect, the theoretical cooling time can be calculated with high accuracy.

[0169] In the injection molding system (100) according to the fifth aspect, in the third or fourth aspect, the injection molding machine (10) has a cylinder (10a), a screw (10b), and a water pipe (20a). The cylinder (10a) and the screw (10b) are members for metering the amount of resin injected into the mold (20). The water pipe (20a) is a pipe through which cooling water for cooling the mold (20) flows. The multiple physical quantities further include at least one physical quantity among a cylinder temperature, an outside air temperature, a screw rotation speed, and a water pipe flow rate. The cylinder temperature is the temperature of the cylinder (10a). The outside air temperature is the temperature of the outside air. The screw rotation speed is the number of rotations per unit time of the screw (10b). The water pipe flow rate is the flow rate of the cooling water flowing through the water pipe (20a) per unit time. The multiple measured values ​​further include at least one measured value corresponding to at least one physical quantity among the multiple measured values ​​corresponding to the multiple physical quantities. The multiple measured values ​​corresponding to the multiple physical quantities further include a cylinder temperature measured value, an outside air temperature measured value, a screw rotation speed measured value, and a water tube flow rate measured value. The cylinder temperature measured value is a measured value corresponding to the cylinder temperature. The outside air temperature measured value is a measured value corresponding to the outside air temperature. The screw rotation speed measured value is a measured value corresponding to the screw rotation speed. The water tube flow rate measured value is a measured value corresponding to the water tube flow rate. The multiple time series data further includes at least one time series data corresponding to at least one physical quantity among the multiple time series data corresponding to the multiple physical quantities. The multiple time series data corresponding to the multiple physical quantities further includes cylinder temperature time series data, outside air temperature time series data, screw rotation speed time series data, and water tube flow rate time series data. The cylinder temperature time series data is time series data corresponding to the cylinder temperature. The outside air temperature time series data is time series data corresponding to the outside air temperature. The screw rotation speed time series data is time series data corresponding to the screw rotation speed. The water tube flow rate time series data is time series data corresponding to the water tube flow rate.

[0170] According to this embodiment, the multiple physical quantities to be measured by the measurement system (2) include at least one of the cylinder temperature, the outside air temperature, the screw rotation speed, and the water pipe flow rate in addition to the mold temperature and the resin temperature, thereby improving the accuracy of adjusting the molding conditions.

[0171] In the injection molding system (100) according to the sixth aspect, in the fifth aspect, the molding cycle includes an injection time (T1), a cooling time (T2), and a metering time (T4). The injection time (T1) is a time corresponding to the injection process. The injection process is a process of injecting the resin metered in the previous molding cycle into the mold (20). The cooling time (T2) is a time corresponding to the cooling process. The cooling process is a process of cooling the resin injected into the mold (20) in the injection process. The metering time (T4) is a time corresponding to the metering process. The metering process is performed in parallel with the cooling process, and is a process of metering the resin to be injected into the mold (20) in the next molding cycle. The molding conditions further include a scheduled injection time value, and a scheduled metering time value. The scheduled injection time value is a predetermined value of the injection time (T1). The scheduled metering time value is a predetermined value of the metering time (T4). The adjustment value further includes at least one adjustment value of the scheduled injection time value and the scheduled metering time adjustment value. The scheduled injection time adjustment value is an adjustment value for the scheduled metering time value. The shortening unit (133) further shortens at least one scheduled time value corresponding to at least one adjustment value of the scheduled injection time value and the scheduled metering time value.

[0172] According to this embodiment, by further shortening at least one of the cooling time (T2: at least one of the time for cooling while maintaining pressure and the time for cooling without maintaining pressure) and the injection time (T1) and the measurement time (T4), the trial injection period can be further shortened.

