OSP coating thickness adjusting system and method in printed circuit board production

Abstract

The invention relates to the technical field of printed circuit board production, and discloses an OSP coating thickness adjusting system and method in printed circuit board production, and the method comprises the steps: firstly constructing an element welding demand database, and determining a target coating thickness range according to the welding demand of a target element type and the real-time environment and material data of the surface of a printed circuit board; then, three different thickness values are obtained according to the welding requirement, the environment data and the material data of the target element type, and the three different thickness values are divided into corresponding thickness grades; according to the thickness grades, a coating thickness adjustment value is determined, and a coating thickness control value d4 is further calculated; finally, coating equipment parameters are adjusted according to the coating thickness control value d4, coating production is conducted, and it is ensured that the coating thickness meets the quality standard. According to the method, by comprehensively considering element types, environmental conditions and material characteristics, accurate control over the thickness of the OSP coating is achieved, and therefore the production efficiency and the product quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of printed circuit board production, and more specifically, to an OSP coating thickness adjustment system and method in printed circuit board production. Background Art

[0002] With the rapid development of electronic technology, the precision and reliability of the manufacturing process of printed circuit boards (PCBs) as the core components of electronic products are particularly important. Especially in the coating process of the surface protection layer (OSP), the control of the coating thickness directly affects the welding quality, corrosion resistance and overall service life of the PCB. Therefore, developing a method and system that can accurately adjust the thickness of the OSP coating has become an important research direction for improving the level of PCB production technology.

[0003] In the prior art, a Chinese patent with publication number CN111654976A discloses a circuit board processing production line, which realizes the ink coating and drying of thin plates through a production line structure composed of a board loading module, a soaking module, a drying module, etc. This method adjusts the coating thickness by controlling the speed of the ink rising after soaking, and has the advantages of simple structure and low cost. However, in actual application, this method has the problem of insufficient precision in coating thickness control, especially when facing different component types and complex environmental conditions, dynamic adjustment cannot be achieved, resulting in difficulty in ensuring the stability and consistency of coating quality.

[0004] Another related technology, a Chinese patent with publication number CN115633440A discloses a printed circuit board and its coating method, and a three-proof coating process product. This method improves the reliability of the coating process by first coating the solder mask on the circuit board to avoid the forbidden area from being accidentally coated with the three-proof paint. However, this method mainly solves the problem of miscoating in the forbidden area, and lacks effective means for the precise control of the overall thickness of the coating. In addition, this method lacks flexibility in responding to real-time environmental and material changes, and it is difficult to adapt to the coating thickness requirements under different production conditions, resulting in the stability of the coating quality still cannot be effectively guaranteed in a complex and changeable production environment.

[0005] In summary, the existing technology lacks a dynamic adjustment mechanism based on design parameters and real-time data in adjusting the thickness of PCB OSP coating, and cannot accurately match the welding requirements of different components; it is not sensitive enough to the changes in production environment and material properties, and it is difficult to achieve real-time optimization control of coating thickness. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides a system and method for adjusting the thickness of the OSP coating in the production of printed circuit boards, which comprehensively considers the component type, environmental conditions and material properties, and utilizes intelligent algorithms and data models to achieve precise adjustment and control of the thickness of the OSP coating, thereby significantly improving the quality and efficiency of PCB production.

[0007] To achieve the above object, the present invention provides the following technical solutions: The OSP coating thickness adjustment method in printed circuit board production includes: Acquire design parameters of the printed circuit board, build a component welding requirement database, and determine the welding requirements of the target component type; collect real-time environmental data and real-time material data on the surface of the printed circuit board, and determine the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; According to the welding requirements of the target component type, a first thickness value d1 is obtained; according to the real-time environmental data of the surface of the printed circuit board, a second thickness value d2 is obtained; according to the real-time material data of the surface of the printed circuit board, a third thickness value d3 is obtained; the first thickness value, the second thickness value and the third thickness value are divided into corresponding thickness levels L1, L2 and L3; according to the thickness levels L1, L2 and L3, a coating thickness adjustment value is obtained; According to the coating thickness adjustment value and the target coating thickness range, a final coating thickness control value d4 is obtained; and coating production control is performed according to the coating thickness control value d4.

[0008] Further, the determining of the welding requirements of the target component type includes: Acquire design parameters of the printed circuit board, wherein the design parameters include package type, number of pins and package size of each component; According to the package type, pin number and package size of each component, combined with the preset component classification rules, the components on the printed circuit board are classified to obtain N component types; Determine the soldering temperature, soldering time and solder fluidity of each component type according to the package type, number of pins and package size of each component, and build a component soldering requirement database; Obtaining the package type, the number of pins and the package size of the target component, and determining the target component type according to the package type, the number of pins and the package size of the target component; A soldering temperature of a target component type, a soldering time of a target component type, and solder fluidity of a target component type are obtained from a component soldering requirement database.

[0009] Further, the determining of the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and the real-time material data of the printed circuit board surface includes: According to the real-time environmental data of the printed circuit board surface and the preset production environment and coating thickness relationship model, the recommended coating thickness range under the current production environment conditions is calculated and marked as the recommended coating thickness range for the production environment; Establish a model for the relationship between material properties and coating adhesion, and calculate coating adhesion based on real-time material data on the surface of the printed circuit board and the model for the relationship between material properties and coating adhesion; obtain a recommended coating thickness range under the current material surface state based on the coating adhesion, and mark it as the recommended coating thickness range for the material surface state; According to the welding requirements of the target component type, the recommended coating thickness range of the production environment and the recommended coating thickness range of the material surface condition, the final target coating thickness range [d min ,d max ],in, is the lower limit of the target coating thickness range, is the upper limit of the target coating thickness range.

[0010] Furthermore, the final target coating thickness range [d min ,d max ]include: Calculate the theoretical coating thickness d based on the welding requirements of the target component type s ; Calculate the environmental factor adjustment coefficient based on the recommended coating thickness range for the production environment ; Calculate the material factor adjustment coefficient based on the recommended coating thickness range according to the material surface condition ; According to the theoretical coating thickness , Environmental Factor Adjustment Coefficient and material factor adjustment coefficient , calculate the final recommended coating thickness ; According to the final recommended coating thickness and preset coating thickness safety margin factor , calculate the upper limit of the target coating thickness range and lower limit .

[0011] Further, obtaining the first thickness value d1 according to the welding requirements of the target component type includes: Acquire historical welding data of the target component type, wherein the historical welding data includes historical welding parameters and historical coating thickness corresponding to the historical welding parameters; the historical welding parameters include historical welding temperature, historical welding time and historical solder fluidity; Based on the historical welding data of the target component type, a mapping relationship model between welding parameters and coating thickness is constructed; the welding requirements of the target component type are input into the mapping relationship model to obtain a first thickness value d1.

[0012] Further, the dividing the first thickness value, the second thickness value and the third thickness value into corresponding thickness levels L1, L2 and L3 includes: Obtaining a preset thickness grade classification standard, wherein the thickness grade classification standard divides the coating thickness into n1 thickness grades, and each thickness grade corresponds to a coating thickness interval; According to the coating thickness interval corresponding to each thickness level, the thickness levels to which the first thickness value d1, the second thickness value d2 and the third thickness value d3 belong are determined, and the corresponding thickness levels L1, L2 and L3 are obtained.

[0013] Further, obtaining the coating thickness adjustment value according to the thickness levels L1, L2 and L3 includes: Determine whether the thickness grades L1, L2 and L3 are consistent; If L1, L2 and L3 are consistent, the median value of the coating thickness interval of the corresponding thickness grade is taken as the coating thickness adjustment value; If L1, L2 and L3 are inconsistent, the final thickness grade L is determined according to the preset priority rule, and the median value of the coating thickness interval corresponding to the final thickness grade L is taken as the coating thickness adjustment value.

[0014] Further, obtaining the final coating thickness control value d4 according to the coating thickness adjustment value and the target coating thickness range includes: If the coating thickness adjustment value is within the target coating thickness range, the coating thickness adjustment value is used as the final coating thickness control value d4; if the coating thickness adjustment value is not within the target coating thickness range, the coating thickness adjustment value and the target coating thickness range [d min ,d max ] The upper limit deviation Δd1 and the lower limit deviation Δd2; if |Δd1|≤|Δd2|, then take d max As the corrected coating thickness adjustment value d'; if |Δd1|>|Δd2|, then take d min As the corrected coating thickness adjustment value d'; the corrected coating thickness adjustment value d' is used as the final coating thickness control value d4.

[0015] Further, the coating production control according to the coating thickness control value d4 includes: Adjust the coating equipment parameters according to the coating thickness control value d4, spray the OSP coating on the surface of the printed circuit board, and carry out coating production; obtain the measured coating thickness value d0 after spraying; calculate the deviation Δd between the measured coating thickness value d0 and the coating thickness control value d4. If Δd is less than the preset thickness deviation threshold ε, it is considered that the OSP coating thickness meets the requirements and the coating production is terminated; otherwise, fine-tune the coating equipment parameters and re-carry out coating production until the OSP coating thickness meets the requirements.

[0016] The OSP coating thickness adjustment system in the production of printed circuit boards is used to implement the above-mentioned OSP coating thickness adjustment method in the production of printed circuit boards. The system comprises: Target thickness determination module: used to obtain the design parameters of the printed circuit board, build a component welding requirement database, and determine the welding requirements of the target component type; collect real-time environmental data and real-time material data on the surface of the printed circuit board, and determine the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; Thickness adjustment value determination module: obtain a first thickness value d1 according to the welding requirements of the target component type; obtain a second thickness value d2 according to the real-time environmental data of the printed circuit board surface; obtain a third thickness value d3 according to the real-time material data of the printed circuit board surface; divide the first thickness value, the second thickness value and the third thickness value into corresponding thickness levels L1, L2 and L3; obtain a coating thickness adjustment value according to the thickness levels L1, L2 and L3; Coating production control module: According to the coating thickness adjustment value and the target coating thickness range [d min ,d max ], and obtain the final coating thickness control value d4; and perform coating production control according to the coating thickness control value d4.

[0017] An electronic device comprises a memory, a central processing unit and a computer program stored in the memory and executable on the central processing unit. When the central processing unit executes the computer program, the above-mentioned method for adjusting the thickness of an OSP coating in the production of printed circuit boards is implemented.

