Molding machine and method of operation of a molding machine

Abstract

The molding machine of the embodiment is provided with: a mold clamping device; an injection device; a control device that controls molding operation using the mold clamping device and the injection device; a part life prediction device including an operation history information storage unit that stores operation history information of the molding operation, a replacement history information storage unit that stores replacement history information of a first part, a life prediction value storage unit that stores a life prediction value of the first part, and a correction unit that corrects the life prediction value of the first part based on the operation history information and the replacement history information of the first part at the time of replacement of the first part; and a display device that enables display of the operation history information, the replacement history information, and the life prediction value.

Description

Technical Field

[0001] This invention relates to a molding machine and a method of operating the molding machine, and particularly to a molding machine and a method of operating the molding machine for predicting the lifespan of parts. Background Technology

[0002] In molding machines such as die-casting machines or injection molding machines, control devices regulate the injection and clamping mechanisms according to desired operating conditions to manufacture products. If a part of the molding machine is damaged, malfunctions, or is worn out, product manufacturing ceases until the damaged, malfunctioning, or worn-out part is replaced. In particular, in cases where a replacement part is not readily available, the time required to prepare the part is added to the manufacturing downtime. Prolonged downtime in product manufacturing can lead to significant losses.

[0003] If the replacement period for parts is known in advance, replacement parts can be prepared in advance. By preparing replacement parts in advance, manufacturing downtime caused by part damage, malfunction, or consumption can be minimized.

[0004] On the other hand, the increased costs due to preparing too many replacement parts can also lead to losses. Therefore, it is desirable to predict the lifespan of molding machine parts with high accuracy.

[0005] Existing technical documents

[0006] Patent documents

[0007] Patent Document 1: Japanese Patent Application Publication No. 2019-36158 Summary of the Invention

[0008] The problem that the invention aims to solve

[0009] The problem to be solved by the present invention is to provide a molding machine and a method for operating the molding machine that can predict the life of parts with high accuracy.

[0010] Methods used to solve problems

[0011] A molding machine according to one embodiment of the present invention includes: a mold clamping device; an injection device; a control device for controlling the molding operation using the mold clamping device and the injection device; a part life prediction device, comprising an action history information storage unit for storing action history information of the molding operation, a replacement history information storage unit for storing replacement history information of a first part, a life prediction value storage unit for storing a life prediction value of the first part, and a correction unit, wherein the correction unit corrects the life prediction value of the first part based on the action history information and the replacement history information of the first part when the first part is replaced; and a display device capable of displaying the action history information, the replacement history information, and the life prediction value.

[0012] In the molding machine of the above technical solution, it is preferable that after the correction unit corrects the life prediction value of the first part when the first part is replaced, the life prediction value of the first part is further corrected based on the operation history information during the period until the first part is replaced again.

[0013] In the molding machine of the above technical solution, it is preferable that the correction unit corrects the life prediction value of the first part based on the information from the previous replacements in the replacement history information of the first part.

[0014] In the molding machine of the above technical solution, preferably, the replacement history information storage unit stores the replacement history information of the second part; and the life prediction value storage unit stores the life prediction value of the second part.

[0015] In the molding machine of the above technical solution, it is preferable that when the first part is replaced, the correction unit corrects the life prediction value of the first part based on the replacement history information of the second part.

[0016] In the molding machine of the above technical solution, it is preferable that the correction unit corrects the life prediction value of the second part when the first part is replaced.

[0017] In the molding machine of the above technical solution, it is preferable to further include an environmental information storage unit that stores environmental history information of the environment in which the mold clamping device and the injection device are placed; when the first part is replaced, the correction unit corrects the life prediction value of the first part based on the environmental history information.

[0018] In the molding machine of the above technical solution, it is preferable to display an alarm on the display device based on the above action history information and the life prediction value of the first part.

[0019] In the molding machine of the above technical solution, preferably, the life prediction value of the first part includes different prediction values ​​based on different action counts in the above action history information.

[0020] The present invention provides a method for operating a molding machine, the molding machine comprising: a mold clamping device; an injection device; and a control device for controlling the molding operation using the mold clamping device and the injection device; and when a first part of the molding machine is replaced, the life prediction value of the first part is corrected based on the operation history of the molding machine and the replacement history of the first part.

[0021] In the above-described method for operating the molding machine, it is preferable that, after the life prediction value of the first part is corrected when the first part is replaced, the life prediction value of the first part is further corrected based on the operation history information of the molding machine until the next replacement of the first part.

[0022] In the operating method of the molding machine in the above technical solution, it is preferable to correct the life prediction value of the first part based on information from previous replacements of the first part.

[0023] In the operating method of the molding machine in the above technical solution, it is preferred that when the first part is replaced, the life prediction value of the first part is corrected based on the replacement history of the second part.

[0024] In the operating method of the molding machine in the above technical solution, it is preferable to correct the life prediction value of the second part when the first part is replaced.

[0025] In the operating method of the molding machine in the above technical solution, it is preferable that when the first part is replaced, the life prediction value of the first part is corrected based on the environmental history of the environment in which the mold clamping device and the injection device are placed.

[0026] Invention Effects

[0027] According to the present invention, a molding machine and a method of operating the molding machine are provided that can predict the lifespan of parts with high accuracy. Attached Figure Description

[0028] Figure 1 This is a schematic diagram showing the molding machine according to the first embodiment.

[0029] Figure 2 This is a schematic diagram of a part of the molding machine according to the first embodiment.

[0030] Figure 3 This is an action block diagram of the operation method of the molding machine according to the first embodiment.

[0031] Figure 4 This is an action block diagram of the operation method of the molding machine according to the second embodiment.

[0032] Figure 5 This is an action block diagram of the operation method of the molding machine according to the third embodiment.

[0033] Figure 6 This is an action block diagram of the operation method of the molding machine according to the fourth embodiment.

[0034] Figure 7 This is a schematic diagram showing the molding machine according to the fifth embodiment.

[0035] Figure 8 This is an action block diagram of the operation method of the molding machine according to the fifth embodiment. Detailed Implementation

[0036] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

[0037] (First Embodiment)

[0038] The molding machine of the first embodiment includes: a mold clamping device; an injection device; a control device for controlling the molding operation using the mold clamping device and the injection device; a part life prediction device, including an action history information storage unit for storing action history information of the molding operation, a replacement history information storage unit for storing replacement history information of a first part, a life prediction value storage unit for storing a life prediction value of the first part, and a correction unit, wherein the correction unit corrects the life prediction value of the first part based on the action history information and the replacement history information of the first part when the first part is replaced; and a display device capable of displaying the action history information, the replacement history information, and the life prediction value.

[0039] Figure 1 This is a schematic diagram showing the molding machine according to the first embodiment. Figure 1 This is a plan view of the molding machine according to the first embodiment. Figure 2 This is a schematic diagram of a part of the molding machine according to the first embodiment.

[0040] Figure 2 This is a side view of the mold clamping device, ejection device, injection device, and mold of the molding machine according to the first embodiment. The molding machine of the first embodiment is a die-casting machine 100.