[0173] In the injection molding system (100) according to the seventh aspect, in the fifth or sixth aspect, the molding cycle includes an injection time (T1), a cooling time (T2), a measuring time (T4), and a removal time (T3). The injection time (T1) is a time corresponding to the injection process. The injection process is a process of injecting the resin measured in the previous molding cycle into the mold (20). The cooling time (T2) is a time corresponding to the cooling process. The cooling process is a process of cooling the resin injected into the mold (20) in the injection process. The measuring time (T4) is a time corresponding to the measuring process. The measuring process is performed in parallel with the cooling process, and is a process of measuring the resin to be injected into the mold (20) in the next molding cycle. The removal time (T3) is performed after the cooling process, and is a process of removing the molded product produced by injection molding from the mold (20). The molding conditions further include a planned injection time value, a planned metering time value, and a planned removal time value. The planned injection time value is a predetermined value of the injection time (T1). The planned metering time value is a predetermined value of the metering time (T4). The planned removal time value is a predetermined value of the removal time (T3). The injection process includes a filling process and a pressure holding process. The filling process is a process of filling the resin into the mold (20). The pressure holding process is a process of cooling the resin filled in the mold (20) while holding the pressure. The injection time (T1) includes a filling time (T11) and a pressure holding time (T12). The filling time (T11) is a time corresponding to the filling process. The pressure holding time (T12) is a time corresponding to the pressure holding process. The planned injection time value includes a planned filling time value and a planned pressure holding time value. The planned filling time value is a predetermined value of the filling time (T11). The planned dwell time value is a predetermined value of the dwell time (T12). The theoretical cooling time value is the time from when the resin filled into the mold (20) in the filling process starts to be cooled while being held under pressure in the dwell process until the temperature reaches a temperature at which the resin can be removed. The cooling time (T2) includes the dwell time (T12). The molding conditions further include conditions related to the dwell time (T12). The adjustment value further includes a dwell time adjustment value. The dwell time adjustment value is an adjustment value for the planned dwell time value. The shortening unit (133) shortens the dwell time (T12) included in the cooling time (T2) based on the dwell time adjustment value.

[0174] According to this embodiment, the injection process includes a filling process and a pressure holding process, and in the pressure holding process, the resin filled in the filling process is cooled while being held under pressure. In this way, the pressure holding time (T12), which is part of the cooling time (T2), can be shortened, thereby shortening the trial injection period.

[0175] In the injection molding system (100) according to the eighth aspect, in the seventh aspect, the shortening section (133) shortens the pressure holding time (T12) included in the cooling time (T2), and further shortens the cooling time (T2) excluding the pressure holding time (T12).

[0176] According to this embodiment, the pressure holding time with cooling (T1: in other words, the cooling time with pressure holding T2) is shortened, and the cooling time without pressure holding (T2) is also shortened, thereby enabling the shortening of the trial shot period.

[0177] In the injection molding system (100) according to the ninth aspect, in the eighth aspect, the multiple measurement values ​​further include a screw rotation speed measurement value corresponding to the screw rotation speed. The multiple time series data further include screw rotation speed time series data corresponding to the screw rotation speed. The multiple calculation data further include a screw rotation speed prediction value. The screw rotation speed prediction value is a screw rotation speed prediction value for completing the metering step by the end of the cooling step when the pressure holding time (T12) included in the cooling time (T2) is shortened and the cooling time (T2) excluding the pressure holding time (T12) is further shortened. The molding conditions further include a condition related to the metering time (T4). The adjustment value further includes a metering time adjustment value. The metering time adjustment value is an adjustment value for the metering time (T4). The shortening section (133) shortens the pressure holding time (T12) included in the cooling time (T2) and further shortens the cooling time (T2) excluding the pressure holding time (T12). As a result, if the metering step is not completed by the end of the cooling step, the shortening section (133) shortens the metering time (T4) based on the predicted screw rotation speed so that the metering step is completed by the end of the cooling step.

[0178] According to this embodiment, if the metering is not completed within the cooling time (T2), the metering time (T4) is shortened based on the predicted screw rotation speed so that the metering is completed within the cooling time (T2), thereby making it possible to further shorten the trial injection period.

[0179] In the injection molding system (100) according to the tenth aspect, in the ninth aspect, the plurality of calculation data further includes a predicted rise rate value of the mold temperature. The adjustment value is a value that shortens the scheduled cooling time value based on the cooling time adjustment value while aligning the rise prediction curve (CV1) based on the predicted rise rate value with the rise target curve (CV2).

