Plating solution formula process optimization method and system

Abstract

The invention discloses a plating solution formula process optimization method and system, and relates to the technical field of plating solutions, and the method comprises the following steps: obtaining an initial formula; identifying the electroplating process parameters of every two plating layers in the multiple plating layers, and outputting electroplating change parameters; performing adjustment complexity identification on the change parameters; generating a far penalty factor according to the adjustment complexity; the plating layer sequence is input into a plating layer sequence optimizer for optimization, and a plating layer optimization sequence is obtained; and the initial plating solution formula is optimized based on the plating layer optimization sequence, and an optimized plating solution formula is obtained. The technical problem that the plating layer structure and performance cannot be accurately controlled due to the fact that electroplating formula parameters cannot be finely regulated and controlled according to workpiece multi-layer electroplating in existing plating solution formula optimization is solved, the plating solution formula parameters are adjusted according to the plating layer sequence, the plating solution formula is prevented from being repeatedly replaced according to the requirements, and the plating solution quality is improved. And the uniformity and the adhesive force of the plating layer are improved.

Description

Technical Field

[0001] The present application relates to the field of electroplating solution technology, and specifically to a method and system for optimizing a plating solution formulation process. Background Art

[0002] With the continuous advancement of modern industrial technology, electroplating, as an important surface treatment process, has become increasingly widely used, and the performance and quality requirements of electroplated products are becoming increasingly higher. Electroplating is to deposit one or more layers of metal or alloy on the surface of the substrate to improve its appearance, corrosion resistance, conductivity and other properties. However, different electroplating requirements often require different coating structures and properties, which requires fine regulation of the electroplating process, which becomes a vital part of the electroplating process. However, in the traditional electroplating process, the deposition speed and adhesion of different metals or alloys are affected by the plating solution environment, and the plating solution formula parameters cannot be accurately adjusted, which makes it difficult to control the uniformity, density and adhesion of the coating to the substrate, resulting in low quality and performance of the electroplated products.

[0003] Therefore, in the current technology related to optimization of plating solution formula process, there is a technical problem that the plating formula parameters cannot be finely adjusted according to the multi-layer electroplating of the workpiece, resulting in the inability to accurately control the structure and performance of the coating. Summary of the invention

[0004] The present application provides a method and system for optimizing the process of plating solution formula, and adopts technical means such as parameter identification, adjustment complexity identification, and sequential optimization to solve the technical problem that the existing plating solution formula optimization cannot finely adjust the electroplating formula parameters according to the multi-layer electroplating of the workpiece, resulting in the inability to accurately control the structure and performance of the coating. The application achieves the technical effect of adjusting the plating solution formula parameters according to the plating sequence, so that the plating solution formula avoids repeated processes and is replaced as needed, thereby improving the uniformity and adhesion of the coating.

[0005] The present application provides a method for optimizing a plating solution formulation process, the method comprising: obtaining an initial plating solution formulation; The electroplating process parameters of every two coatings in the multi-layer coating are identified, and the electroplating variation parameters between every two coatings are output, wherein the electroplating process parameters include electroplating solution parameters and electroplating control parameters; the adjustment complexity of the electroplating variation parameters between every two coatings is identified, and the adjustment complexity is output; according to the adjustment complexity, a distance penalty factor for every two coatings is generated; the distance penalty factor is input into a coating sequence optimizer, and the coating sequence optimizer optimizes the multi-layer coatings in the initial coating solution formula with the distance penalty factor as the optimization direction to obtain a coating optimization sequence, wherein the coating optimization sequence satisfies a first response condition, and the first response condition is that the sum of the adjustment complexities under the coating optimization sequence condition is minimized; the initial coating solution formula is optimized based on the coating optimization sequence to obtain an optimized coating solution formula.

[0006] In a possible implementation, the coating sequence optimizer optimizes the multi-layer coatings in the initial coating solution formula with the distance penalty factor as the optimization direction, and also performs the following processing: generates an initial coating sequence of N coatings in the initial coating solution formula, wherein N is the number of multi-layer coatings and N is a positive integer greater than or equal to 2; obtains N-1 coating neighboring groups of the N coatings and N-1 distance penalty factors corresponding to the N-1 coating neighboring groups; obtains an identified coating neighboring group that is greater than a preset penalty factor among the N-1 distance penalty factors; uses the identified coating neighboring group as the object of the next round of optimization, and the coatings belonging to the same neighboring group in the identified coating neighboring group are kept away from each other, and outputs an optimization result once, until the coating sequence optimizer converges and obtains a coating optimization sequence.

[0007] In a possible implementation, after obtaining the N-1 neighboring groups of the N coating layers, the following processing is performed: setting a compatible constraint condition, wherein the compatible constraint condition is a constraint condition in the coating sequence optimizer; The compatibility constraint conditions are used to identify the compatibility of the N-1 coating neighbor groups, and N-1 compatibility indicators are output; incompatible coating neighbor groups that do not meet the preset compatibility indicators among the N-1 compatibility indicators are obtained; the incompatible coating neighbor groups are used as the objects of the next round of optimization, and the coatings belonging to the same neighbor group in the incompatible coating neighbor groups are kept away from each other, so as to optimize the optimization result of the first round.

[0008] In a possible implementation, the compatibility constraint condition is used to identify the compatibility of the N-1 coating neighbor groups, and the following processing is performed: obtaining N-1 coating material groups in the N-1 coating neighbor groups; performing material adhesion, electrochemical compatibility and thermal stability analysis on each coating material group in the N-1 coating material groups, and outputting adhesion index, compatibility index and stability index; outputting N-1 compatibility indexes based on the adhesion index, the compatibility index and the stability index.