[0041] like Figure 1As shown, the die-casting machine 100 includes a mold clamping device 10, an ejection device 12, an injection device 14, a mold 16, a control device 18, a display device 20, an operating device 24, a spraying device 26, a melt supply device 28, and a part life prediction device 30. The part life prediction device 30 includes a correction unit 30a, an operation history information storage unit 30b, a replacement history information storage unit 30c, and a life prediction value storage unit 30d.

[0042] like Figure 2 As shown, the die-casting machine 100 includes a base 32, a fixed template 34, a movable template 36, a connecting rod housing 38, a tie rod 40, a sliding plate 42, a mold closing cylinder 44, an injection cylinder 46, a top core 48, and an injection sleeve 50.

[0043] The die-casting machine 100 is operated by casting through a cavity formed by the mold 16. Figure 2 A machine that manufactures die-cast products by injecting liquid metal (molten metal) into a mold 16 and solidifying the metal. The metal may be, for example, an aluminum alloy, zinc alloy, or magnesium alloy.

[0044] The mold 16 is located between the mold closing device 10 and the injection device 14. The mold 16 includes, for example, a fixed mold 16a and a movable mold 16b.

[0045] The mold closing device 10 has the function of opening, closing and closing the mold 16. The mold closing device 10 uses the mold closing cylinder 44 to open, close and close the mold 16.

[0046] The injection device 14 has the function of injecting liquid metal into the interior of the mold 16. The injection device 14 includes an injection cylinder 46, an ejector core 48, and an injection sleeve 50. The injection device 14 uses the injection cylinder 46 to move the ejector core 48 in the injection sleeve 50. Liquid metal is injected into the interior of the mold 16 through the ejector core 48.

[0047] The ejection device 12 has the function of ejecting the die-cast product from the fixed mold or the movable mold to separate it.

[0048] The fixed template 34 is fixed on the base 32. The fixed template 34 can hold the fixed mold 16a.

[0049] The movable template 36 is mounted on a sliding plate 42 above the base 32. The movable template 36 is capable of moving in the mold opening and closing direction. The mold opening and closing direction is... Figure 2 The diagram shows the mold opening direction and the mold closing direction. The movable template 36 can hold the movable mold 16b against the fixed mold 16a.

[0050] The connecting rod housing 38 is mounted on the base 32. One end of the connecting rod mechanism constituting the mold clamping device 10 is fixed to the connecting rod housing 38.

[0051] The fixed template 34 and the connecting rod housing 38 are secured by a tie rod 40. The tie rod 40 supports the closing force during the application of the closing force to the fixed mold 16a and the movable mold 16b.

[0052] The spraying device 26 has the function of spraying air used to clean the mold 16 into the mold 16. In addition, the spraying device 26 has the function of spraying a release agent used to facilitate the ejection of the die-cast product from the mold 16 into the mold 16.

[0053] The molten metal supply device 28 has the function of supplying molten metal to the injection sleeve 50 of the injection device 14. In each cycle of die casting production, molten metal is supplied to the injection sleeve 50.

[0054] The operating device 24 includes operating switches for operating the mechanical actions of the mold clamping device 10, the ejection device 12, and the injection device 14. The operating device 24 may include, for example, power switches, start switches, and stop switches for the mold clamping device 10, the ejection device 12, and the injection device 14. Furthermore, the operating device 24 may include, for example, an opening / closing switch for the mold 16.

[0055] The control device 18 has the function of controlling the molding operations of the mold clamping device 10, the ejector device 12, and the injection device 14. The control device 18 outputs commands to the mold clamping device 10, the ejector device 12, and the injection device 14 to perform molding operations under preset desired operating conditions. For example, the control device 18 provides feedback on the operating status of the monitored mold clamping device 10, the ejector device 12, and the injection device 14, and controls the molding operations of the mold clamping device 10, the ejector device 12, and the injection device 14.

[0056] The control device 18 may be composed of a combination of hardware and software. The control device 18 may include, for example, a CPU (Central Processing Unit), a semiconductor memory, and a control program stored in the semiconductor memory.

[0057] The part life prediction device 30 includes a correction unit 30a, an operation history information storage unit 30b, a replacement history information storage unit 30c, and a life prediction value storage unit 30d. The part life prediction device 30 has the function of predicting the lifespan of the parts constituting the die-casting machine 100. For example, the part life prediction device 30 has the function of calculating a life prediction value for the parts constituting the die-casting machine 100 plus a predetermined safety factor.

[0058] The parts for which life prediction is performed include, for example, the base 32, the fixed template 34, the movable template 36, the connecting rod housing 38, the sliding plate 42, the mold closing cylinder 44, the tie rod 40, the injection cylinder 46, the ejector core 48, or the injection sleeve 50. The base 32, the fixed template 34, the movable template 36, the connecting rod housing 38, the sliding plate 42, the mold closing cylinder 44, the tie rod 40, the injection cylinder 46, the ejector core 48, or the injection sleeve 50 are examples of the first part. The parts for which life prediction is performed may also be added by the user of the die-casting machine 100.

[0059] The motion history information storage unit 30b stores the motion history information of the molding motion of the die-casting machine 100. The motion history information includes, for example, motion counts of various motions included in the molding motion, which are associated with a date and time. The motion counts are the cumulative number of times or cumulative time for various motions. Examples of motion counts include the cumulative number of times or cumulative time for mold closing motions, mold opening and closing motions, ejection motions, injection motions, or pressurization motions.

[0060] For example, the mold-closing action can be further divided into multiple actions for counting. For example, the mold-closing action can be divided into all mold-closing actions and mold-closing actions above the specified mold-closing force for counting.

[0061] For example, the pressurization action can be further divided into multiple actions for counting. For example, the cumulative number of pressurization actions can be divided into the cumulative number of all pressurization actions and the cumulative number of pressurization actions above the specified pressure for counting.

[0062] By linking the counts of each action with date and time, it is possible to track the cumulative number of times and the cumulative time for each action within a specific period. For example, it is possible to track the cumulative number of times and the cumulative time for mold closing actions within a specific period. Furthermore, it is possible to track the cumulative number of times and the cumulative time for injection actions within a specific period.

[0063] The replacement history information storage unit 30c stores the replacement history information of the parts. The replacement history information of the parts includes, for example, the replacement date and time for each part.

[0064] The life prediction value storage unit 30d stores the life prediction values ​​of the parts. The life prediction value of a part is represented, for example, by the action count up to the point where the part is damaged, malfunctions, or consumed. The initial value of the life prediction value of each part is entered into the life prediction value storage unit 30d, for example, at the time when the die-casting machine 100 first starts working.

[0065] The motion history information storage unit 30b, the replacement history information storage unit 30c, and the lifespan prediction value storage unit 30d are storage devices. For example, the motion history information storage unit 30b, the replacement history information storage unit 30c, and the lifespan prediction value storage unit 30d are semiconductor memories or hard disks.

[0066] The correction unit 30a has the function of correcting the life prediction value of a part based on the operation history information and the part replacement history information when the part is replaced.