[0018] A computer-readable storage medium stores a computer program, and when the computer program is executed, the method for adjusting the thickness of an OSP coating in the production of a printed circuit board is implemented.

[0019] Compared with the prior art, the present invention has the following beneficial effects: First, by acquiring the design parameters of the printed circuit board and building a component welding requirement database, the present invention can accurately identify the welding requirements of different component types, ensure that the OSP coating thickness is highly matched with the component welding process, and improve the welding quality and the overall reliability of the circuit board. Secondly, the environmental data and material data of the printed circuit board surface are collected in real time, and combined with the preset production environment and coating thickness relationship model and the material property and coating adhesion relationship model, the coating thickness range can be dynamically adjusted to adapt to the changes in the environment and materials during the production process, and the stability and consistency of the coating quality can be ensured.

[0020] In addition, the present invention enhances the flexibility and adaptability of the system by dividing the thickness values ​​from different sources into corresponding thickness levels and determining the coating thickness adjustment value according to the priority rule, and can maintain accurate control of coating thickness under variable production conditions. The mapping relationship model of coating thickness is constructed using historical welding data, which realizes data-driven intelligent adjustment, significantly improves the prediction accuracy of coating thickness, reduces the need for human intervention and adjustment, and thus improves production efficiency and product consistency.

[0021] In terms of coating production control, through real-time monitoring and feedback mechanisms, it is possible to quickly respond to coating thickness deviations and make fine adjustments to ensure the accuracy of the final coating thickness control value. This not only reduces the scrap rate and material waste in the production process, but also extends the service life of coating equipment and reduces production costs.

[0022] The present invention comprehensively considers design parameters, real-time environment and material data, and utilizes intelligent algorithms and data models to achieve precise adjustment and control of OSP coating thickness, significantly improving the quality and efficiency of printed circuit board production, and has broad application prospects and significant economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 The principle flow chart of the OSP coating thickness adjustment method in the production of printed circuit boards in the present invention; Figure 2 A flow chart of a method for determining the welding requirements of a target component type in a method for adjusting the thickness of an OSP coating in printed circuit board production according to the present invention; Figure 3A flow chart of a method for determining a target coating thickness range in a method for adjusting OSP coating thickness in printed circuit board production of the present invention; Figure 4 It is a flow chart of a method for calculating the first thickness value d1 in the method for adjusting the thickness of an OSP coating in the production of a printed circuit board of the present invention; Figure 5 A flow chart of a method for obtaining a coating thickness adjustment value in a method for adjusting OSP coating thickness in printed circuit board production of the present invention; Figure 6 This is a functional module diagram of the OSP coating thickness adjustment system in the printed circuit board production of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Example 1 See also Figure 1 As shown, this embodiment provides a method for adjusting the thickness of an OSP coating in the production of a printed circuit board, comprising: Step S1000, obtaining design parameters of the printed circuit board, constructing a component welding requirement database, and determining the welding requirements of the target component type; collecting real-time environmental data and real-time material data on the surface of the printed circuit board, and determining the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; Further, step S1000 includes: Step S1100, obtaining design parameters of the printed circuit board, constructing a component welding requirement database, and determining welding requirements of a target component type; the welding requirements of the target component type include welding temperature of the target component type, welding time of the target component type, and solder fluidity of the target component type; Furthermore, if Figure 2 As shown, step S1100 includes: Step S1110, obtaining design parameters of the printed circuit board, wherein the design parameters include the package type, the number of pins and the package size of each component; Step S1120, classifying the components on the printed circuit board according to the package type, number of pins and package size of each component in combination with a preset component classification rule to obtain N component types; Step S1130, determining the welding temperature, welding time and solder fluidity of each component type according to the package type, pin number and package size of each component, and constructing a component welding requirement database; Step S1140, obtaining the package type, the number of pins and the package size of the target component, and determining the type of the target component according to the package type, the number of pins and the package size of the target component; Step S1150 , obtaining the soldering temperature of the target component type, the soldering time of the target component type, and the solder fluidity of the target component type from the component soldering requirement database.

[0027] Specifically, step S1100 is the starting stage of the entire welding process. Its main purpose is to build a component welding requirement database by acquiring the design parameters of the printed circuit board (PCB), so as to provide necessary parameter support for the subsequent welding process. This step involves three key aspects: acquiring design parameters, building a welding requirement database, and determining the welding requirements of the target component type. The welding requirements of the target component type include welding temperature, welding time, and solder fluidity, which are important factors affecting welding quality and efficiency.

[0028] In step S1110, it is first necessary to obtain PCB design parameters, especially to collect detailed parameters for each component on the PCB. Specific design parameters include: Package Type: refers to the external packaging form of the component, usually including BGA (ball grid array), QFN (quad package without leads), SMD (surface mount device), etc. Components with different package types require different welding processes, because the packaging form affects the heat transfer efficiency during the welding process.

[0029] Pin Count: refers to the number of pins connecting the component to the PCB. The number of pins affects the difficulty and time of soldering. For example, a large integrated circuit (IC) may have hundreds of pins, so it takes longer to solder and more precise temperature control.

[0030] Package Size: The size of a component, usually measured in length, width, and thickness. Larger components require higher soldering temperatures and times to ensure even heat distribution and avoid soldering defects.

[0031] Obtaining these design parameters is the basis for determining the welding requirements of components and can effectively guide the subsequent process settings. By recording the package type, number of pins and size of each component in detail, it can be ensured that the welding quality will not be inconsistent due to differences in component characteristics during the welding process, thereby improving overall production efficiency.

[0032] The key to step S1120 is to classify all components according to the obtained design parameters using the preset component classification rules. The preset component classification rules are usually formulated based on industry standards or rules accumulated from specific experience, and their purpose is to classify similar components together to facilitate unified formulation of welding requirements. Classification rules may include: Package type: For example, all BGA packaged components are grouped in one category, and all QFN packaged components are grouped in another category.

[0033] Pin count: For example, all components with the same pin count (e.g. 32 pins, 64 pins, etc.) can be grouped together.

[0034] Package size: For components of similar size, a unified classification method is adopted.

[0035] Through such classification, the welding requirements database can be generated more efficiently. Component classification can help simplify the management and formulation of welding requirements. By managing the same type of components together, not only can the complexity of each component needing to be considered separately be avoided, but also the uniformity and repeatability of the welding process can be improved, thereby saving production time and reducing welding defects.

[0036] In step S1130, based on the aforementioned component classification information, combined with the package type, pin number and package size, the soldering temperature, soldering time and solder fluidity of each type of component are determined. The specific determination method is as follows: Soldering temperature: Depending on the thermal sensitivity and material properties of the component, components of different package types and sizes require different soldering temperatures. For example, BGA package components require higher soldering temperatures to ensure that heat can be evenly distributed to all pins, while smaller components (such as QFN) may require lower temperatures to prevent damage.

[0037] Soldering time: Soldering time is closely related to the size and number of pins of the component. Large-sized components or components with more pins usually require longer soldering time to ensure that all pins can be fully soldered. Small-sized components can shorten the soldering time.

[0038] Solder fluidity: The fluidity of solder is related to the temperature and material selection. Through soldering process optimization, it can be ensured that the solder reaches the optimal fluidity state at the correct time and temperature to ensure soldering quality.

[0039] The setting of these parameters will be determined according to the type of component, material characteristics and characteristics of the welding equipment. Establishing a welding requirement database can ensure that suitable process parameters can be quickly obtained during the welding process of different types of components, avoid errors caused by manual judgment, and ensure the stability of welding quality. In addition, this method helps to quickly adjust the welding of different types of components and improve production flexibility and efficiency.

[0040] The goal of step S1140 is to determine the type of the target component based on the specific design parameters of the target component (package type, number of pins and package size). This step locates the category to which the target component belongs by matching it with the classification rules established in step S1120. This means that each target component will be compared with the classification rules in the database based on its design parameters to determine the type of welding requirement to which the target component belongs. In this way, the type of the target component can be quickly determined and an accurate reference can be provided for the subsequent welding process. The beneficial effect of this method is that it reduces the risk of classification errors, can accurately locate the component type, and ensure that there will be no errors in the subsequent welding process.

[0041] Step S1150 involves extracting welding requirement parameters corresponding to the target component type from the established component welding requirement database. These parameters include welding temperature, welding time and solder fluidity, which will be directly used in the actual welding process to ensure that the target component can be welded according to the optimal process requirements. This step ensures that accurate information in the welding requirement database can be directly referenced in actual operation to avoid manual intervention and potential errors. By quickly obtaining accurate welding requirement parameters, production efficiency can be improved and the defect rate caused by improper operation can be reduced. In addition, the maintenance of the database can standardize the welding requirements of each component type, which is convenient for efficient mass production.

[0042] Step S1200, collecting real-time environmental data of the surface of the printed circuit board, wherein the real-time environmental data includes real-time temperature data, real-time humidity data and real-time roughness data; Specifically, the purpose of step S1200 is to monitor and collect key parameters of the printed circuit board (PCB) surface environment in real time so as to adjust the production or welding process in time. This step involves three core environmental data: temperature, humidity and roughness. These data can provide important information for subsequent welding processes, help optimize process parameters, and ensure welding quality. The specific operation process includes arranging sensors on the PCB surface, collecting data in real time, and preprocessing the collected data.

[0043] Temperature is a very critical parameter in the welding process. Too high or too low temperature may affect the welding quality, resulting in poor solder joints or welding defects. Therefore, accurate temperature monitoring is essential. Usually, temperature sensors such as thermocouples and thermistors are used for collection. The effect of humidity on the welding process is mainly reflected in the moisture content on the PCB surface. If the humidity is too high, bubbles, welding defects or solder flow may occur during the welding process, so real-time humidity monitoring is very important. Common humidity sensors include capacitive humidity sensors and resistive humidity sensors. The roughness of the PCB surface directly affects the adhesion of the solder and the stability of the solder joints. A rougher surface may cause uneven solder joints and affect the welding quality. Commonly used roughness sensors include laser scanners, optical sensors, etc. Once the sensors are arranged and start real-time monitoring, the impact of environmental changes on welding quality can be analyzed based on the collected data. In practical applications, changes in temperature, humidity and roughness may affect the stability of the welding process, so these data need to be accurately analyzed.

