A control method and control system for a solder paste production process

Abstract

The present application provides a control method and control system for a tin solder paste production process flow, which obtains a particle size distribution data set of solder paste particles when the tin solder paste is mixed; determines the distribution entropy and distribution difference set of the solder paste particles in different ingredient mixing areas based on the particle size distribution data set; extracts the first ingredient mixing area and the second ingredient mixing area in the tin solder paste production process through all the distribution entropies, and determines the mixing correlation amount when the tin solder paste is mixed; performs a fusion morphological analysis on the solder paste particles in the current tin solder paste production process based on the mixing correlation amount, obtains the dispersion characteristics and sedimentation characteristics of the solder paste particles, and determines the plasticity of the tin solder paste through the dispersion characteristics and sedimentation characteristics; adjusts the baking process parameters of the tin solder paste production process flow based on the plasticity; the present application adjusts the baking process parameters based on the plasticity, and can achieve uniformity adjustment of the solder paste particles in the tin solder paste, thereby improving the production quality of the tin solder paste.

Description

Technical Field

[0001] The present application relates to the technical field of solder paste production control, and more specifically, to a control method and control system for a solder paste production process. Background Art

[0002] Solder paste is one of the key materials in electronic manufacturing and welding processes. It is used to connect electronic components and printed circuit boards (PCBs). In order to ensure welding quality, production efficiency and product performance, a series of control technologies are needed to manage the production of solder paste. Solder paste production control includes knowledge and technologies in multiple fields such as chemical engineering, materials science, quality management and environmental protection to ensure the high quality and compliance of solder paste. These technologies contribute to the development of the electronic manufacturing industry and the improvement of product quality.

[0003] In the existing technology, the core of solder paste production control covers multiple key steps such as strict raw material selection, mixing, preparation, casting / extrusion, particle size distribution control, viscosity control, quality control and environmental management, aiming to ensure the quality, performance, consistency and compliance of solder paste to meet the urgent needs of the electronic manufacturing industry for high standards, high reliability and sustainability. However, in the production of solder paste, due to the influence of various factors (such as raw material characteristics, production process, etc.), the solder paste particles in some areas of the solder paste production are clustered and distributed, while the solder paste particles in some areas are sparsely distributed, resulting in uneven distribution of solder paste particles in the solder paste production, which makes it impossible to effectively adjust the uniformity of the solder paste particles in the solder paste, thereby reducing the production quality of the solder paste. Therefore, how to achieve uniformity adjustment of the solder paste particles in the solder paste to improve the production quality of the solder paste has become a problem faced by the industry. Summary of the invention

[0004] The present application provides a control method and control system for a solder paste production process, which can achieve uniformity adjustment of solder paste particles in the solder paste, thereby improving the production quality of the solder paste.

[0005] In a first aspect, the present application provides a method for controlling a solder paste production process, comprising the following steps:

[0006] Start the production of solder paste and obtain the particle size distribution data set of solder paste particles when the solder paste is mixed;

[0007] Determine the distribution entropy and distribution difference set of solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data set;

[0008] Extracting the first ingredient mixing area and the second ingredient mixing area in the production process of the solder paste through all the distribution entropies, and then determining the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing area and the distribution difference set corresponding to the second ingredient mixing area;

[0009] Performing fusion morphology analysis on solder paste particles in the current solder paste production process based on the mixed correlation quantity to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then determining the plasticity of the solder paste in the current production state based on the dispersion characteristics and the sedimentation characteristics;

[0010] The baking process parameters of the solder paste production process are adjusted based on the plasticity, and the solder paste is produced according to the adjusted baking process parameters.

[0011] In some embodiments, determining the distribution entropy and distribution difference set of solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data set specifically includes:

[0012] Selecting a batching and mixing area as a selected batching and mixing area, and extracting particle size distribution data of the selected batching and mixing area;

[0013] Extract all different particle size distribution values ​​from the particle size distribution data;

[0014] Determine the distribution proportion of each different particle size distribution value;

[0015] Determine the distribution entropy of the solder paste particles in the selected ingredient mixing area according to the distribution proportions of all different particle size distribution values;

[0016] Performing slip calculation on each particle size distribution value in the particle size distribution data to obtain all particle size distribution difference values;

[0017] Combining all particle size distribution difference values ​​to obtain a distribution difference set of solder paste particle distribution in the selected ingredient mixing area;

[0018] Continue to determine the distribution entropy and distribution difference set of the solder paste particle distribution in the remaining ingredient mixing area.

[0019] In some embodiments, determining the distribution ratio of each different particle size distribution value specifically includes:

[0020] Obtaining the frequency of occurrence of each different particle size distribution value in the particle size distribution data;

[0021] Acquire the total amount of data of the particle size distribution data;

[0022] For each different particle size distribution value, the frequency ratio of the different particle size distribution value in the particle size distribution data is calculated with respect to the total amount of the data, thereby obtaining the distribution proportion of each different particle size distribution value.

[0023] In some embodiments, extracting the first ingredient mixing zone and the second ingredient mixing zone in the solder paste production process through all distribution entropy specifically includes:

[0024] Extract the maximum distribution entropy and the minimum distribution entropy from all distribution entropies;

[0025] The batching and mixing area corresponding to the maximum distribution entropy is used as the first batching and mixing area;

[0026] The ingredient mixing zone corresponding to the minimum distribution entropy is used as the second ingredient mixing zone.

