Optimization method for intaglio printing process of RFID (Radio Frequency Identification) electronic tag
By establishing a simulation model and real-time monitoring system in the RFID electronic tag gravure printing process, optimizing printing parameters and process conditions, the problem of poor printing quality in the existing technology is solved, and efficient and high-quality RFID electronic tag printing is achieved, ensuring the stability of product performance and recognition effect.
Patent Information
- Application Number
- CN202510049406.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-13
- Publication Date
- 2025-04-25
AI Technical Summary
In the existing RFID electronic label gravure printing process, the printing parameters depend on operating experience or trial and error methods, and the differences in substrate characteristics, ink performance and environmental conditions cannot be fully considered, resulting in poor printing quality, affecting RF performance and identification effect.
An RFID electronic label gravure printing process optimization method is adopted. By establishing a simulation model in a computer, training and optimizing the simulation model based on historical printing data, determining the best printing parameters, and using sensors to obtain printing parameter data in real time, adjusting process parameters, and using positioning overprinting technology and automatic ink mixing module to monitor the printing process in real time.
It realizes efficient and high-quality printing of RFID electronic tag antennas, ensures the stability of RF performance and identification effect, reduces printing quality fluctuations caused by human factors or accidental factors, and ensures the consistency of product quality.
Smart Images
Figure CN119885894A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of printing, and in particular to a method for optimizing a gravure printing process for an RFID electronic tag. Background Art
[0002] With the rapid development of Internet of Things technology, RFID electronic tags have been widely used in logistics, retail, warehouse management, identity recognition and many other fields. RFID electronic tags are usually composed of antennas, chips and the substrates that carry them. The printing quality of the antenna pattern plays a vital role in the radio frequency performance and recognition accuracy of the entire electronic tag. In order to meet the performance requirements in different application scenarios, high-precision and high-quality printing processes are required to ensure the accurate printing of the antenna pattern and good compatibility with the chip components.
[0003] At present, in the gravure printing process of RFID electronic tags, printing parameters are mostly set based on the operator's experience or traditional trial and error methods. This method often fails to fully consider the differences in the characteristics of electronic tag substrates of different batches, subtle changes in ink performance, and the influence of printing environmental conditions, resulting in the printed electronic tag antenna patterns being prone to quality problems such as insufficient line clarity, insufficient pattern accuracy, and uneven ink adhesion, which in turn affects the radio frequency performance and recognition effect of RFID electronic tags. In addition, the ink mixing and control means are limited, and there is a lack of systematic optimization methods. In this regard, we propose an optimization method for the gravure printing process of RFID electronic tags. Summary of the invention
[0004] In order to solve the above technical problems, a method for optimizing the gravure printing process of RFID electronic tags is provided. This technical solution solves the problem that the above manual experience judgment leads to poor RFID electronic tag recognition effect.
[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is: a method for optimizing the gravure printing process of RFID electronic tags, the optimization steps are:
[0006] S1. Optimize printing plate parameters. Establish a simulation model in the computer. Based on historical printing data, train and optimize the simulation model to determine the best printing parameters in the historical data. Input the current electronic label data to be printed into the simulation model, and output the optimal screen line number, mesh depth and cell shape of the gravure printing cylinder.
[0007] S2, process parameter adjustment, based on the real-time acquisition of parameter data in printing by sensors, upload, build a comparison database, obtain the optimal printing process parameter range threshold of different electronic labels based on big data, compare the collected data with the threshold, and adjust the printing process parameters if it is greater than the threshold range, including the tension of the winding and unwinding, the pressure of the printing rubber embossing roller, and the thixotropic viscosity of the slurry;
[0008] S3, positioning overprinting technology, using positioning overprinting technology to accurately align the pattern of the RFID electronic tag antenna;
[0009] S4, ink mixing and adjustment, based on the automatic ink mixing module, mix the ink according to the formula ratio, and combine with the color measuring instrument to detect the difference between the mixed ink color and the target color in real time, and make adjustments and optimizations;
[0010] S5. Real-time monitoring of the printing process: The printing process is monitored in real time based on a camera, and the monitored data is stored as historical data for subsequent analysis.
