Method and system for controlling metal deposition in light-transmitting PVD (Physical Vapor Deposition) coating

Abstract

The invention provides a control method and system for metal deposition in light-transmitting PVD coating, and relates to the technical field of strategy optimizing.The control method comprises the steps that plastic part feature information and a target metal deposition effect of a plastic part sample are obtained, and the plastic part sample is a plastic part subjected to light-transmitting PVD coating; acquiring light-transmitting PVD coating process information, wherein the light-transmitting PVD coating process information comprises an initial light-transmitting PVD coating control scheme corresponding to the plastic part feature information; carrying out metal deposition characteristic detection to obtain a detected metal deposition effect; judging whether a target metal deposition effect is met or not; and if not, performing optimization adjustment on the initial light-transmitting PVD coating control scheme to obtain an optimized light-transmitting PVD coating control scheme. The method solves the technical problems that in the prior art, control over the light-transmitting PVD coating process often depends on experience and rules for parameter adjustment, the requirements of different plastic parts for coating process parameters are ignored, the film layer quality cannot stably reach the target effect, and then the product quality is affected.

Description

Technical Field

[0001] The present invention relates to the technical field of strategy optimization, and in particular to a control method and system for metal deposition in light-transmitting PVD coatings. Background Art

[0002] Transparent PVD (physical vapor deposition) coating technology is widely used in surface coatings of materials such as plastics, glass, and metals. The transparent PVD coating process evaporates and deposits metal on the surface of the substrate to form a thin film with excellent functionality and decorative properties. In order to achieve the ideal metal deposition effect, the process parameters need to be precisely adjusted within the control range. However, since the deposition process is affected by multiple variables, process control presents certain challenges. The control of transparent PVD coating processes in the existing technology often relies on experience and rules to adjust parameters. However, different plastic parts or substrate characteristics have different requirements for process parameters, resulting in difficulty in obtaining the best metal deposition effect without precise adjustment. In addition, the strategy optimization of control parameters in the existing technology is relatively simple, mainly relying on trial and error to determine the optimal process parameters, resulting in low production efficiency and the possibility of a large amount of waste and substandard products. Summary of the Invention

[0003] The present application provides a control method and system for metal deposition in translucent PVD coatings, aiming to solve the technical problem in the prior art that the process control of translucent PVD coatings often relies on experience and rules to adjust parameters, ignoring the requirements of different plastic parts for coating process parameters, resulting in the film quality being unable to stably achieve the target effect, thereby affecting product quality.

[0004] The first aspect disclosed in the present application provides a method for controlling metal deposition in a translucent PVD coating, the method comprising: obtaining plastic part characteristic information and a target metal deposition effect of a plastic part sample, wherein the plastic part sample is a plastic part that has undergone translucent PVD coating; obtaining translucent PVD coating process information, wherein the translucent PVD coating process information includes an initial translucent PVD coating control scheme corresponding to the plastic part characteristic information; performing metal deposition characteristic detection on the plastic part sample to obtain a detected metal deposition effect; determining whether the detected metal deposition effect satisfies the target metal deposition effect; if not, optimizing and adjusting the initial translucent PVD coating control scheme based on the target metal deposition effect to obtain an optimized translucent PVD coating control scheme.

[0005] The second aspect disclosed in the present application provides a control system for metal deposition in a light-transmitting PVD coating, the system being used for the above-mentioned method for controlling metal deposition in a light-transmitting PVD coating, the system comprising: a feature information acquisition module for acquiring plastic part feature information and a target metal deposition effect of a plastic part sample, wherein the plastic part sample is a plastic part that has undergone light-transmitting PVD coating; a process information acquisition module for acquiring light-transmitting PVD coating process information, wherein the light-transmitting PVD coating process information includes an initial light-transmitting PVD coating control scheme corresponding to the plastic part feature information; a feature detection module for performing metal deposition feature detection on the plastic part sample to obtain a detected metal deposition effect; an effect judgment module for judging whether the detected metal deposition effect satisfies the target metal deposition effect; and an optimization adjustment module for optimizing the initial light-transmitting PVD coating control scheme based on the target metal deposition effect if the target metal deposition effect is not satisfied, to obtain an optimized light-transmitting PVD coating control scheme.

[0006] One or more technical solutions provided in this application have at least the following beneficial effects:

[0007] By obtaining the plastic part characteristic information and target metal deposition effect of the plastic part sample, accurate input data is provided for subsequent process control. The plastic part characteristic information lays the foundation for formulating a reasonable initial transparent PVD coating control plan, ensuring the pertinence and effectiveness of the coating process; by obtaining the initial transparent PVD coating control plan corresponding to the plastic part characteristic information, it can be ensured that the control plan matches the actual production needs. This matching relationship helps to reduce errors or deviations in the initial process plan, improve the success rate of the preliminary control plan, and provide a reasonable starting point for subsequent metal deposition optimization; by performing metal deposition characteristic detection on plastic part samples, the effect of the metal deposition layer can be comprehensively evaluated. The detection results can reveal the uniformity and surface quality of the deposition layer. This detection provides a direct basis for subsequent judgment on whether the coating control plan needs to be adjusted, thereby providing support for further optimization. By comparing the detected metal deposition effect with the target metal deposition effect, it is possible to quickly determine whether the current process has achieved the expected effect. If the detected effect does not meet the target requirements, the process deficiencies can be discovered in a timely manner, thereby optimizing in a timely manner to avoid unqualified products from entering the next process, effectively ensuring production quality and reducing resource waste in the production process; if the detected metal deposition effect does not meet the target metal deposition effect, the initial translucent PVD coating control scheme is optimized and adjusted to obtain an optimized translucent PVD coating control scheme. This optimization process enables the process parameters to be precisely adjusted according to the target deposition effect, thereby ensuring the quality stability of the coating process. This optimization method helps to obtain consistent and high-quality deposition effects under different production conditions, improve the flexibility and controllability of the production process, and ultimately achieve strategy optimization of the entire process, further improving production efficiency and product quality.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 Schematic diagram of the flow chart of the method for controlling metal deposition in a light-transmitting PVD coating provided in an embodiment of the present application.