[0044] Preprocessing operations: Data cleaning: Remove noise, redundant or invalid data that occurs during the acquisition process. For example, if the temperature sensor has some abnormal readings due to poor contact, these abnormal data need to be cleared.

[0045] Outlier removal: By setting reasonable thresholds, we can remove extreme data that does not conform to the expected range. For example, if the data of the humidity sensor is much lower or higher than the normal value, it may be that the sensor is faulty or the environmental conditions are abnormal, and this data needs to be removed.

[0046] Data normalization: Convert data to a unified dimension or standard range so that data from different sources can be compared and analyzed on the same scale. For example, temperature, humidity, and roughness may have different dimensions and units. Data normalization can help unify the scale so that data from different parameters can be analyzed in a linked manner.

[0047] By collecting and processing environmental data in real time, unstable factors in the production process can be identified in advance and the welding process can be adjusted in time. Such monitoring can significantly improve welding quality and reduce welding defects caused by changes in environmental factors. In addition, data normalization and preprocessing steps can ensure data accuracy and consistency, providing a reliable basis for subsequent process optimization and quality control.

[0048] Step S1300, acquiring real-time material data of the surface of the printed circuit board, wherein the real-time material data includes real-time conductivity and real-time surface energy; Specifically, the purpose of step S1300 is to obtain material performance data of the printed circuit board surface, especially conductivity and surface energy, which are of great significance to welding quality and process stability. Like environmental data, material data also needs to be collected through real-time sensors and applied to the optimization of welding process after preprocessing.

[0049] Conductivity reflects the conductive properties of the PCB surface material. During the soldering process, conductivity directly affects the heat transfer efficiency of soldering and the formation of solder joints. If the conductivity is too low, the soldering temperature may not be transferred quickly, affecting the soldering effect. Common conductivity sensors are usually based on the resistance measurement principle or the capacitance principle. Surface energy is a parameter that measures the molecular attraction of the material surface when it contacts the outside world. Higher surface energy usually means better solder wettability, and the solder can flow better and form a good connection with the surface. Surface energy can be obtained by contact angle measurement or other surface tension measurement methods.

[0050] By collecting surface material data in real time through these sensors, the required material parameters can be provided for the subsequent welding process, thereby adjusting the welding process. For example, when the surface energy of the material is low, the solder or welding temperature can be adjusted to ensure good welding quality.

[0051] Preprocessing operations: Data cleaning: Similar to environmental data, the collected conductivity and surface energy data may also contain errors or noise, and these invalid data need to be removed. The purpose of data cleaning is to ensure that the collected data is accurate and reliable and to avoid erroneous analysis results.

[0052] Outlier removal: Based on historical experience or equipment specifications, set reasonable upper and lower limits for conductivity and surface energy, and remove data that does not meet the conditions. For example, if the conductivity measurement value is far below the set lower limit, it may indicate equipment failure or inaccurate measurement.

[0053] Data normalization: Different sensors may have different measurement units and dimensions, so data normalization is required so that the conductivity and surface energy data can be compared under the same standard. For example, the values ​​of conductivity and surface energy are standardized to a range between 0 and 1 for unified processing and analysis.

[0054] By collecting and processing real-time material data, the material status can be monitored in real time and the welding process can be adjusted in time to ensure that the heat transfer and solder fluidity during the welding process meet expectations. By cleaning and normalizing the data, the accuracy and comparability of the data can be improved, thereby enhancing the accuracy of the welding process control. Furthermore, accurate monitoring of material data helps to improve product quality and reduce rework and non-conformity rates.

[0055] Step S1400, determining a target coating thickness range according to the welding requirements of the target component type, real-time environmental data and real-time material data of the surface of the printed circuit board.

[0056] Furthermore, if Figure 3 As shown, step S1400 includes: Step S1410, calculating the recommended coating thickness range under the current production environment conditions according to the real-time environmental data of the printed circuit board surface and the preset production environment and coating thickness relationship model, and marking it as the production environment recommended coating thickness range; Specifically, the core of step S1410 is to calculate a recommended coating thickness range based on production environment data (such as temperature, humidity, roughness, etc.) and the coating thickness relationship model, which is adapted to the current production environment conditions. The production environment and coating thickness relationship model is a mathematical model established based on historical data and experimental results to describe the influence of different production environment conditions (such as temperature, humidity and roughness, etc.) on coating thickness. The purpose of this model is to help dynamically adjust the coating thickness according to the current environmental conditions to ensure the uniformity, adhesion and protection of the coating. In the model, environmental parameters (temperature, humidity, roughness, etc.) are usually used as independent variables, and coating thickness is used as a dependent variable. For example, when the ambient temperature is high, the evaporation rate of the coating is accelerated, which may cause the coating thickness to be too thin; when the humidity is too high, it may cause the coating to be uneven, so the coating thickness needs to be adjusted accordingly. The model can be established through regression analysis or machine learning methods, and the specific form can be a multiple regression equation or a neural network model.

[0057] Based on the environmental data (such as temperature, humidity and roughness) collected by the sensor in real time, these data are input into the established environment and coating thickness relationship model to calculate the coating thickness range under the current production environment conditions.

[0058] This range is an upper and lower limit interval, indicating the recommended coating thickness range under the current environmental conditions. For example, the recommended coating thickness range calculated in a production environment may be 0.1mm to 0.2mm, which means that the coating effect is best within this range.

[0059] By monitoring the production environment in real time and dynamically adjusting the coating thickness according to environmental changes, the quality of the coating can be effectively improved to prevent coating defects or inconsistent quality caused by environmental changes. The use of the model makes the calculation process of coating thickness more scientific and accurate, and can be quickly adjusted according to real-time data, optimize the production process, and improve production efficiency and yield.

[0060] Step S1420, establishing a model for the relationship between material properties and coating adhesion, calculating the coating adhesion according to the real-time material data on the surface of the printed circuit board and the model for the relationship between material properties and coating adhesion; obtaining a recommended coating thickness range under the current material surface state according to the coating adhesion, and marking it as the recommended coating thickness range under the material surface state; Specifically, the purpose of step S1420 is to establish a model of the relationship between material properties and coating adhesion, and use the model and real-time collected material data (such as conductivity and surface energy, etc.) to calculate the coating adhesion, so as to recommend the coating thickness that best suits the current material surface state. The coating adhesion directly affects the stability, durability and protection of the coating, so it is very important to calculate and optimize the coating adhesion.

[0061] The relationship model between material properties and coating adhesion describes how the properties of PCB surface materials (such as conductivity, surface energy, etc.) affect the adhesion of coatings. Adhesion refers to the adhesion between the coating and the substrate. Good adhesion can ensure that the coating is not easy to fall off, peel off or have other defects.

[0062] Materials with higher surface energy generally have better coating adhesion because they are more likely to interact with the coating and form stronger physical or chemical bonds. Materials with higher electrical conductivity may also affect coating adhesion, especially in some specialty coatings where electrical conductivity may be related to the hardness or durability of the coating.

[0063] The conductivity and surface energy data collected in real time are input into the material properties and coating adhesion relationship model to calculate the coating adhesion under the current material surface state. Based on the calculated coating adhesion, the recommended coating thickness range under the current material surface state is further determined. Generally, surfaces with stronger adhesion can use thinner coatings, while surfaces with weaker adhesion require thicker coatings to ensure the firmness and stability of the coating. For example, if the coating adhesion is strong, the recommended coating thickness range may be smaller (such as 0.1mm to 0.15mm); if the adhesion is weak, the coating thickness may need to be increased (such as 0.2mm to 0.3mm) to enhance the adhesion of the coating.

[0064] By adjusting the coating thickness based on the calculation of coating adhesion, the stability and durability of the coating can be greatly improved, and the coating can be prevented from peeling or falling off. In addition, the relationship model between material properties and adhesion can help to make precise adjustments based on the real-time state of the material, optimize the coating effect, reduce waste and improve production efficiency.

[0065] The material property and coating adhesion relationship model includes: A: Coating adhesion, usually measured in N / m². It indicates the strength of the coating's adhesion to the material surface. The higher the coating adhesion, the less likely the coating will fall off.

[0066] E: Material conductivity, usually in S / m (Siemens / meter). Conductivity can be obtained through resistance measurement, usually by applying a known voltage and measuring the current of the material to calculate the conductivity. It reflects the conductivity of the material, which in turn affects the electronic interaction between the coating and the substrate.

[0067] γ: Surface energy of the material, in J / m² (joule / square meter). Surface energy can be obtained by contact angle measurement. The contact angle is the wetting angle of the liquid on the surface of the material. By measuring this angle, the surface energy of the material can be inferred. It reflects the interaction force between molecules on the surface of the material and directly affects the adhesion strength between the coating and the surface of the material.

[0068] : The first regression coefficient of material conductivity.

[0069] : The second regression coefficient of material conductivity, , Obtained through experimental fitting, representing the linear and nonlinear effects of conductivity on adhesion.

[0070] : The first regression coefficient of the material surface energy.

[0071] : The second regression coefficient of the material surface energy, , Obtained through experimental fitting, representing the linear and nonlinear effects of surface energy on adhesion.

[0072] : Exponential factor of conductivity.

[0073] : exponential factor of surface energy, , It reflects the nonlinear effect of material properties on adhesion. It is obtained by regression fitting of experimental data.

[0074] : The first nonlinear adjustment factor.

[0075] : The second nonlinear adjustment factor, , It represents the interaction between material conductivity and surface energy and is usually obtained by fitting more complex experimental models to describe how material conductivity and surface energy jointly affect coating adhesion.

[0076] Regression coefficient ( , , , ) Perform regression analysis on experimental data to fit the values ​​of each coefficient. You can use optimization algorithms such as least squares method and gradient descent method. Nonlinear factor ( , , , ) is obtained through multiple experiments, simulations or more complex mathematical modeling, which can describe more detailed interactions between the coating and the material surface.

[0077] Through the regression coefficient and nonlinear factor in the formula, the change of E and γ will affect the coating adhesion A. When the conductivity and surface energy of the material increase, the coating adhesion will change significantly. For example, the coating adhesion is stronger on the high conductivity material, while the coating is easy to adhere to the high surface energy material.

[0078] When the material conductivity E increases, the coating adhesion A will show a nonlinear growth or decrease trend, depending on the regression coefficient and exponential factor When the surface energy γ of the material increases, the coating adhesion A will also show a similar nonlinear change. The trend of this change is given by and The interaction term It indicates the complex coupling between conductivity and surface energy, which makes the adhesion show a more complicated variation law under specific material conditions.

