CN115072970B - Intelligent glass molding press monitoring system and method - Google Patents
Intelligent glass molding press monitoring system and method Download PDFInfo
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- CN115072970B CN115072970B CN202210656219.1A CN202210656219A CN115072970B CN 115072970 B CN115072970 B CN 115072970B CN 202210656219 A CN202210656219 A CN 202210656219A CN 115072970 B CN115072970 B CN 115072970B
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- 238000000034 method Methods 0.000 title claims abstract description 146
- 238000012544 monitoring process Methods 0.000 title claims abstract description 83
- 239000011521 glass Substances 0.000 title claims abstract description 46
- 238000000465 moulding Methods 0.000 title claims abstract description 46
- 238000004519 manufacturing process Methods 0.000 claims abstract description 95
- 230000008569 process Effects 0.000 claims abstract description 94
- 238000007405 data analysis Methods 0.000 claims abstract description 19
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- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims description 9
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- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 8
- 238000013439 planning Methods 0.000 claims description 8
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Classifications
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- C—CHEMISTRY; METALLURGY
- C03—GLASS; MINERAL OR SLAG WOOL
- C03B—MANUFACTURE, SHAPING, OR SUPPLEMENTARY PROCESSES
- C03B11/00—Pressing molten glass or performed glass reheated to equivalent low viscosity without blowing
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- C—CHEMISTRY; METALLURGY
- C03—GLASS; MINERAL OR SLAG WOOL
- C03B—MANUFACTURE, SHAPING, OR SUPPLEMENTARY PROCESSES
- C03B11/00—Pressing molten glass or performed glass reheated to equivalent low viscosity without blowing
- C03B11/16—Gearing or controlling mechanisms specially adapted for glass presses
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C3/00—Registering or indicating the condition or the working of machines or other apparatus, other than vehicles
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Manufacturing & Machinery (AREA)
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- General Physics & Mathematics (AREA)
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Abstract
The invention relates to an intelligent glass molding press monitoring system and method, comprising the following steps: obtaining original information of glass production state through a six-cavity molding press; reading in recipe parameters corresponding to the obtained molded device; monitoring the production state, displaying the data analysis result and optimizing the technological parameters of glass preparation; the production and preparation of the glass are adjusted by optimized process parameters to obtain a better molded product. The intelligent monitoring system and the intelligent monitoring method can realize real-time analysis and dynamic display of industrial control data, thereby realizing optimization of process flow.
Description
Technical Field
The invention relates to an intelligent glass molding press monitoring system and method, in particular to a system and method for intelligently monitoring a high-temperature glass molding press in an interactive mode.
Background
The precision compression molding is a precision manufacturing technology for copying the surface morphology of a mold onto an optical material matrix at high temperature, has the characteristics of high precision, high efficiency, low cost and the like, and can easily cope with the manufacture of large-area optical elements with complex morphologies. Because the real-time monitoring and dynamic display of temperature, pressure and other data are needed in the preparation process of the precision optical glass device, a system and a method for intelligently monitoring the high-temperature glass molding press in an interactive mode are needed to cope with the molding conditions which change at any time so as to better control the preparation of the glass device.
In the field of precision compression molding of optical devices, traditional back-end data processing includes real-time technical analysis, providing data such as yield, production cycle, yield prediction, and the like. On the data, basic data such as mean, extremum, variance/standard deviation and the like are provided. In the aspect of control of the molding press, the traditional industrial control touch screen and configuration software mainly provide visual display and control of production flow, but deep analysis is difficult to provide, and complex charts are difficult to display.
In the field of precision compression molding of optical devices, real-time deep data analysis is needed to provide hidden danger/abnormality analysis of the production state of equipment, meet maintenance requirements, and further analyze the process flow in real time and continuously iterate and optimize in the production process. The existing industrial control software mainly based on PLC is difficult to carry out complex operation, and the existing static chart is difficult to meet the requirements of deep data analysis and understanding. In the aspect of data visualization, with the development of data science, an interactive dynamic data chart provides possibility for visual display and deep understanding of complex and deep data.
Disclosure of Invention
The invention aims to provide an intelligent glass molding press monitoring system and method, in particular to a system and method for intelligently monitoring a high-temperature glass molding press in an interactive mode. The intelligent monitoring system and the intelligent monitoring method can realize real-time analysis and dynamic display of industrial control data, thereby realizing optimization of process flow.
The invention discloses a monitoring method of an intelligent glass molding press, which comprises the following steps: obtaining original information of glass production state through a six-cavity molding press; reading in recipe parameters corresponding to the obtained molded device; monitoring the production state, displaying the data analysis result and optimizing the technological parameters of glass preparation; the production and preparation of the glass are adjusted by optimized process parameters to obtain a better molded product.
