Injection molding machine production data acquisition monitoring system and production data processing method

Abstract

The technical problem to be solved by the invention is to overcome the defects in the prior art and provide the injection molding machine group networking management and production data processing method, so that the operation condition and parameter setting of the injection molding machine group can be efficiently and conveniently inquired in real time; according to the injection molding machine production data acquisition monitoring system and the production data processing method thereof, the operation problem of the injection molding machine and the operation parameter setting problem are found in time through production parameter big data algorithm processing, the labor and time cost is reduced, the product batch quality problem is avoided, and the enterprise production efficiency and the management efficiency are improved.

Description

Technical Field

[0001] The invention relates to the technical field of monitoring of injection molding machines, and in particular to a production data acquisition monitoring system for injection molding machines and a production data processing method thereof. Background Art

[0002] Injection molding machine is the main molding equipment that uses plastic molding molds to make plastic products of various shapes from thermoplastics or thermosetting plastics.

[0003] At present, most injection molding machines are independent CNC equipment. Single injection molding machines can gradually realize automated production. For large-scale industrialized production enterprises, they form a group of injection molding machines for centralized control. However, in the injection molding production process, the quality control of injection molding products and the real-time operation status of injection molding machines are controlled. Professional personnel are arranged to patrol to reduce product quality and the risk of equipment failure or misoperation. This consumes a lot of manpower and time costs. At the same time, its production management efficiency is low. It is easy to have problems such as batch scrapping or quality defects of injection molding products due to equipment failure, operator misoperation or inconsistent operator operation parameter settings. The failure to respond quickly to repair and correct can cause great economic losses to the enterprise and seriously reduce the production efficiency and management efficiency of the enterprise. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide an injection molding machine group networking management and production data processing method, which can query the operation status and parameter settings of the injection molding machine group in real time, efficiently and conveniently, and timely discover the operation problems of the injection molding machine and the operation parameter setting problems through the algorithm processing of the production parameter big data, thereby reducing labor and time costs, avoiding product batch quality problems, and improving the production efficiency and management efficiency of the enterprise. Invention content: The technical solution adopted by the present invention to solve the technical problem is: an injection molding machine production data collection and monitoring system and a production data processing method of the present invention, including an injection molding machine, a data collector, an edge computing gateway, a cloud server, and an interactive terminal;

[0005] Injection molding machines generate a large amount of production data when performing injection molding operations;

[0006] A data collector, the injection molding machine is connected to the cloud server through the data collector, and the interactive terminal is connected to the cloud server through the data collector;

[0007] Edge computing gateway, the data collector collects production data generated when the injection molding machine is in operation and processes the data through the edge computing gateway;

[0008] A cloud server, through which the production data processed by the edge computing gateway is read, collected and stored in real time;

[0009] The interactive terminal is used to send a query request to the cloud server and browse the production data of the injection molding machine obtained through the cloud server and processed by the edge computing gateway, so as to timely monitor the quality of the injection molded products produced by the injection molding machine and the operating status of the injection molding machine.

[0010] The production data includes the real-time parameters, process parameters, molding parameters and quality parameters of the injection molding machine. The real-time parameters include the temperature parameters, pressure parameters, position parameters, modulus and cycle time of each section of the injection molding machine during operation;

[0011] The process parameters include mold opening and closing parameters, ejection parameters, ejection parameters, injection parameters, pressure holding parameters, and material storage parameters when the injection molding machine is operating;

[0012] The molding parameters include the switch mold timing parameters, ejection time parameters, ejection position parameters, pressure holding conversion pressure parameters, and material storage timing parameters when the injection molding machine is operating;

[0013] The quality parameters include the ejection parameters, cycle parameters, and injection endpoint parameters of the injection molding machine;

[0014] The production data processing method of the injection molding machine production data acquisition and monitoring system is characterized by comprising the following steps:

[0015] S1, the collected temperature parameters, pressure parameters, position parameters, mold number, cycle time, mold opening and closing parameters, ejection parameters, ejection parameters, injection parameters, holding pressure parameters, material storage parameters, mold opening and closing timing parameters, ejection time parameters, ejection position parameters, holding pressure conversion pressure parameters, material storage timing parameters, mold closing parameters, ejection parameters, cycle parameters, injection endpoint parameters, respectively, with 50 molds as samples;

[0016] S2. Calculate its standard deviation, and use plus or minus three times the standard deviation as the upper and lower control lines, with the middle line as the sample average, to divide the area into plus or minus one times the standard deviation, plus or minus two times the standard deviation, and plus or minus three times the standard deviation;