[0079] This formula can calculate coating adhesion based on real-time conductivity and surface energy. Since coating adhesion directly affects the quality and durability of the coating, and coating adhesion is closely related to coating thickness, real-time adjustment of coating thickness during the production process helps improve production efficiency and product quality. This formula takes into account the mutual influence of conductivity and surface energy, can adapt to changes in the surface state of different types of materials (such as metals, plastics, ceramics, etc.), and gives a suitable coating thickness range. By introducing the exponential term ( , ) and interaction terms, the model can accommodate complex nonlinear behaviors in real applications. For example, coating adhesion can change significantly on surfaces with high or low conductivity and surface energy. By accurately representing the relationship between material properties and coating adhesion, the model can provide more accurate coating thickness recommendations and reduce coating peeling problems caused by poor adhesion.

[0080] Step S1430, determining the final target coating thickness range [d min ,d max ],in, is the lower limit of the target coating thickness range, is the upper limit of the target coating thickness range.

[0081] The core purpose of step S1430 is to determine an optimal coating thickness range by comprehensively considering the welding requirements of the target component, the production environment conditions, and the surface state of the material. This range includes the lower and upper limits of the coating, that is, [d min ,d max ], through reasonable calculation and adjustment, ensure that the coating thickness meets the requirements of production and welding process.

[0082] Further, step S1430 includes: Step S1431, calculate the theoretical coating thickness d according to the welding requirements of the target component type s ; Theoretical coating thickness d s It is an ideal coating thickness calculated based on the welding requirements of the target component (such as welding temperature, welding time, solder fluidity, etc.). The welding requirements mainly affect the physical properties required by the coating during the welding process, such as heat conduction efficiency and the stability of the welding contact surface, which in turn affects the selection of coating thickness. For example, if the welding requirements of the target component are high-temperature and short-time welding (such as fast welding of surface mount components), the theoretical coating thickness is usually thinner because thicker coatings may affect heat transfer. By calculating the theoretical coating thickness, it can be ensured that the coating can fully meet the heat conduction requirements during the welding process, while avoiding welding defects caused by too thick or too thin coatings. This step is the basis for subsequent adjustments and optimizations.

[0083] The calculated theoretical coating thickness d s include: in: d s : Theoretical coating thickness (unit: micrometer).

[0084] T W :The welding temperature of the target component type (unit: Celsius). The effect of temperature on coating thickness is closely related to heat conduction and material fluidity during welding. Generally, when the welding temperature is high, the coating thickness is small. The temperature of the component surface during welding is monitored in real time through a temperature sensor. Commonly used equipment includes thermocouples, infrared thermometers, etc.

[0085] tW : The welding time of the target component type (in seconds). The welding time affects the deposition process of the coating. The longer the time, the thicker the coating may be. The duration of the welding process is obtained through a control system or timer, which is usually controlled by the welding equipment.

[0086] F W : The solder fluidity of the target component type. The better the fluidity, the more uniform the coating will be. The coating thickness is also affected by this. Usually, when the fluidity is poor, the coating is thinner. It can be measured experimentally and is usually related to the viscosity and chemical composition of the solder.

[0087] : Welding constant, based on the material type and welding method of the target component, represents the reference coating thickness under standard welding conditions. It will be affected by factors such as material type and welding method.

[0088] : The sensitivity index of welding temperature to coating thickness, indicating the degree of influence of temperature change on coating thickness. It can be obtained through experimental data or regression analysis.

[0089] : The sensitivity index of welding time to coating thickness, indicating the influence of welding time change on coating thickness.

[0090] : The sensitivity index of solder fluidity to coating thickness, indicating the influence of fluidity on coating thickness.

[0091] : The heat transfer coefficient of the material surface affects the heat transfer effect during welding and is usually obtained through experiments.

[0092] : The electrical conductivity of the material affects the distribution of heat during welding and the formation of the coating, and can usually be estimated by the electrical conductivity of the material.

[0093] : The temperature and fluidity composite effect adjustment factor reflects the synergistic effect between soldering temperature and solder fluidity, and reflects their joint influence on coating thickness.

[0094] T0: Reference temperature, usually a fixed ambient temperature (such as room temperature), used to adjust the effect of temperature on coating thickness. Usually takes room temperature value (such as 25°C), can be adjusted according to actual conditions.

[0095] : An exponential function with the base e of the natural logarithm as its base.

[0096] , , , , :These coefficients can be obtained by fitting experimental data. Generally, through welding tests, the coating thickness data under different welding conditions are collected, and then these parameters are estimated using regression analysis methods.

[0097] (heat transfer coefficient) and (Electrical conductivity): These two parameters reflect the thermal conductivity and electrical conductivity of the material. They affect the transfer and distribution of heat during the welding process, thereby affecting the coating formation process. They are usually obtained through physical property experiments of the material, or by consulting the standard data sheet of the relevant material.

[0098] T W ,t W and F W : These are the core factors in the welding process, which together affect the heat conduction, material flow and coating deposition during welding, thereby determining the thickness of the coating.

[0099] , , :These are the sensitivity coefficients of the welding process, which are used to quantify the specific effects of welding temperature, time and fluidity on coating thickness. Usually obtained by fitting experimental data.

[0100] Through this formula, the theoretical coating thickness can be accurately calculated according to the welding requirements, so as to achieve precise control in the production process. The influence of multiple factors such as welding temperature, duration, solder fluidity, etc. on the coating thickness is comprehensively considered, and the coating formation process can be fully optimized. As the welding conditions (temperature, duration, fluidity, etc.) change, the theoretical coating thickness can be adjusted in real time, providing a basis for the optimization of the welding process. By accurately controlling the theoretical coating thickness, welding defects caused by too thick or too thin can be avoided, and the overall quality of the product can be improved.

[0101] Step S1432, recommend coating thickness range based on production environment Calculate the environmental adjustment factor ; Recommended coating thickness range based on material surface conditions Calculate material factor adjustment coefficient ;in, The lower limit of the coating thickness range is recommended for production environments. The upper limit of the coating thickness range is recommended for production environments; The lower limit of the coating thickness range recommended for the material surface condition, The upper limit of the coating thickness range is recommended for the material surface condition; The influence of environmental factors (such as temperature, humidity, roughness, etc.) on coating thickness is adjusted by the environmental factor adjustment coefficient This factor reflects the specific impact of the production environment on the coating thickness. If the ambient temperature is high, the evaporation rate of the coating is accelerated, and the coating may be thinner, otherwise it will be thicker. The environmental factor adjustment coefficient is usually calculated by dividing the average of the recommended coating thickness range of the production environment by the theoretical coating thickness. is determined by the ratio between them.

[0102] The surface state of the material (such as surface energy, conductivity, etc.) will also affect the adhesion and stability of the coating, thereby affecting the final thickness of the coating. Material Factor Adjustment Coefficient It is used to reflect the influence of material surface condition on coating thickness. Similar to the environmental factor adjustment coefficient, the material factor adjustment coefficient is the average of the recommended coating thickness range based on the material surface condition and the theoretical coating thickness. is determined by the ratio between them.

[0103] in: : Environmental factor adjustment coefficient, reflecting the impact of production environment on coating thickness.

[0104] : Material factor adjustment coefficient, reflecting the influence of material surface state on coating thickness.

[0105] : The upper limit of the coating thickness range recommended for production environments.

[0106] : The lower limit of the coating thickness range recommended for production environments.

[0107] : The upper limit of the recommended coating thickness range for material surface conditions.

[0108] : The lower limit of the recommended coating thickness range for material surface conditions.

[0109] The adjustment factor reflects the degree of influence of environmental conditions and material surface conditions on coating thickness. If the adjustment factor is greater than 1, it means that the factor will increase the coating thickness; if it is less than 1, it means that the factor will reduce the coating thickness. The adjustment factor is calculated by dividing the average of the recommended range by the theoretical thickness. By calculating the adjustment coefficients of environmental factors and material factors, the coating thickness can be dynamically adjusted to ensure the adaptability of the coating under different environmental and material conditions. This adjustment can improve the flexibility of the production process, ensure stable coating quality, and reduce defects caused by environmental or material changes.

[0110] Step S1433, according to the theoretical coating thickness , Environmental Factor Adjustment Coefficient and material factor adjustment coefficient , calculate the final recommended coating thickness ; in, is the weight coefficient of environmental factors, is the weight coefficient of material factors, reflecting their relative importance to coating thickness. The weight coefficient can be obtained through expert experience or machine learning algorithms (such as hierarchical analysis method, support vector machine, etc.). Generally, environmental factors have a more significant impact on coatings, so the weight coefficient may be larger. Material factors may be more important for certain production processes, and the weight coefficient will be adjusted according to the situation. The coating thickness and each adjustment coefficient are in a power function relationship, reflecting the nonlinear coupling effect between the factors. In this way, a coating thickness that meets production requirements can be obtained under the combined effect of multiple factors. This calculation method can reasonably consider the nonlinear coupling effect of different factors, ensure that the coating thickness is reasonably adjusted, meet welding requirements, adapt to environmental and material changes, and improve the stability and quality of the coating.

[0111] Step S1434, according to the final recommended coating thickness and preset coating thickness safety margin factor , calculate the upper limit of the target coating thickness range and lower limit .

[0112] In order to cope with random fluctuations in the production process and measurement errors, it is necessary to A certain safety margin is reserved on the basis of the coating thickness. It is usually greater than 1 and is used to reserve a certain safety margin based on the recommended thickness to cope with random fluctuations and measurement errors in the production process. The value of can be determined by statistical analysis based on factors such as process capability index and product reliability requirements. By reserving a safety margin, it can be ensured that the coating thickness still meets the quality requirements within the fluctuation range of the production process, avoiding unqualified coating thickness due to errors or sudden environmental changes. This step further enhances the stability and reliability of coating thickness control.

[0113] Step S1430 determines the final coating thickness range by comprehensively considering the welding requirements, production environment and material surface conditions of the target component. By gradually adjusting the coating thickness, the coating thickness is precisely controlled using parameters such as adjustment coefficient, weight coefficient and coating safety margin coefficient. This process not only takes into account the welding requirements, but also fully reflects the influence of environmental factors and material surface conditions, thereby improving the stability and production efficiency of the coating while ensuring welding quality.