[0027] In some embodiments, determining the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing area and the distribution difference set corresponding to the second ingredient mixing area specifically includes:

[0028] Obtaining a distribution difference set corresponding to the first ingredient mixing zone and a distribution difference set corresponding to the second ingredient mixing zone;

[0029] Performing same-space mapping fitting on the distribution difference set corresponding to the first ingredient mixing zone and the distribution difference set corresponding to the second ingredient mixing zone to obtain a distribution difference fitting hyperbola;

[0030] Extract all fitting intersection points from the distribution difference fitting hyperbola;

[0031] Obtaining the total number of data of the distribution difference set corresponding to the first ingredient mixing zone;

[0032] The mixing correlation amount when the solder paste is mixed is determined based on all the fitting intersection points and the total number of data.

[0033] In some embodiments, the fusion morphology analysis of solder paste particles in the current solder paste production process is performed based on the mixed correlation amount to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, specifically including:

[0034] Determine the mixing correlation threshold of solder paste particles during solder paste production;

[0035] The mixed correlation amount is compared with the mixed correlation threshold, and when the mixed correlation amount is greater than the mixed correlation threshold, solder paste particle density data in the current solder paste production process is obtained;

[0036] Determine, according to the solder paste particle density data, a density deviation value sequence of solder paste particles at different solder paste areas in the current solder paste production process;

[0037] The dispersion characteristics and sedimentation characteristics of the solder paste particles are determined by the density deviation value sequence of the solder paste particles at different solder paste areas.

[0038] In some embodiments, a data set of particle size distribution of solder paste particles when the solder paste is mixed is obtained from a solder paste production monitoring database.

[0039] In a second aspect, the present application provides a solder paste production process control system, comprising:

[0040] An acquisition module is used to start the production of solder paste and obtain the particle size distribution data of solder paste particles when the solder paste is mixed;

[0041] A processing module, used for determining a distribution entropy and a distribution difference set of solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data;

[0042] The processing module is further used to extract the first ingredient mixing area and the second ingredient mixing area in the production process of the solder paste through all the distribution entropies, and then determine the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing area and the distribution difference set corresponding to the second ingredient mixing area;

[0043] The processing module is further used to perform fusion morphology analysis on solder paste particles in the current solder paste production process based on the mixed correlation quantity to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then determine the plasticity of the solder paste in the current production state through the dispersion characteristics and the sedimentation characteristics;

[0044] An execution module is used to adjust the baking process parameters of the solder paste production process based on the plasticity, and produce the solder paste according to the adjusted baking process parameters.

[0045] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned method for controlling the solder paste production process.

[0046] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the control method of the above-mentioned solder paste production process is implemented.

[0047] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0048] In the control method and control system of the solder paste production process provided in the present application, first, the solder paste production is started, and a particle size distribution data set of the solder paste particles when the solder paste is mixed is obtained; secondly, the distribution entropy and distribution difference set of the solder paste particles in different mixing zones are determined based on the particle size distribution data set; further, the first mixing zone and the second mixing zone in the solder paste production process are extracted through all the distribution entropies, and then the mixing correlation quantity when the solder paste is mixed is determined according to the distribution difference set corresponding to the first mixing zone and the distribution difference set corresponding to the second mixing zone; then, the solder paste particles in the current solder paste production process are analyzed in fusion morphology according to the mixing correlation quantity to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then the plasticity of the solder paste in the current production state is determined according to the dispersion characteristics and the sedimentation characteristics; finally, the baking process parameters of the solder paste production process are adjusted based on the plasticity, and the solder paste is produced according to the adjusted baking process parameters.

[0049] It can be seen that the present application can realize the uniformity adjustment of the solder paste particles in the solder paste, thereby improving the production quality of the solder paste; firstly, the distribution entropy and distribution difference set of the solder paste particle distribution are determined by the particle size distribution data in different ingredient mixing areas, so as to effectively analyze the uneven aliasing of the solder paste particles in the solder paste, and avoid the problem of uneven distribution of solder paste particles caused by factors such as raw material characteristics and production process; secondly, the ingredient mixing area with the smallest distribution chaos of the solder paste particles and the ingredient mixing area with the largest distribution chaos of the solder paste particles in the production process of the solder paste are extracted from all the distribution entropies, so as to characterize the distribution trend of the solder paste particles in the production of the solder paste; further, the mixing correlation amount when the solder paste is mixed is determined according to the ingredient mixing areas with the largest and smallest distribution chaos of the solder paste particles, so as to Identify the correlation of the distribution of solder paste particles in the ingredient mixing sensitive area, so as to further identify the uniform distribution of solder paste particles in the solder paste; then, use the mixed correlation quantity to perform a fusion morphological analysis on the solder paste particles in the current solder paste production process to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, which can effectively identify the distribution morphology of the solder paste particles in the solder paste, avoid the problems of insufficient fluidity and wettability of the produced solder paste, and thus improve the effectiveness and feasibility of solder paste production; finally, adjust the baking process parameters of the solder paste production process flow according to the plasticity degree determined by the dispersion characteristics and the sedimentation characteristics; in summary, the technical solution provided in the present application can achieve uniformity adjustment of the solder paste particles in the solder paste, thereby improving the production quality of the solder paste. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is an exemplary flow chart of a method for controlling a solder paste production process according to some embodiments of the present application;

[0051] Figure 2 is an exemplary flow chart for determining a mixed correlation amount according to some embodiments of the present application;

[0052] Figure 3 is an exemplary flow chart for determining dispersion characteristics and sedimentation characteristics according to some embodiments of the present application;

[0053] Figure 4 is a schematic diagram of exemplary hardware and / or software of a control system for a solder paste production process according to some embodiments of the present application;

[0054] Figure 5 It is a structural schematic diagram of a computer device for implementing a control method for a solder paste production process flow according to some embodiments of the present application. DETAILED DESCRIPTION