[0067] When replacing parts, for example, the life prediction value may be adjusted to the actual number of motions from the previous part replacement to the current replacement. Alternatively, the life prediction value may be adjusted to the number of motions from the previous part replacement to the current replacement plus a specified margin.

[0068] Specifically, for example, it is assumed that the life prediction value is defined by the cumulative number of mold closing actions. When a part is damaged, malfunctions, or worn out and needs to be replaced, a correction is made to change the life prediction value to the cumulative number of mold closing actions from the previous replacement to the current replacement.

[0069] The algorithm for correcting the lifetime prediction is stored, for example, in a semiconductor memory contained in the correction unit 30a.

[0070] The correction unit 30a may be composed of a combination of hardware and software. The correction unit 30a may include, for example, a CPU, a semiconductor memory, and a correction algorithm stored in the semiconductor memory.

[0071] Furthermore, the part life prediction device 30 may not necessarily be located near the mold clamping device 10, the ejection device 12, the injection device 14, and the control device 18. For example, part or all of the part life prediction device 30 may be located away from the mold clamping device 10, the ejection device 12, the injection device 14, and the control device 18. For example, part or all of the part life prediction device 30 may be wirelessly connected to the control device 18. For example, the data stored in the part life prediction device 30 may be read from an external storage medium. For example, the data stored in the part life prediction device 30 may be editable by the user.

[0072] Display device 20 is an input / output device for control device 18 and part life prediction device 30. Display device 20 has the function of accessing control device 18 and setting desired operating conditions of die casting machine 100 for actual molding operations.

[0073] The display device 20 can display the operating conditions of the molding operation of the die-casting machine 100. In addition, the display device 20 can display, for example, the injection waveform of the molding operation, warning messages (alarms), the number of products produced, the production progress, quality data, and the running time.

[0074] Furthermore, the display device 20 can display operation history information, replacement history information, and lifespan prediction values. For example, the display device 20 accesses the part lifespan prediction device 30 and displays the operation count for each operation. The display device 20 also accesses the part lifespan prediction device 30 and displays the replacement date and time for each part. Additionally, the display device 20 accesses the part lifespan prediction device 30 and displays the lifespan prediction value for each part. Furthermore, the display device 20 has, for example, the function of accessing the part lifespan prediction device 30 and inputting the initial value of the lifespan prediction value for each part. Furthermore, the display device 20 has, for example, the function of displaying the correction result of the lifespan prediction value given by the part lifespan prediction device 30.

[0075] Display device 20 may be a liquid crystal display, for example, including a touch panel. Display device 20 may also be an organic EL display, for example, including a touch panel.

[0076] Next, the operation method of the molding machine according to the first embodiment will be described. The operation method of the molding machine according to the first embodiment is a method of operating a molding machine equipped with a mold clamping device, an injection device, and a control device for controlling the molding operation using the mold clamping device and the injection device. When the first part of the molding machine is replaced, the life prediction value of the first part is corrected based on the operation history of the molding machine and the replacement history of the first part.

[0077] Figure 3 This is an operation block diagram of the operation method of the molding machine according to the first embodiment. The operation method of the molding machine according to the first embodiment, for example, uses... Figure 1 and Figure 2 The die-casting machine 100 shown is used for this process.

[0078] The following explanation will take the case where the first part is the sliding plate 42 of the die-casting machine 100 as an example. Furthermore, the explanation will also take the case where the life prediction value and life forecast value of the sliding plate 42 are determined by the cumulative number of mold closing operations as an example.

[0079] First, input the initial values ​​for the life prediction and life forecast of the slide plate 42. The initial life forecast value is, for example, 1000 cumulative mold closing operations. Similarly, the initial life prediction value is, for example, 990 cumulative mold closing operations. The life prediction value is based on the life forecast value and is set considering a specified safety factor.

[0080] Then, the molding process continues. The number of mold closing actions is counted, and the cumulative number of mold closing actions is calculated.

[0081] Furthermore, after a molding operation is completed, the cumulative number of mold closing operations is compared with the life prediction value and the life forecast value.

[0082] For example, an alarm is issued when the cumulative number of mold closing actions reaches 990 times, the life prediction value. The alarm is displayed, for example, on display device 20. For example, at the time the alarm is issued, a new slide plate 42 is prepared for replacement.

[0083] Furthermore, for example, an alarm is issued when the cumulative number of mold closing operations reaches 1000 times, the predicted lifespan. The alarm is displayed, for example, on the display device 20. If a new slide plate 42 for replacement has not been prepared by the time the alarm is issued, a new slide plate 42 is prepared.

[0084] If a replacement event occurs during or after the molding process, the slide plate 42 shall be replaced. Such a replacement event could be damage, malfunction, or wear and tear of the slide plate 42. For example, if the slide plate 42 is damaged during the molding process, it shall be replaced.

[0085] For example, if the life prediction of the slide plate 42 continues, the life prediction value and the life forecast value of the slide plate 42 are revised. For example, if it is decided that the replacement parts of the slide plate 42 are kept on hand and the life prediction of the slide plate 42 is no longer needed, the slide plate 42 is excluded from the parts subject to life prediction, and the life prediction of the slide plate 42 ends.

[0086] For example, if the slide plate 42 is damaged after 1100 cumulative mold closing operations since the last replacement, the predicted lifespan of the slide plate 42 is revised to 1100 operations. Alternatively, the predicted lifespan of the slide plate 42 is revised to 1000 operations.

[0087] Furthermore, the correction of the life prediction value and the life forecast value can be performed automatically, for example, based on the correction algorithm stored in the correction unit 30a of the part life prediction device 30. In addition, the correction of the life prediction value and the life forecast value can also be performed manually, taking into account various situations.

[0088] Then, continue the molding process. For example, reset the cumulative number of mold closing actions for the sliding plate 42 to zero.

[0089] The following describes the function and effects of the molding machine and its operating method according to the first embodiment.

[0090] In molding machines such as die-casting machines and injection molding machines, control devices regulate the injection and clamping mechanisms according to desired operating conditions to manufacture products. If a part of the molding machine is damaged, malfunctions, or is worn out, product manufacturing ceases until the damaged, malfunctioning, or worn-out part is replaced. In particular, if a replacement part is not readily available, the time until the part is prepared is added to the manufacturing downtime. Prolonged downtime in product manufacturing can result in significant losses.

[0091] If the replacement period for parts is known in advance, replacement parts can be prepared in advance. By preparing replacement parts in advance, manufacturing downtime caused by part damage, malfunction, or consumption can be minimized.

[0092] On the other hand, the increased costs due to preparing too many replacement parts can also lead to losses. Therefore, it is desirable to predict the lifespan of molding machine parts with high accuracy.

[0093] The die-casting machine 100 of the first embodiment includes a part life prediction device 30. The part life prediction device 30 has the function of correcting the predicted life value of the part based on the operation history information and the part replacement history information when the part is replaced. By correcting the life prediction value when the part is replaced, the life of the parts of the die-casting machine 100 can be predicted with high accuracy.