In one aspect of the present invention, the step of obtaining raw information of the glass production state by the six-cavity molding press further comprises: detecting an online Programmable Logic Controller (PLC) and a working chamber to obtain production monitoring data; each PLC corresponds to three chambers in the six-chamber molding press, data in the chambers can be read on line, and the PLC which does not work does not have data update; reading in process formula data; the time segments of the process are modified according to the modification period of the recipe data and the key recipe data selected according to the purpose of the experiment.
In another aspect of the invention, wherein the production monitoring data comprises what state several chambers of the apparatus are in: automatic, manual, stopping, vacuum, heating, film pressing and cooling, and the number of the die set, the number of the die core, the product which is produced are used in the cavity, and the production statistical information such as the formula number, the daily yield, the type and the quantity of defective products and the like are used; and the state of the six-cavity machine and the current production progress of each cavity; when each cavity is currently in a certain state, the front and back states of the state are displayed.
In still another aspect of the present invention, the six-chamber machine state and the current production schedule of each chamber include manipulator discharging, quartz glass cover descending, lower mold ascending, vacuumizing, heating, constant temperature holding, lower mold ascending to a working position, dwell time, cooling to 400 degrees to start charging nitrogen, cooling to 200 degrees, working position to manipulator feeding position, continuously cooling to 100 degrees, quartz glass cover ascending, manipulator material taking, manipulator discharging to a mold platform, manipulator discharging, and manipulator material sucking.
In another aspect of the present invention, the process recipe data is recipe parameters related to the production process, including current equipment, servo movement speed of the current chamber in each process stage, grating position moved to, duration of each production process stage, set temperature of each production process stage, and safety control parameters of each production process stage such as maximum temperature, maximum pressure tolerance, maximum vacuum of different components, etc.
In another aspect of the invention, the process recipe data includes an import recipe, an enterprise resource planning (Enterprise Resource Planning, ERP) dock, and a worksheet management interface; the display content information is the work order number, the customer, the process formula, the product number, the mold core model and the mold frame model; the method also comprises an ERP system, CVD, ultra-precision machining, mould pressing, quality inspection and packaging; the three states of the mold core and the mold frame of each cavity comprise in use, in replacement and in replacement; PLC output data and work order production conditions; a real-time profile of various temperatures in the cavity is displayed.
In another aspect of the present invention, the step of obtaining the recipe parameters corresponding to the molded sample comprises: creating a new process for a certain key formula; recording the starting and ending time of the process; reading experimental data in the process of the mould pressing device produced by the key formula; reading the formula data of the process; drawing the formula data in the process; drawing a whole graph according to the fact data read in one process and the formula data drawn in the process; check the data for anomalies and output anomaly type and time.
In another aspect of the invention, experimental data in the process of the molded device produced by the key formula is data transmitted back by each sensor in real time in order to ensure production safety and stability in the production process, wherein the data comprise the current equipment, the current cavity, the current temperature, the movement speed, the grating position, the voltage and the current of each component, and the vacuum degree and the pressure of the whole cavity.
In another aspect of the present invention, the steps of monitoring the production state, displaying the data analysis results and optimizing the process parameters of the glass production further comprise: according to the abnormality type and time obtained by the abnormality data, taking the abnormality type and time as an abnormality process control point; checking whether the sample photo has a die drop; checking whether the mold core photo is damaged or not; monitoring and dynamically displaying data analysis results; and optimizing the process parameters.
In another aspect of the invention, the temperature and pressure of the outlier process control point are found, and whether the die life and the sample are affected is judged according to empirical data; whether the die life and the sample are affected as described herein refers to whether the die core needs to be replaced and whether the glass sample is crushed.
In another aspect of the present invention, wherein the step of optimizing the process parameters further comprises: counting the past parameters and the result conditions; fine tuning one of the previous parameters; judging whether the trimming result is positive or negative according to the molding result; if positive, the fine tuning is continued, and if negative, the last well-formed parameters are used.
In another aspect of the invention, where the molding speed at the time of molding is assumed to be 0.5mm/s, the system fine-tunes the speed to 0.55mm/s to find that the molding result is still normal, and then continues to tune the speed to 0.6mm/s until the speed is found to be fast enough, and after the mold life or the sample is crushed, the last speed setting is returned.
The intelligent glass molding press monitoring system comprises an information obtaining module, wherein the information obtaining module is used for obtaining the original information of the glass production state through a six-cavity molding press; the parameter reading module reads recipe parameters corresponding to the obtained molded devices; the monitoring display optimization module is used for monitoring the production state, displaying the data analysis result and optimizing the technological parameters of glass preparation; and the product adjusting module is used for adjusting the production and preparation of the glass through optimized process parameters so as to obtain a better molded product.
The monitoring system and the method of the invention connect the general computer server with the industrial control PLC through the Ethernet and the optical fiber communication, the computer directly reads and writes the PLC register in real time to monitor the production state, and the data is analyzed and processed in real time, and is displayed to production operation and process optimizing personnel by utilizing an interactive dynamic data chart based on Javascript, CSS, HTML. Provides a feasible scheme for preparing the silicon die with high efficiency and high quality, and creates favorable conditions for realizing mass, high-precision and high-efficiency production of optical elements.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below. It will be apparent to those skilled in the art that the drawings in the following description are merely examples of the invention and that other drawings may be derived from them without undue burden to those skilled in the art.