[0009] In a possible implementation, the adjustment complexity is identified for the electroplating change parameters between every two plating layers, the adjustment complexity is output, and the following processing is also performed: the electroplating change parameters are collected, the electroplating change parameters include electroplating solution change parameters and electroplating control change parameters; a first weight is assigned to the electroplating solution change parameters, and a second weight is assigned to the electroplating control change parameters, the first weight is greater than 2 times the second weight; a weight network layer is generated with the first weight and the second weight; a fully connected neural network is obtained; according to the electroplating solution change samples, the electroplating control change samples and the identification information identifying the adjustment complexity, the neural network is trained with the weight network layer to generate a complexity identification model, and according to the complexity identification model, the adjustment complexity is output.

[0010] In a possible implementation, the electroplating change parameters are collected and the following processing is performed: the indicators of the electroplating solution change parameters include at least solution type, solution concentration, solution content, additive type, additive concentration and additive content, and the sub-weights of each indicator are assigned in descending order.

[0011] In a possible implementation, the optimal order of coatings is obtained, and the following processing is also performed: the multi-layer coatings are identified to determine whether there is a composite coating among the multi-layer coatings, wherein the composite coating is a coating that is electroplated by two types of solutions; if there is a composite coating, the first coating neighbor group of the composite coating is determined, the first coating neighbor group is composed of two coatings that are away from the smallest penalty factor, and the first coating neighbor group includes the previous coating to be electroplated and the next coating to be electroplated; the coating sequence optimizer performs adaptive optimization on the remaining coatings according to the first coating neighbor group and the composite coating to obtain the optimal order of coatings.

[0012] In a possible implementation, after obtaining the initial plating solution formula, the following processing is also performed: determining the coating function type of the multi-layer coating according to the initial plating solution formula; delineating functional layer areas according to the coating function type, wherein each functional layer area includes multiple functional coatings; outputting the coating sequence of each functional layer area according to the coating sequence optimizer, and then splicing the functional layer areas to generate a coating optimization sequence. The present application also provides a plating solution formulation process optimization system, comprising: An initial plating solution formula acquisition module, the initial plating solution formula acquisition module is used to obtain an initial plating solution formula, wherein the initial plating solution formula is a plating solution formula for a multi-layer coating; An electroplating variation parameter output module, the electroplating variation parameter output module is used to identify the electroplating process parameters of every two coating layers in the multi-layer coating, and output the electroplating variation parameters between every two coating layers, wherein the electroplating process parameters include electroplating solution parameters and electroplating control parameters; An adjustment complexity identification module, the adjustment complexity identification module is used to identify the adjustment complexity of the electroplating variation parameters between every two plating layers, output the adjustment complexity, and generate a distance penalty factor between every two plating layers according to the adjustment complexity; A coating optimization sequence obtaining module, wherein the coating optimization sequence obtaining module is used to input the away penalty factor into a coating sequence optimizer, wherein the coating sequence optimizer optimizes the multi-layer coatings in the initial plating solution formula with the away penalty factor as the optimization direction to obtain a coating optimization sequence, wherein the coating optimization sequence satisfies a first response condition, and the first response condition is that the sum of the adjustment complexities under the coating optimization sequence condition is minimized; The optimized plating solution formula acquisition module is used to optimize the initial plating solution formula based on the plating layer optimization sequence to obtain the optimized plating solution formula.

[0013] The present application proposes a plating solution formula process optimization method and system to obtain an initial formula; identify the electroplating process parameters of every two plating layers in the multi-layer plating, and output the electroplating change parameters; identify the adjustment complexity of the change parameters; generate a distance penalty factor based on the adjustment complexity; input the optimization into a plating sequence optimizer to obtain a plating optimization sequence; optimize the initial plating solution formula based on the plating optimization sequence to obtain an optimized plating solution formula, which solves the technical problem that the existing plating solution formula optimization cannot finely adjust the electroplating formula parameters according to the multi-layer electroplating of the workpiece, resulting in the inability to accurately control the structure and performance of the plating layer, and achieves the technical effect of adjusting the plating solution formula parameters according to the plating sequence, so that the plating solution formula avoids process repetition and is replaced as needed, thereby improving the uniformity and adhesion of the plating layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of a process flow of a plating solution formulation process optimization method provided in an embodiment of the present application; Figure 2A schematic diagram of the structure of a plating solution formulation process optimization system provided in an embodiment of the present application.

[0016] Explanation of the reference numerals: initial plating solution formula acquisition module 10 , electroplating change parameter output module 20 , adjustment complexity identification module 30 , plating layer optimal sequence acquisition module 40 , optimized plating solution formula acquisition module 50 . DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The present application embodiment provides a method for optimizing the plating solution formulation process, such as Figure 1 As shown, the method includes: Step S100, obtaining an initial plating solution formula, wherein the initial plating solution formula is a plating solution formula for a multi-layer coating. Obtaining an initial plating solution formula, wherein the initial plating solution formula is a plating solution formula for a multi-layer coating, specifically refers to the plating solution components and their proportions required to be used when multiple layers of different metals or alloys need to be deposited on a substrate in order to meet a specific electroplating requirement. The plating solution formula for a multi-layer coating generally includes a variety of plating solution components required for different coatings, such as metal salts, additives, buffers, conductive salts, etc., and the type, concentration and proportion of each component are determined based on the electroplating principle, the characteristics of the coating material and the requirements of the electroplating process. For example, in a coating containing a copper layer, a nickel layer and a chromium layer, In a multi-layer electroplating system, the initial plating solution formula may include a copper plating solution formula, a nickel plating solution formula, and a chromium plating solution formula. Specifically, the copper plating solution formula contains copper salts (such as copper sulfate), additives (such as brighteners, leveling agents) and necessary conductive salts and buffers for depositing a copper layer; the nickel plating solution formula contains nickel salts, additives (such as stress relievers, wetting agents) and necessary conductive salts and pH adjusters for depositing a nickel layer on the copper layer; the chromium plating solution formula contains chromium salts, additives (such as hard chromium additives, decorative chromium additives) and necessary conductive salts and buffers for depositing a chromium layer on the nickel layer.