[0055] The core of the present application is to first start the production of solder paste and obtain a particle size distribution data set of solder paste particles when the solder paste is mixed; secondly, determine the distribution entropy and distribution difference set of the solder paste particles in different mixing zones based on the particle size distribution data set; further, extract the first mixing zone and the second mixing zone in the production process of the solder paste through all the distribution entropies, and then determine the mixing correlation when the solder paste is mixed according to the distribution difference set corresponding to the first mixing zone and the distribution difference set corresponding to the second mixing zone; then, perform a fusion morphological analysis on the solder paste particles in the current solder paste production process based on the mixing correlation to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then determine the plasticity of the solder paste in the current production state through the dispersion characteristics and the sedimentation characteristics; finally, adjust the baking process parameters of the solder paste production process based on the plasticity, and produce the solder paste according to the adjusted baking process parameters, so as to achieve uniformity adjustment of the solder paste particles in the solder paste, thereby improving the production quality of the solder paste.

[0056] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of a method for controlling a solder paste production process according to some embodiments of the present application. The method 100 for controlling a solder paste production process mainly includes the following steps:

[0057] In step 101, the production of solder paste is started, and a data set of particle size distribution of solder paste particles when the solder paste is mixed is obtained.

[0058] Solder paste production includes a series of steps and operations for preparing solder paste to ensure that the final solder paste meets specific quality and performance requirements. The solder paste production includes steps such as raw material control, solder paste viscosity control, solder paste particle size control, and solder paste cutting control. Each step is crucial in solder paste production. Among them, precise control of solder paste particle distribution is the most critical to the performance and application of solder paste. Solder paste particle distribution can directly affect the wettability, viscosity and uniformity of welding.

[0059] In specific implementation, the production of solder paste is started, and a particle size distribution dataset of solder paste particles when the solder paste is mixed is obtained from the solder paste production monitoring database, the particle size distribution dataset includes particle size distribution data of different mixing zones, and the particle size distribution values ​​in the particle size distribution data can be collected by a laser particle size analyzer. In the present application, the particle size distribution dataset is a combination of data collected from different mixing zones at the same time. For example, the mixing of the solder paste ingredients is evenly divided into partitions and collected from different mixing zones at the same time. In addition, the particle size distribution dataset can also be collected by other collection equipment, which is not limited here.

[0060] It should be noted that the particle size distribution data set includes particle size distribution data of different ingredient mixing areas, and the particle size distribution data includes multiple particle size distribution values. The particle size distribution value in the present application represents an indicator describing the size distribution of solder paste particles in the solder paste, and the particle size distribution value provides information about the size and quantity of solder paste particles distributed within different particle size ranges. In the solder paste production process, the solder paste usually contains components such as metal particles and flux. The determination of the particle size distribution data set of the solder paste particles can more effectively analyze the changes in the solder paste in the production process, thereby making effective control strategies and improving the production quality and accuracy of the solder paste.

[0061] In step 102, distribution entropies and distribution difference sets of solder paste particle distribution in different ingredient mixing areas are determined based on the particle size distribution data set.

[0062] It should be noted that the particle size distribution data set in the present application includes the particle size distribution data of different ingredient mixing zones, that is, one ingredient mixing zone corresponds to one particle size distribution data.

[0063] In some embodiments, the distribution entropy and distribution difference set of solder paste particle distribution in different ingredient mixing areas can be determined based on the particle size distribution data set in the following manner, namely:

[0064] Selecting a batching and mixing area as a selected batching and mixing area, and extracting particle size distribution data of the selected batching and mixing area;

[0065] Extract all different particle size distribution values ​​from the particle size distribution data;

[0066] Determine the distribution proportion of each different particle size distribution value;

[0067] Determine the distribution entropy of the solder paste particles in the selected ingredient mixing area according to the distribution proportions of all different particle size distribution values;

[0068] Performing slip calculation on each particle size distribution value in the particle size distribution data to obtain all particle size distribution difference values;

[0069] Combining all particle size distribution difference values ​​to obtain a distribution difference set of solder paste particle distribution in the selected ingredient mixing area;

[0070] Continue to determine the distribution entropy and distribution difference set of the solder paste particle distribution in the remaining ingredient mixing area.

[0071] In some embodiments, the following steps may be used to determine the distribution ratio of each different particle size distribution value, namely:

[0072] Obtaining the frequency of occurrence of each different particle size distribution value in the particle size distribution data;

[0073] Acquire the total amount of data of the particle size distribution data;

[0074] For each different particle size distribution value, the frequency ratio of the different particle size distribution value in the particle size distribution data is calculated with respect to the total amount of the data, thereby obtaining the distribution proportion of each different particle size distribution value.

[0075] It should be noted that in other embodiments, other calculation methods may be used to calculate the distribution ratio, which is not limited here. In addition, the distribution ratio in this embodiment represents the ratio of different particle size distribution values ​​in the total particle size distribution data.

[0076] In specific implementation, the distribution entropy of the solder paste particles in the selected ingredient mixing area is determined according to the distribution proportions of all different particle size distribution values, that is, the distribution proportions of all different particle size distribution values ​​are input as input parameters into the entropy function model, and then the entropy function model outputs the distribution entropy of the solder paste particles in the selected ingredient mixing area.

[0077] It should be noted that the entropy function model in this embodiment is an information entropy model in the prior art. In addition, in other embodiments, other entropy models may be used to determine the distribution entropy, which is not limited here.