[0010] Figure 2 Schematic diagram of the control system structure for metal deposition in a light-transmitting PVD coating provided in an embodiment of the present application.

[0011] Explanation of the accompanying symbols: feature information acquisition module 10, process information acquisition module 20, feature detection module 30, effect judgment module 40, optimization and adjustment module 50. DETAILED DESCRIPTION

[0012] The embodiments of the present application provide a control method and system for metal deposition in a translucent PVD coating, which solves the technical problem in the prior art that the process control of translucent PVD coating often relies on experience and rules to adjust parameters, ignores the requirements of different plastic parts for coating process parameters, resulting in the film layer quality being unable to stably achieve the target effect, thereby affecting product quality.

[0013] After introducing the basic principles of this application, various non-limiting embodiments of this application will be specifically described below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0014] Example 1, as Figure 1 As shown, an embodiment of the present application provides a method for controlling metal deposition in a light-transmitting PVD coating, the method comprising:

[0015] Obtain plastic part characteristic information and target metal deposition effect of a plastic part sample, wherein the plastic part sample is a plastic part that has completed a light-transmitting PVD coating.

[0016] Plastic part samples refer to plastic parts that have undergone a translucent PVD (physical vapor deposition) coating process. PVD technology coats the surface of plastic parts with a thin metal film, typically to increase surface hardness, conductivity, or achieve a specific optical effect. Plastic part feature information includes dimensions, surface smoothness, shape, surface treatment, and substrate material, and can be acquired through testing methods such as laser scanning, 3D imaging, and surface profile analysis. The target metal deposition effect, which includes the control of surface defects and light transmittance of the metal film, is closely related to the functional requirements of the plastic part and can be set based on the intended use of the plastic part.

[0017] Obtaining light-transmitting PVD coating process information, wherein the light-transmitting PVD coating process information includes an initial light-transmitting PVD coating control scheme corresponding to the plastic part characteristic information.

[0018] The core process information of the transparent PVD coating process includes the coating equipment conditions, operating environment, coating materials, deposition time, temperature, pressure, atmosphere and other parameters. All of this information is key to ensuring that the coating quality achieves the expected effect. The initial transparent PVD coating control plan is set before the PVD coating process based on the characteristic information of the plastic parts. The initial transparent PVD coating control plan is set based on historical data, experimental results or theoretical analysis.

[0019] The metal deposition characteristics of the plastic part sample are detected to obtain the metal deposition effect.

[0020] Plastic samples are tested for metal deposition characteristics. Specifically, a scanning electron microscope (SEM) is used to scan and analyze the surface morphology of the plastic sample in detail. This analyzes the surface structure and morphology of the metal layer, identifies existing defects such as bubbles and cracks, and generates a surface defect characteristic evaluation coefficient, which helps determine whether the metal deposition quality meets requirements. A spectrometer is also used to test the light transmittance of the sample and measure the light transmittance characteristics of the metal deposition layer. The light transmittance of the metal layer has a significant impact on the performance of the final product. Based on the obtained light transmittance data, a light transmittance characteristic evaluation coefficient is generated as another important indicator for evaluating the metal deposition effect. The surface defect characteristic evaluation coefficient and light transmittance characteristic evaluation coefficient obtained by the SEM and spectrometer are integrated to form the final metal deposition effect evaluation.

[0021] It is determined whether the detected metal deposition effect meets the target metal deposition effect.

[0022] The target metal deposition effect is preset and formulated according to the functional requirements of the plastic parts, including the control of surface defects and light transmittance of the metal film. The detected metal deposition effect is compared with the preset target metal deposition effect. The comparison process includes analyzing the evaluation coefficients of various aspects such as surface defects and light transmittance. If the target requirements are met, it means that the detected metal deposition effect is in line with expectations and no adjustment is required; if not, optimization and adjustment are required.

[0023] If not, the initial light-transmitting PVD coating control scheme is optimized and adjusted based on the target metal deposition effect to obtain an optimized light-transmitting PVD coating control scheme.

[0024] Based on the judgment results, determine which aspects of the metal deposition effect do not meet the target requirements, such as surface defects, insufficient light transmittance, etc., and combine the target effect with the test results to find out where the gap lies. For example, is it caused by factors such as temperature, pressure or deposition rate during the deposition process? Based on the target metal deposition effect, the initial light-transmitting PVD coating control plan is optimized and adjusted. The adjusted parameters include evaporation rate parameters, substrate temperature parameters, atmosphere pressure parameters, deposition time parameters, bias voltage parameters, sputtering power parameters, and film stress parameters. Using optimization algorithms, such as genetic algorithms and particle swarm optimization, iterative adjustments are made on the basis of the initial light-transmitting PVD coating control plan to achieve the optimal metal deposition effect. During the adjustment process, the metal deposition effect evaluation function is used to evaluate and compare each optimized plan to ensure that each adjustment can make the metal deposition effect closer to the target. After multiple optimization adjustments, the final optimized light-transmitting PVD coating control plan is obtained. This plan can be applied in actual production to ensure that the metal deposition effect meets the requirements and improve the overall coating quality.