[0021] In a possible implementation, after step S100, step S150 is further included, determining the coating function type of the multi-layer coating according to the initial plating solution formula. By analyzing the chemical composition and its function in the initial plating solution formula, the main function of each coating layer is inferred and determined. For example, if the initial plating solution formula contains metal salts and additives for increasing corrosion resistance, it can be inferred that one of the coating layers may mainly play an anti-corrosion role; if the formula includes ingredients that can improve hardness and wear resistance, then the corresponding coating may be mainly used to increase hardness and wear resistance. The coating function type may also include decorative, conductive, magnetic, antioxidant, fatigue resistance, etc., which are usually achieved by adding specific additives to the plating solution formula or adjusting the type and concentration of metal salts. Step S160 is also included, defining functional layer areas according to the coating function type, wherein each functional layer area includes multiple functional coatings. According to the main function of each layer of the multi-layer coating, the entire coating structure is divided into different functional areas, wherein the functional layer area includes the bottom layer, the middle layer, and the outer layer, and each functional layer area includes multiple functional coatings that realize specific functions. For example, in a multi-layer electroplating structure, it may include an anti-corrosion layer area and a hardness enhancement layer area. The anti-corrosion layer area may be composed of multiple layers of metal or alloy coatings with different corrosion resistance, which is generally used as an intermediate layer; the hardness enhancement layer area may include coatings specifically used to improve hardness and wear resistance, such as hard chrome layers, which are generally used as bottom functional areas. It also includes step S170, according to the coating sequence optimizer, after outputting the coating sequence of each functional layer area, the functional layer areas are spliced ​​to generate a coating optimization sequence. The coating sequence optimizer is used to determine the best coating sequence for each functional layer area in the multi-layer coating, and then these functional layer areas are spliced ​​together according to certain logic or rules to form an overall, optimized coating sequence. Specifically, the coating sequence optimizer will simulate and evaluate different coating sequences according to preset optimization goals (such as maximizing corrosion resistance, improving hardness, optimizing appearance, etc.) and constraints (such as adhesion between coatings, process feasibility, etc.), and output the optimal coating sequence within each functional layer area through comparison. After that, the functional layer areas are spliced, and the transition and connection between the functional layer areas need to be considered to ensure that they can form a complete and coherent coating structure. During the splicing process, it may be necessary to fine-tune the thickness, composition or process parameters of some coatings to ensure that the performance of the overall coating is optimized, and finally generate a coating optimization sequence.

[0022] Step S200, identifying the electroplating process parameters of every two coating layers in the multi-layer coating, and outputting the electroplating variation parameters between every two coating layers, wherein the electroplating process parameters include electroplating solution parameters and electroplating control parameters. The electroplating process parameters of every two coating layers in the multi-layer coating are identified, the electroplating process parameters between adjacent coating layers in the multi-layer coating structure are analyzed in detail, the relevant electroplating process parameter change information is extracted, and the electroplating change parameters between every two coating layers are output, including electroplating solution parameters and electroplating control parameters. Specifically, the electroplating solution parameters mainly refer to the composition, concentration, pH value, etc. of the plating solution, which directly determine the properties and quality of the electroplated layer. For example, different coating layers may require the use of different metal salts as the main salt, or the type and concentration of additives need to be adjusted to improve the appearance and performance of the coating. The pH value affects the formation speed and uniformity of the electroplated layer, as well as the corrosion resistance of the coating. The electroplating control parameters include current density, temperature, anode and cathode area ratio, etc., which play a key role in the growth rate, thickness distribution and uniformity of the electroplated layer. For example, increasing the current density can speed up the formation speed of the coating, but may cause uneven coating or defects. Changes in temperature will affect the chemical reaction rate and ion diffusion rate in the plating solution, thereby affecting the electroplating effect. By identifying the changes in electroplating process parameters between every two coating layers, the electroplating process can be controlled more accurately to ensure that the quality and performance of each coating layer meet the expected requirements. When outputting the electroplating change parameters between every two coating layers, it is usually necessary to provide detailed parameter values ​​and change trends, and adjust and optimize the electroplating process accordingly.

[0023] Step S300, by identifying the adjustment complexity of the electroplating change parameters between every two coating layers, the adjustment complexity is output. Identifying the adjustment complexity of the electroplating change parameters between every two coating layers and outputting the adjustment complexity refers to evaluating and quantifying the adjustment complexity required for the change of electroplating process parameters between adjacent coating layers in a multi-layer coating structure, and outputting the adjustment complexity, including the range of change of electroplating process parameters, adjustment frequency, technical difficulty and potential risks. Specifically, when the range of change of electroplating process parameters between adjacent coating layers is large, the adjustment required is more complex. For example, if the current density or the plating solution temperature needs to be adjusted significantly, the corresponding adjustment process may be more cumbersome and delicate; if the electroplating process parameters between every two coating layers in the multi-layer coating need to be adjusted frequently, the overall adjustment complexity will increase; some electroplating process parameter adjustments may involve more advanced technical knowledge or operating skills. For example, optimizing the plating solution formula to improve the coating performance may require a deep understanding of the plating solution components and their interactions, so the adjustment complexity is also correspondingly high; the adjustment of electroplating process parameters may bring certain risks, such as unstable coating quality, reduced production efficiency or environmental pollution, which will also increase the adjustment complexity. Through comprehensive analysis of these factors, a quantitative adjustment complexity can be output.

