A method and system for optimizing the robustness of reflow soldering process

Abstract

The present application provides a method and system for optimizing the robustness of the reflow soldering process, which relates to the field of digital manufacturing. The method includes: constructing a thermal model of the PCB component during the reflow soldering process based on the surface device structure and substrate layout in the obtained PCB component; constructing a mechanical model of the PCB component, establishing a convective heat transfer model during the reflow soldering process based on the thermal model, adding temperature boundary conditions to the mechanical model, and constructing a coupled mechanical-thermal simulation model; constructing a simulation surrogate model and a robustness optimization model; based on the robustness optimization model, using a genetic algorithm to search the simulation surrogate model to optimize the robustness of the reflow soldering process parameters. The present application constructs a surrogate model for the reflow soldering process, realizes the rapid simulation analysis of the temperature change and warping deformation of any solder joint of the PCB component during the reflow soldering process, and realizes the robustness optimization of the reflow process under the condition of considering the uncertainty of process parameters, ensuring the yield of the reflow soldering process.

Description

Technical Field

[0001] The present application relates to the field of digital manufacturing technology, and particularly relates to a method and system for optimizing the robustness of reflow soldering process. Background Art

[0002] With the progress of technology, modern printed circuit board assemblies have a large variety and high density of devices. Especially, large-size devices such as microcontroller units (MCUs) have numerous I / O pins, small solder joint pitches, high densities, and low yields of welded batches, and are prone to electrical faults such as short circuits and open circuits. Reflow soldering is the main assembly technology for high-density printed circuit board (PCB) assemblies. All the electronic components on the PCB pass through each temperature zone of the reflow soldering furnace in sequence, and the overall heating is completed in one-time soldering. Ideal reflow soldering process control parameters can enable all solder joints to withstand qualified temperature curves and produce small deformations, which is a key link to ensure the yield of PCB assemblies. During the actual reflow soldering process of PCB assemblies, the temperature response curves of different solder joints are different, and solder joints with temperature response curves that do not meet the welding requirements will not be able to achieve effective soldering. During the reflow soldering process of PCB assemblies, thermal deformation will also inevitably occur. The essence of solder joint interconnection is that the solder joint connects the device substrate pad and the PCB substrate pad. Excessive deformation will directly lead to soldering failure or poor soldering quality.

[0003] Reflow soldering is a key process in the production process of PCB assemblies. It is necessary to ensure the temperature response and warpage deformation of all solder joints, and has high requirements for the accuracy of process parameters. In theory, the reflow soldering process must be strictly and precisely controlled. However, during the reflow soldering process, the actual process parameters often fluctuate around the design parameters, and it is difficult and costly to precisely control. The instability of various process parameters during the reflow soldering process will lead to unstable quality and yield of the reflow soldering process, and a small process window.

[0004] Based on the general (99.7% yield) quality control requirements in modern manufacturing, it is particularly important to improve the robustness of the reflow soldering process itself, realize the rapid debugging of process parameters, and ensure the yield. The traditional method for reflow soldering process debugging is based on iterative trial production, which requires repeated experiments, has a long cycle and low efficiency, and the fluctuations of process parameters lead to difficult process debugging and low yield, which is contrary to the current situation of multiple models, small batches, and short development cycles of electronic equipment. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present application provides a method and system for optimizing the robustness of reflow soldering process, which solves the problems of slow debugging speed of current reflow soldering process parameters and poor robustness of reflow soldering process.

[0006] To achieve the above object, the present application is implemented through the following technical solutions:

[0007] In a first aspect, an embodiment of the present application provides a method for optimizing the robustness of a reflow soldering process. The method for optimizing the robustness of the reflow soldering process includes:

[0008] Based on the obtained surface device structure and substrate layout in the PCB component, a thermal model of the PCB component during the reflow soldering process is constructed; wherein, the thermal model includes a surface device thermal model and a substrate thermal model;

[0009] Construct a mechanical model of the PCB component, where the mechanical model includes a surface device mechanical model and a substrate mechanical model;

[0010] Based on the thermal model, a convective heat transfer model of the reflow soldering process is established, and based on the convective heat transfer model, a temperature boundary condition is added to the mechanical model to construct a thermal-structural coupled simulation model;

[0011] Respectively construct a simulation proxy model and a robustness optimization model for the reflow soldering process;

[0012] Based on the robustness optimization model, use the genetic algorithm to search the simulation proxy model to perform robustness optimization of the reflow soldering process parameters considering uncertainty, and obtain the target solution of the robustness optimization to characterize the reflow soldering process parameters.