[0025] Furthermore, the method of performing metal deposition feature detection on the plastic sample to obtain the metal deposition effect includes:

[0026] The surface morphology of the plastic part sample is detected by a scanning electron microscope to obtain a surface morphology detection result, wherein the surface morphology detection result includes a surface defect characteristic evaluation coefficient; the light transmittance detection result of the plastic part sample is detected by a spectrometer to obtain a light transmittance detection result, wherein the light transmittance detection result includes a light transmittance characteristic evaluation coefficient; the surface defect characteristic evaluation coefficient and the light transmittance characteristic evaluation coefficient are integrated to obtain the detected metal deposition effect.

[0027] Scanning electron microscopes scan the sample surface and use the signal reflected by the electron beam to form a high-resolution image. They can capture details such as surface microstructure, defects, and cracks. They are commonly used to inspect the surface quality of thin films. Specifically, a sample is placed in a scanning electron microscope, where an electron beam scans the sample surface in a vacuum environment. Scanning electron microscope image analysis identifies surface defects in the metal layer, such as bubbles, cracks, and uneven particle distribution. The surface defect characteristic evaluation coefficient is used to describe the severity of surface defects in metal deposits. Evaluation indicators include defect density, defect type, and defect size.

[0028] Spectrometers evaluate a sample's light transmittance by analyzing the wavelength and intensity of light reflected, transmitted, or scattered by the sample. For plastic samples coated with translucent PVD coatings, light transmittance is a crucial performance indicator, impacting the visual quality of the final product. Specifically, a spectrometer is aimed at a metal-deposited plastic sample, using a light source within a specific wavelength range. Transmittance data is obtained by measuring the transmittance of light passing through the metal film layer. The light transmittance characteristic evaluation coefficient is used to quantify the light transmittance of the deposited metal layer. Evaluation indicators include transmittance, transmittance range, and optical clarity.

[0029] The integrated surface defect characteristic evaluation coefficient and light transmittance characteristic evaluation coefficient can be assigned different weights to each characteristic according to the impact of different parameters on the overall deposition effect. For example, if light transmittance is more critical than surface defects, then the light transmittance characteristic evaluation coefficient can be assigned a higher weight. The integration formula can use the weighted average method or the multivariate analysis method to generate a comprehensive detection metal deposition effect through the integrated evaluation coefficient. This result is used to guide subsequent process adjustments to ensure that the metal deposition effect reaches the predetermined goal.

[0030] Furthermore, the method comprises:

[0031] The surface morphology of the plastic part sample is detected by a scanning electron microscope to generate a surface morphology detection data set, wherein the surface morphology detection data set includes defect morphology type, defect size, defect distribution, surface flatness, and surface smoothness; based on the surface morphology detection data set, the surface defect feature evaluation coefficient is output.

[0032] The surface of the plastic sample is scanned by a scanning electron microscope, and detailed image data is obtained. Specifically, the surface of the plastic sample is ensured to be clean and all contaminants that affect the measurement results are removed. Solvent cleaning, ultrasonic cleaning and other methods are usually used to clean the surface. According to the characteristics and needs of the film layer, the appropriate electron beam energy is selected, such as 5-10kV, to ensure the best image resolution. Through high-resolution scanning, an electron microscopic image of the surface of the plastic sample is generated. The electron microscopic image provides detailed morphology of the film layer, including surface defects, particles, microcracks, bubbles and other information. Image analysis software is used to process and analyze the collected electron microscopic images. Specifically, image recognition algorithms are used to identify various defect types, such as particles, bubbles, cracks, and holes. Defect sizes, such as diameter and aspect ratio, are measured, and the size of each defect is recorded. This data helps understand the uniformity and quality of the film. The distribution of defects on the film surface is analyzed, and by statistically analyzing the spatial locations of defects in the image, the distribution characteristics of the defects, such as whether they are uniform or concentrated, are derived. Surface profile analysis methods are used to assess the flatness of the film surface. For example, by measuring the height difference of the film surface, the presence of large fluctuations on the surface can be determined. Smoothness is assessed by quantifying the roughness of the film surface. Commonly used surface roughness parameters include Ra value (average roughness) and Rz value (maximum height difference). Ultimately, the electron microscopic images and the above analysis results form a surface topography detection dataset, which includes defect morphology type, defect size, defect distribution, surface flatness, and surface smoothness.

[0033] Quantitative analysis is performed based on defect information extracted from electron microscopic images. For example, a weight is assigned to each defect type based on defect size and distribution, generating scores for different defect types. For different types of defects, such as cracks and bubbles, severity weights are assigned based on their impact on film performance. Generally, cracks and holes have a greater impact, while bubbles and particles have a relatively smaller impact. For example, by calculating parameters such as the standard deviation of the film surface height variation, surface flatness can be quantified. Films with large height differences indicate uneven deposition, resulting in unstable film performance. Roughness analysis can be used to evaluate the smoothness of the film surface. Higher roughness values ​​generally indicate irregularities on the surface, which can affect the adhesion and durability of the film.

[0034] Combining factors such as defect morphology, size, distribution, surface flatness and smoothness, a comprehensive surface defect characteristic evaluation coefficient is generated through weighted summation or other statistical methods. The surface defect characteristic evaluation coefficient is output as a quantitative indicator, reflecting the surface quality of the film layer. The lower the value, the fewer surface defects it indicates and the better the film quality.

[0035] Furthermore, the method comprises:

[0036] Perform a light-transmitting PVD coating record retrieval to obtain multiple historical light-transmitting PVD coating control records, wherein the multiple historical light-transmitting PVD coating control records include multiple historical light-transmitting PVD coating control schemes corresponding to multiple historical plastic part feature information; based on the plastic part feature information, traverse the multiple historical plastic part feature information, perform feature similarity calculation, and extract the historical light-transmitting PVD coating control scheme corresponding to the historical plastic part feature information with the highest feature similarity as the initial light-transmitting PVD coating control scheme.