[0024] In a possible implementation, step S300 further includes step S310, collecting electroplating variation parameters, wherein the electroplating variation parameters include electroplating solution variation parameters and electroplating control variation parameters. In the electroplating process, collecting electroplating variation parameters is crucial to ensuring the stability of the electroplating process and optimizing the electroplating quality. For example, as the electroplating process proceeds, the concentration of metal ions in the plating solution will gradually decrease. This is because metal ions are reduced to metal atoms on the electrode and deposited on the metal surface. The concentration of the plating solution needs to be regularly detected and supplemented and adjusted as needed to maintain a stable electroplating environment; changes in current density will directly affect the deposition rate and thickness distribution of the electroplated layer; temperature fluctuations may affect the chemical reaction rate and ion diffusion rate in the plating solution, thereby affecting the electroplating effect. By collecting and analyzing these electroplating variation parameters, the dynamic changes of the electroplating process can be understood more accurately, which helps to improve the performance and quality of the electroplated layer. It also includes step S320, assigning a first weight to the electroplating solution variation parameter and a second weight to the electroplating control variation parameter, wherein the first weight is greater than 2 times the second weight. The changing parameters of the electroplating solution directly determine the basic environment and conditions of the electroplating reaction, and directly affect the formation, structure and performance of the electroplated layer. Therefore, they play a vital role in the electroplating process. Therefore, a higher weight (i.e., the first weight) is assigned to the changing parameters of the electroplating solution; and the electroplating control changing parameters (such as current density, temperature, etc.), although they also have a certain influence on the formation and performance of the electroplated layer, their role is more to fine-tune the electroplating process based on the changing parameters of the electroplating solution, for further optimizing the electroplating effect, therefore, a lower weight (i.e., the second weight) is assigned to the electroplating control changing parameters; the second weight that is greater than 2 times the first weight is to more clearly indicate that the importance of the changing parameters of the electroplating solution in the electroplating process is far greater than the electroplating control changing parameters, which can ensure that when analyzing the changing parameters of the electroplating solution, the decisive influence of the changing parameters of the electroplating solution on the quality and performance of the electroplating can be more accurately reflected. It also includes step S330, generating a weight network layer with the first weight and the second weight. A weight network layer is constructed according to the first weight of the electroplating solution change parameter and the second weight of the electroplating control change parameter. In this weight network layer, each node may represent an electroplating parameter or a step of an electroplating process, and the connection between the nodes and their weights reflect the mutual influence and importance between these parameters or steps. It also includes step S340, obtaining a fully connected neural network. It also includes step S350, according to the electroplating solution change sample, the electroplating control change sample and the identification information of the identification adjustment complexity, the neural network is trained with the weight network layer to generate a complexity recognition model, and the complexity adjustment is output according to the complexity recognition model.Collect electroplating solution change samples and electroplating control change samples, covering parameter changes under different electroplating conditions, and identification information of adjustment complexity. According to the design of the weight network layer obtained above, build a fully connected neural network, take the electroplating solution change parameters and electroplating control change parameters as input, and perform feature extraction through the hidden layer. Specifically, use the prepared electroplating change samples and adjustment complexity identification information to train the neural network. The network will continuously adjust its weights and biases according to the input electroplating change parameters and the corresponding adjustment complexity identification information to minimize the difference between the predicted adjustment complexity and the actual adjustment complexity. Through iterative training and optimization, a complexity recognition model is obtained. The model can receive new electroplating change parameters as input and output the corresponding adjustment complexity prediction value. When it is necessary to evaluate the adjustment complexity of a certain electroplating process, it is only necessary to input the relevant electroplating solution change parameters and electroplating control change parameters into the complexity recognition model, and the model can output the corresponding adjustment complexity value.

[0025] In a possible implementation, the indicators of the electroplating solution change parameters in step S310 include at least solution type, solution concentration, solution content, additive type, additive concentration and additive content, and the sub-weights of each indicator are assigned in descending order. Specifically, the solution type is the most basic and key indicator of the electroplating solution change parameters. Different types of electroplating solutions correspond to different electroplating processes and coating characteristics. For example, acidic electroplating solutions and alkaline electroplating solutions have different reaction mechanisms and effects during the electroplating process. Therefore, the solution type sub-weight should be assigned a larger value; the solution concentration directly affects the ion concentration and current efficiency during the electroplating process, thereby affecting the deposition rate and coating quality of the coating. Too high or too low a concentration may result in uneven, rough or substandard coating. Therefore, the sub-weight of the solution concentration should also be relatively high; the solution content usually refers to the content of the main metal ions in the electroplating solution. The solution content is related to the solution concentration to a certain extent, but it focuses more on the total amount of metal ions in the solution. Insufficient content may result in a too thin coating or an inability to form a complete coating. If the content is too high, the production cost may increase. Therefore, the sub-weight of the solution content should be moderate. Various additives need to be added to the electroplating solution to improve the quality of the coating, increase the current efficiency or stabilize the electroplating process. Different additives have different effects on the electroplating results. The selection of additive type is also an important indicator of the electroplating solution variation parameters. However, compared with parameters such as solution type and concentration, the sub-weight of additive type may be slightly lower. The concentration of additives also has an important influence on the electroplating process. Too high or too low concentration may weaken or fail the effect of the additives. However, compared with the main solution concentration and solution content, the sub-weight of additive concentration may be ranked lower. Additive content refers to the total amount of additives in the electroplating solution. Similar to additive concentration, additive content is also a relatively minor indicator, and its sub-weight is usually small.

[0026] Step S400, generating a distance penalty factor for each two coatings according to the adjustment complexity. The distance penalty factor for each two coatings is generated according to the adjustment complexity. The distance penalty factor is a quantitative index used to describe the adverse effects on the process or the additional costs required when a certain characteristic (such as composition, thickness, structure, etc.) between two coatings differs too much. Specifically, the obtained adjustment complexity is mapped to the corresponding distance penalty factor. Generally speaking, the higher the adjustment complexity, the larger the corresponding distance penalty factor should be to reflect the additional costs required or the adverse effects.