[0078] It should also be noted that the distribution entropy in the present application represents the degree of chaotic distribution of solder paste particles in different ingredient mixing areas, that is, the larger the distribution entropy, the greater the degree of chaotic distribution of solder paste particles in different ingredient mixing areas, and the smaller the distribution entropy, the smaller the degree of chaotic distribution of solder paste particles in different ingredient mixing areas. In the production of solder paste, the particle size distribution of solder paste particles may change to varying degrees. For example, over time, small particles may gradually aggregate into larger particles, or larger particles may break into small particles due to vibration and other reasons, resulting in uneven distribution of solder paste particles in different ingredient mixing areas. Therefore, by determining the distribution entropy, the performance changes of solder paste at different distribution entropies can be effectively identified, so that corresponding measures can be taken to ensure the stability of the welding process and the welding quality.

[0079] It should be noted that the slip calculation in the present application refers to the process of performing residual calculation on the current data and the previous data in a set of data. In the present embodiment, the slip calculation is performed on each particle size distribution value in the particle size distribution data, that is, for each particle size distribution value, the previous particle size distribution value is subtracted from the particle size distribution value, thereby completing the slip calculation of each particle size distribution value in the particle size distribution data.

[0080] It should also be noted that the distribution difference set contains multiple particle size distribution difference values. In addition, the particle size distribution difference value in the present application represents the value obtained after sliding calculation of the particle size distribution value in the particle size distribution data. The particle size distribution difference value characterizes the deviation between the particle sizes of the solder paste particles. The determination of the particle size distribution difference value can effectively identify the correlation characteristics of the distribution of solder paste particles in different ingredient mixing areas, thereby better analyzing the distribution of local solder paste particles.

[0081] In step 103, the first ingredient mixing zone and the second ingredient mixing zone in the solder paste production process are extracted through all distribution entropies, and then the mixing correlation when the solder paste is mixed is determined according to the distribution difference set corresponding to the first ingredient mixing zone and the distribution difference set corresponding to the second ingredient mixing zone.

[0082] In some embodiments, the first ingredient mixing zone and the second ingredient mixing zone in the solder paste production process can be extracted by all the distribution entropy, specifically by the following steps, namely:

[0083] Extract the maximum distribution entropy and the minimum distribution entropy from all distribution entropies;

[0084] The batching and mixing area corresponding to the maximum distribution entropy is used as the first batching and mixing area;

[0085] The ingredient mixing zone corresponding to the minimum distribution entropy is used as the second ingredient mixing zone.

[0086] It should be noted that the first ingredient mixing zone in the present application represents the ingredient mixing zone corresponding to the largest distribution entropy, and the second ingredient mixing zone in the present application represents the ingredient mixing zone corresponding to the smallest distribution entropy. In the production of solder paste, as the production continues, there will be distribution deviations in the solder paste particles. Some areas may gather more solder paste particles, while some areas may have fewer solder paste particles. Therefore, in order to effectively identify the distribution deviation of solder paste particles in the production of solder paste, the first ingredient mixing zone and the second ingredient mixing zone can be determined to characterize the distribution trend of solder paste particles in the production of solder paste.

[0087] In some embodiments, reference Figure 2 As shown in FIG. 1 , this figure is an exemplary flow chart for determining the mixing correlation amount according to some embodiments of the present application. In this embodiment, the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing zone and the distribution difference set corresponding to the second ingredient mixing zone can be determined by the following steps:

[0088] First, in step 1031, a distribution difference set corresponding to the first ingredient mixing zone and a distribution difference set corresponding to the second ingredient mixing zone are obtained;

[0089] Next, in step 1032, a distribution difference set corresponding to the first ingredient mixing zone and a distribution difference set corresponding to the second ingredient mixing zone are subjected to same-space mapping fitting to obtain a distribution difference fitting hyperbola;

[0090] Further, in step 1033, all fitting intersection points are extracted from the distribution difference fitting hyperbola;

[0091] Then, in step 1034, the total number of data of the distribution difference set corresponding to the first ingredient mixing zone is obtained;

[0092] Finally, in step 1035, the mixing correlation amount when the solder paste is mixed is determined according to all the fitting intersection points and the total number of data.

[0093] In specific implementation, the distribution difference set corresponding to the first ingredient mixing zone and the distribution difference set corresponding to the second ingredient mixing zone can be fitted in the same space through the least squares method to obtain a distribution difference fitting hyperbola, which will not be elaborated here. In addition, in other embodiments, other fitting methods can be used for fitting, which are not limited here.

[0094] It should be noted that, in this embodiment, the same-space mapping fitting refers to the process of mapping two or more data sets to the same space and fitting them. In this embodiment, the distribution difference set corresponding to the first ingredient mixing zone and the distribution difference set corresponding to the second ingredient mixing zone are subjected to same-space mapping fitting to obtain a distribution difference fitting hyperbola, that is, the particle size distribution difference value is the vertical coordinate, and the label of the particle size distribution difference value is the horizontal coordinate, and the distribution difference set corresponding to the first ingredient mixing zone and the distribution difference set corresponding to the second ingredient mixing zone are fitted in the same two-dimensional space to obtain a distribution difference fitting hyperbola.

[0095] It should also be noted that the distribution difference fitting hyperbola in this embodiment represents a curve obtained by fitting two distribution difference sets. By fitting the distribution difference fitting hyperbola, the correlation of solder paste particle distribution in different ingredient mixing areas is effectively analyzed, thereby improving the production quality of solder paste.

[0096] In specific implementation, all fitting intersection points can be extracted from the distribution difference fitting hyperbola through data processing tools. For example, all fitting intersection points can be extracted from the distribution difference fitting hyperbola through Python, which will not be repeated here. In addition, in other embodiments, other extraction tools can also be used for extraction, which is not limited here.

[0097] It should be noted that, in this embodiment, the fitting intersection point represents the point where two curves in the distribution difference fitting hyperbola intersect. By determining the fitting intersection point, the correlation and similarity of the distribution of solder paste particles in different ingredient mixing areas can be effectively identified.