[0037] Using a database or storage system to retrieve translucent PVD coating records, multiple historical translucent PVD coating control records are obtained to provide a reference for metal deposition on current plastic parts. Historical records can provide past successful process parameters and results, which can serve as a basis for subsequent process optimization and adjustment. During the PVD coating process, each plastic part has corresponding characteristics, such as size, shape, material type, etc. This characteristic information can be obtained through physical measurement, 3D modeling, or other analytical techniques. The historical translucent PVD coating control plan includes the coating process parameters used for each plastic part, such as evaporation rate, substrate temperature, atmosphere pressure, deposition time, etc. These parameters determine the quality and effect of metal deposition.

[0038] By calculating the similarity between the current plastic part feature information and the historical plastic part feature information, the most similar historical record is selected as the basis for the initial control plan. Similar plastic part features usually correspond to similar coating control plans, thereby improving the success rate and shortening the adjustment time. Similarity calculation methods such as Euclidean distance, cosine similarity, Manhattan distance, etc. are used to calculate the similarity between the current plastic part feature information and each historical plastic part feature information. Based on the calculation results, the historical record most similar to the current plastic part feature information is selected. The record with the highest feature similarity usually indicates that its coating effect is most consistent with the current requirements. Therefore, the corresponding historical coating control plan can be used as the initial control plan. The control plan most similar to the current plastic part in the historical record is extracted as the current initial translucent PVD coating control plan. This plan will serve as a starting point to help accelerate subsequent optimization adjustments.

[0039] Furthermore, the method for optimizing and adjusting the initial light-transmitting PVD coating control scheme based on the target metal deposition effect includes:

[0040] Based on the multivariate coating control parameter index of the translucent PVD coating, the multivariate coating control interval analysis is performed on the multiple historical translucent PVD coating control schemes to establish a multivariate coating control interval; the multivariate coating control interval is used as a spatial constraint condition to optimize the initial translucent PVD coating control scheme.

[0041] In the process of transparent PVD coating, the key factors affecting the metal deposition effect include multiple process parameters, such as evaporation rate, substrate temperature, atmosphere pressure, deposition time, bias voltage, sputtering power, film stress, etc. All these process parameters work together to determine the quality and effect of the coating. By analyzing multiple historical transparent PVD coating control schemes, the reasonable range of each parameter in the historical coating records is found. Through these historical data, the working range of each process parameter can be determined. For example, through experimental data or regression analysis, the relationship between each parameter and the metal deposition effect is established. For each control parameter, its influence range on the metal deposition effect is obtained. By analyzing the interval of each control parameter, the optimal working range of multiple control parameters is obtained. Each parameter will have a corresponding value range. Through these single parameter intervals, combined with multi-dimensional data analysis, a multi-element coating control interval is established to ensure that the metal deposition effect can be optimized when the various process parameters are combined within these ranges.

[0042] Taking the multivariate coating control interval as a spatial constraint means that in the subsequent optimization process, the values ​​of all process parameters must be adjusted within these preset intervals. The optimization goals include maximizing the quality of the metal film, minimizing film defects, and improving the uniformity of the film layer. The optimization process hopes to find a set of optimal process parameters within the control interval so that the final coating effect reaches or approaches the target metal deposition effect. Numerical optimization methods such as genetic algorithms, particle swarm optimization, simulated annealing, and gradient descent are used for adjustment. These methods can find the optimal solution in multidimensional space while ensuring that the value of each control parameter is within a predetermined interval. Through iterative optimization, the values ​​of each process parameter are continuously adjusted so that they gradually approach the optimal combination within the control interval. In each iteration, the coating process is simulated or experimentally verified based on the current parameter settings, and the metal deposition effect evaluation index is calculated. After each round of iteration, the evaluation results of the current parameter combination are compared with the target metal deposition effect, and the parameters are adjusted again until an optimal light-transmitting PVD coating control solution that meets the target requirements is found.

[0043] Furthermore, the multi-element coating control parameter index includes an evaporation rate parameter, a substrate temperature parameter, an atmosphere pressure parameter, a deposition time parameter, a bias voltage parameter, a sputtering power parameter, and a film stress parameter.

[0044] The evaporation rate refers to the mass or number of atoms evaporated per second from the metal evaporation source material. The evaporation rate directly affects the deposition speed of the metal layer and the quality of the film. A too high evaporation rate may cause metal particles to excessively impact the substrate surface, forming a rough film and increasing film defects. A too low evaporation rate may result in a slow deposition rate, affecting production efficiency and causing uneven deposition. The substrate temperature refers to the temperature of the plastic substrate surface during the coating process. Temperature has a significant impact on the deposition process, diffusion behavior of metal particles, and the structure of the film. Excessive temperature may lead to a loose film structure or weak adhesion of the metal film, affecting the adhesion and hardness of the film. Excessive temperature may lead to insufficient deposition of metal particles, forming a film with poor density and uneven structure. The atmosphere pressure refers to the gas pressure used in the PVD coating process. The atmosphere pressure affects the diffusion behavior of metal vapor during the deposition process. At low pressure, metal vapor can freely deposit on the substrate surface, forming a dense film. At high pressure, metal vapor molecules will collide with gas molecules, affecting the deposition rate and film quality. High pressure may cause defects such as pores and voids in the metal film; deposition time refers to the length of time the metal film is deposited on the surface of the substrate. Deposition time directly determines the thickness of the film. Longer deposition time will make the metal layer thicker and may increase the strength of the film, but too long a time may also cause film defects, such as increased brittleness. Too short a deposition time may result in insufficient film thickness, affecting its functionality and stability; bias voltage refers to the voltage applied between the substrate and the target during the PVD coating process. This voltage controls the structure, quality and adhesion of the film. Increasing the bias voltage can change the energy of metal particles during the deposition process and affect the structure of the film. For example, it can improve the density of the film by promoting the rearrangement of metal atoms on the substrate surface. Excessive bias voltage may cause arc instability, metal sputtering and other phenomena, thereby affecting the quality of the film; sputtering power refers to the voltage applied to the target during the sputtering deposition process. The power of the target material determines the generation rate and energy of metal sputtering particles. When the sputtering power is high, the sputtering process is more intense and the generated metal particles have higher energy, which helps to improve the quality and strength of the film. However, too high power may cause the sputtering to be too intense, which may cause damage to the surface of the substrate or uneven film. Film stress refers to the mechanical stress between the inside of the film and the interface of the substrate. This stress mainly comes from factors such as temperature changes during the deposition process, expansion or contraction of the film. Films with smaller internal stress usually have better adhesion and stability, and can prevent the film from peeling or cracking. Films with larger internal stress may cause cracks, peeling and other problems in the film, especially when the thermal expansion coefficient of the film and the substrate are significantly different.