[0011] Preferably, the historical printing data in step S1 includes characteristics of different types of printing materials, various parameters of inks, environmental conditions during printing, and combinations of printing parameters used in history. The historical printing data is input into the model through data analysis technology, so that the model can learn and analyze the printing effects presented under different printing parameter combinations. Based on the analysis results, the model is repeatedly adjusted and optimized so that the model can determine the printing parameters that achieve the best printing effect from the historical data. After the training is completed, the data of the electronic label to be printed is input into it. The electronic label includes its own material, size and purpose. The simulation model is based on the learning rules and, through simulation analysis, finally outputs the optimal screen line count, mesh depth and cell shape of the gravure printing cylinder for this electronic label printing task.
[0012] Preferably, the model training measures the difference between the printing effect of the simulation model and the actual historical printing effect by adopting a defined loss function J(θ), and the mean square error is used for training. The training formula is:
[0013]
[0014] Where J(θ) is the loss function, d i is the data of the i-th record in the historical data, n is the number of historical data, f M is the prediction function of model M, θ is the internal parameter, r i is the corresponding printing effect evaluation index; initialize the model parameter θ, update it in each iteration t, and update the model parameter. The expression is:
[0015]
[0016] The above updating process is repeated until the stopping condition is met. The stopping condition is that the preset number of iterations T and the value of the loss function J(θ) converge to the minimum.
[0017] Input the data into the trained model, analyze it and output the printing plate parameters.
[0018] Preferably, in step S2, sensors are distributed on the printing equipment, including at the ink delivery pipeline, on the printing roller and on the reel-up and unreel device. The sensors obtain parameter data in printing, transmit it wirelessly, and build a database. By accumulating data in printing through electronic tags of different types and specifications in the big data, the optimal printing process parameter range threshold for different electronic tags is obtained. The data collected by the sensor in real time is compared with the optimal printing process parameter range threshold. When it is greater than the threshold, the printing parameters are adjusted.
[0019] Preferably, the tension of the reel is adjusted by controlling the speed of the motor and the tightness of the tension adjusting device; the pressure of the printing rubber embossing roller is adjusted by changing the downward pressure of the embossing roller through the pressure adjusting mechanism to return the pressure to the optimal range; the thixotropic viscosity of the slurry is adjusted by adding a diluent.
[0020] Preferably, the positioning overprinting technology in step S3 is implemented based on a positioning system. A positioning device is provided on the printing equipment. The positioning device includes a sensor and a control system. The sensor is used to monitor the position and movement status of the printing substrate in real time, and transmit the collected data to the control system. The control system adjusts the position and movement of the printing components based on the data, so that each printing operation is performed at an accurate position.
[0021] Preferably, the printing control component performs physical limit and position adjustment on the printing substrate through mechanical components, and the control system receives information, performs analysis and processing, generates control instructions, and sends them to various execution components of the printing device to perform positioning and overprinting; during the control process, the control system needs to first calculate the deviation value between the printing substrate and the printing device, and calculate the distance difference between the two based on the Euclidean distance, and the calculation formula is:
[0022]
[0023] Wherein A(b, c) is the calculated distance deviation value between the printing substrate and the printing device, (x2, y2) is the current distance of the printing device, and (x1, y1) is the current distance of the printing substrate. The distance difference between the two is obtained by calculation. The control system controls the movement of the mechanical parts based on the obtained difference data to align the printing device with the printing substrate.
[0024] Preferably, in step S4, the automatic ink mixing module internally stores ink formulas obtained from historical practices, from which corresponding mixing ratio information is extracted, and each ink storage container is connected to the mixing center through pipes and valves. The module controls the opening and closing degree of each valve and the flow rate of the delivery pump according to the set mixing ratio, and delivers the ink to the mixing container.
[0025] Preferably, after the preparation is completed, the color measuring instrument works, the probe emits light, and receives the light reflected by the ink. Through data processing, the current ink color parameter values are obtained, and the measured data are compared and analyzed with the pre-set target color parameters to calculate the difference between the two. After the difference is calculated, adjustments and optimizations are made based on the difference data.
[0026] Preferably, in step S5, when the printing process is in progress, the printing process is recorded in real time by a camera to capture key parameters of each process in the printing process. After the capture is completed, the data is stored and the recorded image data and key parameters are classified and sorted in chronological order.