[0017] S3. The following eight situations require early warning:

[0018] 1. One point falls outside the range of plus or minus three times the standard deviation

[0019] 2. 9 consecutive points fall on the same side of the center line

[0020] 3. 6 consecutive points increase or decrease

[0021] 4. The adjacent points in 14 consecutive points alternate up and down

[0022] 5. 2 out of 3 consecutive points fall outside the area of ​​plus or minus two standard deviations on the same side of the center line 6. 4 out of 5 consecutive points fall outside the area of ​​plus or minus one standard deviation on the same side of the center line 7. 15 consecutive points fall within the area of ​​plus or minus one standard deviation on both sides of the center line

[0023] 8. 8 consecutive points fall on both sides of the center line and none of them is within the range of plus or minus one standard deviation; BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a structural schematic diagram of the injection molding machine production data acquisition and monitoring system of the present invention.

[0025] Figure 2 It is a parameter control standard diagram of the production data processing method of the injection molding machine production data acquisition monitoring system of the present invention. X represents the sample average value, UCL represents, LCL represents; A represents the positive and negative three times standard deviation area, B represents the positive and negative two times standard deviation area, and C represents the positive and negative one times standard deviation area; DETAILED DESCRIPTION

[0026] In this embodiment, an injection molding machine production data acquisition and monitoring system of the present invention includes an injection molding machine 1, a data collector 2, an edge computing gateway 3, a cloud server 4, an interactive terminal 5, and production data 6;

[0027] The injection molding machine 1 generates a large amount of production data 6 when performing the injection molding operation;

[0028] Data collector 2, the injection molding machine is connected to the cloud server through the data collector, and the interactive terminal is connected to the cloud server through the data collector;

[0029] Edge computing gateway 3, the data collector collects the production data generated when the injection molding machine is in operation and processes the data through the edge computing gateway;

[0030] Cloud server 4, through which the production data processed by the edge computing gateway is read, collected and saved in real time;

[0031] The interactive terminal 5 is used to send a query request to the cloud server and browse the production data of the injection molding machine obtained through the cloud server and processed by the edge computing gateway, so as to timely monitor the quality of the injection molded products produced by the injection molding machine and the operating status of the injection molding machine.

[0032] The production data 6 include real-time parameters 7 , process parameters 8 , molding parameters 9 and quality parameters 10 when the injection molding machine 1 is in operation.

[0033] The real-time parameters 7 include temperature parameters 701, pressure parameters 702, position parameters 703, modulus 704, and cycle time 705 of each section when the injection molding machine 1 is operating;

[0034] The process parameters 8 include mold opening and closing parameters 801, ejection parameters 802, ejection parameters 803, injection parameters 804, pressure holding parameters 805, and material storage parameters 806 when the injection molding machine 1 is operating;

[0035] The molding parameters 9 include a switch mold timing parameter 901, a shot-out time parameter 902, a shot-out position parameter 903, a holding pressure conversion pressure parameter 904, and a material storage timing parameter 905 when the injection molding machine 1 is operating;

[0036] The quality parameter 10 includes a mold ejection parameter 1001, a cycle parameter 1002, and an injection endpoint parameter 1003 when the injection molding machine 1 is operating;

[0037] The production data processing method of the injection molding machine production data acquisition and monitoring system is characterized by comprising the following steps:

[0038] S1, the collected temperature parameters 701, pressure parameters 702, position parameters 703, modulus 704, cycle time 705, mold opening and closing parameters 801, ejection parameters 802, ejection parameters 803, injection parameters 804, holding pressure parameters 805, material storage parameters 806, mold opening and closing timing parameters 901, ejection time parameters 902, ejection position parameters 903, holding pressure conversion pressure parameters 904, material storage timing parameters 905, ejection parameters 1001, cycle parameters 1002, injection endpoint parameters 1003, respectively, take 50 molds as samples;

[0039] S2. Calculate its standard deviation, and use plus or minus three times the standard deviation as the upper and lower control lines, with the middle line as the sample average, to divide the area into plus or minus one times the standard deviation, plus or minus two times the standard deviation, and plus or minus three times the standard deviation;

[0040] S3. The following eight situations require early warning:

[0041] 1. One point falls outside the range of plus or minus three times the standard deviation

[0042] 2. 9 consecutive points fall on the same side of the center line

[0043] 3. 6 consecutive points increase or decrease

[0044] 4. The adjacent points in 14 consecutive points alternate up and down

[0045] 5. 2 out of 3 consecutive points fall outside the area of ​​plus or minus two standard deviations on the same side of the center line 6. 4 out of 5 consecutive points fall outside the area of ​​plus or minus one standard deviation on the same side of the center line

[0046] 7. 15 consecutive points fall within the range of plus or minus one standard deviation on both sides of the center line

[0047] 8. Eight consecutive points fall on both sides of the center line and none of them is within the area of ​​plus or minus one standard deviation.