FIG. 1 is a flow chart of a monitoring method of the present invention.
FIG. 2 is a flow chart of the monitoring method of the present invention for obtaining raw information of glass production status.
FIG. 3 is a flow chart of the monitoring method of the present invention reading in recipe parameters corresponding to obtaining molded samples.
FIG. 4 (a) is a flow chart of the monitoring method of the present invention for monitoring production status, displaying data analysis results and optimizing process parameters for glass production.
FIG. 4 (b) is a flowchart showing the detailed steps for optimizing parameters of a glass manufacturing process in the monitoring method of the present invention.
Fig. 5 (a) - (i) are examples of possible cause analysis of abnormal data in the steps of monitoring production status, displaying data analysis results and optimizing process parameters of glass production according to the monitoring method of the present invention.
FIGS. 6 (a) - (b) are tables illustrating the data timing analysis process points of the monitoring method of the present invention.
Detailed Description
Specific embodiments of the present invention will now be described with reference to the accompanying drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. The terminology used in the detailed description of the embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention.
FIG. 1 is a flow chart of a monitoring method of the present invention. In step 101, obtaining original information of glass production state through a six-cavity molding press; in step 102, recipe parameters corresponding to the obtained molded sample are read in, wherein the recipe parameters refer to preset parameters such as pressure, temperature and the like; in step 103, monitoring the production state, displaying the data analysis result and optimizing the technological parameters of glass preparation; in step 104, the production preparation of the glass is adjusted by the optimized process parameters to obtain a better product.
FIG. 2 is a flow chart of the monitoring method of the present invention for obtaining raw information of glass production status. The step of obtaining original information through the six-cavity molding press comprises the steps of detecting an online programmable logic controller (Programmable Logic Controller, PLC) and working cavities to obtain production monitoring data, wherein each PLC corresponds to three cavities in the six-cavity molding press, data in the cavities can be read online, and the PLC which does not work does not have data update; step 202, reading in process recipe data (parameters); in step 203, the time segments of the process are modified according to the modification period of the recipe data and the key recipe data selected according to the purpose of the experiment.
Wherein the production monitoring data is an overall production situation of the apparatus, including in what state several chambers of the apparatus are: automatic, manual, stopping, vacuum, heating, film pressing and cooling, and the number of the die set, the number of the die core, which product is produced, the number of the formula, the daily yield, the type and the number of defective products and the like are used in the cavity. In one embodiment, six chamber machine states are included with the current production schedule for each chamber. The specific state is that the manipulator is discharged, the quartz glass cover descends, the lower die ascends, vacuumizing, heating and constant temperature keeping are carried out, the lower die ascends to a working position, the pressure maintaining time is shortened, the temperature is reduced to 400 ℃, nitrogen is started to be filled, the temperature is reduced to 200 ℃, the working position is increased to a manipulator feeding position, the temperature is continuously reduced to 100 ℃, the quartz glass cover ascends, the manipulator is used for taking materials, the manipulator is discharged to a die platform, the manipulator is discharged, and the manipulator is used for sucking materials. Each cavity is currently in a certain state and shows the state before and after the state.
The process recipe data are recipe parameters related to the production process, including the current equipment, the servo motion speed of the current cavity in each process stage, the position of the grating moved to, the duration of each production process stage, the set temperature of each production process stage, and the safety control parameters of each production process stage, such as the highest temperature, the highest pressure tolerance, the highest vacuum and the like of different components. In one embodiment, a recipe is imported from a computer, an enterprise resource planning (Enterprise Resource Planning, ERP) interface is included, and a worksheet management interface is presented. The display content information is the work order number, the customer, the process formula, the product number, the mold core model and the mold frame model. The method also comprises an ERP system, CVD, ultra-precision machining, mould pressing, quality inspection and packaging; the three states of the mold core and the mold frame of each cavity comprise in use, in replacement and in replacement; PLC output data and work order production conditions; a real-time profile of various temperatures in the cavity is displayed.
FIG. 3 is a flow chart of the monitoring method of the present invention reading in recipe parameters corresponding to obtaining molded samples. The step of reading recipe parameters corresponding to the obtained molded sample is, step 301, creating a new process for a certain key recipe; step 302, recording the starting and ending time of the process; step 303, reading experimental data during the process of producing the optical device according to the key recipe imported in step 301; and simultaneously at step 304, the recipe data for the process is read in; step 305 is performed after step 304, and the recipe data is drawn in the process; in step 306, a whole graph is drawn according to the fact data read in one process segment and the formula data drawn in the process; in step 307, the data is checked for anomalies and the anomaly type and time are output. Experimental data in the process of the optical device produced by the imported key formula, in order to ensure safe and stable production in the production process, data transmitted back by each sensor in real time comprises the current equipment, the current cavity, the current temperature, the movement speed, the grating position, the voltage and the current of each component, and the vacuum degree and the pressure of the whole cavity.