[0180] According to this embodiment, by using an adjustment value that shortens the cooling time (T2) while aligning the predicted rise curve (CV1) with the target rise curve (CV2), it is possible to shorten the cooling time (T2) while controlling the rise in mold temperature.

[0181] In an injection molding system (100) according to an eleventh aspect, in the tenth aspect, the rise prediction curve (CV1) is a curve showing a temperature change such that a mold temperature prediction value based on a rise rate prediction value rises at a first rise rate in a first period and rises at a second rise rate in a second period. The first period is a period from an initial temperature to reaching the first temperature. The first temperature is a temperature close to the mold thermal equilibrium temperature. The first rise rate is a rise rate based on a theoretical cooling time value. The second period is a period from the first temperature to reaching or exceeding the mold thermal equilibrium temperature. The second rise rate is a rise rate smaller than the first rise rate.

[0182] According to this embodiment, the mold temperature is raised (e.g., raised sharply) to a first temperature at a first rise rate, and then raised (e.g., raised slowly) from the first temperature to the mold thermal equilibrium temperature at a second rise rate (<the first rise rate). This makes it possible to shorten the cooling time (T2) while suppressing the phenomenon that occurs when the mold temperature is raised sharply to the mold thermal equilibrium temperature, in which the mold temperature exceeds the mold thermal equilibrium temperature and then drops to the mold thermal equilibrium temperature.

[0183] In the injection molding system (100) according to the twelfth aspect, in any of the second to eleventh aspects, the thermal equilibrium state is a state in which the temperature difference in the mold temperature during a predetermined number of consecutive molding cycles is equal to or less than a third threshold value.

[0184] According to this embodiment, it is possible to determine whether the mold (20) has reached thermal equilibrium based on the mold temperature time series data.

[0185] In the injection molding system (100) according to the thirteenth aspect, in the twelfth aspect, the mold thermal equilibrium temperature is the average value of the mold temperature during a predetermined number of consecutive molding cycles in a thermal equilibrium state.

[0186] According to this aspect, the mold thermal equilibrium temperature can be calculated based on the mold temperature time series data.

[0187] In the injection molding system (100) according to the fourteenth aspect, in any one of the second to thirteenth aspects, the measurement system (2) starts measuring a plurality of physical quantities every time a molding cycle starts.

[0188] According to this aspect, multiple measurements corresponding to multiple physical quantities are started at the start of each molding cycle, and multiple measurement values ​​corresponding to the multiple physical quantities are stored, thereby generating multiple time series data corresponding to the multiple physical quantities.

[0189] In the injection molding system (100) according to the fifteenth aspect, in any one of the second to fourteenth aspects, the trained model (131a) is a first trained model (131a). The second calculation unit (132) includes a second trained model (132a) of machine learning. The second trained model (132a) receives a plurality of pieces of calculation data and outputs an adjustment value.

[0190] According to this aspect, the second calculation unit (132) includes a second trained model (132a) that receives multiple calculation data and outputs an adjustment value, making it possible to output an adjustment value using the trained model.

[0191] The injection molding system (100) according to a sixteenth aspect is in any one of the second to fifteenth aspects, and further includes a model generation unit (134). The model generation unit (134) generates a trained model (131a) by executing a machine learning learning process based on a plurality of time-series data.

[0192] According to this embodiment, a trained model (131a) can be generated. [Explanation of symbols]

[0193] 1 Adjustment device 12 First calculation unit (calculation unit) 13 Adjustment part 131 Data output section 131a First trained model (trained model) 132 Second Calculation Section 132a Second trained model 133 Shortened section 134 Model Generation Unit 2. Measurement System 100 Injection Molding System 10 injection molding machine 10a Cylinder 10b Screw 20 Mold 20a water pipe T1 Injection time T11 Filling time T12 Pressure retention time T2 Cooling time T4 Weighing time T20 Theoretical cooling time