[0094] Because the lifespan of parts can be predicted with high accuracy, replacement parts can be prepared in advance. Even in the event of part damage, malfunction, or wear and tear, downtime of the die-casting machine 100 can be minimized. Therefore, significant losses due to prolonged downtime in product manufacturing can be prevented. Furthermore, the increased costs caused by excessive preparation of replacement parts can be suppressed.

[0095] The operating method of the die-casting machine 100 in the first embodiment can predict the lifespan of the parts of the die-casting machine 100 with high accuracy by correcting the lifespan prediction value when the parts are replaced. Therefore, it is possible to suppress significant losses caused by prolonged shutdowns of product manufacturing. In addition, it is also possible to suppress the increase in costs caused by preparing an excess of replacement parts.

[0096] The correction unit 30a can also correct the predicted lifespan of a part based on information from past replacements in the part's replacement history. For example, it can correct the predicted lifespan by setting the average of the number of operations from the last part replacement to the latest part replacement and the number of operations from the time before that to the last part replacement. Alternatively, it can correct the predicted lifespan by setting the smaller of the number of operations from the last part replacement to the latest part replacement and the number of operations from the time before that to the last part replacement.

[0097] By correcting the life prediction of a part based on information from multiple past replacements in the part's replacement history, the life of parts in the die-casting machine 100 can be predicted with higher accuracy.

[0098] According to the molding machine and its operation method in the first embodiment, by correcting the life prediction value when the part is replaced, the life of the part can be predicted with high accuracy.

[0099] (Second Implementation)

[0100] The molding machine of the second embodiment differs from the molding machine of the first embodiment in the following respect: after the correction unit corrects the lifespan prediction value of the first part when the first part is replaced, it further corrects the corrected lifespan prediction value of the first part based on operation history information during the period until the next replacement of the first part. Furthermore, the operating method of the molding machine of the second embodiment differs from the operating method of the molding machine of the first embodiment in the following respect: after correcting the lifespan prediction value of the first part when the first part is replaced, it further corrects the corrected lifespan prediction value of the first part based on operation history information during the period until the next replacement of the first part. Hereinafter, some descriptions that are repeated with the molding machine and its operating method of the first embodiment will be omitted.

[0101] The molding machine of the second embodiment is Figure 1 and Figure 2 The die-casting machine 100 shown.

[0102] The correction unit 30a of the part life prediction device 30 has the function of correcting the predicted life value of the part when the part is replaced, and further correcting the corrected predicted life value of the part based on the operation history information during the period until the next replacement of the part. In other words, the correction unit 30a has the function of correcting the predicted life value of the part based on the operation history information before the part is damaged, malfunctions or consumed.

[0103] For example, if the operation of the molding machine exceeds the predetermined range, the correction unit 30a will correct the predicted lifespan of the part, even if it is not a part replacement. The part lifespan prediction device 30, for example, has the function of monitoring whether the operation of the molding machine exceeds the predetermined range.

[0104] Figure 4 This is an operation block diagram of the operation method of the molding machine according to the second embodiment. The operation method of the molding machine according to the second embodiment, for example, uses... Figure 1 and Figure 2 The die-casting machine 100 shown is used for this process.

[0105] The following explanation will take the case where the first part is the sliding plate 42 of the die-casting machine 100 as an example. Furthermore, the explanation will also take the case where the predicted lifespan of the sliding plate 42 is determined by the cumulative number of mold closing operations as an example.

[0106] First, input the initial value for the life prediction of the slide plate 42. For example, the initial value for the life prediction is 1000 cumulative mold closing operations. Furthermore, the initial value for the life forecast is, for example, 990 cumulative mold closing operations. The life forecast value is based on the life prediction value. Additionally, the cumulative mold closing operations are preset to a range of less than 30 times per week.

[0107] Then, continue the molding process. Count the number of mold closing actions and calculate the cumulative number of mold closing actions.

[0108] Next, after one molding operation is completed, monitor whether the cumulative number of mold closing operations within one cycle is less than 30. If the cumulative number of mold closing operations within one cycle is less than 30 (within the expected range), continue the molding operation.

[0109] If the cumulative number of mold closing actions exceeds 30 times within one cycle, the life prediction and life forecast values ​​of the sliding plate 42 are corrected. For example, the life forecast value is corrected to 900 times, which is 90% of the initial value. For example, the life prediction value is corrected to 800 times.

[0110] Next, the cumulative number of mold closing actions is compared with the life prediction value and the life forecast value.

[0111] For example, an alarm is issued when the cumulative number of mold closing operations reaches 800 or 990 times, which is the life prediction value. The alarm is displayed, for example, on the display device 20. For example, a new slide plate 42 is prepared for replacement at the time the alarm is issued.

[0112] Furthermore, an alarm may be issued, for example, when the cumulative number of mold closing operations reaches 990 or 1000 times, which is the predicted lifespan. The alarm may be displayed, for example, on the display device 20. If a new slide plate 42 is not prepared for replacement at the time the alarm is issued, a new slide plate 42 may be prepared.

[0113] For example, if it is decided that the replacement parts of the slide plate 42 will be kept on hand and the life prediction of the slide plate 42 will no longer be needed, the slide plate 42 will be removed from the list of parts to be predicted for life, and the life prediction of the slide plate 42 will be terminated.

[0114] For example, if the slide plate 42 is damaged after 950 cumulative mold closing operations since the last replacement, the predicted lifespan of the slide plate 42 is revised to 950 operations. Alternatively, the predicted lifespan of the slide plate 42 may be revised to 900 operations.

[0115] Then, continue the molding process. For example, reset the cumulative number of mold closing actions to zero.

[0116] If the operation of the die-casting machine 100 exceeds the intended range, an excessive load will be applied to the parts of the die-casting machine 100, and the intended lifespan of the parts will be shortened.

[0117] In the second embodiment, the molding machine and its operating method correct the predicted lifespan of the parts even when the operation of the die-casting machine 100 exceeds a predetermined range, even if it is not a part replacement. Therefore, compared to the first embodiment, the lifespan of the parts in the die-casting machine 100 can be predicted with higher accuracy.

[0118] According to the molding machine and its operation method in the second embodiment, by correcting the lifespan prediction value when the part is replaced, the lifespan of the part can be predicted with higher accuracy. Furthermore, even when the operation of the molding machine exceeds a predetermined range, by correcting the lifespan prediction value of the part even when it is not a part replacement, the lifespan of the parts of the die-casting machine 100 can be predicted with even higher accuracy.

[0119] (Third Implementation)

[0120] The molding machine of the third embodiment differs from the molding machine of the first embodiment in that: the replacement history information storage unit stores the replacement history information of the second part, and the correction unit corrects the life prediction value of the first part based on the replacement history information of the second part when the first part is replaced. Furthermore, the operating method of the molding machine of the third embodiment differs from the operating method of the molding machine of the first embodiment in that it corrects the life prediction value of the first part based on the replacement history of the second part when the first part is replaced. Hereinafter, some descriptions that are repeated with the molding machine and its operating method of the first embodiment will be omitted.