FIG. 4 (a) is a flow chart of the monitoring method of the present invention for monitoring production status, displaying data analysis results and optimizing process parameters for glass production. Step 401, according to the abnormality type and time obtained by the abnormality data, taking the abnormality type and time as an abnormality process control point; finding the temperature and pressure of the abnormal point process control point, and judging whether the service life of the die and the sample are affected according to empirical data; whether the service life of the die and the sample are influenced or not refers to whether the die core needs to be replaced or not and whether the glass sample is crushed or not; at step 402, check whether the sample photo has a die drop; at step 403, checking whether the core photo is broken; at step 404, the data analysis results are monitored and dynamically presented. In step 405, the process parameters are optimized.
FIG. 4 (b) is a flowchart showing the detailed steps for optimizing parameters of a glass manufacturing process in the monitoring method of the present invention. The step of optimizing the process parameters comprises the following sub-steps: counting previous parameters and result conditions in step 4051; in step 4052, the monitoring system of the present invention performs fine tuning on one of the previous parameters, and in step 4053, determines whether the fine tuning result is positive or negative according to the molding result; if the result is positive, continuing fine tuning, and if the result is negative, using the parameter of the last good result; in one embodiment, the molding speed at the time of molding is assumed to be 0.5mm/s, the system fine-tunes the speed to 0.55mm/s and finds that the molding result is still normal, and then continues to adjust the speed to 0.6mm/s until the speed is found to be fast enough, and after the mold life or the sample is crushed, the last speed setting is returned. Through the step setting, the speed parameter is optimized, and the production efficiency is improved.
The abnormal data that may be generated by the six-cavity molding press is possible, and fig. 5 (a) - (i) are examples of possible cause analysis of the abnormal data in the steps of monitoring the production state, displaying the data analysis results, and optimizing the process parameters of glass production by the monitoring method of the present invention.
The abnormal data example of fig. 5 (a) shows that the data transmission speed is abnormal. The data transmission speed can be found to be slow due to the influence of the content by observing the data transmission time, the abnormal time and the duration of the transmission time can be found by combining the Gaussian distribution center of the transmission time and the 90% distribution range, the main reasons for generating the abnormal time and the duration are that the network module is an auxiliary module, the PLC needs to communicate with the network module through an interface, the existing network is 100Mbps Ethernet, and the speed is relatively slow compared with the direct internal communication, so that the PLC with a built-in gigabit network interface can be selected to solve the problem of abnormal data.
Fig. 5 (b) shows the data location of the abnormal data of fig. 5 (a), marked with red circles. Wherein the circled portion emphasizes the time point and duration of the transmission time anomaly. Distribution of transmission time (gaussian center of mean and 90% distribution range, e.g. plus or minus 22 ms), three lines, two straight lines of mean line and upper and lower limits. From fig. 5 (b), it can be seen that, from possible reasons, by analysis and display of software, the abnormal data position and abnormal transmission speed period are determined, so that technicians can trace back and improve the performance of the device.
The abnormal data example of fig. 5 (c) shows a pressure difference control abnormality. By observing the pressure difference of the data, the data pressure difference is not effective, and the abnormal time and duration of the pressure difference can be found by combining the Gaussian distribution center of the pressure difference and the 99% distribution range;
fig. 5 (d) shows the analysis and presentation of the anomaly data of fig. 5 (c), wherein the circled portion highlights the time point and duration of the pressure differential anomaly. From fig. 5 (d), it can be seen that, by modifying the action zone, the pressure difference can be controlled within the target range, ensuring smooth progress of the molding process, for possible reasons.
The example of anomaly data of FIG. 5 (e) shows a grating position anomaly. The data grating position is found to be unstable by observing the grating position of the data, and the grating position can shake after the hot pressing is finished. The circled portions of fig. 5 (e) represent the positional instability, respectively. The time and specific change value of the grating position change can be found out by combining the grating position with the work grating position.
Fig. 5 (f) analysis and presentation of the anomaly data of fig. 5 (e), wherein the time period during which the change in grating position (rise or fall) occurs, and the comparison of the specific changed values with the position between the set working gratings, are presented. From fig. 5 (f), it can be seen that for possible reasons, the continuously stable control can continuously stably control the rise and fall during the molding process, targeting the grating position.
An example of the abnormal data of fig. 5 (g) shows that the upper and lower dies are abnormal in temperature rise and fall. The infrared temperature of the upper die and the lower die of the data is observed, so that the temperature rise and fall of the upper die and the lower die of the data are asynchronous, namely the temperature control of the upper die and the lower die is inaccurate. By combining the infrared temperature differences of the upper die and the lower die, the power start and the power return-to-zero time differences of the upper die and the lower die and the heating, heat preservation and cooling power differences of the upper die and the lower die, the abnormal time of the infrared temperature rise and fall of the upper die and the lower die can be found. The circled portions of fig. 5 (g) show inaccuracy in upper and lower die temperature control, respectively.
