Injection molding production monitoring method and system based on mold action induction and storage medium

Abstract

The invention discloses an injection molding production monitoring method and system based on mold action induction and a storage medium. The injection molding production monitoring method comprises the steps that S1, the opening and closing state of a mold is obtained through a differential induction circuit; s2, according to the opening and closing state of the mold, the average production period is calculated; and S3, product quality monitoring, production yield monitoring and mold service life and health state monitoring are carried out according to the average production cycle. By the adoption of the technical scheme, the injection molding production efficiency and quality control are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of injection molding, and in particular relates to an injection molding production monitoring method and system, and a storage medium based on mold motion sensing. Background Art

[0002] The automatic monitoring of the injection molding production process in each injection molding factory is mainly divided into two methods: monitoring based on injection molding machine data and monitoring based on mold action. Among them, the monitoring method based on injection molding machine data has obvious advantages in the number and accuracy of monitoring functions because it can usually obtain relatively rich signals and data. However, due to the wide variety of brands and models of injection molding machines, the signal types, communication interfaces, and data formats of each injection molding machine system are different, resulting in a large workload for the implementation of the monitoring system. In addition, the monitoring system based on injection molding machine data has no direct correlation with the mold itself. When counting the production output of the mold and conducting mold health management, it is necessary to first match and associate it with the mold through the production scheduling and reporting system. The functional requirements of the injection molding MES management system are relatively complete, and the cost is high, so it is less applicable to small and medium-sized enterprises.

[0003] At present, the injection molding production monitoring method based on mold action is mainly used for production output statistics, and mold maintenance planning is carried out based on the output data. At present, the monitoring equipment used in this monitoring method is mainly divided into two categories: mechanical counters and magnetic induction counters. Mechanical counters are used to record the number of times the mold is opened and closed, which is used as the basis for production statistics and mold maintenance and scrapping. Mechanical counters are usually installed on the fixed mold. When the mold is closed, the movable mold pushes the ejector of the counter to drive the cam to rotate and count. The main disadvantages of mechanical counters include: single function, only used for counting, unable to calculate the production cycle and quality monitoring based on this; no communication function, large manual copying workload, data lag; large mechanical wear and short counter life. Magnetic induction counters can realize functions such as statistical output, calculation of production cycle, data communication, etc. The main body of the magnetic induction counter is installed on the fixed mold of the mold, and a magnet needs to be installed on the movable mold. The installation workload is large and the cost is high. There are also risks such as magnet damage due to vibration, magnet demagnetization due to high temperature, strong magnetic interference, and natural demagnetization. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an injection molding production monitoring method and system, and a storage medium based on mold motion sensing, so as to realize injection molding production output statistics, product quality monitoring, mold health status and mold life management, and improve the efficiency and quality control of injection molding production.

[0005] To achieve the above object, the present invention adopts the following technical solution: An injection molding production monitoring method based on mold motion sensing, comprising: Step S1, obtaining the opening and closing state of the mold through a differential sensing circuit; wherein the differential sensing circuit comprises: a sensing module and a reference module, both of which comprise an inductor, a resonant circuit and a frequency-voltage conversion circuit, and the output signals of the sensing module and the reference module are processed by a differential amplifier; Step S2, calculating the average production cycle according to the opening and closing state of the mold; Step S3: Perform product quality monitoring, production output monitoring, and mold life and health status monitoring based on the average production cycle.

[0006] Preferably, step S2 comprises: According to the mold opening and closing state, the mold opening and closing action time is obtained, and the duration data of each molding cycle is calculated; The bubble sort algorithm is used to process the molding cycle time data to eliminate outliers and calculate the average production cycle.

[0007] The present invention also provides an injection molding production monitoring system based on mold motion sensing, comprising: A first processing module is used to obtain the opening and closing state of the mold through a differential sensing circuit; wherein the differential sensing circuit includes: a sensing module and a reference module, the sensing module and the reference module both include an inductor, a resonant circuit and a frequency-voltage conversion circuit, and the output signals of the sensing module and the reference module are processed by a differential amplifier; The second processing module is used to calculate the average production cycle according to the opening and closing state of the mold; The third processing module is used to monitor product quality, production output, mold life and health status based on the average production cycle.

[0008] Preferably, the second processing module comprises: The first processing unit is used to obtain the opening and closing action time of the mold according to the opening and closing state of the mold, and calculate the duration data of each molding cycle; The second processing unit is used to process the molding cycle duration data using a bubble sort algorithm to eliminate abnormal values ​​and calculate the average production cycle.

[0009] The present invention also provides a storage medium, on which a computer program is stored, and when the computer program is running, the injection molding production monitoring method based on mold motion sensing is executed.