[0121] The molding machine in the third embodiment is Figure 1 and Figure 2 The die-casting machine 100 shown.

[0122] The replacement history information storage unit 30c of the part life prediction device 30 stores the replacement history information of the first part and the second part. Furthermore, the correction unit 30a of the part life prediction device 30 has the function of correcting the life prediction value of the first part based on the operation history information, the replacement history information of the first part, and the replacement history information of the second part when the first part is replaced.

[0123] For example, the correction unit 30a has the function of correcting the life prediction value of the first part based on the number of operation counts of molding operations since the last replacement of the second part when the first part is replaced. For example, the correction unit 30a has the function of correcting the life prediction value of the first part to make it larger when the number of operation counts of the second part is less than 10% of the life prediction value of the second part.

[0124] Figure 5 This is an operation block diagram of the operation method of the molding machine according to the third embodiment. The operation method of the molding machine according to the third embodiment, for example, uses... Figure 1 and Figure 2 The die-casting machine 100 shown is used for this process.

[0125] The following explanation will be based on the case where the first part is the core 48 of the injection device 14 and the second part is the injection sleeve 50 of the injection device 14.

[0126] First, input the initial values ​​for the predicted and predicted lifetime of the core 48. For example, the initial predicted lifetime value is 50 cumulative injection attempts. The initial predicted lifetime value is, for example, 45 cumulative injection attempts.

[0127] Next, input the initial value for the predicted lifespan of the injection cannula 50. For example, the initial value for the predicted lifespan is 200 cumulative injection cycles.

[0128] Then, continue with the molding process. Count the number of injection actions and calculate the cumulative number of injection actions.

[0129] Furthermore, after a molding operation is completed, the number of injection operations is compared with the predicted and estimated lifespan values ​​of the top core 48.

[0130] For example, an alarm is triggered when the cumulative number of injection actions reaches 45, the lifespan prediction value. The alarm is displayed, for example, on display device 20. For example, at the time the alarm is triggered, a replacement core 48 is prepared.

[0131] Furthermore, an alarm may be issued, for example, when the cumulative number of injection actions reaches 50 times the predicted lifespan. The alarm may be displayed, for example, on the display device 20. If a replacement core 48 is not prepared at the time the alarm is issued, a new core 48 may be prepared.

[0132] If a replacement event occurs during or after the molding process, the top core 48 will be replaced. The replacement event could be due to damage, malfunction, or wear of the top core 48. For example, if the top core 48 is damaged, it will be replaced. Alternatively, if the lifespan prediction of the top core 48 continues, the predicted lifespan value will be revised.

[0133] For example, if the core 48 is damaged after a cumulative number of injection actions of 60 since the last replacement, the predicted lifespan of the core 48 is revised from the initial value of 50 to 60. Furthermore, the predicted lifespan of the core 48 is revised from the initial value of 45 to 50.

[0134] Furthermore, the predicted lifespan of the core 48 is adjusted based on the cumulative number of injection actions since the last replacement of the injection cannula 50. For example, if the cumulative number of injection actions for which the predicted lifespan of the injection cannula 50 is specified is less than 10% of 200 injection actions, which is the predicted lifespan of the injection cannula 50, the predicted lifespan of the core 48 is increased. Additionally, the predicted lifespan of the core 48 is increased.

[0135] For example, if the cumulative number of injection actions for which the predicted lifespan of the injection cannula 50 is specified is 10, the predicted lifespan of the core 48 is set to 1.2 times. That is, it is corrected to 1.2 times 60 times, or 72 times. In addition, the predicted lifespan of the core 48 is corrected to 1.2 times 50 times, or 60 times.

[0136] Then, continue the molding process. For example, reset the cumulative number of injection actions for the top core 48 to zero.

[0137] For example, there may be a causal relationship between the lifespan of the first part and the replacement period of the second part in the die-casting machine 100. For instance, consider the case where the first part is the ejector core 48 that moves within the injection sleeve 50, and the second part is the injection sleeve 50 itself. If the elapsed time since the replacement of the injection sleeve 50 is short, the lifespan of the ejector core 48 tends to be longer. In other words, if the cumulative number of injection actions since the replacement of the injection sleeve 50 is low, the lifespan of the ejector core 48 tends to be longer.

[0138] Therefore, by correcting the predicted lifespan of the top core 48 towards an increasing value when the cumulative number of injection actions from the replacement of the injection cannula 50 is small, the lifespan of the top core 48 can be predicted with higher accuracy.

[0139] In the third embodiment, the molding machine and its operation method correct the life prediction value of the first part based on operation history information, replacement history information of the first part, and replacement history information of the second part when the first part is replaced. Therefore, compared with the first embodiment, the life of the parts of the die-casting machine 100 can be predicted with higher accuracy.

[0140] According to the molding machine and its operation method in the third embodiment, by correcting the lifespan prediction value when the first part is replaced, the lifespan of the first part can be predicted with higher accuracy. Furthermore, by correcting the lifespan prediction value of the first part based on the replacement history information of the second part, the lifespan of the first part can be predicted with even higher accuracy.

[0141] (Fourth implementation)

[0142] The molding machine of the fourth embodiment differs from the molding machine of the third embodiment in that the correction unit corrects the life prediction value of the second part when the first part is replaced. Furthermore, the operating method of the molding machine of the fourth embodiment differs from the operating method of the molding machine of the third embodiment in that the correction of the life prediction value of the second part is performed when the first part is replaced. Hereinafter, some descriptions that are repeated with the molding machines and their operating methods of the first and third embodiments will be omitted.

[0143] The molding machine in the fourth embodiment is Figure 1 and Figure 2 The die-casting machine 100 shown.

[0144] The replacement history information storage unit 30c of the part life prediction device 30 stores the replacement history information of the first part and the second part. Furthermore, the correction unit 30a of the part life prediction device 30 has the function of correcting the life prediction value of the second part when the first part is replaced.

[0145] For example, the correction unit 30a has the function of making corrections when the first part is replaced so as to increase the life prediction value of the second part.

[0146] Figure 6 This is an operation block diagram of the operation method of the molding machine according to the fourth embodiment. The operation method of the molding machine according to the fourth embodiment, for example, uses... Figure 1 and Figure 2 The die-casting machine 100 shown is used for this process.

[0147] The following explanation will be based on the case where the first part is the core 48 of the injection device 14 and the second part is the injection sleeve 50 of the injection device 14.

[0148] First, input the initial value for the predicted lifetime of the core 48. For example, the initial value for the predicted lifetime is 50 cumulative injection actions. Alternatively, the initial value for the predicted lifetime is 45 cumulative injection actions.

[0149] Next, input the predicted lifespan value and the initial value of the lifespan forecast for the injection cannula 50. For example, the initial value of the lifespan forecast is 200 cumulative injection actions. For example, the initial value of the predicted lifespan is 180 cumulative injection actions.

[0150] Then, continue with the molding process. Count the number of injection actions and calculate the cumulative number of injection actions.