[0027] Step S500, input the away penalty factor into the coating sequence optimizer, the coating sequence optimizer optimizes the multi-layer coating in the initial plating solution formula with the away penalty factor as the optimization direction, and obtains the coating optimization sequence, wherein the coating optimization sequence satisfies the first response condition, and the first response condition is that the sum of the adjustment complexity under the coating optimization sequence condition is the smallest. The away penalty factor is used as the input data of the coating sequence optimizer, and the away penalty factor provides an optimization direction for the coating sequence optimizer, that is, those coating combinations that may lead to high adjustment complexity should be avoided as much as possible, wherein the coating sequence optimizer is an intelligent tool, and the multi-layer coating in the initial plating solution formula is arranged and combined according to the input away penalty factor to find the optimal coating sequence, and the goal is to find a coating sequence, so that the sum of the adjustment complexity under this sequence is the smallest, that is, the first response condition, the lower the adjustment complexity, the less process adjustment is required to achieve this coating sequence, and the production cost and difficulty are correspondingly reduced, which helps to improve the stability and reliability of the electroplating process, thereby improving product quality. By inputting the away penalty factor into the plating sequence optimizer and using the first response condition as the optimization target, a plating sequence that meets the process requirements and reduces the adjustment complexity can be effectively found.

[0028] In a possible implementation, step S500 also includes step S510, generating an initial coating sequence of N coatings in the initial coating solution formula, wherein N is the number of multilayer coatings, and N is a positive integer greater than or equal to 2. Before the electroplating process begins, the order in which these coatings are applied during the electroplating process is determined based on the type and quantity of coatings in the initial coating solution formula. It also includes step S520, obtaining N-1 coating neighbor groups of the N coatings, and N-1 away penalty factors corresponding to the N-1 coating neighbor groups. It also includes step S530, obtaining an identified coating neighbor group that is greater than a preset penalty factor among the N-1 away penalty factors. After calculating the N-1 away penalty factors between N layers of coating, obtain the marked coating neighbor group that is greater than the preset penalty factor, where N represents the total number of coatings, and N-1 is because for N coatings, there are a total of N-1 away penalty factors between each coating. The preset penalty factor is a threshold value set according to the requirements of the electroplating process and experience, which is used to determine which coating neighbor groups (i.e., adjacent coating combinations) have too high away penalties. The marked coating neighbor group refers to a coating combination whose away penalty factor is greater than the preset penalty factor, which may lead to a higher adjustment complexity, thereby affecting the stability of the electroplating process and the coating quality. It also includes step S540, taking the marked coating neighbor group as the object of the next round of optimization, and the coatings belonging to the same neighbor group in the marked coating neighbor group are away from each other, and outputting an optimization result once until the coating sequence optimizer converges and obtains the coating optimization sequence. Specifically, the marked coating neighbor groups that are greater than the preset penalty factor are taken as the objects of the next round of optimization. According to the principle of staying away from each other, the order of these coatings is adjusted so that they are as non-adjacent as possible in the final coating optimization order to reduce the adjustment complexity. The coating sequence optimizer is used to optimize the marked coating neighbor groups. After each round of optimization, the coating sequence optimizer will output an optimization result, that is, a possible coating order. When the coating sequence optimizer can no longer significantly improve the optimization result in multiple consecutive rounds of optimization, it indicates that it has converged, which means that a relatively optimal coating order has been found, and the final coating optimization order is output.

[0029] In a possible implementation, step S520 further includes step S521, setting compatible constraints, which are constraints in the coating sequence optimizer. A series of rules and restrictions are introduced into the coating sequence optimizer to ensure that the coating sequence generated by the optimization process meets the actual requirements and feasibility of the electroplating process, and are used as constraints of the optimizer to guide the optimization process and avoid generating coating sequences that do not conform to practical applications, including material physical adhesion, chemical compatibility, process requirements, equipment limitations, etc. For example, some materials may react chemically when in contact, resulting in reduced coating quality or unstable process; the bottom coating needs to be applied first so that the subsequent coating can adhere or play a specific role; maximum current density, maximum plating solution temperature, etc. It also includes step S522, using the compatible constraints to identify the compatibility of the N-1 coating neighbor groups, and output N-1 compatible indicators. Using the set compatible constraints, the compatibility of N-1 coating neighbor groups is identified, that is, for each pair of adjacent coatings, it is checked whether the preset compatible constraints are met, and finally N-1 compatible indicators are output, which are quantitative representations of the compatibility of each coating neighbor group. They can be specific values ​​or levels, which are used to reflect the performance of the coating neighbor group under the compatible constraints. It also includes step S523, obtaining the incompatible coating neighbor groups that do not meet the preset compatible indicators in the N-1 compatible indicators. It also includes step S524, taking the incompatible coating neighbor groups as the object of the next round of optimization, and the coatings belonging to the same neighbor group in the incompatible coating neighbor groups are kept away from each other, so as to optimize the optimization result of the first optimization. These incompatible coating neighbor groups are taken as the main objects of the next round of optimization. According to the principle of staying away from each other, special attention will be paid to incompatible coatings belonging to the same neighbor group during the optimization process. This means that when adjusting the coating order, these incompatible coatings will be avoided as much as possible. Instead, they will be dispersed to different positions of the entire coating sequence to reduce their mutual influence. Through this round of optimization process, the previous optimization result will be optimized.