[0013] According to the first aspect of the embodiment of the present application, in the surface device thermal model, it is determined that the thermal resistances of the top surface and the bottom surface of the surface device structure are respectively thermal resistance and thermal resistance, The thermal resistance is the thermal resistance from the junction node to the case node, The thermal resistance is the thermal resistance from the junction node to the board node.

[0014] According to the first aspect of the embodiment of the present application, the substrate thermal model is a thermal grid model of the alternating laminated structure of the multi-layer copper clad layer and the fiberglass material of the substrate in the PCB component; the substrate thermal model is provided with the thermal conductivity and the interfacial thermal resistance of the copper clad layer and the fiberglass material.

[0015] According to the first aspect of the embodiment of the present application, the construction process of the foregoing surface device mechanical model may specifically include the following steps: According to different package types of the devices, a first finite element mesh model of a typical device is constructed with the device core and pins as the core elements; in the first finite element mesh model, the mechanical properties of the device core and pins are set to complete the device mechanical modeling.

[0016] According to the first aspect of the embodiments of the present application, the construction process of the substrate mechanical model includes: based on the substrate layout of the PCB component, constructing a second finite element mesh model of the PCB component substrate including a multi-layer structure of a copper-clad layer and fiberglass; in the second finite element mesh model, setting the mechanical properties of the copper-clad layer and fiberglass to achieve substrate mechanical modeling; wherein, the mechanical properties include elastic modulus and Poisson's ratio.

[0017] According to the first aspect of the embodiments of the present application, based on the above thermal model, a convective heat transfer model of the reflow soldering process is established, and temperature boundary conditions are added to the mechanical model based on the convective heat transfer model to construct a mechanical-thermal coupled simulation model, which may specifically include the following steps:

[0018] Determine the target process parameters including chain speed and temperature of each temperature zone during the reflow soldering process;

[0019] Based on the thermal model, use the Flotherm tool and the Ansys Icepak tool to establish a convective heat transfer model of the reflow soldering process;

[0020] Based on the convective heat transfer model, set the thermal simulation boundary conditions according to the actual time of each temperature zone and the temperature of the temperature zone to perform thermal simulation of the reflow soldering process, and obtain the temperature response time history data of the PCB component;

[0021] Use the temperature response time history data as the temperature boundary condition for mechanical simulation of the mechanical model to construct a mechanical-thermal coupled simulation model.

[0022] According to the first aspect of the embodiments of the present application, the above simulation proxy model is a Kriging proxy model; the temperature response time history data includes heating rate, peak temperature, high-temperature holding time, and cooling rate; the construction process of the simulation proxy model may specifically include the following steps:

[0023] Determine the target process parameters affecting the quality of the reflow soldering process as input variables;

[0024] Select the temperature response time history data of the solder joints of the PCB component and the warping deformation at the solder joints as the quantitative evaluation criteria for the quality of the reflow soldering process, and determine the quantitative evaluation criteria as the output variables of the proxy model;

[0025] For the determined input variables and output variables, through Latin square experimental design, select multiple groups of input sample points in the design space, perform simulation calculations on the reflow soldering process for each sample point, and obtain the output response values corresponding to the input sample points;

[0026] Combine the obtained input variables and output response values to establish a Kriging proxy model.

[0027] According to the first aspect of the embodiments of the present application, the construction process of the aforementioned robustness optimization model may specifically include the following steps:

[0028] Determine the target process parameters that affect the quality of the reflow soldering process as design variables; the target process parameters include deterministic process parameters and uncertain process parameters; the deterministic process parameters include the chain speed of the reflow soldering furnace, and the uncertain process parameters include the temperatures of each temperature zone;

[0029] Determine the warpage deformation in the quantitative evaluation criterion of the reflow soldering process quality as the optimization objective;

[0030] Determine the heating rate, peak temperature, high-temperature holding time, cooling rate in the quantitative evaluation criterion of the reflow soldering process quality, and the chain speed setting of the process parameters as design constraints;

[0031] Among them, the heating rate, peak temperature, high-temperature holding time, and cooling rate follow a normal probability distribution, and the mean and variance are set according to the requirements for ensuring welding quality.