[0151] For example, an alarm is issued when the cumulative number of injection actions reaches 45, the lifespan prediction value. The alarm is displayed, for example, on display device 20. For example, at the time the alarm is issued, the replacement core 48 is prepared.

[0152] Furthermore, an alarm may be issued, for example, when the cumulative number of injection actions reaches 50 times the predicted lifespan. The alarm may be displayed, for example, on the display device 20. If a replacement core 48 is not prepared at the time the alarm is issued, a new core 48 may be prepared.

[0153] If a replacement event occurs during or after the molding process, the top core 48 will be replaced. The replacement event could be due to damage, malfunction, or wear of the top core 48. For example, if the top core 48 is damaged, it will be replaced. Alternatively, if the lifespan prediction of the top core 48 continues, the predicted lifespan value will be revised.

[0154] For example, if the core 48 is damaged after 60 injection cycles since the last replacement, the predicted lifespan of the core 48 is revised from the initial value of 50 cycles to 60 cycles. Furthermore, the predicted lifespan of the core 48 is revised from the initial value of 45 cycles to 50 cycles.

[0155] Furthermore, the predicted lifespan of the injection cannula 50 is revised to increase it. For example, if the cumulative number of injection actions specified at the replacement time of the core 48 as the predicted lifespan of the injection cannula 50 is 100 times (half of the predicted lifespan of 200 times), a revision is made to increase the predicted lifespan of the injection cannula 50 to 220 times. The predicted lifespan of the injection cannula 50 is calculated as follows: 100 times (the cumulative number of injection actions) + 100 times (the number of remaining injection actions before reaching the predicted lifespan) × 1.2 times = 220 times. Alternatively, for example, the predicted lifespan of the injection cannula 50 may be revised to 200 times.

[0156] Then, continue the molding process. For example, reset the cumulative number of injection actions for injection cannula 50 to zero.

[0157] For example, there may be a causal relationship between the replacement period of the first part of the die-casting machine 100 and the lifespan of the second part. For instance, consider the case where the first part is the ejector core 48 that moves within the injection sleeve 50, and the second part is the injection sleeve 50 itself. If the elapsed time since the replacement of the ejector core 48 is short, the lifespan of the injection sleeve 50 tends to be extended. In other words, after replacing the ejector core 48, the lifespan of the injection sleeve 50 tends to be extended.

[0158] Therefore, by correcting the predicted lifespan of the injection sleeve 50 to a larger value according to the specified benchmark when the top core 48 is replaced, the lifespan of the injection sleeve 50 can be predicted with higher accuracy.

[0159] The molding machine and its operating method in the fourth embodiment correct the lifespan prediction value of the second part when the first part is replaced. Therefore, compared with the first embodiment, the lifespan of the parts of the die-casting machine 100 can be predicted with higher accuracy.

[0160] According to the molding machine and its operating method in the fourth embodiment, by correcting the lifespan prediction value when the first part is replaced, the lifespan of the first part can be predicted with higher accuracy. Furthermore, by correcting the lifespan prediction value of the second part when the first part is replaced, the lifespan of the second part can be predicted with higher accuracy.

[0161] (Fifth Embodiment)

[0162] The molding machine of the fifth embodiment differs from the molding machine of the first embodiment in that it also includes an environmental information storage unit that stores environmental history information about the environment in which the mold clamping device and the injection device are placed, and a correction unit that corrects the lifespan prediction value of the first part based on the environmental history information when the first part is replaced. Furthermore, the operating method of the molding machine of the fifth embodiment differs from the operating method of the molding machine of the first embodiment in that it corrects the lifespan prediction value of the first part based on the environmental history information when the first part is replaced. Hereinafter, some descriptions that are repetitive with those of the molding machine and its operating method in the first embodiment will be omitted.

[0163] Figure 7 This is a schematic diagram showing the molding machine according to the fifth embodiment. Figure 7 This is a plan view of the molding machine according to the fifth embodiment. The molding machine in the fifth embodiment is a die-casting machine 200.

[0164] like Figure 1 As shown, the die-casting machine 100 includes a mold clamping device 10, an ejection device 12, an injection device 14, a mold 16, a control device 18, a display device 20, an operating device 24, a spraying device 26, a melt supply device 28, and a part life prediction device 30. The part life prediction device 30 includes a correction unit 30a, an operation history information storage unit 30b, a replacement history information storage unit 30c, a life prediction value storage unit 30d, and an environmental information storage unit 30e.

[0165] The environmental information storage unit 30e of the part life prediction device 30 stores environmental history information of the environment in which the mold closing device 10 and the injection device 14 are placed. The environmental history information includes, for example, temperature and humidity associated with date and time.

[0166] By linking temperature with date and time, it is possible to determine, for example, the cumulative number of days exceeding a specific temperature within a given period. Similarly, by linking humidity with date and time, it is possible to determine, for example, the cumulative number of days exceeding a specific humidity level within a given period.

[0167] The environmental information storage unit 30e is a storage device. The environmental information storage unit 30e may be, for example, a semiconductor memory or a hard disk.

[0168] Figure 8 This is an operation block diagram of the molding machine operation method according to the fifth embodiment. The molding machine operation method of the fifth embodiment, for example, uses... Figure 1 and Figure 2 The die-casting machine 100 shown is used for this process.

[0169] The following explanation will take the case where the first part is the sliding plate 42 of the die-casting machine 100 as an example. Furthermore, the explanation will also take the case where the predicted lifespan of the sliding plate 42 is determined by the cumulative number of mold closing operations as an example.

[0170] First, input the initial values ​​for the life prediction and life forecast of the slide plate 42. The initial life forecast value is, for example, 1000 cumulative mold closing operations. Furthermore, the initial life prediction value is, for example, 990 cumulative mold closing operations. The life prediction value is based on the life forecast value.

[0171] Then, continue the molding process. Count the number of mold closing actions and calculate the cumulative number of mold closing actions.

[0172] Furthermore, after a molding operation is completed, the cumulative number of mold closing operations is compared with the life prediction value and the life forecast value.

[0173] For example, an alarm is issued when the cumulative number of mold closing operations reaches 990 times, the life prediction value. The alarm is displayed, for example, on the display device 20. For example, at the time the alarm is issued, a new slide plate 42 is prepared for replacement.

[0174] Furthermore, for example, an alarm is issued when the cumulative number of mold closing operations reaches 1000 times, the predicted lifespan. The alarm is displayed, for example, on the display device 20. If a new slide plate 42 is not prepared for replacement at the time the alarm is issued, a new slide plate 42 is prepared.

[0175] If the sliding plate 42 needs replacement during or after the molding process, the sliding plate 42 shall be replaced. Reasons for replacement include, for example, damage, malfunction, or wear and tear of the sliding plate 42. For instance, if the sliding plate 42 is damaged during the molding process, it shall be replaced.

[0176] For example, while continuing to predict the lifespan of the sliding plate 42, the predicted lifespan value and the lifespan forecast value of the sliding plate 42 are corrected.