[0045] Furthermore, the method for optimizing and adjusting the initial light-transmitting PVD coating control scheme based on the target metal deposition effect includes:

[0046] Based on the target metal deposition effect, metal deposition effect evaluation indicators are extracted to obtain multiple metal deposition effect evaluation indicators; based on the multiple metal deposition effect evaluation indicators, function fitting is performed to generate a metal deposition effect evaluation function; within the multivariate coating control range, the initial transparent PVD coating control scheme is subjected to parameter iterative optimization, and after each round of iteration, with the target metal deposition effect as the target, the metal deposition effect evaluation and parameter optimization comparison are performed through the metal deposition effect evaluation function to determine the optimized transparent PVD coating control scheme.

[0047] Metal deposition effect evaluation indicators are multiple parameters used to quantify and evaluate the quality of metal deposition. Exemplary metal deposition effect evaluation indicators include: surface defects, which are used to evaluate the number or area of ​​defects such as flaws, bubbles, and cracks on the surface of the film layer; film density, which is used to evaluate the density of the film layer and measure the uniformity of the distribution of metal particles on the surface of the substrate; film adhesion, which is used to evaluate the adhesion strength between the film layer and the substrate; optical transmittance, which is used to evaluate the transmittance of the film layer, usually for application scenarios with transparent or translucent substrates; film stress, which is used to evaluate the stress state inside the film layer. Excessive stress may cause the film layer to crack or peel off.

[0048] The values ​​of the above metal deposition effect evaluation indicators are extracted through experiments, simulations or data analysis. The extraction of evaluation indicators is usually based on experimental measurement results. For example, the specific values ​​of each parameter are obtained by using laser rangefinders, scanning electron microscopes, spectrometers and other equipment for detection. Multiple metal deposition effect evaluation indicators are obtained and used as the basis for the subsequent optimization process.

[0049] Mathematical modeling and fitting are performed based on the multiple metal deposition effect evaluation indicators obtained. That is, the relationship between the multiple evaluation indicators is converted into a mathematical formula to generate a metal deposition effect evaluation function. This function can help predict the metal deposition effect when given coating control parameters. For example, each metal deposition effect evaluation indicator is weighted according to specific usage requirements, and the multiple metal deposition effect evaluation indicators are weighted and summed according to the weight distribution results. Based on this calculation process, the metal deposition effect evaluation function is generated. The generated metal deposition effect evaluation function can predict the effect of new parameter combinations based on the known multiple evaluation indicators and control parameters.

[0050] The multivariate coating control interval represents the possible value range of each control parameter, such as the optimal working range of evaporation rate, substrate temperature, deposition time, etc. These intervals provide constraints for parameter optimization, ensuring that all control parameters are adjusted within a reasonable range. Through the optimization algorithm, the various parameters in the initial translucent PVD coating control scheme are continuously adjusted until a set of optimal parameter combinations that can maximize the target metal deposition effect is found. In each round of iteration, by adjusting control parameters such as evaporation rate, substrate temperature, etc., the metal deposition effect evaluation function is used to predict the metal deposition effect of the current parameter combination. The metal deposition effect evaluation function will return the deposition effect index under the current parameter setting. The optimization algorithm determines whether the parameters need to be adjusted based on these indicators, and continues to iterate until the optimal solution is found. Finally, an optimized translucent PVD coating control scheme is determined. This scheme can maximize the target metal deposition effect, thereby ensuring the quality and uniformity of the coating.

[0051] Furthermore, before performing parameter iterative optimization on the initial light-transmitting PVD coating control scheme, the method includes:

[0052] Perform a retrieval of translucent PVD coating defect records to obtain multiple historical translucent PVD coating defect records; perform defect analysis on the multiple historical translucent PVD coating defect records to obtain multiple coating defect factors and multiple coating control parameters corresponding to the multiple coating defect factors; establish a list of coating defects and control parameters based on the mapping relationship between the multiple coating defect factors and the multiple coating control parameters; and perform parameter iterative optimization of the initial translucent PVD coating control scheme using the list of coating defects and control parameters as a guide.

[0053] Retrieve defect records for transparent PVD coatings. Historical defect records contain information such as the type, number, and location of film defects that occurred under different process parameters. This can help identify the cause of the problem and provide a reference for current process adjustments. Use existing historical coating defect data or extract all relevant defect records from past production data, specifically the coating process parameters and defect types in the records. These records include defect information under different coating parameters, such as cracks, bubbles, uneven film layers, and peeling. Retrieve multiple historical transparent PVD coating defect records.