[0032] According to the first aspect of the embodiments of the present application, the robustness optimization model satisfies the expression:

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041] Among them, and are design variables, is the chain speed of the reflow soldering furnace, is the temperature of the th temperature zone of the reflow soldering furnace, is the optimization objective and represents the warpage deformation of the th solder joint; is the heating rate of the th solder joint, and are the mean and variance of the heating rate respectively, is the maximum allowable heating rate; is the high temperature holding time of the th solder joint, and are the mean and variance of the high temperature holding time , and are the minimum allowable high temperature holding time and the maximum allowable high temperature holding time respectively; is the cooling rate of the th solder joint, and are the mean and variance of the cooling rate respectively, is the maximum allowable cooling rate; is the peak temperature of the th solder joint, and are the mean and variance of the peak temperature respectively, and are the minimum allowable peak temperature and the maximum allowable peak temperature; is the temperature of each temperature zone, and are the mean and variance of the temperature of each temperature zone respectively, is the maximum allowable temperature of each temperature zone; is the chain speed, and are the minimum allowable chain speed and the maximum allowable chain speed respectively.

[0042] In a second aspect, an embodiment of the present application provides a reflow soldering process robustness optimization system, which includes: a thermal model construction module, a mechanical model construction module, a machine-thermal coupling module, an agent optimization module, and a search optimization module.

[0043] Specifically, the thermal model construction module is used to construct a thermal model of the PCB component during the reflow soldering process based on the obtained surface device structure and substrate layout in the PCB component. Among them, the thermal model includes a surface device thermal model and a substrate thermal model. The mechanical model construction module is used to construct a mechanical model of the PCB component, and the mechanical model includes a surface device mechanical model and a substrate mechanical model. The mechanical-thermal coupling module is used to establish a convective heat transfer model of the reflow soldering process based on the thermal model, add temperature boundary conditions to the mechanical model based on the convective heat transfer model, and construct a mechanical-thermal coupling simulation model. The surrogate optimization module is used to construct a simulation surrogate model and a robustness optimization model for the reflow soldering process respectively. The search optimization module is used to search the simulation surrogate model using the genetic algorithm based on the robustness optimization model, and perform robustness optimization of the reflow soldering process parameters considering uncertainty to obtain the target solution of robustness optimization to characterize the reflow soldering process parameters.

[0044] In a third aspect, an embodiment of the present application provides an electronic device, which includes: a processor, a memory, and a program stored on the memory and executable on the processor. When the program is executed by the processor, it implements a reflow soldering process robustness optimization method in the foregoing first aspect.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by the processor, it implements a reflow soldering process robustness optimization method in the foregoing first aspect.

[0046] The present application provides a method and system for optimizing the robustness of the reflow soldering process. Compared with the prior art, it has the following beneficial effects:

[0047] Based on the surface device structure and substrate layout in the PCB component, the present application constructs a mechanical-thermal coupling simulation model of the reflow soldering process, and further constructs a simulation surrogate model for mathematical simplification. By using the established robustness optimization model to search the simulation surrogate model with the genetic algorithm, it is possible to perform robustness optimization of the reflow soldering process parameters considering uncertainty, and iteratively analyze to obtain an ideal target solution of robustness optimization to characterize the reflow soldering process parameters. The present application constructs a surrogate model of the reflow soldering process, and realizes the rapid simulation analysis of the temperature change and warping deformation of any solder joint of the PCB component during the reflow soldering process. Under the condition of considering the uncertainty of process parameters, the robustness of the reflow process is optimized to ensure the yield of the reflow soldering process. The method provided by the present application can quickly evaluate the manufacturability of the PCB component at the design stage of the PCB component, which can greatly reduce the reflow soldering process debugging time and reduce the manufacturing risk. Description of the Drawings

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0049] Figure 1 is a schematic flowchart of a method for optimizing the robustness of a reflow soldering process provided by an embodiment of the present application;

[0050] Figure 2 is Figure 1 an exemplary flowchart of S130 in

[0051] Figure 3 is a schematic diagram of a reflow soldering process provided by an embodiment of the present application;

[0052] Figure 4 is a schematic diagram of a simplified thermal model of a PCB component provided by an embodiment of the present application;

[0053] Figure 5 is a schematic diagram of a simplified mechanical model of a PCB component provided by an embodiment of the present application;

[0054] Figure 6 is a schematic structural diagram of a system for optimizing the robustness of a reflow soldering process provided by an embodiment of the present application;

[0055] Figure 7 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0056] Description of the drawings: PCB component 101; heater 102; heating fan 103; cooling fan 104; surface device thermal model 301; adiabatic surface 302; top surface of the device 303; bottom surface of the device 304; substrate thermal model 305; surface device mechanical model 401; solder joints at the bottom of the device 402; substrate mechanical model 403. Detailed implementation manners

[0057] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0058] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0059] By providing an optimization method and system for the robustness of the reflow soldering process, the embodiments of the present application solve the problems of slow debugging speed of current reflow soldering process parameters and poor robustness of the reflow soldering process.