[0177] For example, if the slide plate 42 is damaged after 1100 cumulative mold closing operations since the last replacement, the predicted lifespan of the slide plate 42 is revised to 1100 operations. Alternatively, the predicted lifespan of the slide plate 42 is revised to 1000 operations.

[0178] Next, the percentage of days exceeding the specified temperature during the period from the previous replacement to the current replacement is calculated. This percentage is calculated, for example, by the correction unit 30a based on environmental history information stored in the environmental information storage unit 30e.

[0179] For example, if the aforementioned proportion exceeds a predetermined threshold, the predicted lifespan of the sliding plate 42 is further revised. For example, if the aforementioned proportion exceeds 50%, the predicted lifespan of the sliding plate 42 is revised to be smaller. For example, the predicted lifespan of the sliding plate 42 is revised to 0.9 times 990 times. For example, the predicted lifespan of the sliding plate 42 is revised to 0.9 times 900 times.

[0180] Then, continue the molding process. For example, reset the cumulative number of mold closing actions for the sliding plate 42 to zero.

[0181] For example, if the environment in which the die-casting machine 100 is placed exceeds the intended range, the deterioration of the parts may proceed more rapidly. For example, if the temperature or humidity in which the die-casting machine 100 is placed exceeds the intended range, the deterioration of the parts may proceed more rapidly.

[0182] The molding machine and its operating method in the fifth embodiment correct the predicted lifespan of the parts when the environment in which the die-casting machine 100 is placed exceeds a predetermined range. Therefore, the lifespan of the parts from the die-casting machine 100 can be predicted with higher accuracy compared to the first embodiment.

[0183] According to the molding machine and its operating method in the fifth embodiment, by correcting the lifespan prediction value during part replacement, the lifespan of the part can be predicted with higher accuracy. Furthermore, by correcting the lifespan prediction value when the molding machine is placed in an environment exceeding a predetermined range, the lifespan of the part can be predicted with even higher accuracy.

[0184] (Sixth Embodiment)

[0185] The molding machine of the sixth embodiment differs from the molding machine of the first embodiment in that the predicted lifespan of the first part includes different predicted values ​​based on different motion counts in the motion history information. Furthermore, the operating method of the molding machine of the sixth embodiment differs from the operating method of the molding machine of the first embodiment in that the predicted lifespan of the first part includes different predicted values ​​based on different motion counts in the motion history information. Hereinafter, some descriptions that are repeated with the molding machine and its operating method of the first embodiment will be omitted.

[0186] The molding machine in the sixth embodiment is Figure 1 and Figure 2 The die-casting machine 100 shown.

[0187] The life prediction values ​​of the parts stored in the life prediction value storage unit 30d of the part life prediction device 30 include different prediction values ​​based on different motion counts in the motion history information. For example, the life prediction values ​​of the parts stored in the life prediction value storage unit 30d include a first prediction value and a second prediction value. Furthermore, life forecast values ​​include, for example, a first forecast value and a second forecast value.

[0188] For example, when the part is a sliding plate 42, the first predicted value is determined by the cumulative number of mold closing actions, and the second predicted value is determined by the cumulative time of mold closing actions. Furthermore, for example, the first predicted value is determined by the cumulative number of mold closing actions, and the second predicted value is determined by the cumulative number of mold opening and closing actions.

[0189] Assuming the part is a sliding plate 42, for example, the initial value of the first prediction is the cumulative number of mold closing actions of 1000 times, and the initial value of the second prediction is the cumulative time of mold closing actions of 1000 hours. For example, assuming the initial value of the first prediction is the cumulative number of mold closing actions of 900 times, and the initial value of the second prediction is the cumulative time of mold closing actions of 900 hours.

[0190] In the operation method of the die-casting machine 100, for example, an alarm is issued when the cumulative number of mold closing actions reaches 900 times, which is the first warning value. In addition, for example, an alarm is issued when the cumulative time of mold closing actions reaches 900 hours, which is the second warning value.

[0191] In the operation method of the die-casting machine 100, for example, an alarm is issued when the cumulative number of mold closing actions reaches 1000 times, which is the first predicted value. In addition, for example, an alarm is issued when the cumulative time of mold closing actions reaches 1000 hours, which is the second prediction value.

[0192] When the sliding plate 42 is damaged and replaced, both the first and second predicted values ​​of the sliding plate 42 are corrected.

[0193] In the molding machine and its operation method according to the sixth embodiment, the predicted lifespan of the part includes different predicted values ​​based on different motion counts in the motion history information. Therefore, compared with the first embodiment, the lifespan of the parts of the die-casting machine 100 can be predicted with higher accuracy.

[0194] According to the molding machine and its operation method in the sixth embodiment, by correcting the lifespan prediction value during part replacement, the lifespan of the part can be predicted with higher accuracy. Furthermore, by including different prediction values ​​based on different motion counts in the motion history information in the part's lifespan prediction value, the lifespan of the part can be predicted with even higher accuracy.

[0195] (Seventh Embodiment)

[0196] The operating method of the molding machine in the seventh embodiment differs from the operating method of the molding machine in the first embodiment in that it does not correct the predicted lifespan of the first part when the replacement cause of the first part is an accident. Hereinafter, some descriptions that are repetitive with the operating method of the molding machine in the first embodiment will be omitted.

[0197] The molding machine in the seventh embodiment is Figure 1 and Figure 2 The die-casting machine 100 shown.

[0198] For example, if the part is a sliding plate 42, the sliding plate 42 will be replaced if a replacement event occurs. In this case, for example, if the replacement event is accidental, the life prediction of the sliding plate 42 will not be corrected.

[0199] Whether the replacement event is an accident can be determined, for example, by analyzing the measurement values ​​of various sensors installed on the die-casting machine 100 within the control device 18. A replacement event that is accidental can be, for example, a situation where the replacement event occurs due to a natural disaster. A replacement event that is accidental can be, for example, a situation where the replacement event occurs in a chain reaction due to the failure of a part different from the first part.

[0200] In the operating method of the molding machine according to the seventh embodiment, the predicted lifespan of the parts is not affected by accidental replacement of the parts. Therefore, compared with the first embodiment, the lifespan of the parts of the die-casting machine 100 can be predicted with higher accuracy.

[0201] According to the operating method of the molding machine in the seventh embodiment, by correcting the life prediction value when the part is replaced, the life of the part can be predicted with high accuracy.

[0202] (Eighth Embodiment)

[0203] The operating method of the molding machine in the eighth embodiment differs from that of the molding machine in the first embodiment in that the first part is replaced when it reaches the life prediction or life forecast value. Hereinafter, some descriptions that are repetitive with the operating method of the molding machine in the first embodiment will be omitted.

[0204] The molding machine in the eighth embodiment is Figure 1 and Figure 2 The die-casting machine 100 shown.

[0205] For example, if the part is a slide plate 42, the slide plate 42 will be replaced when an alarm is triggered, for instance, when the cumulative number of mold closing operations reaches the life prediction or life forecast value. In other words, the slide plate 42 will be replaced before any replacement event occurs, such as damage, malfunction, or wear. In this case, the life prediction or life forecast value of the slide plate 42 will not be corrected.