Claims

1. The mold and an injection molding machine that repeatedly performs injection molding of a resin using the mold in accordance with a molding cycle based on predetermined molding conditions; a measurement system that measures a plurality of physical quantities related to the injection molding each time the injection molding machine executes the injection molding and outputs a plurality of measurement values ​​corresponding to the plurality of physical quantities; and an adjustment device that adjusts the molding conditions based at least on a plurality of time-series data corresponding to the plurality of physical quantities, the time-series data being generated by storing the plurality of measurement values ​​output by the measurement system in a time series manner, the molding cycle includes a cooling time from when the resin is injected into the mold by the injection molding machine until the injected resin is cooled and can be removed from the mold, The molding conditions include a cooling time schedule value that is a predetermined value of the cooling time, The adjustment device is A calculation unit that calculates a theoretical cooling time value, which is a theoretical value of the cooling time, by using the plurality of time series data and a calculation formula or information equivalent to the calculation formula; and an adjustment unit that adjusts the molding conditions so as to shorten a trial shot period before the die reaches a thermal equilibrium state when a possible condition that the expected cooling time value is longer than the theoretical cooling time value by a threshold value or more is satisfied. Injection molding system.

2. the calculation unit is a first calculation unit, the plurality of physical quantities include a mold temperature, which is a temperature of the mold, and a resin temperature, which is a temperature of the resin injected into the mold; the plurality of measurement values ​​include a mold temperature measurement value corresponding to the mold temperature and a resin temperature measurement value corresponding to the resin temperature, the plurality of time series data include mold temperature time series data corresponding to the mold temperature and resin temperature time series data corresponding to the resin temperature, the threshold is a first threshold, The adjustment unit is a data output unit including a machine learning trained model to which the plurality of time series data are input and which outputs a plurality of calculation data including a mold thermal equilibrium temperature prediction value, which is a prediction value of the mold thermal equilibrium temperature when the mold is in a thermal equilibrium state; a second calculation unit that calculates an adjustment value for the molding conditions to increase a rate of increase of the mold temperature based on the plurality of calculation data when a necessary condition that the measured mold temperature value is lower than the predicted mold thermal equilibrium temperature value by a second threshold value or more is further satisfied; A shortening unit that shortens the waste-shooting period based on the adjustment value. The injection molding system of claim 1 .

3. the adjustment value includes a cooling time adjustment value that is the adjustment value for the cooling time scheduled value, The shortening unit shortens the expected cooling time value based on the cooling time adjustment value. The injection molding system of claim 2 .

4. The calculation formula is: A first variable into which the mold temperature measurement value is assigned; A second variable into which the resin temperature measurement value is assigned; A first constant corresponding to a removable temperature, which is a temperature at which the resin injected into the mold is cooled and can be removed from the mold; and and at least one second constant corresponding to at least one of the thickness of the molded product by the injection molding, the thermal diffusivity, the thermal conductivity, the specific heat, the density, the glass transition temperature, the latent heat of crystallization, and the degree of temporary crystallization of the resin.

4. The injection molding system of claim 3.

5. The injection molding machine includes: A cylinder and a screw for measuring the amount of the resin to be injected into the mold; and a water pipe through which cooling water for cooling the mold flows, The plurality of physical quantities are a cylinder temperature, which is the temperature of the cylinder; Outside temperature, which is the temperature of the outside air; The screw rotation speed, which is the number of rotations per unit time of the screw, and and a water pipe flow rate, which is a flow rate of the cooling water flowing through the water pipe per unit time; the plurality of measurement values ​​further includes at least one measurement value corresponding to the at least one physical quantity among the plurality of measurement values ​​corresponding to the plurality of physical quantities; The plurality of time series data further includes at least one time series data corresponding to the at least one physical quantity among the plurality of time series data corresponding to the plurality of physical quantities.

4. The injection molding system of claim 3.

6. The molding cycle comprises: an injection time corresponding to an injection step of injecting the resin metered in the previous molding cycle into the mold; a cooling step for cooling the resin injected into the mold in the injection step, a measuring time corresponding to a measuring step which is performed in parallel with the cooling step and measures the resin to be injected into the mold in the next molding cycle; The molding conditions are: An injection time schedule value, which is a predetermined value of the injection time, and A measurement time schedule value, which is a predetermined value of the measurement time, is further included. The adjustment value is An injection time adjustment value for the scheduled injection time value, and a metering time adjustment value to the metering time scheduled value; The shortening unit further shortens at least one scheduled time value corresponding to the at least one adjustment value among the scheduled injection time value and the scheduled metering time value.