[0030] In a possible implementation, step S522 further includes step S522-1, obtaining N-1 coating material groups in the N-1 coating neighbor groups. Based on the N-1 coating neighbor groups, the corresponding N-1 coating material groups are obtained, specifically, each coating neighbor group is analyzed, and the type of coating material contained therein is determined. It also includes step S522-2, performing material adhesion, electrochemical compatibility and thermal stability analysis on each coating material group in the N-1 coating material groups, and outputting adhesion index, compatibility index and stability index. Material adhesion analysis is to evaluate the bonding strength between the coating and the substrate, quantitatively or qualitatively evaluate the adhesion of the coating material group, and output the corresponding adhesion index, which helps to determine whether the coating is easy to peel or fall off, thereby ensuring the quality of the electroplated product; electrochemical compatibility analysis is to check whether there is an electrochemical reaction between the coating material groups, which may cause damage to the coating or performance degradation. Specifically, by measuring the potential difference, corrosion rate and other parameters of different coating materials in the electrolyte, the electrochemical compatibility between them can be evaluated, and the compatibility index is output, which helps to avoid the coating failure problem caused by electrochemical incompatibility; thermal stability analysis is to evaluate the performance stability of the coating material group under high temperature environment. By measuring the thermal expansion coefficient, thermal conductivity, oxidation resistance and other parameters of the coating material under high temperature, its thermal stability can be judged, and the stability index is output, which helps to ensure that the coating can maintain stable performance under high temperature environment and avoid performance degradation caused by thermal stress or oxidation. It also includes step S522-3, outputting N-1 compatible indicators according to the adhesion index, the compatibility index and the stability index. Taking into account the adhesion, electrochemical compatibility, thermal stability and other properties of each coating material group, the compatibility between them is comprehensively evaluated and specific compatibility indicators are output.

[0031] In a possible implementation, step S500 further includes step S550, identifying the multi-layer coating, and determining whether the multi-layer coating has a composite coating, wherein the composite coating is a coating that is electroplated by two types of solutions. When identifying whether the multi-layer coating contains a composite coating, attention should be paid to the formation method and material composition of the coating. A notable feature of the composite coating is that it is usually formed by electroplating two or more different types of solutions, containing different metal ions, solid particles or other additives, which work together on the surface of the workpiece to form a composite coating, wherein the composite coating refers to a special coating in which solid phase particles are mixed in the metal coating matrix by chemical or electrochemical methods, by co-depositing one or more insoluble solid particles and metal ions on the surface of the workpiece. It also includes step S560, if there is a composite coating, determining the first coating neighbor group of the composite coating, the first coating neighbor group is composed of two coatings with the smallest penalty factor, and the first coating neighbor group includes the previous coating to be electroplated and the next coating to be electroplated. If there is a composite coating, determine the first coating neighbor group of the composite coating, wherein the first coating neighbor group refers to two coatings directly adjacent to the composite coating, and is composed of two coatings away from the smallest penalty factor, i.e., the last coating to be electroplated and the next coating to be electroplated. These two coatings and the composite coating together constitute a key combination in the coating sequence, specifically, the two coatings away from the smaller penalty factor are considered to be more compatible with the composite coating, and constitute the first coating neighbor group, which means that during the electroplating process, the interaction and influence between the two coatings and the composite coating are small, which is conducive to achieving a more stable and efficient electroplating effect. It also includes step S570, wherein the coating sequence optimizer performs adaptive optimization on the remaining coatings according to the first coating neighbor group and the composite coating to obtain a coating optimization sequence. The coating sequence optimizer performs adaptive optimization operations on the remaining coatings based on the known information of the first coating neighboring group and the composite coating, tries different coating arrangements and combinations, and evaluates the pros and cons of each combination, and ultimately determines a coating optimization sequence that meets the process requirements and achieves good performance and cost-effectiveness. The coating optimization sequence fully considers the compatibility of the composite coating with the adjacent coatings, as well as the rationality and feasibility of the entire coating sequence, to achieve optimization and improvement of the electroplating process, which helps to improve the stability and efficiency of the electroplating process and improve product quality.

[0032] Step S600, optimizing the initial plating solution formula based on the coating optimization sequence to obtain an optimized plating solution formula. In the electroplating process, the initial plating solution formula is adjusted and optimized according to the coating sequence determined by the optimization process to obtain a formula that better meets the actual production needs. By optimizing the initial plating solution formula based on the coating optimization sequence, an optimized plating solution formula that is more suitable for actual production can be obtained, thereby improving the efficiency of the electroplating process and product quality.

[0033] In the above, refer to Figure 1 A method for optimizing a plating solution formulation process according to an embodiment of the present invention is described in detail. Figure 2 A plating solution formulation process optimization system according to an embodiment of the present invention is described.

[0034] A plating solution formula process optimization system according to an embodiment of the present invention is used to solve the technical problem that the existing plating solution formula optimization cannot finely adjust the electroplating formula parameters according to the multi-layer electroplating of the workpiece, resulting in the inability to accurately control the structure and performance of the coating layer, and achieves the technical effect of adjusting the plating solution formula parameters according to the plating sequence, so that the plating solution formula avoids repeated process changes as needed, and improves the uniformity and adhesion of the coating. A plating solution formula process optimization system includes: an initial plating solution formula acquisition module 10, an electroplating change parameter output module 20, an adjustment complexity recognition module 30, a coating optimization sequence acquisition module 40, and an optimized plating solution formula acquisition module 50.