[0010] The present invention uses inductive metal sensing technology to monitor the opening and closing status of the mold in real time. The differential circuit design can improve the anti-interference ability of the circuit and can accurately record the production action time data; the bubble sort algorithm is used to process the data to exclude abnormal values ​​and calculate the average production cycle; the standard deviation is calculated to compare the numerical deviation, exclude abnormal production actions, and calculate the effective production output. Furthermore, based on the real-time monitoring of the production cycle, the monitoring and early warning of product quality can be realized; based on the statistics of the number of mold opening and closing times and the tracking of the standard deviation of the production cycle, the evaluation of the health status and service life of the mold can be realized. All collected and calculated data, as well as real-time monitoring and early warning information, are sent to the industrial Internet platform through 5G communication technology, which is convenient for the expansion and optimization of system functions and further improves the level of intelligent production management.

[0011] The present invention is based on the principle of inductive non-contact electromagnetic induction, and does not have the possible failure problems of reed switches, mechanical switches, contact switches, etc.; it does not require the use of magnets, has a smaller installation workload and lower costs, is not affected by a constant magnetic field, has stronger anti-interference capabilities, and can work reliably in dusty, humid, oily, and other environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0013] Figure 1 This is a flow chart of an injection molding production monitoring method based on mold motion sensing according to an embodiment of the present invention; Figure 2 This is the principle block diagram of the differential inductive metal sensing circuit; Figure 3 It is a schematic diagram of the signal output curve of the sensing circuit during the mold action process; Figure 4 This is a schematic diagram of the inductor coil arrangement; Figure 5 Schematic diagram of inductor coil stacking. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0016] Embodiment 1: like Figure 1 As shown, an embodiment of the present invention provides an injection molding production monitoring method based on mold motion sensing, comprising: Step S1, obtaining the opening and closing state of the mold through a differential sensing circuit; Step S2, calculating the average production cycle according to the opening and closing state of the mold; Step S3: Perform product quality monitoring, production output monitoring, and mold life and health status monitoring based on the average production cycle.

[0017] As an implementation of an embodiment of the present invention, in step S1, based on the metal properties of the mold, the present invention uses inductive metal sensing technology to monitor the opening and closing state of the mold in real time. This method only requires the installation of a sensing device on the fixed mold of the mold, and no device is required to be installed on the movable mold. The sensing device can accurately capture the opening and closing actions of the mold and convert these actions into electrical signals for recording and analysis.

[0018] The inductive device of the present invention contains a resonant circuit. When metal is close to the inductor of the resonant circuit, eddy currents will be generated around the inductor, causing the equivalent inductance to increase, forcing the resonant frequency to decrease. The calculation formula of the resonant frequency is as follows: Where L is the inductance and C is the capacitance. When L increases, the resonant frequency f decreases. The change in the resonant frequency directly reflects the opening and closing action of the mold.

[0019] In order to monitor the change of resonant frequency in real time, the present invention designs a frequency-voltage (F / V) conversion circuit to convert the frequency signal into an analog voltage signal that is more suitable for subsequent circuit processing. The frequency-voltage conversion circuit can linearly convert the input frequency signal into a corresponding voltage output. When the input resonant frequency increases, the voltage output by the conversion circuit will increase accordingly; when the input resonant frequency decreases, the output voltage will decrease accordingly. This linear relationship enables the change of frequency to be intuitively reflected in the form of voltage, thereby facilitating further processing of the circuit.

[0020] In order to enhance the anti-interference performance of the system, the present invention designs a differential sensing circuit. By introducing a differential structure, the circuit can effectively suppress common-mode interference and improve the stability and measurement accuracy of the system. The differential sensing circuit includes: a sensing module, a reference module, a differential amplifier and a reference bias adjustment circuit. The sensing module includes: a first sensing inductor, a first resonant circuit and a first frequency-voltage conversion circuit. The reference module includes: a second sensing inductor, a second resonant circuit and a second frequency-voltage conversion circuit. The first sensing inductor, the first resonant circuit and the first frequency-voltage conversion circuit are connected in sequence. The second sensing inductor, the second resonant circuit and the second frequency-voltage conversion circuit are connected in sequence. The first frequency-voltage conversion circuit and the second frequency-voltage conversion circuit are connected to the differential amplifier, and the reference bias adjustment circuit is connected to the output end of the second frequency-voltage conversion circuit and the input end of the differential amplifier. The output signals of the sensing module and the reference module are processed by the differential amplifier. By comparing the output signals of the two modules, the influence of interference factors such as environmental noise and temperature drift is eliminated. The principle block diagram of the differential sensing circuit is shown in FIG. Figure 2 As shown: The sensing module is as follows: The first inductive inductor L sense : Used to sense changes in the opening and closing state of the mold. Its inductance value will change with the position of the movable mold.