[0054] Defect analysis was performed on multiple historical translucent PVD coating defect records to identify the main coating defect factors that affect metal deposition quality. For example, temperatures that are too high or too low can lead to poor or uneven film adhesion; changes in air pressure can affect the movement path of metal particles, leading to film defects such as bubbles or uneven deposition; deposition times that are too long or too short can cause the film to be too thick or too thin, affecting its performance; sputtering power that is too high or too low can lead to poor or uneven film adhesion; and an evaporation rate that is too fast can cause excessive particle impact, resulting in increased film roughness. For each coating defect factor, its relationship with different coating control parameters was analyzed. Through multiple experiments and data analysis, it was determined which coating control parameter changes may lead to which types of film defects. Through defect analysis, multiple coating defect factors and their corresponding coating control parameters were obtained. The relationship between these factors and the corresponding coating control parameters will provide guidance for subsequent optimization.

[0055] A mapping relationship is established between each coating defect factor and the corresponding coating control parameter. This mapping relationship helps understand how different process parameters affect the quality and performance of the metal film and provides clear adjustment directions. By analyzing historical defect records, the relationship between each coating defect factor and the coating control parameter is statistically analyzed. For example, regression analysis, correlation analysis, and other methods are used to determine which coating control parameters have the greatest impact on specific coating defect factors. A mapping list of coating defects and control parameters is created. Each coating defect factor corresponds to one or more possible coating control parameters. Through this mapping relationship, a list of coating defects and control parameters is formed, which provides a basis for subsequent parameter adjustments.

[0056] Based on the list of coating defects and control parameters, the initial transparent PVD coating control scheme is optimized through parameter iterative optimization. This process aims to avoid the occurrence of historical defects and improve the quality of the film layer. Specifically, according to the mapping relationship between coating defects and control parameters, the process parameters that may cause defects in the initial transparent PVD coating control scheme are identified and adjusted. For example, if a certain control parameter is related to film cracks, the parameter value can be adjusted based on the list suggestions. By adjusting the process parameters through multiple iterations, the optimal control scheme is gradually approached. In each round of iteration, the metal deposition effect after the current adjustment is evaluated, and new defects are avoided through defect analysis. After multiple rounds of iteration, an optimal transparent PVD coating control scheme is determined.

[0057] Furthermore, the method comprises:

[0058] Based on the optimized light-transmitting PVD coating control scheme, sampling re-inspection is performed to obtain a re-inspected metal deposition effect; if the re-inspected metal deposition effect still does not meet the target metal deposition effect, feedback optimization of the optimized light-transmitting PVD coating control scheme is performed.

[0059] The purpose of sampling re-inspection is to verify the optimized light-transmitting PVD coating control plan and ensure that the plan can achieve the expected metal deposition effect in actual production. A certain number of samples are selected, coated according to the optimized light-transmitting PVD coating control plan, and these samples are tested to confirm whether the optimized plan can continue to maintain the expected coating quality. The metal deposition effect of the re-inspected samples is tested, including the surface quality and optical properties of the film layer, to obtain the re-inspected metal deposition effect.

[0060] The retested metal deposition results are compared with the target metal deposition results to check for any deviations. If the retest results meet the target requirements, the effectiveness of the optimization plan is confirmed; if the target effect is still not achieved, further feedback optimization is required. In actual production, even if the initial control plan is optimized through historical data and experiments, the actual retest results may still vary. These differences can be caused by a variety of factors, such as changes in the production environment, fluctuations in equipment accuracy, or differences in raw materials. All problems and deficiencies encountered during the retest are analyzed to identify the reasons for the substandard metal deposition effect. For example, it may be that a parameter such as substrate temperature, atmosphere pressure, sputtering power, etc. is not functioning as expected, resulting in a large number of surface defects in the film layer. Based on the analysis results, the relevant process parameters are gradually adjusted. For example, if surface defects appear, the substrate temperature or atmosphere pressure needs to be adjusted. Optimization algorithms are then used to perform feedback optimization within the control parameter range. These algorithms can automatically adjust the combination of multiple parameters to find the most suitable process solution. Feedback optimization is an iterative process. After each adjustment, retest is required and compared with the target effect. Optimization continues until the coating effect fully meets the target requirements.

[0061] In summary, the method for controlling metal deposition in a transparent PVD coating provided by the embodiments of the present application has the following technical effects:

[0062] By obtaining the plastic part characteristic information and target metal deposition effect of the plastic part sample, accurate input data is provided for subsequent process control. The plastic part characteristic information lays the foundation for formulating a reasonable initial light-transmitting PVD coating control plan, ensuring the pertinence and effectiveness of the coating process; by obtaining the initial light-transmitting PVD coating control plan corresponding to the plastic part characteristic information, it can be ensured that the control plan matches the actual production needs. This matching relationship helps to reduce errors or deviations in the initial process plan, improve the success rate of the preliminary control plan, and provide a reasonable starting point for subsequent metal deposition optimization; by performing metal deposition characteristic detection on plastic part samples, the effect of the metal deposition layer can be comprehensively evaluated. The detection results can reveal the uniformity and surface quality of the deposition layer. This detection provides a direct basis for subsequent judgment on whether the coating control plan needs to be adjusted. By comparing the detected metal deposition effect with the target metal deposition effect, it is possible to quickly determine whether the current process has achieved the expected effect. If the detected effect does not meet the target requirements, the process deficiencies can be discovered in a timely manner, thereby optimizing in a timely manner to avoid unqualified products from entering the next step, effectively ensuring production quality and reducing resource waste in the production process. If the detected metal deposition effect does not meet the target metal deposition effect, the initial transparent PVD coating control scheme is optimized and adjusted to obtain an optimized transparent PVD coating control scheme. This optimization process enables the process parameters to be precisely adjusted according to the target deposition effect, thereby ensuring the quality stability of the coating process. This optimization method helps to obtain consistent and high-quality deposition effects under different production conditions, thereby improving the flexibility and controllability of the production process.