[0060] The overall idea of the technical solution in the embodiments of the present application to solve the above technical problems is as follows:

[0061] With the progress of technology, modern printed circuit board assemblies have a wide variety of devices and high density. Especially, large-sized devices such as MCUs have numerous I / O pins, small solder joint pitches, high density, and low yield of welded batches, and are prone to electrical faults such as short circuits and open circuits. Reflow soldering is the main assembly technology for high-density PCB assemblies. All the electronic components on the PCB pass through each temperature zone of the reflow soldering furnace in turn, and the overall heating is completed by one-time soldering. Ideal reflow soldering process control parameters can enable all solder joints to withstand a qualified temperature curve and produce less deformation, which is the key link to ensure the yield of PCB assemblies. During the actual reflow soldering process of PCB assemblies, the temperature response curves of different solder joints are different, and solder joints with temperature response curves that do not meet the soldering requirements will not be effectively soldered. During the reflow soldering process of PCB assemblies, thermal deformation will also inevitably occur. The essence of solder joint interconnection is that the solder joint connects the device substrate pad and the PCB substrate pad. Excessive deformation will directly lead to soldering failure or poor soldering quality.

[0062] Reflow soldering is a key process in the production of PCB assemblies. It is necessary to ensure the temperature response and warpage deformation of all solder joints, and has high requirements for the accuracy of process parameters. In theory, the reflow soldering process must be strictly and precisely controlled. However, during the reflow soldering process, the actual process parameters often fluctuate around the design parameters, and it is difficult and costly to precisely control. The instability of various process parameters during the reflow soldering process will lead to unstable quality and yield of the reflow soldering process and a small process window. Based on the common (99.7% yield rate) Quality control requirements. How to improve the robustness of the reflow soldering process itself, achieve rapid debugging of process parameters, and ensure the yield rate is particularly important.

[0063] The traditional method for debugging the reflow soldering process is based on iterative trial production, which requires repeated experiments, has a long cycle and low efficiency. Moreover, the fluctuations in process parameters make it difficult to debug the process and result in a low yield rate, which is contrary to the current situation of multiple models, small batches, and short development cycles in electronic equipment. Therefore, there is an urgent need to develop an optimization method and system for the robustness of the reflow soldering process that can ensure the yield rate of the reflow soldering process under the condition of considering the uncertainty of process parameters.

[0064] To better understand the above technical solution, the following will combine the accompanying drawings of the specification and specific implementation manners to elaborate on the above technical solution in detail.

[0065] First, an optimization method for the robustness of the reflow soldering process provided by the embodiments of the present application will be introduced below.

[0066] The flow chart of an optimization method for the robustness of the reflow soldering process provided by the embodiments of the present application is as Figure 1 shown. The optimization method for the robustness of the reflow soldering process may include the following steps S110 - S150.

[0067] S110. Based on the surface device structure and substrate layout in the obtained PCB component, construct a thermal model of the PCB component during the reflow soldering process; wherein, the thermal model includes a surface device thermal model and a substrate thermal model.

[0068] S120. Construct a mechanical model of the PCB component, and the mechanical model includes a surface device mechanical model and a substrate mechanical model.

[0069] S130. Based on the thermal model, establish a convective heat transfer model of the reflow soldering process, and add temperature boundary conditions to the mechanical model based on the convective heat transfer model to construct a mechanical - thermal coupled simulation model.

[0070] S140. Respectively construct a simulation surrogate model and a robustness optimization model of the reflow soldering process.

[0071] S150. Based on the robustness optimization model, use the genetic algorithm to search the simulation surrogate model, and perform robustness optimization of the reflow soldering process parameters considering uncertainty to obtain the target solution of the robustness optimization to characterize the reflow soldering process parameters.

[0072] It should be noted that the reflow soldering process analyzed in this embodiment is as Figure 3As shown in the figure, the reflow soldering furnace involved in the process includes 10 heating zones and 3 cooling zones. The PCB assembly mainly includes a substrate and surface devices. In this embodiment, only one large-size BGA surface-mounted device is considered. During the reflow soldering process, the PCB assembly is conveyed by the conveying chain of the reflow soldering furnace at a set speed. Inside the furnace, the reflow soldering furnace heats or cools the PCB assembly by blowing air with a fan.