[0098] In specific implementation, the mixing correlation amount when the solder paste is mixed is determined based on all the fitting intersections and the total number of data, that is: the total number of fitting intersections is obtained from all the fitting intersections, and the ratio of the total number of fitting intersections to the total number of data is calculated to obtain the mixing correlation amount when the solder paste is mixed. In addition, in other embodiments, other calculation methods can also be used to calculate the mixing correlation amount, which is not limited here.

[0099] It should be noted that the mixing correlation amount in the present application indicates the degree of correlation between the distribution of solder paste particles in different ingredient mixing areas, that is, the larger the mixing correlation amount, the greater the degree of correlation between the distribution of solder paste particles in different ingredient mixing areas, indicating that the uniformity of the distribution of solder paste particles in the solder paste production process at this time is greater, and the smaller the mixing correlation amount, the smaller the degree of correlation between the distribution of solder paste particles in different ingredient mixing areas, indicating that the uniformity of the distribution of solder paste particles in the solder paste production process at this time is smaller. Usually in the solder paste production process, the solder paste particles in the solder paste often have uneven aliasing. Therefore, by determining the mixing correlation amount, the uneven aliasing of solder paste particles in the solder paste can be effectively analyzed.

[0100] In step 104, the mixed correlation quantity is used to perform a fusion morphology analysis on the solder paste particles in the current solder paste production process to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then the plasticity of the solder paste in the current production state is determined through the dispersion characteristics and the sedimentation characteristics.

[0101] In some embodiments, reference Figure 3 As shown in FIG. 1 , this figure is an exemplary flow chart for determining the dispersion characteristics and sedimentation characteristics according to some embodiments of the present application. In this embodiment, the fusion morphology analysis of the solder paste particles in the current solder paste production process is performed by the mixed correlation amount, and the dispersion characteristics and sedimentation characteristics of the solder paste particles can be obtained by the following steps:

[0102] First, in step 1041, a mixed correlation threshold of solder paste particles in the solder paste production process is determined;

[0103] Secondly, in step 1042, the mixed correlation amount is compared with the mixed correlation threshold, and when the mixed correlation amount is greater than the mixed correlation threshold, the solder paste particle density data in the current solder paste production process is obtained;

[0104] Then, in step 1043, a density deviation value sequence of solder paste particles at different solder paste areas in the current solder paste production process is determined according to the solder paste particle density data;

[0105] Finally, in step 1044, the distribution characteristics and sedimentation characteristics of the solder paste particles are determined through the density deviation value sequence of the solder paste particles at different solder paste areas.

[0106] It should be noted that, in this embodiment, when the hybrid association amount is less than or equal to the hybrid association threshold, no processing is performed.

[0107] It should be noted that the hybrid correlation threshold in this implementation represents a pre-set standard value for comparison with the current hybrid correlation amount, which can be set according to actual needs. For example, a large number of historical hybrid correlation amounts can be learned and set through machine learning, which will not be elaborated here.

[0108] In a specific implementation, the mixed correlation amount is compared with a mixed correlation threshold, and when the mixed correlation amount is greater than the mixed correlation threshold, the solder paste particle density data in the current solder paste production process is obtained through a laser particle size analyzer.

[0109] It should be noted that the solder paste particle density data in the present application represents the solder paste particle density collected from multiple different solder paste areas at the same time, that is, one solder paste particle density corresponds to one solder paste area, wherein the solder paste particle density represents the compactness of the solder paste particles in the solder paste, a higher solder paste particle density indicates that the solder paste particles are more tightly arranged in the solder paste, and a lower solder paste particle density indicates that the solder paste particles are relatively sparsely arranged in the solder paste, and the determination of the solder paste particle density lies in effectively identifying the uniformity of changes and the close contact of the solder paste particles in the solder paste.

[0110] It should also be noted that the fusion morphological analysis in the present application represents the process of analyzing the dispersion characteristics and sedimentation characteristics of solder paste particles in the solder paste, wherein the solder paste particles in the current solder paste production process are subjected to a fusion morphological analysis based on the mixed correlation amount, namely: determining the mixed correlation threshold of the solder paste particles in the solder paste production process; comparing the mixed correlation amount with the mixed correlation threshold, and when the mixed correlation amount is greater than the mixed correlation threshold, obtaining the solder paste particle density data in the current solder paste production process; determining the density deviation value sequence of the solder paste particles in different solder paste areas in the current solder paste production process based on the solder paste particle density data; determining the dispersion characteristics and sedimentation characteristics of the solder paste particles through the density deviation value sequence of the solder paste particles in different solder paste areas; that is, completing the process of fusion morphological analysis.

[0111] In some embodiments, the density deviation value sequence of solder paste particles at different solder paste areas in the current solder paste production process is determined according to the solder paste particle density data, and the following steps may be used, namely:

[0112] Selecting a solder paste particle density as a selected solder paste particle density, and performing deviation calculations on the selected solder paste particle density and the remaining solder paste particle densities to obtain all density deviation values;

[0113] Combining all density deviation values ​​to obtain a density deviation value sequence of solder paste particles in the solder paste area corresponding to the selected solder paste particle density;

[0114] Continue to determine the density deviation value sequence of the solder paste particles in the tin solder paste area corresponding to the remaining solder paste particle density.

[0115] In specific implementation, the selected solder paste particle density can be respectively calculated with the remaining solder paste particle density by Euclidean distance to obtain all density deviation values, which will not be repeated here. In addition, in other embodiments, other deviation calculation methods can also be used for calculation, which are not limited here.