[0027] Compared with the prior art, the present invention has the following beneficial effects:
[0028] The present invention optimizes the printing process by determining the appropriate number of screen lines, mesh depth and cell shape of the gravure printing cylinder, and adjusting printing process parameters such as the tension of the winding and unwinding rolls, the pressure of the printing rubber embossing roller, and the thixotropic viscosity of the slurry, thereby achieving efficient and high-quality printing of RFID electronic tag antennas and providing technical support for large-scale industrial production. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] Figure 1 The present invention is a flow chart of the printing process optimization steps. DETAILED DESCRIPTION
[0030] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.
[0031] Reference Figure 1 As shown, a method for optimizing the gravure printing process of RFID electronic tags, the optimization steps are:
[0032] S1. Optimize printing plate parameters. Establish a simulation model in the computer. Based on historical printing data, train and optimize the simulation model to determine the best printing parameters in the historical data. Input the current electronic label data to be printed into the simulation model, and output the optimal screen line number, mesh depth and cell shape of the gravure printing cylinder.
[0033] S2, process parameter adjustment, based on the real-time acquisition of parameter data in printing by sensors, upload, build a comparison database, obtain the optimal printing process parameter range threshold of different electronic labels based on big data, compare the collected data with the threshold, and adjust the printing process parameters if it is greater than the threshold range, including the tension of the winding and unwinding, the pressure of the printing rubber embossing roller, and the thixotropic viscosity of the slurry;
[0034] S3, positioning overprinting technology, using positioning overprinting technology to accurately align the pattern of the RFID electronic tag antenna;
[0035] S4, ink mixing and adjustment, based on the automatic ink mixing module, mix the ink according to the formula ratio, and combine with the color measuring instrument to detect the difference between the mixed ink color and the target color in real time, and make adjustments and optimizations;
[0036] S5. Real-time monitoring of the printing process: The printing process is monitored in real time based on a camera, and the monitored data is stored as historical data for subsequent analysis.
[0037] This application establishes a simulation model in a computer and performs training and optimization based on a large amount of historical printing data, which can fully explore the hidden rules and optimal parameter combinations in past printing practices; it no longer relies on traditional empirical judgment or blind trial and error to determine the printing plate parameters, but obtains the optimal parameters based on a data-driven simulation model. In this way, in the printing process of different batches of electronic labels, as long as the corresponding accurate data is input, high-quality printing effects can be stably reproduced, reducing printing quality fluctuations caused by human factors or accidental factors, and ensuring the consistency of product quality;
[0038] Sensors are used to obtain various parameter data in real time during printing, and compared with the optimal printing process parameter range threshold obtained by big data analysis, so as to timely detect abnormal changes in parameters during the printing process;
[0039] In tasks such as RFID tag antenna pattern printing, which requires extremely high position accuracy, the antenna pattern is accurately aligned to ensure that multi-layer patterns, patterns of different colors or patterns printed in different processes are accurately overlapped, avoiding ghosting and misalignment problems caused by inaccurate overprinting, so that the integrity and accuracy of the antenna pattern are guaranteed;
[0040] The automatic ink mixing module mixes ink according to the formula ratio, and uses a color measuring instrument to detect the difference between the mixed ink color and the target color in real time for adjustment and optimization, ensuring that the mixed ink color is highly consistent with the design requirements.
[0041] The historical printing data in step S1 includes the characteristics of different types of printing materials, various parameters of inks, environmental conditions during printing, and historical printing parameter combinations. Through data analysis technology, the historical printing data is input into the model, allowing the model to learn and analyze the printing effects presented under different printing parameter combinations. Based on the analysis results, the model is repeatedly adjusted and optimized so that the model can determine the printing parameters that achieve the best printing effect from the historical data; after the training is completed, the current electronic label data to be printed is input into it, and the electronic label includes its own material, size and purpose. The simulation model is based on the learning rules and, through simulation analysis, finally outputs the optimal screen line count, mesh depth and mesh shape for the gravure printing roller in this electronic label printing task.
[0042] The historical printing data of this application covers various information such as the characteristics of different types of printing materials, various parameters of inks, environmental conditions during printing, and historical combinations of printing parameters. With the help of data analysis technology, the model can learn the printing effects presented under different parameter combinations in a large amount of historical printing data. Based on the analysis results, the model is repeatedly adjusted and optimized, so that the model can grasp the internal laws of achieving the best printing effect under different conditions, and then continuously optimize the optimal parameters of its own output.