[0063] The second embodiment is based on the same inventive concept as the control method of metal deposition in the transparent PVD coating in the above embodiment. Figure 2 As shown, an embodiment of the present application provides a control system for metal deposition in a light-transmitting PVD coating, the system comprising:

[0064] The characteristic information acquisition module 10 is used to obtain characteristic information of a plastic part and a target metal deposition effect of a plastic part sample, wherein the plastic part sample is a plastic part that has undergone a light-transmitting PVD coating.

[0065] The process information acquisition module 20 is used to acquire the light-transmitting PVD coating process information, wherein the light-transmitting PVD coating process information includes an initial light-transmitting PVD coating control scheme corresponding to the plastic part characteristic information.

[0066] The feature detection module 30 is used to perform metal deposition feature detection on the plastic part sample to obtain a metal deposition effect.

[0067] The effect judgment module 40 is used to judge whether the detected metal deposition effect meets the target metal deposition effect.

[0068] The optimization adjustment module 50 is used to optimize and adjust the initial light-transmitting PVD coating control scheme based on the target metal deposition effect if the conditions are not met, so as to obtain an optimized light-transmitting PVD coating control scheme.

[0069] Furthermore, the feature detection module 30 is configured to perform the following steps:

[0070] The surface morphology of the plastic part sample is detected by a scanning electron microscope to obtain a surface morphology detection result, wherein the surface morphology detection result includes a surface defect characteristic evaluation coefficient; the light transmittance detection result of the plastic part sample is detected by a spectrometer to obtain a light transmittance detection result, wherein the light transmittance detection result includes a light transmittance characteristic evaluation coefficient; the surface defect characteristic evaluation coefficient and the light transmittance characteristic evaluation coefficient are integrated to obtain the detected metal deposition effect.

[0071] Furthermore, the feature detection module 30 is configured to perform the following steps:

[0072] The surface morphology of the plastic part sample is detected by a scanning electron microscope to generate a surface morphology detection data set, wherein the surface morphology detection data set includes defect morphology type, defect size, defect distribution, surface flatness, and surface smoothness; based on the surface morphology detection data set, the surface defect feature evaluation coefficient is output.

[0073] Furthermore, the process information acquisition module 20 is configured to perform the following steps:

[0074] Perform a light-transmitting PVD coating record retrieval to obtain multiple historical light-transmitting PVD coating control records, wherein the multiple historical light-transmitting PVD coating control records include multiple historical light-transmitting PVD coating control schemes corresponding to multiple historical plastic part feature information; based on the plastic part feature information, traverse the multiple historical plastic part feature information, perform feature similarity calculation, and extract the historical light-transmitting PVD coating control scheme corresponding to the historical plastic part feature information with the highest feature similarity as the initial light-transmitting PVD coating control scheme.

[0075] Furthermore, the optimization and adjustment module 50 is configured to perform the following steps:

[0076] Based on the multivariate coating control parameter index of the translucent PVD coating, the multivariate coating control interval analysis is performed on the multiple historical translucent PVD coating control schemes to establish a multivariate coating control interval; the multivariate coating control interval is used as a spatial constraint condition to optimize the initial translucent PVD coating control scheme.

[0077] Furthermore, the multi-element coating control parameter index includes an evaporation rate parameter, a substrate temperature parameter, an atmosphere pressure parameter, a deposition time parameter, a bias voltage parameter, a sputtering power parameter, and a film stress parameter.

[0078] Furthermore, the optimization and adjustment module 50 is configured to perform the following steps:

[0079] Based on the target metal deposition effect, metal deposition effect evaluation indicators are extracted to obtain multiple metal deposition effect evaluation indicators; based on the multiple metal deposition effect evaluation indicators, function fitting is performed to generate a metal deposition effect evaluation function; within the multivariate coating control range, the initial transparent PVD coating control scheme is subjected to parameter iterative optimization, and after each round of iteration, with the target metal deposition effect as the target, the metal deposition effect evaluation and parameter optimization comparison are performed through the metal deposition effect evaluation function to determine the optimized transparent PVD coating control scheme.

[0080] Furthermore, the optimization and adjustment module 50 is configured to perform the following steps:

[0081] Perform a retrieval of translucent PVD coating defect records to obtain multiple historical translucent PVD coating defect records; perform defect analysis on the multiple historical translucent PVD coating defect records to obtain multiple coating defect factors and multiple coating control parameters corresponding to the multiple coating defect factors; establish a list of coating defects and control parameters based on the mapping relationship between the multiple coating defect factors and the multiple coating control parameters; and perform parameter iterative optimization of the initial translucent PVD coating control scheme using the list of coating defects and control parameters as a guide.

[0082] Furthermore, the system further includes a feedback optimization module for performing the following steps:

[0083] Based on the optimized light-transmitting PVD coating control scheme, sampling re-inspection is performed to obtain a re-inspected metal deposition effect; if the re-inspected metal deposition effect still does not meet the target metal deposition effect, feedback optimization of the optimized light-transmitting PVD coating control scheme is performed.

[0084] Through the detailed description of the control method for metal deposition in light-transmitting PVD coatings mentioned above in this specification, those skilled in the art can clearly understand the control system for metal deposition in light-transmitting PVD coatings in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0085] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling metal deposition in a transparent PVD coating, characterized in that: The method comprises: Obtaining plastic part characteristic information and target metal deposition effect of a plastic part sample, wherein the plastic part sample is a plastic part that has undergone light-transmitting PVD coating; Acquiring light-transmitting PVD coating process information, wherein the light-transmitting PVD coating process information includes an initial light-transmitting PVD coating control scheme corresponding to the plastic part characteristic information; Performing metal deposition feature detection on the plastic part sample to obtain a metal deposition detection effect; Determining whether the detected metal deposition effect meets the target metal deposition effect; If not, the initial light-transmitting PVD coating control scheme is optimized and adjusted based on the target metal deposition effect to obtain an optimized light-transmitting PVD coating control scheme.