6. The injection molding system of claim 5.

7. The molding cycle comprises: an injection time corresponding to an injection step of injecting the resin metered in the previous molding cycle into the mold; the cooling time corresponding to a cooling step of cooling the resin injected into the mold in the injection step; A measurement time corresponding to a measurement step that is performed in parallel with the cooling step and measures the resin to be injected into the mold in the next molding cycle; and a removal step, which is performed after the cooling step and removes the molded product obtained by the injection molding from the mold, The molding conditions are: An injection time schedule value which is a predetermined value of the injection time; A measurement time schedule value, which is a predetermined value of the measurement time, and A predetermined value of the take-out time, which is a take-out time schedule value, The injection step includes: A filling step of filling the mold with the resin; and A pressure-holding step of cooling the resin filled in the mold while holding the pressure, The injection time is A filling time corresponding to the filling step, and A pressure holding time corresponding to the pressure holding step, The injection time schedule value is A filling time estimate value, which is a predetermined value of the filling time, and a pressure-holding time expected value, which is a predetermined value of the pressure-holding time; The theoretical cooling time is a time from when the resin filled in the mold in the filling step starts to be cooled while being held under pressure in the holding pressure step until the resin reaches a temperature at which the resin can be taken out of the mold, and The cooling time includes the pressure retention time, The molding conditions further include a condition regarding the pressure retention time, The adjustment value further includes a pressure-holding time adjustment value that is the adjustment value for the pressure-holding time scheduled value, The shortening unit shortens the pressure retention time included in the cooling time based on the pressure retention time adjustment value.

7. An injection molding system according to claim 5 or 6.

8. The shortening unit shortens the pressure retention time included in the cooling time, and further shortens the cooling time excluding the pressure retention time.

8. The injection molding system of claim 7.

9. The plurality of measurement values ​​further includes a screw rotation speed measurement value corresponding to the screw rotation speed, The plurality of time series data further includes screw rotation speed time series data corresponding to the screw rotation speed, the plurality of calculation data further include a screw rotation speed prediction value which is a prediction value of the screw rotation speed for completing the metering step by the end of the cooling step when the pressure holding time included in the cooling time is shortened and the cooling time excluding the pressure holding time is further shortened, The molding conditions further include a condition regarding the metering time, The adjustment value further includes a metering time adjustment value that is an adjustment value for the metering time, the shortening unit, when the metering step is not completed by the end of the cooling step as a result of shortening the pressure holding time included in the cooling time and further shortening the cooling time excluding the pressure holding time, shortens the metering time based on the predicted screw rotation speed value so that the metering step is completed by the end of the cooling step.

9. The injection molding system of claim 8.

10. The plurality of calculation data further includes a predicted value of a rise rate of the mold temperature, The adjustment value is a value that shortens the scheduled cooling time value based on the cooling time adjustment value while aligning the predicted increase curve based on the predicted increase rate value with the target increase curve.

10. The injection molding system of claim 9.

11. The rise prediction curve is a mold temperature prediction value based on the rise rate prediction value, During a first period from the initial temperature to a first temperature in the vicinity of the mold thermal equilibrium temperature, the temperature rises at a first rate of increase based on the theoretical cooling time value, a curve showing a temperature change in which the temperature rises at a second rate of increase which is smaller than the first rate of increase during a second period from the first temperature to the mold thermal equilibrium temperature or higher; 11. The injection molding system of claim 10.

12. The thermal equilibrium state is a state in which a temperature difference between the mold temperature and a predetermined number of consecutive molding cycles is equal to or less than a third threshold value. The injection molding system of claim 2 .

13. The mold thermal equilibrium temperature is an average value of the mold temperature during the predetermined number of consecutive molding cycles in the thermal equilibrium state.

13. The injection molding system of claim 12.

14. the measurement system starts measuring the plurality of physical quantities every time the molding cycle starts. The injection molding system of claim 2 .

15. The trained model is a first trained model, The second calculation unit includes a second trained model of the machine learning to which the plurality of calculation data are input and which outputs the adjustment value. The injection molding system of claim 2 .

16. A model generation unit that generates the trained model by executing the machine learning learning process based on the plurality of time series data. The injection molding system of claim 2 .

Images