[0073] The above is the specific implementation manner of a method for optimizing the robustness of the reflow soldering process provided by the present application. It can be understood that the present application constructs a thermal model and a mechanical model of the reflow soldering process based on the surface device structure and substrate layout in the PCB assembly. According to this thermal model, a convective heat transfer model of the reflow soldering can be established. After obtaining this convective heat transfer model, a temperature boundary condition can be added to the mechanical model, and then a mechanical-thermal coupled simulation model can be obtained; after obtaining the mechanical-thermal coupled simulation model, a simulation surrogate model is further constructed for mathematical simplification. By using the genetic algorithm to search the simulation surrogate model through the established robustness optimization model, the robustness optimization of the reflow soldering process parameters considering uncertainty can be carried out, and the ideal target solution of the robustness optimization can be obtained through iterative analysis to characterize the reflow soldering process parameters.

[0074] Based on this, the present application constructs a surrogate model of the reflow soldering process, realizing the rapid simulation analysis of the temperature change and warping deformation of any solder joint of the PCB assembly during the reflow soldering process. Under the condition of considering the uncertainty of process parameters, the robustness optimization of the reflow process is realized, ensuring the yield of the reflow soldering process. The method provided by the present application can quickly evaluate the manufacturability of the PCB assembly at the scheme stage of the PCB assembly, which can greatly reduce the reflow soldering process debugging time and reduce the manufacturing risk; the method for optimizing the robustness of the reflow soldering process based on quality control provided by the present application provides a very promising and feasible technical path.

[0075] In some embodiments, in the surface device thermal model, the thermal resistances of the top surface and the bottom surface of the surface device structure are determined to be thermal resistance and thermal resistance, The thermal resistance is the thermal resistance from the junction node to the case node, The thermal resistance is the thermal resistance from the junction node to the board node. The substrate thermal model is a thermal grid model of the alternating laminated structure of the multi-layer copper-clad layer and glass fiber material of the substrate in the PCB assembly; the substrate thermal model is set with the thermal conductivity and interface thermal resistance of the copper-clad layer and the glass fiber material.

[0076] In the embodiment of the present application, the simplified thermal model of the large-size BGA surface-mounted device constructed is as Figure 4 shown. The device is simplified to a cuboid structure, and the thermal resistances of the top surface and the bottom surface of the device are respectively set to thermal resistance and Thermal resistance, and the periphery of the device is set as an insulating interface. The shell node is the part where the upper surface of the device package is in direct contact with the thermal interface material connecting to the heat sink, the junction node is the location where the chip power consumption occurs, and the board node is the part directly connected to the bottom of the package, i.e., the PCB board. Thermal resistance and Thermal resistance can be obtained by conducting tests according to JEDEC standards or by referring to the product manual of the device. In addition, based on the layout design of the PCB substrate, a thermal grid model of the alternating laminated structure of the multi-layer copper cladding and fiberglass in the PCB substrate can be established, and thermal properties such as the thermal conductivity coefficients and interface thermal resistances of the copper cladding and fiberglass are set.

[0077] In some embodiments, the construction process of the foregoing surface device mechanical model may specifically include the following steps: According to different package types of the device, a first finite element mesh model of a typical device is constructed with the device core and pins as the core elements; in the first finite element mesh model, the mechanical properties of the device core and pins are set to complete the device mechanical modeling.

[0078] The construction process of the substrate mechanical model includes: Based on the substrate layout of the PCB component, a second finite element mesh model of the PCB component substrate including a multi-layer structure of copper cladding and fiberglass is constructed; in the second finite element mesh model, the mechanical properties of the copper cladding and fiberglass are set to achieve substrate mechanical modeling; wherein, the mechanical properties include elastic modulus and Poisson's ratio.

[0079] In the embodiments of the present application, it can be understood that as Figure 5 shown, the PCB component mechanical model mainly includes two parts: the surface device mechanical model and the substrate mechanical model. According to the structural characteristics of the large-size BGA device, a simplified finite element mesh model of a typical device is constructed with the device plastic package, internal chip, device substrate, and BGA solder ball array as the core elements, and mechanical properties such as the material elastic modulus and Poisson's ratio of the device plastic package, internal chip, device substrate, and BGA solder ball array are set to achieve device mechanical modeling. Based on the PCB component substrate layout, a finite element mesh model of the PCB component substrate including a multi-layer structure of copper cladding and fiberglass is constructed, and mechanical properties such as the elastic modulus and Poisson's ratio of the copper cladding and fiberglass are set to achieve substrate mechanical modeling.