[0116] It should be noted that the density deviation value in this embodiment represents the deviation between the densities of different solder paste particles, that is, the larger the density deviation value, the larger the deviation between the densities of different solder paste particles, and the smaller the density deviation value, the smaller the deviation between the densities of different solder paste particles. The determination of the density deviation value is to identify and match similar entities in different solder paste areas, so as to perform data integration and similarity judgment.

[0117] In some embodiments, the following method can be used to determine the distribution characteristics and sedimentation characteristics of the solder paste particles through the density deviation value sequence of the solder paste particles at different solder paste areas, namely:

[0118] Determine the density deviation dispersion of the density deviation value sequence of solder paste particles at each solder paste area;

[0119] Determine the density deviation concentration trend of the density deviation value sequence of solder paste particles in each solder paste area;

[0120] Determining the dispersion characteristics of the solder paste particles according to all density deviation dispersions;

[0121] The sedimentation characteristics of the solder paste particles are determined based on the concentration trends of all density deviations.

[0122] In the specific implementation, the density deviation dispersion of the density deviation value sequence of the solder paste particles in each solder paste area is determined, that is: for the density deviation value sequence of the solder paste particles in each solder paste area, the standard deviation of the density deviation value sequence is calculated, and then the density deviation dispersion of the density deviation value sequence of the solder paste particles in each solder paste area is obtained. In addition, in other embodiments, other calculation methods can also be used to calculate the density deviation dispersion, which is not limited here.

[0123] It should be noted that, in this embodiment, the density deviation dispersion represents the degree of dispersion of the density deviation values ​​in the density deviation value sequence, that is, the larger the density deviation dispersion, the greater the degree of dispersion of the density deviation values ​​in the density deviation value sequence, and the smaller the density deviation dispersion, the smaller the degree of dispersion of the density deviation values ​​in the density deviation value sequence.

[0124] In the specific implementation, the density deviation concentration trend of the density deviation value sequence of the solder paste particles in each solder paste area is determined, that is: for the density deviation value sequence of the solder paste particles in each solder paste area, the density deviation value sequence is mean calculated, and then the density deviation concentration trend of the density deviation value sequence of the solder paste particles in each solder paste area is obtained. In addition, in other embodiments, other calculation methods can also be used to calculate the density deviation concentration trend, which is not limited here.

[0125] It should be noted that, in this embodiment, the density deviation centralization trend represents the degree of concentrated change of density deviation values ​​in the density deviation value sequence, that is, the larger the density deviation centralization trend, the greater the degree of concentrated change of density deviation values ​​in the density deviation value sequence, and the smaller the density deviation centralization trend, the smaller the degree of concentrated change of density deviation values ​​in the density deviation value sequence.

[0126] In a specific implementation, the distribution characteristics of the solder paste particles are determined according to all density deviation discretenesses. The distribution characteristics can be obtained by calculating the mean value of all density deviation discretenesses. In addition, in other embodiments, other calculation methods can be used to obtain the distribution characteristics of the solder paste particles, which are not limited here.

[0127] It should be noted that the dispersion characteristics in the present application refer to the characteristics that describe the degree of dispersion of solder paste particles in the solder paste. In the production of solder paste, if the degree of dispersion of the solder paste particles is too small, the produced solder paste will have problems with insufficient fluidity and wettability. Therefore, by determining the dispersion characteristics, the effectiveness and feasibility of solder paste production can be effectively identified.

[0128] In a specific implementation, the sedimentation characteristics of the solder paste particles are determined according to all density deviation concentration trends. The sedimentation characteristics can be obtained by calculating the average of all density deviation concentration trends. In addition, in other embodiments, other calculation methods can be used to obtain the sedimentation characteristics of the solder paste particles, which are not limited here.

[0129] It should be noted that the sedimentation characteristics in the present application refer to the characteristics that describe the concentrated distribution of solder paste particles in the solder paste in some areas, that is, the sedimentation of solder paste particles in the solder paste. The sedimentation characteristics are used to characterize the mixing of ingredients in the current solder paste production process. If the ingredients are not mixed sufficiently, the solder paste particles in the solder paste will be concentrated in some areas, resulting in sedimentation. In the production of solder paste, if the solder paste particles are concentrated in some areas too much, the produced solder paste will also have problems with insufficient fluidity and wettability. Therefore, by determining the sedimentation characteristics, the effectiveness and feasibility of solder paste production can be effectively identified.

[0130] In some embodiments, during specific implementation, the plasticity of the solder paste in the current production state is determined by the scattering characteristics and the sedimentation characteristics, that is, the ratio of the scattering characteristics to the sedimentation characteristics is calculated to obtain the plasticity of the solder paste in the current production state. In addition, in other embodiments, other calculation methods can be used to calculate the plasticity, which is not limited here.

[0131] It should be noted that the plasticity of the solder paste in the present application represents a measure of the ductility and toughness of the solder paste during the production process of the solder paste, that is, the greater the plasticity, the higher the ductility and toughness of the solder paste during the production process of the solder paste, indicating that the production quality and production accuracy of the solder paste are higher; when the plasticity is smaller, the ductility and toughness of the solder paste during the production process of the solder paste are lower, indicating that the production quality and production accuracy of the solder paste are lower; in the solder paste production process, the distribution of solder paste particles in the solder paste directly affects its wettability and uniformity during the welding process; the more uniform the distribution of solder paste particles in the solder paste, the higher the ductility and toughness of the solder paste; therefore, by determining the plasticity, the uniform distribution of the particle size of the solder paste particles in the current solder paste can be effectively identified, and the solder paste temperature curve can be adjusted and controlled in real time according to the size of the plasticity to make the solder paste particles evenly distributed.