[0021] First resonant circuit: used to convert the change of inductance into the change of resonant frequency. The resonant frequency is inversely proportional to the inductance value.

[0022] The first frequency-voltage conversion circuit converts the resonant frequency signal into an analog voltage signal and outputs a voltage value proportional to the frequency.

[0023] The reference modules are as follows: The second reference inductor L ref :The inductor in the reference module has the same structure as the inductor in the sensing module, but in terms of installation position, the reference inductor L ref Specific inductance L sense Located further away from the moving mold sensing surface, such as Figure 3 As shown, the difference in the decreasing rate of the inductance values ​​of the two during the same period of mold closing is realized.

[0024] The second resonant circuit is consistent with the resonant circuit in the sensing module and is used to generate a reference frequency signal.

[0025] The second frequency-voltage conversion circuit converts the reference frequency signal into an analog voltage signal and outputs a reference voltage value.

[0026] The reference bias adjustment circuit is as follows: It is used to adjust the static output voltage value of the reference module to ensure that when the mold is in the open state, the output voltage of the reference module is slightly lower than the output voltage of the sensing module, ensuring that the differential circuit will not be at the output switching point to prevent frequent output switching.

[0027] The reference bias makes the reference inductance curve shift downward, and combined with the difference in installation position, the reference inductance curve shifts to the right at the same time, so that the reference curve and the induction curve meet at a certain point, which is the action switching point. Figure 3 shown.

[0028] Adjusting the offset can adjust the action switching point position (sensing distance).

[0029] The differential signal is processed as follows: The output signals of the sensing module and the reference module are processed by a differential amplifier to compare the voltages of the two.

[0030] Through the differential circuit, common mode interference such as environmental noise and temperature drift can be effectively eliminated, and effective signals related to opening and closing the mode can be extracted.

[0031] The inductive inductor and the reference inductor are designed as two PCB coil inductors with exactly the same structure. The inductive inductor is located on the top layer, closer to the dynamic mold, and the reference inductor is located on the bottom layer. The two are staggered. Figure 4 and Figure 5 shown.

[0032] In order to obtain a more appropriate sensing distance, the vertical distance between the sensing inductor and the reference inductor should be maximized as much as possible. It is recommended that the PCB use a thicker board layer of 2.0mm or more. The stacking diagram is shown in the figure. Figure 5 shown.

[0033] When the mold is in the open mold state, the moving mold is away from the sensing device, and the sensing inductance and the reference inductance are not affected. The two have the same inductance value and the same resonant frequency. Both F / Vs output the same voltage, but the reference module is negatively biased and the reference module output voltage is adjusted to be slightly lower than the sensing module output voltage. At this time, the differential amplifier outputs a high level.

[0034] When the moving module is close to the sensing device, both the sensing inductance and the reference inductance will be affected, but because the sensing inductance is closer to the target, its inductance value will decrease more, resulting in a lower voltage output from the sensing module's F / V.

[0035] When the movable mold continues to approach the fixed mold and reaches a certain position, the F / V output voltage of the sensing module is lower than the F / V output voltage of the reference module. At this time, the differential amplifier outputs a low level, indicating that the mold has entered the mold closing state. Figure 3 The intersection point of the voltage curves in .

[0036] As an implementation of an embodiment of the present invention, in step S2, the production cycle duration is an important indicator reflecting the stability of the injection molding process, and it is closely related to product quality. The average production cycle provides a calculation basis for quality monitoring, output statistics, and mold health management based on the production cycle.

[0037] The present invention defines the production cycle time as the time interval from the current mold closing to the current mold opening, that is, the molding time required to produce a mold product.

[0038] Based on the mold opening and closing motion sensing method, this system monitors the mold opening and closing status, records the mold opening and closing motion time in real time, and calculates the duration of each molding cycle.

[0039] The present invention continuously collects the real-time molding cycle of the mold through the induction method, and uses the latest 50 molding cycle durations as the data basis for calculating and updating the average production cycle. When a new duration data is collected, the earliest duration data in the original data sequence will be removed, and the new duration data will be moved in. The first-in-first-out data input method always keeps the 50-mold duration data as the latest data.

[0040] The bubble algorithm is a simple and intuitive sorting algorithm suitable for sorting small-scale data. By traversing the data multiple times, the larger elements are gradually "bubbled" to the end of the sequence. In the present invention, the bubble algorithm is used to sort the collected 50-mode time-length data, and the possible abnormal data is arranged at both ends of the data sequence to facilitate subsequent data processing. The specific steps are as follows: (1). Starting from the first data, compare two adjacent data in turn. If the previous data is greater than the next data, swap their positions.