[0114] Step S2000, obtaining a first thickness value d1 according to the welding requirements of the target component type; obtaining a second thickness value d2 according to the real-time environmental data of the surface of the printed circuit board; obtaining a third thickness value d3 according to the real-time material data of the surface of the printed circuit board; obtaining a coating thickness adjustment value according to the thickness levels L1, L2 and L3 corresponding to the first thickness value d1, the second thickness value d2 and the third thickness value d3; Furthermore, step S2000 includes: Step S2100, obtaining historical welding data of the target component type, and calculating a first thickness value d1 according to the welding requirements of the target component type and the historical welding data; Furthermore, if Figure 4 As shown, step S2100 includes: Step S2110, obtaining historical welding data of the target component type, wherein the historical welding data includes historical welding parameters and historical coating thickness corresponding to the historical welding parameters; the historical welding parameters include historical welding temperature, historical welding time and historical solder fluidity; Step S2120, constructing a mapping relationship model between welding parameters and coating thickness based on historical welding data of the target component type; Step S2130: input the welding requirement of the target component type into the mapping relationship model to obtain a first thickness value d1.

[0115] Specifically, the purpose of step S2100 is to calculate the recommended coating thickness under the current welding requirements by analyzing the relationship between different welding parameters and coating thickness based on the historical welding data of the target component. The ultimate goal of this step is to obtain the first thickness value d1, which reflects the recommended coating thickness of the target component under the current welding conditions.

[0116] To achieve this goal, it is first necessary to collect historical welding data of the target component type and establish a mapping relationship model between welding parameters and coating thickness based on these data. Then, the current welding requirements of the target component are input into the model to calculate the first thickness value d1.

[0117] The historical welding data includes multiple historical welding parameters and the coating thickness corresponding to each set of welding parameters. These data will provide necessary support for the subsequent model establishment. Specific historical welding parameters include: Historical welding temperature: refers to the temperature value used in the past welding process. Temperature is one of the most critical factors in the welding process. Too high a temperature may cause damage to the component, while too low a temperature may cause incomplete welding. By collecting historical welding temperature data, you can understand the variation of coating thickness under different temperature conditions.

[0118] Historical welding time: refers to the time of each operation during the welding process. The effect of welding time on coating thickness is mainly reflected in the accumulation and transfer of heat. Too short welding time may cause the coating to fail to melt or solidify fully, while too long welding time may cause the coating to be too thick or the solder to flow excessively.

[0119] Solder fluidity: refers to the property of solder to flow during heating. Solder fluidity affects the uniformity and adhesion of the coating. Solder with strong fluidity can better cover the welding surface, while solder with poor fluidity may cause uneven coating and even bubbles or other defects.

[0120] All these parameters are closely related to the coating thickness, so it is necessary to collect relevant historical data as the basis for the subsequent establishment of a mapping relationship model. By systematically collecting historical welding data, data support can be provided for the adjustment of coating thickness. These historical data can reveal the influence of different welding parameters on coating thickness, help predict the coating thickness required under similar conditions, and thus improve the accuracy and reliability of the welding process.

[0121] The mapping relationship model between welding parameters and coating thickness is used to describe the mathematical relationship between welding parameters (such as welding temperature, time and solder fluidity) and coating thickness, which helps to understand the variation of coating thickness under different welding conditions.

[0122] There are many ways to build this model, common methods include: Multiple regression analysis: Multiple regression analysis is a classic method for establishing a mapping relationship model. By modeling the relationship between multiple independent variables (soldering temperature, welding time, solder fluidity) and the dependent variable (coating thickness), a regression equation is obtained. This equation can be used to predict the coating thickness under given welding parameters.

[0123] Neural Networks: Neural network is another common modeling method, which is particularly suitable for complex nonlinear relationships. By training the neural network model, the complex mapping relationship between welding parameters and coating thickness can be learned. Neural networks can capture more complex patterns and are suitable for modeling large-scale data and complex processes.

[0124] By establishing a mapping relationship model, the coating thickness can be accurately predicted and adjusted. This model can not only take into account the impact of multiple factors on the coating thickness, but also help optimize the welding process, avoid errors caused by manual experience, and improve production automation and accuracy.

[0125] The purpose of step S2130 is to input the welding requirements of the target component (such as welding temperature, duration and solder fluidity) into the established mapping relationship model, so as to calculate the first thickness value d1. This first thickness value is the recommended coating thickness calculated based on the current welding requirements and historical welding data.

[0126] Soldering requirements usually include parameters such as soldering temperature, duration, and solder fluidity of the target component. By inputting these parameters into the mapping relationship model, the model can calculate the coating thickness that matches these parameters based on the rules obtained from historical data. By inputting the target welding requirements into the established mapping relationship model, an accurate coating thickness value can be calculated based on historical data. This value can help quickly adjust the coating thickness to ensure welding quality.

[0127] Step S2100 collects historical welding data of the target component type, establishes a mapping relationship model between welding parameters and coating thickness, and calculates the first thickness value d1 according to the current welding requirements. This process can accurately predict the coating thickness based on the empirical rules of historical data, thereby providing a scientific basis for the current welding process, helping to optimize coating thickness control, and improving welding quality and production efficiency.

[0128] Step S2200, obtaining a second thickness value d2 according to real-time environmental data of the printed circuit board surface, welding requirements of the target component type and a pre-built coating thickness prediction model; Specifically, the purpose of step S2200 is to calculate the second thickness value d2 by combining the real-time environmental data on the surface of the printed circuit board and the welding requirements of the target component type through a pre-built coating thickness prediction model. This process relies on machine learning models (such as decision trees, random forests, support vector machines, etc.). The decision tree divides the data through a tree structure, each node represents a decision rule, and the final leaf node gives the prediction result. The advantage of the decision tree is that it is easy to understand and handles the nonlinear relationship of the data well. Random forest is an integrated method of decision trees. By constructing multiple decision trees and summarizing their prediction results, overfitting is reduced and the accuracy of the model is improved. The support vector machine maximizes the class interval by finding a hyperplane. The support vector machine works better when processing high-dimensional data and is suitable for complex nonlinear problems. The coating thickness prediction model can learn the intrinsic relationship between environmental conditions, welding requirements and coating thickness, and dynamically predict the coating thickness according to the current production conditions.

[0129] Model structure and training process: Sample data set: The training data set includes a large amount of historical production data, where each sample contains the following information: Input features: including real-time environmental features (such as temperature, humidity, roughness, etc.) and the soldering requirements of the target components (such as soldering temperature, soldering time, solder fluidity, etc.).

[0130] True label: coating thickness (i.e., coating thickness value, used as the target output of the model).

[0131] Input and true labels for the training process: Input: The input features of each training data are composed of real-time environmental data and the welding requirements of the target component. For example, the temperature is , humidity is , the welding temperature is , welding time is , solder fluidity is wait.

[0132] Label: coating thickness, usually provided by actual production measurements. For example, the coating thickness is .

[0133] Model training: Input: The model accepts an input vector consisting of multiple environmental characteristics and welding requirements.

[0134] Training goal: Train the model with a large amount of historical data so that it can map input features to the output of coating thickness. The goal is to optimize the parameters of the model (such as the node splitting rule of the decision tree, the tree structure of the random forest, the hyperplane of the support vector machine, etc.) so that the model has good generalization ability for new data.

[0135] Training methods: Common training methods include regression analysis, cross-validation, etc. During the training process, the model will adjust parameters to minimize the error between the predicted coating thickness and the actual measured coating thickness.

[0136] Model output: After training, the model can accept real-time environmental data and welding requirements as input and output a predicted coating thickness value d2. This value is the recommended coating thickness under current production conditions.

[0137] Feature extraction: In actual operation, real-time environmental data and welding demand data are usually high-dimensional and contain multiple different parameters. The process of feature extraction is to convert these multi-dimensional data into a format suitable for machine learning model input. Common feature extraction methods include: Standardization: Convert features of different scales to a unified scale (such as normalizing to the 0-1 range).

[0138] Feature Selection: Selecting the most relevant features based on the relevance or importance of the data to improve the efficiency of the model.

[0139] By using machine learning models, the most suitable coating thickness can be dynamically predicted while monitoring the production environment and welding requirements in real time, thereby improving production efficiency, reducing coating defects and ensuring welding quality. The advantage of machine learning models is that they can learn and adaptively adjust based on historical data, which can not only optimize current production, but also handle complex environmental factors and welding parameter combinations, improving the accuracy and reliability of predictions.

[0140] Step S2300, constructing a material characteristic and coating adhesion relationship table, searching for a second coating adhesion corresponding to the real-time material data from the material characteristic and coating adhesion relationship table according to the real-time material data on the surface of the printed circuit board; calculating a third thickness value d3 according to the second coating adhesion; Specifically, the goal of step S2300 is to establish a quantitative relationship table between material characteristics and coating adhesion, find the corresponding adhesion value according to the real-time material characteristic data (such as conductivity, surface energy, etc.), and calculate the third thickness value d3 using the relationship between adhesion and coating thickness. The relationship table between material characteristics and coating adhesion is established on the basis of a large amount of experimental data. The table lists the coating adhesion values ​​corresponding to different material characteristics (such as surface energy, roughness, conductivity, etc.). The adhesion values ​​in the table are usually obtained through experimental measurements, reflecting the adhesion strength of the coating under different material surface conditions. For example, when the surface energy of the material is high, the adhesion of the coating is usually strong, so the thickness of the coating can also be increased accordingly; when the surface energy is low, the adhesion of the coating is weak, and the thickness of the coating needs to be reduced to prevent the coating from being poorly adhered.

[0141] Through real-time material data (such as conductivity, surface energy, etc.), the corresponding adhesion value A' is found from the material characteristics and coating adhesion relationship table. Then, the adhesion of the second coating is converted into the third thickness value d3 using the adhesion-thickness conversion formula; the adhesion-thickness conversion formula is a quantitative relationship between adhesion and coating thickness obtained through experimental fitting. When the adhesion of the second coating A' is stronger, the third thickness value d3 will be smaller. Conversely, when the adhesion of the second coating is weaker, the third thickness value is larger. This is because on surfaces with stronger adhesion, the coating can adhere better to the substrate, and stable adhesion can be guaranteed even if the coating is thin; on surfaces with weaker adhesion, thinner coatings may fall off easily, so thicker coatings are required to ensure their firmness.