Claims

1. A production data acquisition and monitoring system for an injection molding machine and a production data processing method, characterized in that: It includes an injection molding machine (1), a data collector (2), an edge computing gateway (3), a cloud server (4), an interactive terminal (5), and production data (6); The injection molding machine (1) generates a large amount of production data (6) when performing an injection molding operation; The data collector (2), the injection molding machine (1) is communicatively connected to the cloud server (4) via the data collector (2), and the interactive terminal (5) is communicatively connected to the cloud server (4); The edge computing gateway (3), the data collector (2) collects production data (6) generated when the injection molding machine (1) is in operation and processes the data through the edge computing gateway (3); The cloud server (4) reads, collects and stores data processed by the edge computing gateway (3) in real time through the cloud server (4); The interactive terminal (5) is used to send a query request to the cloud server (4) and browse the data obtained by the cloud server (4) and processed by the edge computing gateway (3), so as to timely monitor the quality of the injection molded products produced by the injection molding machine (1) and the operating status of the injection molding machine (1).

2. The injection molding machine production data acquisition and monitoring system according to claim 1, characterized in that: The production data (6) include real-time parameters (7), process parameters (8), molding parameters (9) and quality parameters (10) when the injection molding machine (1) is in operation.

3. The injection molding machine production data acquisition and monitoring system according to claim 2, characterized in that: The real-time parameters (7) include temperature parameters (701), pressure parameters (702), position parameters (703), modulus (704), and cycle time (705) of each section when the injection molding machine (1) is operating.

4. The injection molding machine production data acquisition and monitoring system according to claim 2, characterized in that: The process parameters (8) include mold opening and closing parameters (801), ejection parameters (802), ejection parameters (803), injection parameters (804), pressure holding parameters (805), and material storage parameters (806) when the injection molding machine (1) is in operation.

5. The injection molding machine production data acquisition and monitoring system according to claim 2, characterized in that: The molding parameters (9) include mold opening and closing timing parameters (901), ejection time parameters (902), ejection position parameters (903), holding pressure conversion pressure parameters (904), and material storage timing parameters (905) when the injection molding machine (1) is in operation.

6. The injection molding machine production data acquisition and monitoring system according to claim 2, characterized in that: The quality parameters (10) include ejection parameters (1001), cycle parameters (1002), and injection endpoint parameters (1003) when the injection molding machine (1) is in operation.

7. A production data processing method for an injection molding machine production data acquisition and monitoring system according to any one of claims 1 to 6, characterized in that: The steps include: S1, the temperature parameters (701), pressure parameters (702), position parameters (703), mold number (704), cycle time (705), mold opening and closing parameters (801), ejection parameters (802), ejection parameters (803), injection parameters (804), holding pressure parameters (805), material storage parameters (806), mold opening and closing timing parameters (901), ejection time parameters (902), ejection position parameters (903), holding pressure conversion pressure parameters (904), material storage timing parameters (905), ejection parameters (1001), cycle parameters (1002), injection endpoint parameters (1003), with 50 molds as samples respectively; S2. Calculate its standard deviation, and use plus or minus three times the standard deviation as the upper and lower control lines, with the middle line as the sample average, to divide the area into plus or minus one times the standard deviation, plus or minus two times the standard deviation, and plus or minus three times the standard deviation; S3. The following eight situations require early warning:

1. One point falls outside the range of plus or minus three times the standard deviation 2. 9 consecutive points fall on the same side of the center line 3. 6 consecutive points increase or decrease 4. The adjacent points in 14 consecutive points alternate up and down 5. 2 out of 3 consecutive points fall outside the area of ​​positive or negative twice the standard deviation on the same side of the center line.

6. 4 out of 5 consecutive points fall outside the area of ​​positive or negative one times the standard deviation on the same side of the center line.

7. 15 consecutive points fall within the area of ​​positive or negative one times the standard deviation on both sides of the center line.

8. 8 consecutive points fall on both sides of the center line and none of them are within the area of ​​positive or negative one times the standard deviation.

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