[0043] The model training uses the defined loss function J(θ) to measure the difference between the printing effect of the simulated model and the actual historical printing effect, and uses the mean square error for training. The training formula is:
[0044]
[0045] Where J(θ) is the loss function, d i is the data of the i-th record in the historical data, n is the number of historical data, f M is the prediction function of model M, θ is the internal parameter, r i is the corresponding printing effect evaluation index; initialize the model parameter θ, update it in each iteration t, and update the model parameter. The expression is:
[0046] θ t+1 =θ t -α·▽ θ J(θ)
[0047] The above updating process is repeated until the stopping condition is met. The stopping condition is that the preset number of iterations T and the value of the loss function J(θ) converge to the minimum.
[0048] Input the data into the trained model, analyze it and output the printing plate parameters.
[0049] In this application, since the printing plate parameters output by the model are obtained through training and optimization based on a large amount of historical data, these parameters can ensure that the printing effect reaches the best state to the greatest extent. The knowledge accumulated and learned about the relationship between printing plate parameters and printing effects during the model training process is effectively integrated into the model, which realizes the precipitation and inheritance of printing process experience.
[0050] In step S2, sensors are distributed on the printing equipment, including at the ink delivery pipeline, on the printing roller and on the reel-up and unreel device. The sensors obtain parameter data during printing, transmit it wirelessly, and build a database. By accumulating data in printing through electronic tags of different types and specifications in big data, the optimal printing process parameter range threshold for different electronic tags is obtained. The data collected by the sensor in real time is compared with the optimal printing process parameter range threshold. When it is greater than the threshold, the printing parameters are adjusted.
[0051] This application realizes all-round and multi-dimensional parameter data collection of the printing process, compares the data collected by the sensor in real time with the threshold of the optimal printing process parameter range, and can detect in real time during the printing process whether the parameters deviate from the optimal range, and promptly detect potential quality risks. By real-time monitoring and precise adjustment of printing process parameters, it can avoid ink waste and printing material scrapping due to improper parameter settings. Waste of resources.
[0052] The tension of the reel is adjusted by controlling the speed of the motor and the tightness of the tension adjustment device; the pressure of the printing rubber embossing roller is adjusted by changing the downward pressure of the embossing roller through the pressure adjustment mechanism to return the pressure to the optimal range; the thixotropic viscosity of the slurry is adjusted by adding diluent.
[0053] The present application adjusts the tension of the reel by controlling the speed of the motor and the tightness of the tension adjustment device, which can ensure that the printed material is transported smoothly and evenly throughout the printing process. Accurate tension adjustment can prevent excessive stretching of the printed material due to excessive tension, and avoid damage, deformation or even breakage of the material. The downward pressure of the printing rubber embossing roller is changed by the pressure adjustment mechanism, and the pressure is controlled within the optimal range, which can ensure that the ink is accurately and evenly transferred from the printing plate to the printing material. The thixotropic viscosity of the slurry plays a key role in the performance of the ink during the printing process. By adding a diluent to adjust its thixotropic viscosity, the ink can be better adapted to the specific printing process requirements.
[0054] The positioning overprinting technology in step S3 is implemented based on the positioning system. A positioning device is provided on the printing equipment. The positioning device includes a sensor and a control system. The sensor is used to monitor the position and movement status of the printing substrate in real time, and transmit the collected data to the control system. The control system adjusts the position and movement of the printing components based on the data, so that each printing operation is at the correct position.
[0055] During the printing process of the present application, the positioning overprinting technology can monitor the position and movement status of the printing substrate in real time through sensors, and accurately control the position and movement of the printing components with the help of a control system, thereby ensuring that patterns printed in different colors and different processes can be accurately overlapped.
[0056] The control printing components use mechanical components to physically limit and adjust the position of the printing substrate. The control system receives the information, analyzes and processes it, generates control instructions, and sends them to various execution components of the printing equipment for positioning and overprinting. During the control process, the control system needs to first calculate the deviation value between the printing substrate and the printing equipment, and calculate the distance difference between the two based on the Euclidean distance. The calculation formula is:
[0057]
[0058] Wherein A(b, c) is the calculated distance deviation value between the printing substrate and the printing device, (x2, y2) is the current distance of the printing device, and (x1, y1) is the current distance of the printing substrate. The distance difference between the two is obtained by calculation. The control system controls the movement of the mechanical parts based on the obtained difference data to align the printing device with the printing substrate.