[0142] By establishing and applying the relationship between material characteristics and adhesion, the coating thickness can be dynamically adjusted according to the surface conditions of different materials. The conversion formula between adhesion and coating thickness provides a quantitative basis to ensure that the coating can be stably adhered under different material characteristics and avoid coating peeling or unevenness.

[0143] Step S2400, dividing the first thickness value, the second thickness value and the third thickness value into corresponding thickness levels L1, L2 and L3 according to a preset thickness level division standard; Further, step S2400 includes: Step S2410, obtaining a preset thickness grade classification standard, wherein the thickness grade classification standard divides the coating thickness into n1 thickness grades, and each thickness grade corresponds to a coating thickness interval; Step S2420, according to the coating thickness interval corresponding to each thickness level, determine the thickness levels to which the first thickness value d1, the second thickness value d2 and the third thickness value d3 belong, and obtain the corresponding thickness levels L1, L2 and L3.

[0144] Specifically, the core purpose of step S2400 is to classify the coating thickness values ​​(such as the first thickness value d1, the second thickness value d2 and the third thickness value d3) obtained by different methods into corresponding thickness levels (L1, L2 and L3) according to the preset coating thickness level classification standard. This process helps to unify the thickness values ​​from different sources into a standard framework, which is convenient for subsequent comprehensive analysis and decision-making.

[0145] The thickness grade classification standard is formulated according to different production needs and quality requirements. Generally, the coating thickness grade standard is divided according to the functional requirements, durability, adhesion and other factors of the coating. The coating thickness will be divided into n1 different grades. Each grade corresponds to a coating thickness range, and the upper and lower limits of the coating thickness range are set according to the production process requirements and the coating performance requirements.

[0146] The thickness classification standard can be based on the functional requirements of the coating. For example, some applications may require a thinner coating (such as L1 grade) to ensure that there is no excessive heat accumulation on the surface of the component; while other applications may require a thicker coating (such as L3 grade) to increase wear resistance or improve corrosion resistance. It can also be based on a standardized range. The coating thickness classification standard can be set using industry standards (such as ISO, IEC, etc.) or customized standards within the company. These standards define different thickness ranges based on the physical properties, mechanical strength, and adhesion requirements of the coating.

[0147] Through clear grading standards, coating thickness can be effectively quantified and different coating quality and functional requirements can be classified. This helps to accurately control the coating thickness during the production process, ensuring that the final product meets the predetermined quality requirements, and also facilitates quality control and the execution of subsequent decisions. By dividing the coating thickness values ​​into different thickness grades, a clear basis can be provided for subsequent production decisions. Different thickness grades represent different production requirements and coating functions, which can help with quality control, product specification confirmation and process adjustment during the production process. In addition, thickness grade division helps to simplify complex coating management, so that coatings of different thicknesses can be quickly matched to the corresponding production processes and quality standards.

[0148] Step S2500, obtaining a coating thickness adjustment value according to the thickness levels L1, L2 and L3 corresponding to the first thickness value d1, the second thickness value d2 and the third thickness value d3; Furthermore, if Figure 5 As shown, step S2500 includes: Step S2510, determining whether the thickness levels L1, L2 and L3 are consistent; Step S2520, if L1, L2 and L3 are consistent, then take the median value of the coating thickness interval of the corresponding thickness level as the coating thickness adjustment value; Step S2530: If L1, L2 and L3 are inconsistent, the final thickness level L is determined according to the preset priority rule, and the median of the coating thickness interval corresponding to the final thickness level L is taken as the coating thickness adjustment value.

[0149] Specifically, the purpose of step S2500 is to obtain the coating thickness adjustment value based on the thickness levels (L1, L2, L3) and the corresponding coating thickness intervals determined in the previous steps, and to formulate a reasonable coating thickness adjustment plan. The core of this process is to comprehensively judge and adjust the coating thickness based on the thickness values ​​from different sources to adapt it to current production needs.

[0150] Determine whether the thickness levels (L1, L2 and L3) obtained from different sources (first thickness value d1, second thickness value d2 and third thickness value d3) are consistent. The specific determination method is: If L1=L2=L3, it means that the recommended coating thickness values ​​calculated from various factors (welding requirements, material characteristics, environmental characteristics) are all within the same grade range. At this time, the median of this common grade and the corresponding coating thickness range can be directly used as the adjustment plan. This method can greatly simplify the adjustment process. When the coating thickness values ​​from different sources are consistent, the common recommended thickness can be directly used, reducing the complexity of decision-making. It ensures efficient adjustment when the coating thickness is consistent, making the production process smoother.

[0151] If L1, L2 and L3 are inconsistent, the final thickness level L needs to be determined according to the preset priority rules, and the median value is selected from the coating thickness range corresponding to the level as the coating thickness adjustment value.

[0152] By comparing the consistency of the levels corresponding to each thickness value, it is possible to quickly determine whether the coating thickness is affected by different factors. If they are consistent, it means that the production process and material conditions are relatively stable, and a unified adjustment plan can be directly adopted; if they are inconsistent, further processing is required to ensure that the final selected coating thickness meets the most critical process requirements.

[0153] Priority rules: Welding requirements Material characteristics > environmental characteristics, that is, the influence of welding requirements is the most important, followed by material characteristics, and finally environmental characteristics. Once the final thickness grade L is determined, the median value can be calculated through the coating thickness range corresponding to the grade and used as the final coating thickness adjustment plan, which includes the coating thickness adjustment value.

[0154] By comparing the adjustment levels from different sources, various influencing factors can be comprehensively considered, the weights between different factors can be balanced, and a relatively reasonable coating thickness adjustment scheme can be obtained. The priority rule reflects the importance of different factors to coating quality. Welding requirements are usually the most important, followed by material characteristics, and finally environmental characteristics.

[0155] For example, it is assumed that the preset thickness classification standard is as follows: Thickness grade G1: [10μm, 18μm]; Thickness grade G2: (18μm, 26μm]; Thickness grade G3: (26μm, 34μm]; Thickness grade G4: (34μm, 42μm]; Thickness grade G5: (42μm, 50μm].

[0156] In a certain production, through steps S2100-S2300, the following three thickness values ​​are obtained: The first thickness value d1 = 20 μm (derived from welding requirements); The second thickness value d2 = 32 μm (derived from environmental characteristics); The third thickness value d3 = 24 μm (from the material characteristics).

[0157] The execution process of step S2400 is as follows: Step S2420, determine to which thickness level the three thickness values ​​belong respectively: d1=20μm falls within the interval (18μm, 26μm], so the corresponding thickness grade is L1=G2; d2=32μm falls within the interval (26μm, 34μm], so the corresponding thickness grade is L2=G3; d3=24μm falls within the interval (18μm, 26μm], so the corresponding thickness grade is L3=G2.

[0158] The execution process of step S2500 is as follows: Step S2510, determine whether L1, L2 and L3 are consistent: L1=G2, L2=G3, L3=G2, the three thickness levels are not completely consistent.

[0159] Step S2530: determine the final adjustment level L according to the priority rule L1>L3>L2: Because L1=L3=G2, and L1 has the highest priority, the final thickness level L=L1=G2. Take the median value 22μm of the interval (18μm, 26μm] corresponding to thickness level G2 as the coating thickness adjustment value to generate a coating thickness adjustment plan.

[0160] In this example, although the three thickness values ​​give different thickness levels, the adjustment scheme corresponding to the welding requirement (L1) is finally selected through the priority rule. This shows that in the coating thickness adjustment process, the importance of welding requirements is higher than material characteristics and environmental characteristics.

[0161] According to the coating thickness adjustment plan, it can ensure that the coating thickness meets the predetermined standard during the production process, avoiding quality problems caused by too thick or too thin coating. Through the systematic adjustment process, production efficiency can be improved and quality fluctuations can be reduced.

[0162] Step S3000, according to the coating thickness adjustment value and the target coating thickness range [d min ,d max ], and obtain the final coating thickness control value d4; and perform coating production control according to the coating thickness control value d4.

[0163] Furthermore, step S3000 includes: Step S3100, if the coating thickness adjustment value is within the target coating thickness range, the coating thickness adjustment value is used as the final coating thickness control value d4, and step S3300 is executed; if the coating thickness adjustment value is not within the target coating thickness range, step S3200 is executed; Step S3200, calculating the coating thickness adjustment value and the target coating thickness range [d min ,d max ] The upper limit deviation Δd1 and the lower limit deviation Δd2; if |Δd1|≤|Δd2|, then take d max As the corrected coating thickness adjustment value d'; if |Δd1|>|Δd2|, then take d min as the corrected coating thickness adjustment value d'; taking the corrected coating thickness adjustment value d' as the final coating thickness control value d4, executing step S3300; Step S3300, adjust the coating equipment parameters according to the coating thickness control value d4, spray the OSP coating on the surface of the printed circuit board, and carry out coating production; obtain the measured coating thickness value d0 after spraying; calculate the deviation Δd between the measured coating thickness value d0 and the coating thickness control value d4, if Δd is less than the preset thickness deviation threshold ε, it is considered that the OSP coating thickness meets the requirements and the coating production is ended; otherwise, fine-tune the coating equipment parameters and re-carry out coating production until the OSP coating thickness meets the requirements.

[0164] Specifically, step S3000 describes a process of determining a final coating thickness control value according to a comparison result between the coating thickness adjustment value and the target coating thickness range, and performing coating production control based on the control value.

[0165] In step S3100, it is first determined whether the coating thickness adjustment value falls within the target coating thickness range [d min ,d max ]. The target coating thickness range here refers to the allowable deviation range of the ideal coating thickness predetermined according to factors such as component welding requirements, production environment conditions and substrate surface conditions, which is determined by the lower limit value d min and the upper limit d max If the coating thickness adjustment value is within the range, it is directly used as the final coating thickness control value d4 to guide subsequent coating production; if it exceeds the range, the coating thickness adjustment value needs to be corrected and step S3200 is executed.