[0132] In step 105, the baking process parameters of the solder paste production process are adjusted based on the plasticity, and the solder paste is produced according to the adjusted baking process parameters.

[0133] In some embodiments, the baking process parameters of the solder paste production process flow are adjusted based on the plasticity by the following steps, namely:

[0134] The plasticity degree is compared with a preset plasticity degree, and when the plasticity degree is less than or equal to the preset plasticity degree, the solder paste production control system adjusts the baking process parameters in the solder paste production process flow upward;

[0135] When the degree of plasticity is greater than a preset degree of plasticity, the baking process parameters in the solder paste production process are kept unchanged.

[0136] In specific implementation, the baking process parameters in the solder paste production process are adjusted according to the plasticity degree, and the plasticity degree is compared with the preset plasticity degree. When the plasticity degree is less than or equal to the preset plasticity degree, the solder paste production control system adjusts the baking process parameters in the solder paste production process upward; when the plasticity degree is greater than the preset plasticity degree, the baking process parameters in the solder paste production process are kept unchanged. The baking process parameters are parameters for adjusting the change of the temperature curve, for example, the baking temperature. In the solder paste production process, the temperature control has a high degree of coordination and synchronization with the change of the solder paste particle size in the solder paste. Therefore, it is particularly important to adjust the baking process parameters in the solder paste production process. Among them, lax temperature control will lead to uneven distribution of solder paste particles in the solder paste. Then, by determining the plasticity degree, real-time adjustment of the baking process parameters in the solder paste production process can be achieved, thereby improving the uniform distribution of solder paste particles in the solder paste production process.

[0137] It should be noted that the preset plasticity degree in this embodiment is a preset standard plasticity degree, which can be set according to actual needs and will not be described in detail here.

[0138] It should also be noted that the solder paste production control system in this embodiment refers to a system used to monitor, control and optimize the production process during the solder paste production process.

[0139] In specific implementation, the solder paste production device will produce solder paste according to the adjusted baking process parameters to effectively improve the performance and quality of the solder paste, thereby meeting the high requirements in the electronic manufacturing process.

[0140] It should be noted that the solder paste production device in this embodiment refers to a device for producing solder paste.

[0141] In addition, in another aspect of the present application, in some embodiments, the present application provides a solder paste production process control system, referring to Figure 4 , which is a schematic diagram of exemplary hardware and / or software of a solder paste production process control system according to some embodiments of the present application, the solder paste production process control system 200 includes: an acquisition module 201, a processing module 202 and an execution module 203, which are described as follows:

[0142] Acquisition module 201, in this application, acquisition module 201 is mainly used to start the production of solder paste and obtain a particle size distribution data set of solder paste particles when the solder paste is mixed;

[0143] 202 processing module, in the present application, the processing module 202 is mainly used to determine the distribution entropy and distribution difference set of the solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data set;

[0144] The processing module 202 in the present application is also used to extract the first ingredient mixing area and the second ingredient mixing area in the production process of the solder paste through all the distribution entropies, and then determine the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing area and the distribution difference set corresponding to the second ingredient mixing area;

[0145] In addition, the processing module 202 in the present application is also used to perform fusion morphology analysis on the solder paste particles in the current solder paste production process based on the mixed correlation amount to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then determine the plasticity of the solder paste in the current production state through the dispersion characteristics and the sedimentation characteristics;

[0146] Execution module 203, in the present application, execution module 203 is mainly used to adjust the baking process parameters of the solder paste production process flow based on the plasticity, and produce the solder paste according to the adjusted baking process parameters.

[0147] In addition, the present application also provides a computer device, which includes a memory and a processor, the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned control method for the solder paste production process flow.

[0148] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for implementing a control method for a solder paste production process according to some embodiments of the present application. The control method for a solder paste production process in the above embodiment can be Figure 5 The computer device 300 shown in the figure is implemented, and the computer device 300 includes at least one processor 301, a communication bus 302, a memory 303 and at least one communication interface 304.

[0149] The processor 301 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more executions of the control method for controlling the solder paste production process in the present application.

[0150] Communication bus 302 may include a pathway for transmitting information between the above-mentioned components.

[0151] The memory 303 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 303 may exist independently and be connected to the processor 301 through the communication bus 302. The memory 303 may also be integrated with the processor 301.

[0152] The memory 303 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the program code stored in the memory 303. The program code may include one or more software modules. The determination of the control method of the solder paste production process in the above embodiment can be implemented by the processor 301 and one or more software modules in the program code in the memory 303.

[0153] The communication interface 304 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0154] In a specific implementation, as an embodiment, a computer device may include multiple processors, each of which may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0155] The above-mentioned computer device may be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device may be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer device.

[0156] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the control method of the above-mentioned solder paste production process is implemented.