FIG. 5 (h) is an analysis and display of the anomaly data of FIG. 5 (g), wherein the upper and lower die infrared temperature differences are shown; power start and power return to zero time difference of upper and lower modes; the upper die and the lower die are heated, insulated and cooled with different power. As can be seen from fig. 5 (h), the control of the heating for possible reasons enables a stable control of the temperature rise process.
The example of the abnormal data of fig. 5 (i) shows motor rotation conversion abnormality. By observing the position difference of the grating motor of the data, the position difference of the grating motor is positively correlated with the pressure, and the motion of the motor cannot be completely converted into the position, but is converted into the pressure. The position difference constant time of the grating motor can be found out by combining the position difference and the pressure of the grating motor. Because the pressure sensor is installed in the middle of the push rod, the motor pushes the pressure sensor, and the pressure sensor pushes the push rod to move upwards together, and the grating ruler is installed on the push rod. The pressure sensor measures the pressure through slight deformation, so that the friction force of the part of the equipment which clamps the push rod in the process of pushing the transmission rod by the motor is gradually increased along with the rising of the push rod, so that the pressure sensor is slightly deformed (about 0.2 mm), namely, the pressure sensor is stressed and deformed at the moment after the motor rotates, the push rod above the pressure sensor does not move, and the position of the push rod measured by the grating ruler arranged on the push rod is still in situ, so that the inconsistency of the position of the motor and the position of the grating is caused. The deformation of the pressure sensor is compensated algorithmically. In addition, the sample expands thermally during heating, which results in misalignment, which can reduce the transfer of heat to the drive mechanism by adding insulation. Finally, by the method, the abnormity of the motor rotation conversion process is avoided.
FIGS. 6 (a) - (b) are tables illustrating the data timing analysis process points of the monitoring method of the present invention. These two tables show a total of 12 nodes (including start node 0) for a six-chamber process control node, where the positions of node 3 and node 4 can be interchanged.
The control node 0 is the node when the grating reaches the lowest point of the previous mould pressing when the previous mould pressing is finished; starting from the data starting point in case the previous end time cannot be found; and finding the lowest point of the experimental ending grating position in the real-time data and keeping the position stable for analysis, and obtaining the pressure, the pressure difference and the time point at the moment. In one embodiment, the pressure is 0kg; the pressure difference is 1.2; the time period calculated at the node is the interval between the previous experiment and the current experiment.
The control node 1 is a node when the current mould pressing is started, at the moment, the grating is positioned at the lowest point before the current mould pressing is started, and the position of the grating rises from the lowest point; starting from a data starting point under the condition that the data is incomplete and the lowest point before starting cannot be found; and finding the lowest point of the position of the experimental start grating in the real-time data and keeping the position stable for analysis, and obtaining the pressure, the pressure difference, the time point and the time interval from the control point of the previous working procedure at the moment.
The control node 2 is a node when the lower die rises to the preheating position and starts vacuumizing, and at the moment, the grating reaches the preheating position and starts vacuumizing; and (3) finding out a position which is coincident with the HEAT position and keeps stable in the real-time data for analysis, and obtaining the pressure, the pressure difference, the time point and the time interval from the control point of the previous working procedure at the moment. In one embodiment, the pressure is 23.8kg; the pressure difference is 0; the time period calculated at the present node is the period of time to rise to the warm-up position.
The control node 3 is a node which can be heated after vacuumizing, at the moment, the setting is checked, the stable vacuum degree of the current mould pressing is confirmed, the positions where the vacuum degree in the real-time data is reduced to a certain amount and is kept stable are found for analysis, and the pressure, the pressure difference, the time point and the time interval from the control point of the previous working procedure at the moment are obtained. In one embodiment, the vacuum is pulled to 2.5pa or 0.9pa; the pressure is 13kg; the pressure difference is-0.1; the time period calculated at this node is the evacuation time.
The control node 4 is a node for starting heating, and finds the position of the power rising from the lowest point in the real-time data at this time for analysis, and obtains the pressure, the pressure difference, the time point and the time interval from the control point of the previous process at this time. In one embodiment, the vacuum is pulled to 2.5pa or 0.9pa; the pressure is 13kg; the pressure difference is-0.1; the time period calculated at this node is the time difference between the start of heating and the evacuation. The order of the control nodes 3 and 4 may be interchanged, as the evacuation time may be longer or shorter than the difference between the start of heating and evacuation.