[0041] (2). Repeat the above steps until all data are arranged in ascending order.

[0042] Through the bubble algorithm, the system can arrange abnormal values ​​in the duration data (such as values ​​that are too large or too small) to the two ends of the series, thus facilitating subsequent data processing.

[0043] After completing the bubble algorithm sorting, the system takes the duration data of the middle 30 modules (11th to 40th modules) and calculates their average value as the latest average production cycle. The specific calculation formula is as follows: in, is the average production cycle, is the i-th duration data after sorting.

[0044] The bubble sort and intermediate data averaging algorithms can effectively eliminate the interference of extreme values ​​on the average production cycle calculation and improve the reliability of data. At the same time, the first-in-first-out data input method can ensure that after the actual production cycle changes, the calculated average production cycle can gradually approach the actual value with the input of the latest 50-module data.

[0045] As an implementation of an embodiment of the present invention, in step S3, product quality monitoring is specifically as follows: In the injection molding production process, the production cycle length is an important indicator of production efficiency and product quality. Abnormal production cycle often means equipment failure, process parameter fluctuations or raw material problems, which ultimately leads to a decline in product quality. Therefore, real-time monitoring of the production cycle length and effective analysis of it are of great significance to improve the quality and efficiency of injection molding production.

[0046] The present invention processes real-time production cycle duration data, monitors production cycle fluctuations, promptly identifies abnormal production cycle conditions, and sends quality warnings.

[0047] The present invention is based on statistical methods and adopts the principle of standard deviation to identify abnormal data in the production cycle. The steps are as follows: (1) Based on the calculation results of the average production cycle, calculate the overall standard deviation of the intermediate 30-mode data as follows: (2) Set the identification threshold of abnormal data. When the deviation between a data point (real-time production cycle) and the mean (average production cycle) exceeds 2 times the standard deviation, it is considered abnormal data, and it is judged that there is a quality problem in the current production. The formula is as follows: As an implementation of the embodiment of the present invention, in step S3, the production output monitoring is specifically as follows: Output monitoring is an important part of production management, which is directly related to the execution of production plan and optimal allocation of resources. The present invention records the number of times the mold is opened and closed during the current production process, identifies abnormal production actions, and calculates effective production output in real time.

[0048] The production statistics method based on the number of mold opening and closing times is adopted. Each time the mold is closed and an injection molding is completed to the mold opening, the equipment will automatically record a production action, calculate the output in the current production process, and accumulate and calculate the total production output of the mold.

[0049] During the actual use of the mold, the working state of the mold includes abnormal working modes such as mold testing, machine adjustment, and mold repair in addition to the normal production mode. The number of mold opening and closing times collected under the abnormal production mode is not valid production output data, so it cannot be used as injection molding production output monitoring data. The present invention identifies abnormal data by processing real-time production cycle duration data, promptly discovers abnormal production status, and avoids the impact of invalid production action output statistics. The present invention is based on statistical methods and adopts the standard deviation principle to identify abnormal data.

[0050] Based on the calculation of standard deviation, the identification threshold of abnormal data is set. When the deviation between the data point (real-time production cycle) and the mean (average production cycle) exceeds 3 times the standard deviation, it is considered abnormal data, and the opening and closing times of the mold are not included in the actual production. The formula is as follows: As an implementation of the embodiment of the present invention, in step S3, the mold life and health status are monitored as follows: Monitoring the life and health status of molds is of great significance for reducing production costs and improving production efficiency. The present invention can evaluate the service life and health status of molds in real time by recording the number of times the molds are used and monitoring the standard deviation of the production cycle.

[0051] The number of times a mold is used is an important indicator for evaluating its life. The present invention records the number of times a mold is used in real time by monitoring the opening and closing status of the mold. Each time the mold is closed and an injection molding is completed, the number of uses is automatically accumulated. By accumulating the number of uses, the use of the mold can be monitored in real time, and the remaining life of the mold can be predicted based on the preset life threshold and combined with the mold health status data.

[0052] The standard deviation of the production cycle is a statistical indicator to measure the degree of fluctuation of the production cycle. The larger the standard deviation, the greater the fluctuation of the production cycle and the worse the health of the mold may be. Based on the standard deviation calculation method, by monitoring and analyzing the changing trend of the standard deviation of the production cycle, potential health problems of the mold can be discovered in time, maintenance reminders can be issued, and abnormal status and occurrence time of the mold can be recorded to provide data support for subsequent maintenance and replacement.