2. The method for controlling metal deposition in a transparent PVD coating according to claim 1, wherein: The method of performing metal deposition feature detection on the plastic part sample to obtain the metal deposition effect includes: Performing surface morphology detection on the plastic part sample by scanning electron microscopy to obtain a surface morphology detection result, wherein the surface morphology detection result includes a surface defect characteristic evaluation coefficient; Performing a light transmittance test on the plastic sample using a spectrometer to obtain a light transmittance test result, wherein the light transmittance test result includes a light transmittance characteristic evaluation coefficient; The surface defect characteristic evaluation coefficient and the light transmittance characteristic evaluation coefficient are integrated to obtain the metal deposition detection effect.

3. The method for controlling metal deposition in a transparent PVD coating according to claim 2, wherein: The method comprises: Performing surface morphology detection on the plastic part sample by scanning electron microscopy to generate a surface morphology detection data set, wherein the surface morphology detection data set includes defect morphology type, defect size, defect distribution, surface flatness, and surface smoothness; The surface defect feature evaluation coefficient is outputted based on the surface morphology detection data set.

4. The method for controlling metal deposition in a transparent PVD coating according to claim 1, wherein: The method comprises: Performing a light-transmitting PVD coating record search to obtain a plurality of historical light-transmitting PVD coating control records, wherein the plurality of historical light-transmitting PVD coating control records include a plurality of historical light-transmitting PVD coating control schemes corresponding to a plurality of historical plastic part feature information; Based on the plastic part feature information, the plurality of historical plastic part feature information are traversed to perform feature similarity calculation, and the historical transparent PVD coating control scheme corresponding to the historical plastic part feature information with the highest feature similarity is extracted as the initial transparent PVD coating control scheme.

5. The method for controlling metal deposition in a light-transmitting PVD coating according to claim 4, wherein: The method for optimizing and adjusting the initial light-transmitting PVD coating control scheme based on the target metal deposition effect includes: Based on the multi-element coating control parameter index of the light-transmitting PVD coating, performing a multi-element coating control interval analysis on the plurality of historical light-transmitting PVD coating control schemes to establish a multi-element coating control interval; The multi-element coating control range is used as a spatial constraint condition to optimize the initial light-transmitting PVD coating control scheme.

6. The method for controlling metal deposition in a light-transmitting PVD coating according to claim 5, wherein: The multi-element coating control parameter indicators include evaporation rate parameters, substrate temperature parameters, atmosphere pressure parameters, deposition time parameters, bias voltage parameters, sputtering power parameters, and film stress parameters.

7. The method for controlling metal deposition in a light-transmitting PVD coating according to claim 5, wherein: The method for optimizing and adjusting the initial light-transmitting PVD coating control scheme based on the target metal deposition effect includes: Extracting metal deposition effect evaluation indicators based on the target metal deposition effect to obtain multiple metal deposition effect evaluation indicators; Performing function fitting based on the multiple metal deposition effect evaluation indicators to generate a metal deposition effect evaluation function; Within the multi-element coating control range, the initial light-transmitting PVD coating control scheme is subjected to parameter iterative optimization. After each round of iteration, the target metal deposition effect is taken as the goal, and the metal deposition effect evaluation function is used to perform metal deposition effect evaluation and parameter optimization comparison to determine the optimized light-transmitting PVD coating control scheme.

8. The method for controlling metal deposition in a light-transmitting PVD coating according to claim 7, wherein: Before performing parameter iterative optimization on the initial light-transmitting PVD coating control scheme, the method includes: Perform a light-transmitting PVD coating defect record search to obtain multiple historical light-transmitting PVD coating defect records; Performing defect analysis on the plurality of historical translucent PVD coating defect records to obtain a plurality of coating defect factors and a plurality of coating control parameters corresponding to the plurality of coating defect factors; Establishing a list of coating defects and control parameters based on a mapping relationship between the plurality of coating defect factors and the plurality of coating control parameters; Guided by the coating defects and control parameter list, the initial light-transmitting PVD coating control scheme is subjected to parameter iterative optimization.

9. The method for controlling metal deposition in a light-transmitting PVD coating according to claim 1, wherein: The method comprises: Perform sampling re-inspection based on the optimized light-transmitting PVD coating control scheme to obtain re-inspected metal deposition effects; If the re-inspected metal deposition effect still does not meet the target metal deposition effect, feedback optimization of the optimized light-transmitting PVD coating control scheme is performed.

10. A control system for metal deposition in a transparent PVD coating, characterized in that: A method for controlling metal deposition in a light-transmitting PVD coating according to any one of claims 1 to 9, the system comprising: A characteristic information acquisition module is used to obtain characteristic information of a plastic part sample and a target metal deposition effect, wherein the plastic part sample is a plastic part that has undergone a light-transmitting PVD coating; A process information acquisition module, configured to acquire light-transmitting PVD coating process information, wherein the light-transmitting PVD coating process information includes an initial light-transmitting PVD coating control scheme corresponding to the characteristic information of the plastic part; A feature detection module is used to perform metal deposition feature detection on the plastic part sample to obtain a metal deposition effect; An effect judgment module, configured to judge whether the detected metal deposition effect satisfies the target metal deposition effect; The optimization adjustment module is used to optimize and adjust the initial light-transmitting PVD coating control scheme based on the target metal deposition effect if the conditions are not met, so as to obtain an optimized light-transmitting PVD coating control scheme.

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