[0080] In some embodiments, as Figure 2 shown, based on the foregoing thermal model, a convective heat transfer model of the reflow soldering process is established, and temperature boundary conditions are added to the mechanical model based on the convective heat transfer model to construct a thermal-structural coupled simulation model, which may specifically include the following steps:

[0081] S210. Determine the target process parameters including the chain speed and the temperature of each temperature zone during the reflow soldering process.

[0082] S220. Based on the thermal model, use the Flotherm tool and the Ansys Icepak tool to establish a convective heat transfer model for the reflow soldering process.

[0083] S230. Based on the convective heat transfer model, set the thermal simulation boundary conditions according to the actual passing time and temperature of each temperature zone to conduct a thermal simulation of the reflow soldering process, and obtain the temperature response time history data of the PCB assembly.

[0084] S240. Use the temperature response time history data as the temperature boundary condition for mechanical simulation of the mechanical model to construct a thermal-structural coupled simulation model.

[0085] In the embodiments of the present application, it can be understood that the present application determines key process parameters such as the chain speed and the temperature of each temperature zone in the reflow soldering process. Based on the established thermal model of the PCB assembly, use tools such as Flotherm and Ansys Icepak to establish a convective heat transfer model for the reflow soldering process, and set the thermal simulation boundary conditions according to the actual passing time and temperature of each temperature zone to realize the thermal simulation of the reflow soldering process of the PCB assembly, so as to obtain the temperature response time history data of the PCB assembly. Use the obtained temperature response time history data as the temperature boundary condition for mechanical simulation, and use tools such as Hypermesh, Ansys, and Abaqus to realize the mechanical simulation of the reflow soldering process of the PCB assembly, so as to obtain the warpage deformation data of the PCB assembly.

[0086] In some embodiments, the aforementioned simulation proxy model is a Kriging proxy model; the temperature response time history data includes the heating rate, peak temperature, high-temperature holding time, and cooling rate; the construction process of the simulation proxy model may specifically include the following steps:

[0087] S310. Determine the target process parameters that affect the quality of the reflow soldering process as input variables.

[0088] S320. Select the temperature response time history data of the solder joints of the PCB assembly and the warpage deformation at the solder joints as the quantitative evaluation criteria for the quality of the reflow soldering process, and determine the quantitative evaluation criteria as the output variables of the proxy model.

[0089] S330. For the determined input variables and output variables, through Latin square experimental design, select multiple groups of input sample points in the design space, and conduct simulation calculations of the reflow soldering process for each sample point to obtain the output response values corresponding to the input sample points.

[0090] S340. Combine the obtained input variables and output response values to establish a Kriging proxy model.

[0091] In the embodiments of the present application, it can be understood that the present application determines the main process parameters affecting the quality of the reflow soldering process as input variables. Considering the operability in the actual process, the chain speed of the reflow soldering furnace, the temperatures set in each temperature zone, etc. are selected as the main process parameters of the reflow soldering process, and the evaluation criteria for the quality of the reflow soldering process are determined as the output variables of the surrogate model. Considering the causes of the quality defects of the reflow soldering process of PCB components, the temperature response time history data of the solder joints of the PCB components and the warpage deformation at the solder joints are selected as the quantitative evaluation criteria for the quality of the reflow soldering process. For the determined input variables and output responses, through the Latin square experimental design, multiple groups of input sample points are selected within the design space, and the reflow soldering process simulation calculation is performed for each sample point to obtain the output response values corresponding to the input sample points. A Kriging surrogate model is established by combining the obtained input variables and output response sample points.

[0092] In some embodiments, the construction process of the foregoing robustness optimization model may specifically include the following steps:

[0093] S410. Determine the target process parameters affecting the quality of the reflow soldering process as design variables; the target process parameters include deterministic process parameters and uncertain process parameters; the deterministic process parameters include the chain speed of the reflow soldering furnace, and the uncertain process parameters include the temperatures in each temperature zone.

[0094] S420. Determine the warpage deformation in the quantitative evaluation criteria for the quality of the reflow soldering process as the optimization objective.

[0095] S430. Determine the heating rate, peak temperature, high-temperature holding time, cooling rate in the quantitative evaluation criteria for the quality of the reflow soldering process, and the chain speed of the process parameters as design constraints; among them, the heating rate, peak temperature, high-temperature holding time, and cooling rate follow a normal probability distribution, and the mean and variance are set according to the requirements for ensuring welding quality.