The control node 5 is a node heated to the set temperature, finds the position where the lower die infrared temperature coincides with the lower die set temperature and remains stable in the real-time data for analysis, and obtains the upper die infrared temperature, the lower die infrared temperature, the pressure difference, the time point and the time interval from the control point of the previous working procedure at the moment. In one embodiment, the pressure is 12.4kg; the pressure difference is-0.1, and the infrared temperature of the upper die is 618 ℃; the infrared temperature of the lower die is 618 ℃; the time period calculated at this node is the heating time.
The control node 6 is a node that starts cooling by reducing power, and the temperature starts to decrease; and (3) finding out the position where the upper mode calculation power starts to continuously decrease after rising to the highest point in the real-time data, and analyzing to obtain the pressure, the pressure difference, the time point and the time interval from the control point of the previous working procedure at the moment. In one embodiment, the pressure is 32.7kg; the pressure difference was 0.2, and the time period calculated at this node was the total molding time.
The control node 7 is a node which is powered off and starts to naturally cool down, the power is zero after the power is powered off, the position where the calculated power of the upper die in real-time data is reduced to 0 is found for analysis, and the time interval between the infrared temperature of the upper die, the infrared temperature of the lower die, the pressure difference, the time point and the control point of the previous working procedure at the moment is obtained. In one embodiment, the pressure is 31.4kg; the pressure difference is 0.2, and the infrared temperature of the upper die is 560 ℃; the infrared temperature of the lower die is 560 ℃; the time period calculated at this node is the heating power cool-down time.
The control node 8 is a node for starting to charge nitrogen into the cavity to actively cool, finds a first position for continuously descending after the vacuum degree in the real-time data rises to the highest point, analyzes the first position, and obtains the upper die infrared temperature, the lower die infrared temperature, the pressure difference, the time point and the time interval from the control point of the previous process at the moment. Breaking through the vacuum state at the control node 8; in one embodiment, the pressure is 32.1kg; the pressure difference is 0.2, and the infrared temperature of the upper die is 527 ℃; the infrared temperature of the lower die is 540 ℃; the time period calculated at the node is a natural cooling time period.
The control node 9 is a node for the lower die to start descending, the working position of the grating starts descending, and the position of the grating which starts descending in real-time data is found for analysis, so that the upper die infrared temperature, the lower die infrared temperature, the pressure difference, the time point and the time interval from the previous process control point are obtained. In one embodiment, the pressure is 37.5kg; the pressure difference is 0.2, and the infrared temperature of the upper die is 100 ℃; the time period calculated at this node is a forced cooling time period.
The control node 10 is the node at which the lower die descends to the lowest point, and the working position of the grating is close to 0, and in one embodiment is 0.002, which indicates that the procedure is finished; and finding the position where the grating starts to descend to-0.002 in the real-time data for analysis, and obtaining the pressure, the pressure difference, the time point and the time interval from the control point of the previous working procedure at the moment. In one embodiment, the pressure is 1.1kg; the pressure difference is 0; the time period calculated at the present node is a falling time period. And integrating the control nodes 1-10 to obtain the overall time of the working procedure.
The control node 11 is the start of a new process, the working position of the grating is close to 0, the lowest point, in one embodiment 0.002, indicating that the new process starts, and the position in the real-time data where the grating is-0.002 and the value of the grating increases at the next time is found and analyzed. The time period calculated at this node is the start time of the new process.
The control nodes 0-11 represent a complete process, and after the entire process has been completed, the obtained product is inspected and the inspection result is led to the analysis part of the monitoring system according to the invention to form complete mould pressing data. And the monitoring system counts the results of the repeated successful mould pressing to obtain a safety interval of each parameter, and in a new process, if the parameter exceeds the safety interval of the parameter, the monitoring system displays the abnormal position so that a user can check the abnormal cavity to judge whether the cavity can continue to perform a certain process. Meanwhile, the monitoring system can automatically fine-tune parameters according to the previous data and further optimize the process parameters, so that the production efficiency is improved. In the traditional mould pressing process, a judging method of 'one-step cutting' is adopted, namely, a fixed mould pressing frequency is set, and the mould is replaced completely no matter whether the mould is good or bad; compared with the traditional judging method, the monitoring system has more accurate judgment, can furthest develop the service life of the die and optimize the process parameters so as to improve the productivity.
Reference herein to "one embodiment," "an embodiment," or "one or more embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Furthermore, it is noted that the word examples "in one embodiment" herein do not necessarily all refer to the same embodiment.
The above description is only for the purpose of illustrating the technical solution of the present invention, and any person skilled in the art may modify and change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Therefore, the protection scope of the invention should be considered as the scope of the claims. The invention has been described above with reference to examples. However, other embodiments than the above described are equally possible within the scope of the disclosure. The different features and steps of the invention may be combined in other ways than those described. The scope of the invention is limited only by the appended claims. More generally, one of ordinary skill in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings of the present invention are used.