[0206] In the operating method of the molding machine according to the eighth embodiment, the sliding plate 42 is replaced before it becomes damaged, malfunctions, or is worn out. Therefore, the die-casting machine 100 can be operated more safely.

[0207] In addition, if the sliding plate 42 is damaged, malfunctions, or is worn out before the cumulative number of mold closing operations reaches the life prediction value or life forecast value, the sliding plate 42 is replaced in the same manner as in the first embodiment, and the life prediction value and life forecast value of the sliding plate 42 are corrected.

[0208] According to the operating method of the molding machine in the eighth embodiment, by correcting the life prediction value when replacing parts, the life of parts can be predicted with high accuracy. Furthermore, by using parts that do not exceed the life prediction or life forecast value, the molding machine can be operated more safely.

[0209] The embodiments of the present invention have been described above with reference to specific examples. However, the present invention is not limited to these specific examples. In the embodiments, in molding machines and the like, parts that are not directly needed in the description of the present invention have been omitted, but elements related to molding machines and the like can be appropriately selected and used.

[0210] For example, in this embodiment, a die-casting machine is used as an example of a molding machine, but the molding machine is not limited to a die-casting machine. For example, the molding machine can also be an injection molding machine.

[0211] In addition, all molding machines incorporating the elements of this invention and capable of being appropriately designed and modified by those skilled in the art are included within the scope of this invention. The scope of this invention is defined by the scope of the technical solutions and their equivalents.

[0212] Label Explanation

[0213] 10 Mold Closing Device

[0214] 12 Ejector Device

[0215] 14 Injection Device

[0216] 16 molds

[0217] 16a Fixed Mold

[0218] 16b movable mold

[0219] 18 control devices

[0220] 20 display devices

[0221] 24 Operating devices

[0222] 26 spray devices

[0223] 28 Molten Supply Device

[0224] 30-part life prediction device

[0225] 30a Correction Section

[0226] 30b Action History Information Storage Department

[0227] 30c Replacement of Resume Information Storage Department

[0228] 30-day lifespan prediction storage department

[0229] 32 bases

[0230] 34 Fixed Templates

[0231] 36 Movable Templates

[0232] 38-link housing

[0233] 40 tie rod

[0234] 42 Sliding plate (part 1)

[0235] 44 mold cylinder

[0236] 46 injection cylinder

[0237] 48-pin core (part 1)

[0238] 50 Injection Cannula (Part 2)

[0239] 100 die-casting machine (forming machine)

[0240] 200 die-casting machine (forming machine)

Claims

1. A molding machine, characterized in that, have: Mold closing device; Injection device; The control device controls the molding operation using the above-mentioned mold clamping device and injection device; The part life prediction device includes an action history information storage unit that stores action history information of the molding action, a replacement history information storage unit that stores replacement history information of the first part, a life prediction value storage unit that stores the life prediction value of the first part, and a correction unit. When the first part is replaced, the correction unit corrects the life prediction value of the first part based on the action history information and the replacement history information of the first part. as well as The display device is capable of displaying the aforementioned action history information, replacement history information, and lifespan prediction value. The first component mentioned above includes a sliding plate. The aforementioned action history information includes the cumulative number of mold-closing actions linked to dates and times. The replacement history information mentioned above includes the date and time of replacement of the aforementioned sliding plate. When the first part is the sliding plate, during the replacement of the sliding plate, the correction unit adjusts the predicted lifespan of the sliding plate based on the cumulative number of mold closing operations from the previous replacement to the current replacement. The replacement history information storage unit stores replacement history information for a second part that has a causal relationship with the lifespan and replacement period of the first part. The aforementioned lifespan prediction storage unit stores the lifespan prediction value of the second component. When the first part is replaced, the aforementioned correction unit adjusts the predicted lifespan of the first part based on the replacement history information of the second part. The first part mentioned above includes the top core of the injection device, and the second part mentioned above includes the injection sleeve of the injection device.

2. The molding machine as described in claim 1, characterized in that, After the aforementioned correction unit corrects the life prediction value of the first part when the first part is replaced, it further corrects the life prediction value of the first part based on the aforementioned operation history information during the period until the next replacement of the first part.

3. The molding machine as described in claim 1, characterized in that, The aforementioned correction unit corrects the life prediction value of the first part based on information from previous replacements in the replacement history information of the first part.

4. The molding machine as described in claim 1, characterized in that, The aforementioned correction unit corrects the predicted lifespan of the injection sleeve when the aforementioned top core is replaced.

5. The molding machine according to any one of claims 1 to 4, characterized in that, It also has an environmental information storage unit that stores environmental history information of the environment in which the above-mentioned mold closing device and the above-mentioned injection device are placed; When the first part is replaced, the aforementioned correction unit corrects the predicted lifespan of the first part based on the aforementioned environmental history information.

6. The molding machine according to any one of claims 1 to 4, characterized in that, Based on the above-mentioned action history information and the life prediction value of the first part, an alarm is displayed on the above-mentioned display device.

7. The molding machine according to any one of claims 1 to 4, characterized in that, The life prediction value of the first part mentioned above includes different prediction values ​​based on different motion counts in the above motion history information.

8. A method for operating a molding machine, the molding machine comprising: Mold closing device; Injection device; and The control device controls the molding operation using the above-mentioned mold clamping device and injection device; The characteristic of the operating method of this molding machine is that... When the first part of the molding machine is replaced, the life prediction value of the first part is corrected based on the operation history of the molding machine and the replacement history of the first part. The first component mentioned above includes a sliding plate. The aforementioned action history information includes the cumulative number of mold-closing actions linked to dates and times. The replacement history information mentioned above includes the date and time of replacement of the aforementioned sliding plate. When the first part is the sliding plate, during the replacement of the sliding plate, the predicted lifespan of the sliding plate is adjusted based on the cumulative number of mold closing actions from the previous replacement to the current replacement. When the first part is replaced, the lifespan prediction of the first part is adjusted based on the replacement history information of the second part, which has a causal relationship between the lifespan of the first part and the replacement period. The first part mentioned above includes the top core of the injection device, and the second part mentioned above includes the injection sleeve of the injection device.

9. The method of operating the molding machine as described in claim 8, characterized in that, After the life prediction value of the first part is corrected when the first part is replaced, the life prediction value of the first part will be further corrected based on the operation history information of the molding machine until the next replacement of the first part.

10. The method of operating the molding machine as described in claim 8, characterized in that, Based on information from previous replacements of the first component, the predicted lifespan of the first component is revised.

11. The method of operating the molding machine as described in claim 8, characterized in that, When replacing the aforementioned top core, the predicted lifespan of the aforementioned injection sleeve is corrected.

12. The method of operating the molding machine as described in any one of claims 8 to 11, characterized in that, When the first part is replaced, the life prediction value of the first part is revised based on the environmental history of the environment in which the mold clamping device and the injection device are placed.

Images