[0096] In the embodiments of the present application, it can be understood that the present application distinguishes deterministic process parameters and uncertain process parameters according to the controllability of process parameters in process operation, selects the chain speed of the reflow soldering furnace as the deterministic process parameter; selects the temperatures in each temperature zone as the uncertain process parameters, and believes that the actual temperatures in each temperature zone of the reflow soldering furnace follow a normal probability distribution, and its mean and variance are determined according to the measured data or experience. The present application sets the warpage deformation in the quantitative evaluation criteria for the quality of the reflow soldering process as the optimization objective. It is considered that the highest temperature follows a normal probability distribution, and its mean and variance are set according to the requirements for ensuring welding quality. The warpage deformation values of two typical solder joints at the center and edge of large-size BGA devices are extracted as the optimization objective in the analysis.

[0097] In addition, in this application, the heating rate, peak temperature, high-temperature holding time, cooling rate, etc. in the quantitative evaluation criteria for the reflow soldering process quality and the process parameter chain speed are set as design constraints. It is considered that the heating rate, peak temperature, high-temperature holding time, cooling rate, etc. follow a normal probability distribution, and their mean and variance are set according to the requirements for ensuring welding quality. In the analysis, the heating rate, peak temperature, high-temperature holding time, and cooling rate values of two typical solder joints at the center and edge of the device are extracted as design constraints.

[0098] In some embodiments, the robustness optimization model satisfies the expression:

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] Wherein, and are design variables, is the reflow soldering furnace chain speed, is the temperature of the th temperature zone of the reflow soldering furnace, is the optimization objective and characterizes the warping deformation of the th solder joint; is the heating rate of the th solder joint, and are the mean and variance of the heating rate , is the maximum allowable heating rate; is the high-temperature holding time of the th solder joint, and are the mean and variance of the high-temperature holding time , and are the minimum allowable high-temperature holding time and the maximum allowable high-temperature holding time respectively; is the cooling rate of the th solder joint, and The mean and variance of the cooling rate respectively, and the maximum allowable cooling rate; For the peak temperature of the th solder joint, the mean and variance of the peak temperature respectively, and the minimum allowable peak temperature and the maximum allowable peak temperature; For the temperature of each temperature zone, the mean and variance of the temperature of each temperature zone respectively, and the maximum allowable temperature of each temperature zone; For the chain speed, the minimum allowable chain speed and the maximum allowable chain speed respectively. It can be understood that the maximum or minimum allowable value of the constraint condition is obtained through experience, process manuals or tests. Based on the established robustness optimization model, this application uses the genetic algorithm to search for the surrogate model and obtains

[0108] the optimal solution of robustness optimization, that is, the optimal reflow soldering process parameters are obtained. Determine whether the optimization objective and constraint conditions meet the requirements. If they meet the requirements, the optimization ends and the optimal reflow soldering process parameters are obtained. If they do not meet the requirements, reselect the design variables or design constraints and perform iterative optimization. In some embodiments, this application provides a reflow soldering process robustness optimization system 500, as

[0109] shown, the reflow soldering process robustness optimization system 500 may include the following modules: Figure 6 A thermal model construction module 510, configured to construct a thermal model of the PCB component during the reflow soldering process based on the obtained surface device structure and substrate layout in the PCB component; wherein, the thermal model includes a surface device thermal model and a substrate thermal model;

[0110] A mechanical model construction module 520, configured to construct a mechanical model of the PCB component, and the mechanical model includes a surface device mechanical model and a substrate mechanical model;

[0111] A machine-thermal coupling module 530, configured to establish a convective heat transfer model of the reflow soldering process based on the thermal model, and add temperature boundary conditions to the mechanical model based on the convective heat transfer model to construct a machine-thermal coupling simulation model;

[0112] A surrogate optimization module 540, configured to respectively construct a simulation surrogate model and a robustness optimization model of the reflow soldering process;

[0113] ​

[0114] A search optimization module 550, configured to search a simulation surrogate model by using a genetic algorithm based on a robustness optimization model, perform robustness optimization of reflow soldering process parameters considering uncertainty, and obtain an objective solution of robustness optimization to characterize the reflow soldering process parameters.

[0115] According to an embodiment of the present application, any plurality of modules among the thermal model construction module 510, the mechanical model construction module 520, the mechanical-thermal coupling module 530, the surrogate optimization module 540, and the search optimization module 550 may be combined and implemented in one module, or any one of the modules may be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules may be combined with at least part of the functions of other modules and implemented in one module.