[0053] The present invention defines the mold health coefficient h as: in is the average production cycle, is the standard deviation. When it is 0, it means that the production cycle of each mold is the same, which is an ideal state. At this time, h=100% means that the mold is in the best health state.

[0054] The remaining life of the mold under ideal conditions is equal to the total life of the mold (maximum allowable number of uses) minus the consumed life (number of uses). However, during the use of the mold, the health status of the mold cannot reach the ideal value due to improper use of the mold, untimely maintenance, etc. Therefore, in the actual production process, the remaining life of the mold needs to be multiplied by the ideal remaining value and the health status coefficient. The specific life prediction formula is as follows: in, is the remaining life of the mold, is the total mold life, is the number of times the mold has been used, and h is the mold health coefficient. When the mold is poorly maintained or the mold is running with a problem, the mold health coefficient h will be less than 1, and the remaining life of the mold will be less than the ideal remaining number of uses of the mold.

[0055] The embodiment of the present invention adopts differential inductive mold motion sensing to monitor the opening and closing action of the mold in real time, calculate the mold production cycle, and use the bubble sort algorithm and standard deviation statistical algorithm to process the production cycle time data, which can effectively identify product quality problems, accurately calculate production output, and accurately predict the health status and service life of the mold. This method has the characteristics of low cost, high reliability, simple installation and implementation, and wide applicability. It is an efficient injection molding production process monitoring method with broad application prospects.

[0056] Embodiment 2: The embodiment of the present invention further provides an injection molding production monitoring system based on mold motion sensing, comprising: A first processing module is used to obtain the opening and closing state of the mold through a differential sensing circuit; wherein the differential sensing circuit includes: a sensing module and a reference module, the sensing module and the reference module both include an inductor, a resonant circuit and a frequency-voltage conversion circuit, and the output signals of the sensing module and the reference module are processed by a differential amplifier; The second processing module is used to calculate the average production cycle according to the opening and closing state of the mold; The third processing module is used to monitor product quality, production output, mold life and health status based on the average production cycle.

[0057] As an implementation of the embodiment of the present invention, the second processing module includes: The first processing unit is used to obtain the opening and closing action time of the mold according to the opening and closing state of the mold, and calculate the duration data of each molding cycle; The second processing unit is used to process the molding cycle duration data using a bubble sort algorithm to eliminate abnormal values ​​and calculate the average production cycle.

[0058] Embodiment 3: An embodiment of the present invention further provides a storage medium, on which a computer program is stored, and when the computer program is run, an injection molding production monitoring method based on mold motion sensing is executed.

[0059] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for monitoring injection molding production based on mold motion sensing, characterized in that: include: Step S1, obtaining the opening and closing state of the mold through a differential sensing circuit; wherein the differential sensing circuit comprises: a sensing module and a reference module, both of which comprise an inductor, a resonant circuit and a frequency-voltage conversion circuit, and the output signals of the sensing module and the reference module are processed by a differential amplifier; Step S2, calculating the average production cycle according to the opening and closing state of the mold; Step S3: Perform product quality monitoring, production output monitoring, and mold life and health status monitoring based on the average production cycle.

2. The method for monitoring injection molding production based on mold motion sensing according to claim 1, characterized in that: Step S2 includes: According to the mold opening and closing state, the mold opening and closing action time is obtained, and the duration data of each molding cycle is calculated; The bubble sort algorithm is used to process the molding cycle time data to eliminate outliers and calculate the average production cycle.

3. An injection molding production monitoring system based on mold motion sensing, characterized in that: include: A first processing module is used to obtain the opening and closing state of the mold through a differential sensing circuit; wherein the differential sensing circuit includes: a sensing module and a reference module, the sensing module and the reference module both include an inductor, a resonant circuit and a frequency-voltage conversion circuit, and the output signals of the sensing module and the reference module are processed by a differential amplifier; The second processing module is used to calculate the average production cycle according to the opening and closing state of the mold; The third processing module is used to monitor product quality, production output, mold life and health status based on the average production cycle.

4. The injection molding production monitoring system based on mold motion sensing as claimed in claim 3, characterized in that: The second processing module includes: The first processing unit is used to obtain the opening and closing action time of the mold according to the opening and closing state of the mold, and calculate the duration data of each molding cycle; The second processing unit is used to process the molding cycle duration data using a bubble sort algorithm to eliminate abnormal values ​​and calculate the average production cycle.

5. A storage medium, characterized in that: The storage medium stores a computer program, and the computer program, when running, executes the injection molding production monitoring method based on mold motion sensing as described in any one of claims 1 to 2.

Images