Claims (20)
1. The intelligent glass optical device molding press monitoring method comprises the following steps:
obtaining original information of the production state of the glass optical device through a six-cavity molding press; detecting an online Programmable Logic Controller (PLC) and a working chamber to obtain production monitoring data; each PLC corresponds to three chambers in the six-chamber molding press, data in the chambers can be read on line, and the PLC which does not work does not have data update;
reading in recipe parameters corresponding to the obtained molded device;
creating a new process for a certain key formula;
recording the starting and ending time of the process;
reading experimental data in the process of the mould pressing device produced by the key formula; the experimental data in the process of the mould pressing device produced by the key formula is data transmitted back by each sensor in real time in order to ensure the production safety and stability in the production process, and comprises the current equipment, the current cavity, the current temperature, the current movement speed, the grating position, the voltage and the current of each component, and the vacuum degree and the pressure of the whole cavity;
reading the formula data of the process;
drawing the formula data in the process;
drawing a whole graph according to the fact data read in one process and the formula data drawn in the process;
checking data abnormality and outputting abnormality type and time;
monitoring the production state, displaying the data analysis result and optimizing the technological parameters of the preparation of the glass optical device;
the production and preparation of the glass optical device are adjusted by the optimized process parameters to obtain a better molded product.
2. The monitoring method of claim 1, wherein the step of obtaining raw information of the production status of the glass optical device by the six-cavity molding press further comprises:
reading in process formula data;
the time segments of the process are modified according to the modification period of the recipe data and the key recipe data selected according to the purpose of the experiment.
3. The monitoring method of claim 2, wherein the production monitoring data comprises what state several chambers of the apparatus are in: automatic, manual, stopping, vacuum, heating, mould pressing and cooling, and the number of mould frames, the number of mould cores and the production of products used in the cavity, the number of formulas used, the daily yield, the yield and the production statistical information of the types and the quantity of defective products; and the state of the six-cavity machine and the current production progress of each cavity; when a certain cavity is a certain state, the front and back states of the state are displayed.
4. The monitoring method according to claim 3, wherein the six-chamber machine state and the current production schedule of each chamber comprise manipulator discharging, quartz glass cover descending, lower die ascending, vacuumizing, heating, constant temperature maintaining, lower die ascending to working position, dwell time, cooling to 400 ℃ to start charging nitrogen, cooling to 200 ℃, working position to manipulator charging position, continuously cooling to 100 ℃, quartz glass cover ascending, manipulator material taking, manipulator discharging to die platform, manipulator discharging, and manipulator sucking.
5. The monitoring method of claim 2, wherein the process recipe data is a recipe parameter related to a production process, including a current equipment, a servo movement speed of a current chamber in each process stage, a grating position moved to, a duration of each production process stage, a set temperature of each production process stage, and a safety control parameter of each production process stage, the safety control parameter being a maximum temperature, a maximum pressure tolerance, or a maximum vacuum of different components.
6. The monitoring method of claim 5, wherein the process recipe data includes an import recipe, an enterprise resource planning (Enterprise Resource Planning, ERP) dock, a job management interface; the display content information is the work order number, the customer, the process formula, the product number, the mold core model and the mold frame model; the method also comprises an ERP system, CVD, ultra-precision machining, mould pressing, quality inspection and packaging; the three states of the mold core and the mold frame of each cavity comprise in use, in replacement and in replacement; PLC output data and work order production conditions; a real-time profile of various temperatures in the cavity is displayed.
7. The monitoring method of claim 1, wherein the steps of monitoring production conditions, displaying data analysis results, and optimizing process parameters for glass optic fabrication further comprise:
according to the abnormality type and time obtained by the abnormality data, taking the abnormality type and time as an abnormality process control point;
checking whether the sample photo has a die drop;
checking whether the mold core photo is damaged or not;
monitoring and dynamically displaying data analysis results;
and optimizing the process parameters.
8. The monitoring method of claim 7, wherein the temperature and pressure of the abnormal process control point are found, and whether the die life and the sample are affected is determined based on empirical data; whether the die life and the sample are affected as described herein refers to whether the die core needs to be replaced and whether the glass sample is crushed.
9. The monitoring method of claim 7 wherein optimizing the process parameters further comprises:
counting the past parameters and the result conditions;
fine tuning one of the previous parameters;
judging whether the trimming result is positive or negative according to the molding result; if positive, the fine tuning is continued, and if negative, the last well-formed parameters are used.
10. A monitoring method as claimed in claim 9, wherein the moulding speed at the time of moulding is assumed to be 0.5mm/s, the system fine-tuning the speed to 0.55mm/s to find that the moulding result is still normal, and then continuing fine-tuning the speed to 0.6mm/s until the speed is found to be fast to a certain extent, and then returning to the last speed setting if the mould life is affected or the sample is crushed.