[0157] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0158] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for controlling a solder paste production process, characterized in that: The steps include: Start the production of solder paste and obtain the particle size distribution data set of solder paste particles when the solder paste is mixed; Determine the distribution entropy and distribution difference set of solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data set; Extracting the first ingredient mixing area and the second ingredient mixing area in the production process of the solder paste through all the distribution entropies, and then determining the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing area and the distribution difference set corresponding to the second ingredient mixing area; Performing fusion morphology analysis on solder paste particles in the current solder paste production process based on the mixed correlation quantity to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then determining the plasticity of the solder paste in the current production state based on the dispersion characteristics and the sedimentation characteristics; Adjusting the batching parameters of the solder paste production process based on the plasticity, and producing the solder paste according to the adjusted batching parameters; Determining the distribution entropy and distribution difference set of solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data set specifically includes: Selecting a batching and mixing area as a selected batching and mixing area, and extracting particle size distribution data of the selected batching and mixing area; Extract all different particle size distribution values ​​from the particle size distribution data; Determine the distribution proportion of each different particle size distribution value; Determine the distribution entropy of the solder paste particles in the selected ingredient mixing area according to the distribution proportions of all different particle size distribution values; Performing slip calculation on each particle size distribution value in the particle size distribution data to obtain all particle size distribution difference values; Combining all particle size distribution difference values ​​to obtain a distribution difference set of solder paste particle distribution in the selected ingredient mixing area; Continue to determine the distribution entropy and distribution difference set of the solder paste particle distribution in the remaining ingredient mixing area; Determining the distribution ratio of each different particle size distribution value specifically includes: Obtaining the frequency of occurrence of each different particle size distribution value in the particle size distribution data; Acquire the total amount of data of the particle size distribution data; For each different particle size distribution value, the frequency ratio of the different particle size distribution value in the particle size distribution data is calculated to the total amount of the data, thereby obtaining the distribution proportion of each different particle size distribution value; The first ingredient mixing area and the second ingredient mixing area in the solder paste production process are extracted through all distribution entropy, specifically including: Extract the maximum distribution entropy and the minimum distribution entropy from all distribution entropies; The batching and mixing area corresponding to the maximum distribution entropy is used as the first batching and mixing area; The ingredient mixing zone corresponding to the minimum distribution entropy is used as the second ingredient mixing zone.

2. The method according to claim 1, characterized in that Determining the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing area and the distribution difference set corresponding to the second ingredient mixing area specifically includes: Obtaining a distribution difference set corresponding to the first ingredient mixing zone and a distribution difference set corresponding to the second ingredient mixing zone; Performing same-space mapping fitting on the distribution difference set corresponding to the first ingredient mixing zone and the distribution difference set corresponding to the second ingredient mixing zone to obtain a distribution difference fitting hyperbola; Extract all fitting intersection points from the distribution difference fitting hyperbola; Obtaining the total number of data of the distribution difference set corresponding to the first ingredient mixing zone; The mixing correlation amount when the solder paste is mixed is determined based on all the fitting intersection points and the total number of data.

3. The method according to claim 1, characterized in that The fusion morphology analysis of the solder paste particles in the current solder paste production process is performed based on the mixed correlation quantity to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, which specifically include: Determine the mixing correlation threshold of solder paste particles during solder paste production; The mixed correlation amount is compared with the mixed correlation threshold, and when the mixed correlation amount is greater than the mixed correlation threshold, solder paste particle density data in the current solder paste production process is obtained; Determine, according to the solder paste particle density data, a density deviation value sequence of solder paste particles at different solder paste areas in the current solder paste production process; The dispersion characteristics and sedimentation characteristics of the solder paste particles are determined by the density deviation value sequence of the solder paste particles at different solder paste areas.

4. The method according to claim 1, characterized in that The particle size distribution data set of solder paste particles when the solder paste is mixed is obtained from the solder paste production monitoring database.

5. A solder paste production process control system, characterized in that: include: An acquisition module is used to start the production of solder paste and obtain the particle size distribution data of solder paste particles when the solder paste is mixed; A processing module, used for determining a distribution entropy and a distribution difference set of solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data; The processing module is further used to extract the first ingredient mixing area and the second ingredient mixing area in the production process of the solder paste through all the distribution entropies, and then determine the mixing correlation amount when the solder paste is mixed according to the distribution difference set corresponding to the first ingredient mixing area and the distribution difference set corresponding to the second ingredient mixing area; The processing module is further used to perform fusion morphology analysis on solder paste particles in the current solder paste production process based on the mixed correlation quantity to obtain the dispersion characteristics and sedimentation characteristics of the solder paste particles, and then determine the plasticity of the solder paste in the current production state through the dispersion characteristics and the sedimentation characteristics; An execution module, used to adjust the batching parameters of the solder paste production process based on the plasticity, and produce the solder paste according to the adjusted batching parameters; Determining the distribution entropy and distribution difference set of solder paste particle distribution in different ingredient mixing areas based on the particle size distribution data set specifically includes: Selecting a batching and mixing area as a selected batching and mixing area, and extracting particle size distribution data of the selected batching and mixing area; Extract all different particle size distribution values ​​from the particle size distribution data; Determine the distribution proportion of each different particle size distribution value; Determine the distribution entropy of the solder paste particles in the selected ingredient mixing area according to the distribution proportions of all different particle size distribution values; Performing slip calculation on each particle size distribution value in the particle size distribution data to obtain all particle size distribution difference values; Combining all particle size distribution difference values ​​to obtain a distribution difference set of solder paste particle distribution in the selected ingredient mixing area; Continue to determine the distribution entropy and distribution difference set of the solder paste particle distribution in the remaining ingredient mixing area; Determining the distribution ratio of each different particle size distribution value specifically includes: Obtaining the frequency of occurrence of each different particle size distribution value in the particle size distribution data; Acquire the total amount of data of the particle size distribution data; For each different particle size distribution value, the frequency ratio of the different particle size distribution value in the particle size distribution data is calculated to the total amount of the data, thereby obtaining the distribution proportion of each different particle size distribution value; The first ingredient mixing area and the second ingredient mixing area in the solder paste production process are extracted through all distribution entropy, specifically including: Extract the maximum distribution entropy and the minimum distribution entropy from all distribution entropies; The batching and mixing area corresponding to the maximum distribution entropy is used as the first batching and mixing area; The ingredient mixing zone corresponding to the minimum distribution entropy is used as the second ingredient mixing zone.

6. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute the control method for the solder paste production process according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the control method for the solder paste production process according to any one of claims 1 to 4 is implemented.

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