[0059] This application uses the Euclidean distance calculation formula to calculate the distance difference between the printing substrate and the printing equipment, which can accurately measure the deviation of the two in the plane position in a scientific and quantitative way. Based on the precise distance difference calculated, the control system can accurately control the mechanical components to physically limit and adjust the position of the printing substrate, and accurately align the printing equipment with the printing substrate.
[0060] In step S4, the automatic ink mixing module internally stores the ink formula obtained from historical practice, and extracts the corresponding mixing ratio information from it. Each ink storage container is connected to the mixing center through pipes and valves. The module controls the opening and closing degree of each valve and the flow rate of the delivery pump according to the set mixing ratio, and delivers the ink to the mixing container; after the mixing is completed, the color measuring instrument works, the probe emits light, and after receiving the light reflected by the ink, the current ink color parameter values are obtained through data processing, and the measured data is compared and analyzed with the pre-set target color parameters to calculate the difference between the two; after calculating the difference, adjustments and optimizations are made based on the difference data.
[0061] Since this application relies on a standardized and verified ink formula, whether in the printing process of different batches of electronic labels or when different operators are performing mixing operations, as long as the mixing is performed according to the formula ratio stored in the module, the same quality of ink can be stably reproduced, ensuring the consistency of printed colors. This avoids fluctuations in ink formulas due to human factors and experience differences, and further reduces the uneven quality of printed products due to color deviation, which helps to establish a good image of stable and reliable product quality and meet customers' strict requirements for color consistency of printed products.
[0062] In step S5, when the printing process is in progress, the printing process is recorded in real time through the camera to capture the key parameters of each process in the printing process. After the capture is completed, it is stored and the recorded image data and key parameters are classified and sorted in chronological order.
[0063] During the printing process, this application uses a camera to record and capture the key parameters of each process in real time, allowing operators and managers to achieve visual real-time monitoring of the printing process. By reviewing the records of the corresponding time period, they can understand in detail the operating status of the printing equipment when the problem occurred and the specific parameters of each process link, and accurately determine whether the quality defects are caused by equipment failure, improper process parameter settings, raw material problems or other factors. In this way, targeted solutions can be formulated to avoid blind investigations and repeated experiments, quickly solve problems, resume normal production, and reduce downtime and production losses caused by quality problems.
[0064] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention, and these changes and improvements fall within the scope of the present invention claimed.
Claims
1. A method for optimizing the gravure printing process of RFID electronic tags, characterized in that: The optimization steps are: S1. Optimize printing plate parameters. Establish a simulation model in the computer. Based on historical printing data, train and optimize the simulation model to determine the best printing parameters in the historical data. Input the current electronic label data to be printed into the simulation model, and output the optimal screen line number, mesh depth and cell shape of the gravure printing cylinder. S2, process parameter adjustment, based on the real-time acquisition of parameter data in printing by sensors, upload, build a comparison database, obtain the optimal printing process parameter range threshold of different electronic labels based on big data, compare the collected data with the threshold, and adjust the printing process parameters if it is greater than the threshold range, including the tension of the winding and unwinding, the pressure of the printing rubber embossing roller, and the thixotropic viscosity of the slurry; S3, positioning overprinting technology, using positioning overprinting technology to accurately align the pattern of the RFID electronic tag antenna; S4, ink mixing and adjustment, based on the automatic ink mixing module, mix the ink according to the formula ratio, and combine with the color measuring instrument to detect the difference between the mixed ink color and the target color in real time, and make adjustments and optimizations; S5. Real-time monitoring of the printing process: The printing process is monitored in real time based on a camera, and the monitored data is stored as historical data for subsequent analysis.
2. The RFID electronic tag gravure printing process optimization method according to claim 1, characterized in that: The historical printing data in step S1 includes the characteristics of different types of printing materials, various parameters of inks, environmental conditions during printing, and historical printing parameter combinations. Through data analysis technology, the historical printing data is input into the model, allowing the model to learn and analyze the printing effects presented under different printing parameter combinations. Based on the analysis results, the model is repeatedly adjusted and optimized so that the model can determine the printing parameters that achieve the best printing effect from the historical data; after the training is completed, the current electronic label data to be printed is input into it, and the electronic label includes its own material, size and purpose. The simulation model is based on the learning rules and, through simulation analysis, finally outputs the optimal screen line count, mesh depth and mesh shape for the gravure printing roller in this electronic label printing task.