11. An intelligent glass optical device molding press monitoring system comprises
The information acquisition module is used for acquiring the original information of the production state of the glass optical device through the six-cavity molding press; the online monitoring module is used for detecting an online Programmable Logic Controller (PLC) and a working cavity to obtain production monitoring data; each PLC corresponds to three chambers in the six-chamber molding press, data in the chambers can be read on line, and the PLC which does not work does not have data update; the parameter reading module reads recipe parameters corresponding to the obtained molded devices; comprising the following steps:
the new process creation module creates a new process for a certain key formula;
the time recording module is used for recording the starting and ending time of the process;
the data reading module reads experimental data in the process of the molded device produced by the key formula; the experimental data in the process of the mould pressing device produced by the key formula is data transmitted back by each sensor in real time in order to ensure the production safety and stability in the production process, and comprises the current equipment, the current cavity, the current temperature, the current movement speed, the grating position, the voltage and the current of each component, and the vacuum degree and the pressure of the whole cavity;
the formula reading-in module reads in the formula data of the process;
the drawing module draws the formula data in the process;
the whole graph module is used for drawing a whole graph according to the fact data read in one process and the formula data drawn in the process;
the abnormality checking module is used for checking data abnormality and outputting abnormality type and time;
the monitoring display optimization module is used for monitoring the production state, displaying the data analysis result and optimizing the technological parameters of the preparation of the glass optical device;
and the product adjusting module is used for adjusting the production and preparation of the glass optical device through optimized process parameters so as to obtain a better molded product.
12. The monitoring system of claim 11, wherein the information acquisition module further comprises:
the data reading module reads process formula data;
and the process segmentation module is used for modifying the time segments of the process according to the modification period of the recipe data and the key recipe data selected according to the experimental purposes.
13. The monitoring system of claim 12, wherein the production monitoring data includes what states several chambers of the apparatus are in: automatic, manual, stopping, vacuum, heating, mould pressing and cooling, and the number of mould frames, the number of mould cores and the production of products used in the cavity, the number of formulas used, the daily yield, the yield and the production statistical information of the types and the quantity of defective products; and the state of the six-cavity machine and the current production progress of each cavity; when a certain cavity is a certain state, the front and back states of the state are displayed.
14. The monitoring system of claim 13, wherein the six-chamber machine state and current production schedule for each chamber comprises a robot hand discharge, a quartz glass cover lowering, a lower mold lifting, a vacuum pumping, a heating, a constant temperature holding, a lower mold lifting to a working position, a dwell time, a cooling to 400 degrees starting nitrogen gas charging, a cooling to 200 degrees, a working position to a robot hand feeding position, a continuous cooling to 100 degrees, a quartz glass cover lifting, a robot hand material taking, a robot hand discharge to a mold platform, a robot hand discharging, a robot hand sucking.
15. The monitoring system of claim 12, wherein the process recipe data is a recipe parameter associated with a production process, including a current equipment, a servo motion speed of a current chamber in each process stage, a grating position moved to, a duration of each production process stage, a set temperature of each production process stage, and a safety control parameter of each production process stage, the safety control parameter being a maximum temperature, a maximum pressure tolerance, or a maximum vacuum of different components.
16. The monitoring system of claim 15, wherein the process recipe data includes an import recipe, an enterprise resource planning (Enterprise Resource Planning, ERP) dock, a work order management interface; the display content information is the work order number, the customer, the process formula, the product number, the mold core model and the mold frame model; the method also comprises an ERP system, CVD, ultra-precision machining, mould pressing, quality inspection and packaging; the three states of the mold core and the mold frame of each cavity comprise in use, in replacement and in replacement; PLC output data and work order production conditions; a real-time profile of various temperatures in the cavity is displayed.
17. The monitoring system of claim 11, wherein the steps of monitoring production conditions, displaying data analysis results, and optimizing process parameters for glass optic preparation further comprise:
according to the abnormality type and time obtained by the abnormality data, taking the abnormality type and time as an abnormality process control point;
checking whether the sample photo has a die drop;
checking whether the mold core photo is damaged or not;
monitoring and dynamically displaying data analysis results;
and optimizing the process parameters.
18. The monitoring system of claim 17, wherein the temperature and pressure of the abnormal process control point are found, and determining whether to affect die life and sample based on empirical data; whether the die life and the sample are affected as described herein refers to whether the die core needs to be replaced and whether the glass sample is crushed.
19. The monitoring system of claim 17, wherein the monitor presentation optimization module further comprises:
the statistics module is used for counting the past parameters and the result conditions;
a fine tuning module for fine tuning one of the previous parameters;
the positive and negative determination module is used for judging whether the fine adjustment result is positive or negative according to the mould pressing result; if positive, the fine tuning is continued, and if negative, the last well-formed parameters are used.
20. A monitoring system according to claim 19, wherein the molding speed at the time of molding is assumed to be 0.5mm/s, the system fine-tuning the speed to 0.55mm/s to find that the molding result is still normal, and then continuing fine-tuning the speed to 0.6mm/s until the speed is found to be fast enough to affect the life of the mold or the sample is crushed, and then returning to the last speed setting.
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