[0166] The purpose of step S3200 is to find a correction value closest to the target range as the final control value when the coating thickness adjustment value exceeds the target range. Specifically, the deviation Δd1 between the coating thickness adjustment value and the upper limit of the target coating thickness range and the deviation Δd2 between the lower limit are calculated, and the absolute values ​​of the two deviations are compared. If |Δd1|≤|Δd2|, it indicates that the adjustment value is closer to the upper limit, then the upper limit value d is taken. max As the corrected coating thickness adjustment value d'; conversely, if |Δd1|>|Δd2|, the lower limit value d is taken. min As the correction value d'. max Or d min , can ensure that the corrected value falls within the target range, thereby preventing the coating thickness from seriously deviating from the expected value. The corrected coating thickness adjustment value d' is used as the final coating thickness control value d4 and is passed to step S3300.

[0167] Step S3300 is to adjust the coating equipment parameters according to the coating thickness control value d4 and start the actual coating production. The coating equipment parameters here include various process parameters that affect the coating thickness, such as the spraying pressure, spraying distance, spraying angle and spraying time of the spray gun. By adjusting these parameters, the flow rate, atomization degree and deposition rate of the coating material during the spraying process can be accurately controlled, thereby achieving the adjustment of the coating thickness. After the coating production is completed, an online thickness gauge and other equipment are used to obtain the actual coating thickness measurement value d0 formed on the surface of the printed circuit board, which is compared with the coating thickness control value d4 to calculate the deviation Δd. If the deviation is less than the preset thickness deviation threshold ε, it is considered that the OSP coating thickness meets the requirements and the coating production process ends; otherwise, it is necessary to return to adjust the coating equipment parameters, fine-tune and re-produce the coating until the requirements are met.

[0168] Steps S3100-S330 make full use of the idea of ​​closed-loop feedback control. By real-time monitoring of the coating thickness and comparing it with the target value (coating thickness control value), the production parameters are dynamically adjusted, and the coating thickness is finally controlled within the expected target range. This method overcomes the problems of open-loop control being easily affected by external interference and unstable coating thickness, and has stronger robustness and adaptability. At the same time, the comparison and correction process of the coating thickness adjustment value and the target range are separated, and various optimization algorithms, such as fuzzy control and adaptive control, can be flexibly introduced without affecting the overall control process, so as to further improve the control accuracy and stability of the coating thickness.

[0169] For example, assuming the target coating thickness range is [10μm, 20μm], the coating thickness adjustment value calculated in the previous step is 25μm, which exceeds the target range. At this time, step S3200 will calculate the deviations of 25μm from 10μm and 20μm respectively, and the results are Δd1=5μm and Δd2=15μm. Because |Δd1|<|Δd2|, d is selected. max That is, 20μm is used as the corrected coating thickness adjustment value as the final control target value. Then step S3300 optimizes the process parameters of the spray gun according to the target value 20μm, such as appropriately reducing the spray pressure, shortening the spray time, etc., to control the thickness of the OSP coating to about 20μm in actual production. The actual coating thickness measured by the thickness gauge may be 19.5μm, and the deviation from 20μm is 0.5μm, which is less than the preset deviation threshold (for example, 1μm). Therefore, it is considered that the coating production this time meets the requirements and no further adjustment is required.

[0170] In summary, the OSP coating thickness adaptive control method provided by the present invention automatically calculates the adjustment value and control value of the coating thickness by real-time collection of production environment parameters, analysis of component welding requirements and substrate surface characteristics, and real-time monitoring and dynamic optimization during the production process, and finally stably controls the coating thickness within a preset target range. This method overcomes the limitations of manual experience control, reduces the impact of coating thickness deviation on component welding quality, has the advantages of good coating uniformity, high consistency, strong welding reliability, etc., can significantly improve the production efficiency and yield rate of printed circuit boards, and has strong practical value and promotion potential.

[0171] Example 2 This embodiment provides an OSP coating thickness adjustment system in printed circuit board production based on embodiment 1, such as Figure 6 As shown, including: Target thickness determination module: used to obtain the design parameters of the printed circuit board, build a component welding requirement database, and determine the welding requirements of the target component type; collect real-time environmental data and real-time material data on the surface of the printed circuit board, and determine the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; Thickness adjustment value determination module: obtain a first thickness value d1 according to the welding requirements of the target component type; obtain a second thickness value d2 according to the real-time environmental data of the printed circuit board surface; obtain a third thickness value d3 according to the real-time material data of the printed circuit board surface; divide the first thickness value, the second thickness value and the third thickness value into corresponding thickness levels L1, L2 and L3; obtain a coating thickness adjustment value according to the thickness levels L1, L2 and L3; Coating production control module: According to the coating thickness adjustment value and the target coating thickness range [d min ,d max ], and obtain the final coating thickness control value d4; and perform coating production control according to the coating thickness control value d4.

[0172] In the target thickness determination module, the welding requirements for determining the target component type include: Step S1110, obtaining design parameters of the printed circuit board, wherein the design parameters include the package type, the number of pins and the package size of each component; Step S1120, classifying the components on the printed circuit board according to the package type, number of pins and package size of each component in combination with a preset component classification rule to obtain N component types; Step S1130, determining the welding temperature, welding time and solder fluidity of each component type according to the package type, pin number and package size of each component, and constructing a component welding requirement database; Step S1140, obtaining the package type, the number of pins and the package size of the target component, and determining the type of the target component according to the package type, the number of pins and the package size of the target component; Step S1150 , obtaining the soldering temperature of the target component type, the soldering time of the target component type, and the solder fluidity of the target component type from the component soldering requirement database.

[0173] In the target thickness determination module, the target coating thickness range is determined by: Step S1410, calculating the recommended coating thickness range under the current production environment conditions according to the real-time environmental data of the printed circuit board surface and the preset production environment and coating thickness relationship model, and marking it as the production environment recommended coating thickness range; Step S1420, establishing a model for the relationship between material properties and coating adhesion, calculating the coating adhesion according to the real-time material data on the surface of the printed circuit board and the model for the relationship between material properties and coating adhesion; obtaining a recommended coating thickness range under the current material surface state according to the coating adhesion, and marking it as the recommended coating thickness range under the material surface state; Step S1430, determining the final target coating thickness range [d min ,d max ],in, is the lower limit of the target coating thickness range, is the upper limit of the target coating thickness range.

[0174] The step S1430 includes: Step S1431, calculate the theoretical coating thickness d according to the welding requirements of the target component type s ; Step S1432, recommend coating thickness range based on production environment Calculate the environmental adjustment factor ; Recommended coating thickness range based on material surface conditions Calculate material factor adjustment coefficient ;in, The lower limit of the coating thickness range is recommended for production environments. The upper limit of the coating thickness range is recommended for production environments; The lower limit of the coating thickness range recommended for the material surface condition, The upper limit of the coating thickness range is recommended for the material surface condition; Step S1433, according to the theoretical coating thickness , Environmental Factor Adjustment Coefficient and material factor adjustment coefficient , calculate the final recommended coating thickness ; Step S1434, according to the final recommended coating thickness and preset coating thickness safety margin factor , calculate the upper limit of the target coating thickness range and lower limit .

[0175] In the thickness adjustment value determination module, obtaining the first thickness value d1 according to the welding requirements of the target component type includes: Step S2110, obtaining historical welding data of the target component type, wherein the historical welding data includes historical welding parameters and historical coating thickness corresponding to the historical welding parameters; the historical welding parameters include historical welding temperature, historical welding time and historical solder fluidity; Step S2120, constructing a mapping relationship model between welding parameters and coating thickness based on historical welding data of the target component type; Step S2130: input the welding requirement of the target component type into the mapping relationship model to obtain a first thickness value d1.

[0176] In the thickness adjustment value determination module, the dividing of the first thickness value, the second thickness value and the third thickness value into corresponding thickness levels L1, L2 and L3 includes: Step S2410, obtaining a preset thickness grade classification standard, wherein the thickness grade classification standard divides the coating thickness into n1 thickness grades, and each thickness grade corresponds to a coating thickness interval; Step S2420, according to the coating thickness interval corresponding to each thickness level, determine the thickness levels to which the first thickness value d1, the second thickness value d2 and the third thickness value d3 belong, and obtain the corresponding thickness levels L1, L2 and L3.

[0177] In the thickness adjustment value determination module, obtaining the coating thickness adjustment value according to the thickness levels L1, L2 and L3 includes: Step S2510, determining whether the thickness levels L1, L2 and L3 are consistent; Step S2520, if L1, L2 and L3 are consistent, then take the median value of the coating thickness interval of the corresponding thickness level as the coating thickness adjustment value; Step S2530: If L1, L2 and L3 are inconsistent, the final thickness level L is determined according to the preset priority rule, and the median of the coating thickness interval corresponding to the final thickness level L is taken as the coating thickness adjustment value.

[0178] In the coating production control module, the coating thickness adjustment value and the target coating thickness range [d min ,d max ], and obtain the final coating thickness control value d4; and coating production control according to the coating thickness control value d4 includes: Step S3100, if the coating thickness adjustment value is within the target coating thickness range, the coating thickness adjustment value is used as the final coating thickness control value d4, and step S3300 is executed; if the coating thickness adjustment value is not within the target coating thickness range, step S3200 is executed; Step S3200, calculating the coating thickness adjustment value and the target coating thickness range [d min ,d max ] The upper limit deviation Δd1 and the lower limit deviation Δd2; if |Δd1|≤|Δd2|, then take d max As the corrected coating thickness adjustment value d'; if |Δd1|>|Δd2|, then take d min as the corrected coating thickness adjustment value d'; taking the corrected coating thickness adjustment value d' as the final coating thickness control value d4, executing step S3300; Step S3300, adjust the coating equipment parameters according to the coating thickness control value d4, spray the OSP coating on the surface of the printed circuit board, and carry out coating production; obtain the measured coating thickness value d0 after spraying; calculate the deviation Δd between the measured coating thickness value d0 and the coating thickness control value d4, if Δd is less than the preset thickness deviation threshold ε, it is considered that the OSP coating thickness meets the requirements and the coating production is ended; otherwise, fine-tune the coating equipment parameters and re-carry out coating production until the OSP coating thickness meets the requirements.

[0179] Example 3 This embodiment discloses an electronic device, which may include one or more processors and one or more memories, wherein the memories store computer-readable codes, which, when executed by the one or more processors, may execute the OSP coating thickness adjustment method in printed circuit board production as described above.