[0035] An initial plating solution formula acquisition module 10, wherein the initial plating solution formula acquisition module 10 is used to acquire an initial plating solution formula, wherein the initial plating solution formula is a plating solution formula for a multi-layer plating; An electroplating variation parameter output module 20, the electroplating variation parameter output module 20 is used to identify the electroplating process parameters of every two coating layers in the multi-layer coating, and output the electroplating variation parameters between every two coating layers, wherein the electroplating process parameters include electroplating solution parameters and electroplating control parameters; An adjustment complexity identification module 30, wherein the adjustment complexity identification module 30 is used to identify the adjustment complexity of the electroplating variation parameters between each two coating layers, output the adjustment complexity, and generate a distance penalty factor between each two coating layers according to the adjustment complexity; A coating optimization sequence obtaining module 40, wherein the coating optimization sequence obtaining module 40 is used to input the away penalty factor into a coating sequence optimizer, wherein the coating sequence optimizer optimizes the multi-layer coatings in the initial plating solution formula with the away penalty factor as the optimization direction to obtain a coating optimization sequence, wherein the coating optimization sequence satisfies a first response condition, and the first response condition is that the sum of the adjustment complexities under the coating optimization sequence condition is minimized; The optimized plating solution formula acquisition module 50 is used to optimize the initial plating solution formula based on the plating layer optimization sequence to obtain the optimized plating solution formula.

[0036] The specific configuration of the coating optimization order obtaining module 40 will be described in detail below. The coating optimization order obtaining module 40 may further include: generating an initial coating order of N coatings in the initial coating solution formula, wherein N is the number of multilayer coatings, and N is a positive integer greater than or equal to 2; obtaining N-1 coating neighbor groups of the N coatings, and N-1 away penalty factors corresponding to the N-1 coating neighbor groups; obtaining an identified coating neighbor group greater than a preset penalty factor in the N-1 away penalty factors; using the identified coating neighbor group as the object of the next round of optimization, and the coatings belonging to the same neighbor group in the identified coating neighbor group are away from each other, and outputting an optimization result until the coating order optimizer converges and obtains the coating optimization order.

[0037] The specific configuration of the coating optimization order obtaining module 40 will be described in detail below. The coating optimization order obtaining module 40 further includes: setting compatible constraints, the compatible constraints are constraints in the coating order optimizer; using the compatible constraints to identify the compatibility of the N-1 coating neighbor groups, and outputting N-1 compatible indicators; obtaining incompatible coating neighbor groups that do not meet the preset compatible indicators in the N-1 compatible indicators; using the incompatible coating neighbor groups as the object of the next round of optimization, and the coatings belonging to the same neighbor group in the incompatible coating neighbor groups are kept away from each other, so as to optimize the optimization result of the first optimization.

[0038] The specific configuration of the coating optimization order obtaining module 40 will be described in detail below. The coating optimization order obtaining module 40 may further include: obtaining N-1 coating material groups in the N-1 coating neighbor groups; performing material adhesion, electrochemical compatibility and thermal stability analysis on each coating material group in the N-1 coating material groups, and outputting adhesion index, compatibility index and stability index; outputting N-1 compatibility indexes according to the adhesion index, the compatibility index and the stability index.

[0039] The specific configuration of the coating optimization order obtaining module 40 will be described in detail below. The coating optimization order obtaining module 40 may further include: identifying the multi-layer coating, determining whether the multi-layer coating has a composite coating, wherein the composite coating is a coating that is electroplated by two types of solutions; if a composite coating exists, determining the first coating neighbor group of the composite coating, the first coating neighbor group is composed of two coatings that are away from the smallest penalty factor, and the first coating neighbor group includes the previous coating that is electroplated and the next coating that is electroplated; the coating order optimizer performs adaptive optimization on the remaining coatings according to the first coating neighbor group and the composite coating to obtain the coating optimization order.

[0040] The specific configuration of the initial plating solution formula acquisition module 10 will be described in detail below. The initial plating solution formula acquisition module 10 may further include: determining the coating function type of the multi-layer coating according to the initial plating solution formula; delineating functional layer areas according to the coating function type, wherein each functional layer area includes multiple functional coatings; outputting the coating order of each functional layer area according to the coating order optimizer, and then splicing the functional layer areas to generate a coating optimization order.

[0041] The specific configuration of the adjustment complexity identification module 30 will be described in detail below. The adjustment complexity identification module 30 may further include: collecting electroplating change parameters, the electroplating change parameters include electroplating solution change parameters and electroplating control change parameters; assigning a first weight to the electroplating solution change parameters, and assigning a second weight to the electroplating control change parameters, wherein the first weight is greater than 2 times the second weight; generating a weight network layer with the first weight and the second weight; obtaining a fully connected neural network; training the neural network with the weight network layer according to the electroplating solution change samples, the electroplating control change samples, and the identification information identifying the adjustment complexity, generating a complexity identification model, and outputting the adjustment complexity according to the complexity identification model.

[0042] The specific configuration of the adjustment complexity identification module 30 will be described in detail below. The adjustment complexity identification module 30 may further include: the indicators of the change parameters of the electroplating solution include at least solution type, solution concentration, solution content, additive type, additive concentration and additive content, and the sub-weights of each indicator are assigned in descending order.

[0043] A plating solution formula process optimization system provided by an embodiment of the present invention can execute a plating solution formula process optimization method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects of the execution method.

[0044] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0045] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for optimizing a plating solution formulation process, characterized in that: The method comprises: Obtaining an initial plating solution formula, wherein the initial plating solution formula is a plating solution formula for a multi-layer plating; Identify the electroplating process parameters of every two coating layers in the multi-layer coating, and output the electroplating variation parameters between every two coating layers, wherein the electroplating process parameters include electroplating solution parameters and electroplating control parameters; By identifying the adjustment complexity of the electroplating variation parameters between every two plating layers, the adjustment complexity is output; According to the adjustment complexity, generating a distance penalty factor for every two plating layers; The away penalty factor is input into a coating sequence optimizer, and the coating sequence optimizer optimizes the multi-layer coating in the initial plating solution formula with the away penalty factor as the optimization direction to obtain a coating optimization sequence, wherein the coating optimization sequence satisfies a first response condition, and the first response condition is that the sum of the adjustment complexities under the coating optimization sequence condition is minimized; The initial plating solution formula is optimized based on the plating layer optimization sequence to obtain an optimized plating solution formula.