3. The RFID electronic tag gravure printing process optimization method according to claim 2, characterized in that: The model training uses the defined loss function J(θ) to measure the difference between the printing effect of the simulated model and the actual historical printing effect, and uses the mean square error for training. The training formula is: Where J(θ) is the loss function, d i is the data of the i-th record in the historical data, n is the number of historical data, f M is the prediction function of model M, θ is the internal parameter, r i is the corresponding printing effect evaluation index; initialize the model parameter θ, update it in each iteration t, and update the model parameter. The expression is: i t+1 =θ t -a·▽ θ J(θ) The above updating process is repeated until the stopping condition is met. The stopping condition is that the preset number of iterations T and the value of the loss function J(θ) converge to the minimum. Input the data into the trained model, analyze it and output the printing plate parameters.
4. The method for optimizing the gravure printing process of an RFID electronic tag according to claim 1, characterized in that: In step S2, sensors are distributed on the printing equipment, including at the ink delivery pipeline, on the printing cylinder and on the reel-up and unreel device. The sensors obtain parameter data during printing, transmit it wirelessly, and build a database. By accumulating data of electronic tags of different types and specifications in the big data during printing, the optimal printing process parameter range threshold for different electronic tags is obtained; The data collected by the sensor in real time is compared with the threshold of the optimal printing process parameter range. When it is greater than the threshold, the printing parameters are adjusted.
5. The method for optimizing the gravure printing process of an RFID electronic tag according to claim 4, characterized in that: The tension of the reel is adjusted by controlling the speed of the motor and the tightness of the tension adjustment device; the pressure of the printing rubber embossing roller is adjusted by changing the downward pressure of the embossing roller through the pressure adjustment mechanism to return the pressure to the optimal range; the thixotropic viscosity of the slurry is adjusted by adding diluent.
6. The method for optimizing the gravure printing process of an RFID electronic tag according to claim 1, characterized in that: The positioning overprinting technology in step S3 is implemented based on the positioning system. A positioning device is provided on the printing equipment. The positioning device includes a sensor and a control system. The sensor is used to monitor the position and movement status of the printing substrate in real time, and transmit the collected data to the control system. The control system adjusts the position and movement of the printing components based on the data, so that each printing operation is at the correct position.
7. The method for optimizing the gravure printing process of an RFID electronic tag according to claim 6, characterized in that: The control printing components use mechanical components to physically limit and adjust the position of the printing substrate. The control system receives information, analyzes and processes it, generates control instructions, and sends them to various execution components of the printing equipment for positioning and overprinting. During the control process, the control system needs to first calculate the deviation between the printing substrate and the printing equipment, and calculate the distance difference between the two based on the Euclidean distance. The calculation formula is: Wherein A(b, c) is the calculated distance deviation value between the printing substrate and the printing device, (x2, y2) is the current distance of the printing device, and (x1, y1) is the current distance of the printing substrate. The distance difference between the two is obtained by calculation. The control system controls the movement of the mechanical parts based on the obtained difference data to align the printing device with the printing substrate.
8. The method for optimizing the gravure printing process of an RFID electronic tag according to claim 1, characterized in that: In step S4, the automatic ink mixing module internally stores the ink formula obtained from historical practice, from which the corresponding mixing ratio information is extracted. Each ink storage container is connected to the mixing center through pipes and valves. The module controls the opening and closing degree of each valve and the flow rate of the delivery pump according to the set mixing ratio, and delivers the ink to the mixing container.
9. The method for optimizing the gravure printing process of an RFID electronic tag according to claim 8, characterized in that: After the mixing is completed, the color measuring instrument works, the probe emits light, and then receives the light reflected by the ink. Through data processing, the current ink color parameter values are obtained, and the measured data is compared and analyzed with the pre-set target color parameters to calculate the difference between the two. After calculating the difference, adjustments and optimizations are made based on the difference data.
10. The method for optimizing the gravure printing process of an RFID electronic tag according to claim 1, characterized in that: In step S5, when the printing process is in progress, the printing process is recorded in real time through the camera to capture the key parameters of each process in the printing process. After the capture is completed, it is stored and the recorded image data and key parameters are classified and sorted in chronological order.