[0180] The method or system according to the embodiment of the present application can also be implemented with the help of the architecture of an electronic device. The electronic device may include a bus, one or more CPUs, a read-only memory (ROM), a random access memory (RAM), a communication port connected to a network, an input / output component, a hard disk, etc. A storage device in the electronic device, such as a ROM or a hard disk, can store the OSP coating thickness adjustment method in the production of printed circuit boards provided in the present application. The OSP coating thickness adjustment method in the production of printed circuit boards may, for example, include: obtaining the design parameters of the printed circuit board, building a component welding requirement database, and determining the welding requirements of the target component type; collecting real-time environmental data and real-time material data on the surface of the printed circuit board, and determining the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; obtaining a first thickness value d1 according to the welding requirements of the target component type; obtaining a second thickness value d2 according to the real-time environmental data on the surface of the printed circuit board; obtaining a third thickness value d3 according to the real-time material data on the surface of the printed circuit board; dividing the first thickness value, the second thickness value and the third thickness value into corresponding thickness grades L1, L2 and L3; obtaining a coating thickness adjustment value according to the thickness grades L1, L2 and L3; obtaining a final coating thickness control value d4 according to the coating thickness adjustment value and the target coating thickness range; and controlling coating production according to the coating thickness control value d4.

[0181] Furthermore, the electronic device may also include a user interface. Of course, the architecture disclosed in the present invention is only exemplary, and when implementing different devices, one or more components in the electronic device disclosed in the present invention may be omitted according to actual needs.

[0182] Example 4 This embodiment discloses a computer-readable storage medium, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor, the OSP coating thickness adjustment method in the printed circuit board production of the embodiment of the present application can be executed. The storage medium includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0183] In addition, according to an embodiment of the present application, the process described above with reference to the flowchart may be implemented as a computer software program. For example, the present application provides a non-transitory machine-readable storage medium, which stores machine-readable instructions, and the machine-readable instructions can be executed by a processor to execute instructions corresponding to the method steps provided in the present application, for example: obtaining design parameters of a printed circuit board, building a component welding requirement database, and determining the welding requirements of a target component type; collecting real-time environmental data and real-time material data on the surface of the printed circuit board, and determining a target coating thickness range based on the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; obtaining a first thickness value d1 based on the welding requirements of the target component type; obtaining a second thickness value d2 based on the real-time environmental data on the surface of the printed circuit board; obtaining a third thickness value d3 based on the real-time material data on the surface of the printed circuit board; dividing the first thickness value, the second thickness value and the third thickness value into corresponding thickness grades L1, L2 and L3; obtaining a coating thickness adjustment value based on the thickness grades L1, L2 and L3; obtaining a final coating thickness control value d4 based on the coating thickness adjustment value and the target coating thickness range; and performing coating production control based on the coating thickness control value d4. When the computer program is executed by a central processing unit (CPU), the above functions defined in the method of the present application are performed.

[0184] The methods, systems, and devices of the present application may be implemented in many ways. For example, the methods, systems, and devices of the present application may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present application are not limited to the order specifically described above unless otherwise specified. In addition, in some embodiments, the present application may also be implemented as programs recorded in a recording medium, which include machine-readable instructions for implementing the method according to the present application. Therefore, the present application also covers recording media storing programs for executing the method according to the present application.

[0185] In addition, the parts of the above-mentioned technical solutions provided in the embodiments of the present application that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail to avoid excessive redundancy.

[0186] The specific implementation modes as described above further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation mode of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for adjusting the thickness of OSP coating in printed circuit board production, characterized in that: The method comprises: Acquire design parameters of the printed circuit board, build a component welding requirement database, and determine the welding requirements of the target component type; collect real-time environmental data and real-time material data on the surface of the printed circuit board, and determine the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; According to the welding requirements of the target component type, a first thickness value d1 is obtained; according to the real-time environmental data of the surface of the printed circuit board, a second thickness value d2 is obtained; according to the real-time material data of the surface of the printed circuit board, a third thickness value d3 is obtained; the first thickness value, the second thickness value and the third thickness value are divided into corresponding thickness levels L1, L2 and L3; according to the thickness levels L1, L2 and L3, a coating thickness adjustment value is obtained; According to the coating thickness adjustment value and the target coating thickness range, a final coating thickness control value d4 is obtained; and coating production control is performed according to the coating thickness control value d4.

2. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 1, characterized in that: The welding requirements for determining the target component type include: Acquire design parameters of the printed circuit board, wherein the design parameters include package type, number of pins and package size of each component; According to the package type, pin number and package size of each component, combined with the preset component classification rules, the components on the printed circuit board are classified to obtain N component types; Determine the soldering temperature, soldering time and solder fluidity of each component type according to the package type, number of pins and package size of each component, and build a component soldering requirement database; Obtaining the package type, the number of pins and the package size of the target component, and determining the target component type according to the package type, the number of pins and the package size of the target component; A soldering temperature of a target component type, a soldering time of a target component type, and solder fluidity of a target component type are obtained from a component soldering requirement database.

3. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 1, characterized in that: Determining the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and the real-time material data of the printed circuit board surface includes: According to the real-time environmental data of the printed circuit board surface and the preset production environment and coating thickness relationship model, the recommended coating thickness range under the current production environment conditions is calculated and marked as the recommended coating thickness range for the production environment; Establish a model for the relationship between material properties and coating adhesion, and calculate coating adhesion based on real-time material data on the surface of the printed circuit board and the model for the relationship between material properties and coating adhesion; obtain a recommended coating thickness range under the current material surface state based on the coating adhesion, and mark it as the recommended coating thickness range for the material surface state; According to the welding requirements of the target component type, the recommended coating thickness range of the production environment and the recommended coating thickness range of the material surface condition, the final target coating thickness range [d min ,d max ],in, is the lower limit of the target coating thickness range, is the upper limit of the target coating thickness range.

4. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 3, characterized in that: The final target coating thickness range [d min ,d max ]include: Calculate the theoretical coating thickness d based on the welding requirements of the target component type s ; Calculate the environmental factor adjustment coefficient based on the recommended coating thickness range for the production environment ; Calculate the material factor adjustment coefficient based on the recommended coating thickness range according to the material surface condition ; According to the theoretical coating thickness , Environmental Factor Adjustment Coefficient and material factor adjustment coefficient , calculate the final recommended coating thickness ; According to the final recommended coating thickness and preset coating thickness safety margin factor , calculate the upper limit of the target coating thickness range and lower limit .

5. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 1, characterized in that: The step of obtaining the first thickness value d1 according to the welding requirements of the target component type includes: Acquire historical welding data of the target component type, wherein the historical welding data includes historical welding parameters and historical coating thickness corresponding to the historical welding parameters; the historical welding parameters include historical welding temperature, historical welding time and historical solder fluidity; Based on the historical welding data of the target component type, a mapping relationship model between welding parameters and coating thickness is constructed; the welding requirements of the target component type are input into the mapping relationship model to obtain a first thickness value d1.

6. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 1, characterized in that: The dividing the first thickness value, the second thickness value and the third thickness value into corresponding thickness levels L1, L2 and L3 comprises: Obtaining a preset thickness grade classification standard, wherein the thickness grade classification standard divides the coating thickness into n1 thickness grades, and each thickness grade corresponds to a coating thickness interval; According to the coating thickness interval corresponding to each thickness level, the thickness levels to which the first thickness value d1, the second thickness value d2 and the third thickness value d3 belong are determined, and the corresponding thickness levels L1, L2 and L3 are obtained.

7. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 6, characterized in that: The method of obtaining the coating thickness adjustment value according to the thickness levels L1, L2 and L3 includes: Determine whether the thickness grades L1, L2 and L3 are consistent; If L1, L2 and L3 are consistent, the median value of the coating thickness interval of the corresponding thickness grade is taken as the coating thickness adjustment value; If L1, L2 and L3 are inconsistent, the final thickness grade L is determined according to the preset priority rule, and the median value of the coating thickness interval corresponding to the final thickness grade L is taken as the coating thickness adjustment value.

8. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 4, characterized in that: The method of obtaining the final coating thickness control value d4 according to the coating thickness adjustment value and the target coating thickness range includes: If the coating thickness adjustment value is within the target coating thickness range, the coating thickness adjustment value is used as the final coating thickness control value d4; if the coating thickness adjustment value is not within the target coating thickness range, the coating thickness adjustment value and the target coating thickness range [d min ,d max ] The upper limit deviation Δd1 and the lower limit deviation Δd2; if |Δd1|≤|Δd2|, then take d max As the corrected coating thickness adjustment value d'; if |Δd1|>|Δd2|, then take d min As the corrected coating thickness adjustment value d'; the corrected coating thickness adjustment value d' is used as the final coating thickness control value d4.

9. The method for adjusting the thickness of OSP coating in the production of printed circuit boards according to claim 8, characterized in that: The coating production control according to the coating thickness control value d4 includes: Adjust the coating equipment parameters according to the coating thickness control value d4, spray the OSP coating on the surface of the printed circuit board, and carry out coating production; obtain the measured coating thickness value d0 after spraying; calculate the deviation Δd between the measured coating thickness value d0 and the coating thickness control value d4. If Δd is less than the preset thickness deviation threshold ε, it is considered that the OSP coating thickness meets the requirements and the coating production is terminated; otherwise, fine-tune the coating equipment parameters and re-carry out coating production until the OSP coating thickness meets the requirements.

10. A system for adjusting the thickness of an OSP coating in the production of a printed circuit board, which is used to implement the method for adjusting the thickness of an OSP coating in the production of a printed circuit board according to any one of claims 1 to 9, characterized in that: The system comprises: Target thickness determination module: used to obtain the design parameters of the printed circuit board, build a component welding requirement database, and determine the welding requirements of the target component type; collect real-time environmental data and real-time material data on the surface of the printed circuit board, and determine the target coating thickness range according to the welding requirements of the target component type, the real-time environmental data and real-time material data on the surface of the printed circuit board; Thickness adjustment value determination module: obtain a first thickness value d1 according to the welding requirements of the target component type; obtain a second thickness value d2 according to the real-time environmental data of the printed circuit board surface; obtain a third thickness value d3 according to the real-time material data of the printed circuit board surface; divide the first thickness value, the second thickness value and the third thickness value into corresponding thickness levels L1, L2 and L3; obtain a coating thickness adjustment value according to the thickness levels L1, L2 and L3; Coating production control module: According to the coating thickness adjustment value and the target coating thickness range [d min ,d max ], and obtain the final coating thickness control value d4; and perform coating production control according to the coating thickness control value d4.

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