2. A method for optimizing a plating solution formulation as claimed in claim 1, characterized in that: The coating sequence optimizer optimizes the multi-layer coating in the initial plating solution formula by taking the away penalty factor as the optimization direction, including: Generating an initial plating sequence of N plating layers in the initial plating solution formula, wherein N is the number of multi-layer plating layers and N is a positive integer greater than or equal to 2; Obtaining N-1 coating neighbor groups of the N coatings and N-1 away penalty factors corresponding to the N-1 coating neighbor groups; Obtaining a marked coating neighbor group whose distance penalty factors are greater than a preset penalty factor among the N-1 distance penalty factors; The identified coating neighbor group is taken as the object of the next round of optimization, and the coatings belonging to the same neighbor group in the identified coating neighbor group are kept away from each other, and an optimization result is outputted once until the coating sequence optimizer converges to obtain the coating optimization sequence.

3. A method for optimizing a plating solution formulation as claimed in claim 2, characterized in that: After obtaining N-1 adjacent groups of the N coating layers, the method further includes: Setting compatible constraints, wherein the compatible constraints are constraints in the coating sequence optimizer; Using the compatibility constraint condition, the compatibility of the N-1 coating neighbor groups is identified, and N-1 compatibility indicators are output; Obtaining an incompatible coating adjacent group that does not meet a preset compatibility index among the N-1 compatibility indexes; The incompatible coating neighbor group is taken as the object of the next round of optimization, and the coatings belonging to the same neighbor group in the incompatible coating neighbor group are kept away from each other, so as to optimize the optimization result of the first round.

4. A method for optimizing a plating solution formulation as claimed in claim 3, characterized in that: Using the compatibility constraint condition to identify the compatibility of the N-1 coating neighbor groups includes: Obtaining N-1 coating material groups from the N-1 coating neighbor groups; Performing material adhesion, electrochemical compatibility and thermal stability analysis on each of the N-1 coating material groups, and outputting adhesion index, compatibility index and stability index; According to the adhesion index, the compatibility index and the stability index, N-1 compatibility indexes are output.

5. A method for optimizing a plating solution formulation as claimed in claim 1, characterized in that: By identifying the adjustment complexity of the electroplating variation parameters between each two plating layers, the adjustment complexity is output, and the method includes: Collecting electroplating variation parameters, wherein the electroplating variation parameters include electroplating solution variation parameters and electroplating control variation parameters; Assigning a first weight to the electroplating solution variation parameter, and assigning a second weight to the electroplating control variation parameter, wherein the first weight is greater than 2 times the second weight; Generate a weight network layer using the first weight and the second weight; Get a fully connected neural network; According to the electroplating solution change samples, the electroplating control change samples and the identification information of the identification adjustment complexity, the neural network is trained with the weight network layer to generate a complexity recognition model, and the adjustment complexity is output according to the complexity recognition model.

6. A method for optimizing plating solution formulation process as claimed in claim 5, characterized in that: The indicators of the changing parameters of the electroplating solution include at least solution type, solution concentration, solution content, additive type, additive concentration and additive content, and the sub-weights of each indicator are assigned in descending order.

7. A method for optimizing plating solution formulation process according to claim 1, characterized in that: The method further comprises: Identifying the multi-layer coating to determine whether there is a composite coating in the multi-layer coating, wherein the composite coating is a coating that is electroplated using two types of solutions; If there is a composite coating, determine a first coating neighbor group of the composite coating, wherein the first coating neighbor group is composed of two coatings that are away from the smallest penalty factor, and the first coating neighbor group includes the previous coating to be electroplated and the next coating to be electroplated; The coating sequence optimizer performs adaptive optimization on the remaining coatings according to the first coating neighbor group and the composite coating to obtain a coating optimization sequence.

8. A method for optimizing plating solution formulation process as claimed in claim 1, characterized in that: After obtaining the initial plating solution formula, the method further comprises: Determining the coating function type of the multi-layer coating according to the initial plating solution formula; Defining functional layer areas according to the functional type of the coating, wherein each functional layer area includes a plurality of functional coatings; According to the coating sequence optimizer, after outputting the coating sequence of each functional layer area, the functional layer areas are spliced ​​to generate a coating optimization sequence.

9. A plating solution formulation process optimization system, characterized in that: The system is used to implement a plating solution formulation process optimization method according to any one of claims 1 to 8, and the system comprises: An initial plating solution formula acquisition module, the initial plating solution formula acquisition module is used to obtain an initial plating solution formula, wherein the initial plating solution formula is a plating solution formula for a multi-layer coating; An electroplating variation parameter output module, the electroplating variation parameter output module is used to identify the electroplating process parameters of every two coating layers in the multi-layer coating, and output the electroplating variation parameters between every two coating layers, wherein the electroplating process parameters include electroplating solution parameters and electroplating control parameters; An adjustment complexity identification module, the adjustment complexity identification module is used to identify the adjustment complexity of the electroplating variation parameters between every two plating layers, output the adjustment complexity, and generate a distance penalty factor between every two plating layers according to the adjustment complexity; A coating optimization sequence obtaining module, wherein the coating optimization sequence obtaining module is used to input the away penalty factor into a coating sequence optimizer, wherein the coating sequence optimizer optimizes the multi-layer coatings in the initial plating solution formula with the away penalty factor as the optimization direction to obtain a coating optimization sequence, wherein the coating optimization sequence satisfies a first response condition, and the first response condition is that the sum of the adjustment complexities under the coating optimization sequence condition is minimized; The optimized plating solution formula acquisition module is used to optimize the initial plating solution formula based on the plating layer optimization sequence to obtain the optimized plating solution formula.

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