[0116] In some other alternative embodiments, the reflow soldering process robustness optimization system 500 may further include a central processing module 560. The central processing module 560 is configured to send control instructions to other modules and coordinate the actions of other modules. The thermal model construction module 510, the mechanical model construction module 520, the mechanical-thermal coupling module 530, the surrogate optimization module 540, and the search optimization module 550 are all connected to the central processing module 560 and receive control instructions from the central processing module 560.

[0117] Figure 6 Each module in the system shown has the functions of implementing each step in the foregoing reflow soldering process robustness optimization method and can achieve its corresponding technical effects. For the sake of brevity, the description is not repeated herein.

[0118] In some embodiments, the present application provides an electronic device, and a schematic structural diagram of the electronic device is as Figure 7 shown.

[0119] The electronic device may include a processor 610 and a memory 620 storing computer program instructions.

[0120] Specifically, the foregoing processor 610 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be an integrated circuit configured to implement one or more embodiments of the present application.

[0121] The memory 620 may include a mass storage for data or instructions. By way of example and not limitation, the memory 620 may include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disc, a magneto-optical disc, magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In a suitable case, the memory 620 may include removable or non-removable (or fixed) media. In a suitable case, the memory 620 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, the memory 620 is a non-volatile solid-state memory.

[0122] The memory 620 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory 620 includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it can perform the operations described in any of the reflow soldering process robustness optimization methods in the above embodiments.

[0123] The processor 610 realizes any of the reflow soldering process robustness optimization methods in the above embodiments by reading and executing the computer program instructions stored in the memory 620.

[0124] In one example, the electronic device may further include a communication interface 630 and a bus 600. Among them, as Figure 7 shown, the processor 610, the memory 620, and the communication interface 630 are connected through the bus 600 and complete communication with each other.

[0125] The communication interface 630 is mainly used to realize the communication between each module, device, unit, and / or device in the embodiments of the present application.

[0126] The bus 600 includes hardware, software, or both, and couples the components of the online data flow metering device to each other. By way of example and not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, the bus 600 may include one or more buses. Although the embodiments of the present application describe and illustrate specific buses, the present application contemplates any suitable bus or interconnect.

[0127] In addition, in combination with an optimization method for the robustness of a reflow soldering process in the above embodiments, an embodiment of the present application can be implemented by providing a computer storage medium. Computer program instructions are stored on the computer storage medium; when the computer program instructions are executed by a processor, any one of the optimization methods for the robustness of the reflow soldering process in the above embodiments is implemented.

[0128] It should be clear that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present application.

[0129] The functional blocks shown in the above block diagrams can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), appropriate firmware, a plug-in, a functional card, and so on. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium or transmitted via a data signal carried in a carrier wave on a transmission medium or a communication link. A "machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical discs, hard disks, fiber optic media, radio frequency (RF) links, and so on. The code segment can be downloaded via a computer network such as the Internet, an intranet, and so on.

[0130] It should also be noted that in the exemplary embodiments mentioned in this application, some methods or systems are described based on a series of steps or devices. However, this application is not limited to the order of the above steps. That is to say, the steps can be executed in the order mentioned in the embodiments, or different from the order in the embodiments, or several steps can be executed simultaneously.

[0131] As described above with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present disclosure. It should be understood that each block in the flowchart and / or block diagram, and the combination of blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more blocks of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It should also be understood that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can also be implemented by dedicated hardware that performs the specified functions or actions, or by a combination of dedicated hardware and computer instructions.

[0132] In summary, compared with the prior art, the present application has the following beneficial effects:

[0133] 1. After obtaining the thermal-mechanical coupled simulation model of the reflow soldering process, the present application further constructs a simulation proxy model for mathematical simplification, realizing the rapid simulation analysis of the temperature change and warpage deformation of any solder joint of the PCB component in the reflow soldering process; under the condition of considering the uncertainty of process parameters, it realizes the robust optimization of the reflow process and ensures the yield of the reflow soldering process.

[0134] 2. The method provided by the present application can quickly evaluate the manufacturability of the PCB component in the design stage of the PCB component, which can greatly reduce the reflow soldering process debugging time and reduce the manufacturing risk. The robust optimization method of the reflow soldering process provided by the present invention based on quality control provides a very promising and practical technical path.

[0135] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the robustness of a reflow soldering process, characterized in that, Including: Based on the surface device structure and substrate layout in the obtained PCB component, a thermal model of the PCB component during the reflow soldering process is constructed; wherein, the thermal model includes a surface device thermal model and a substrate thermal model; Construct a mechanical model of the PCB component, and the mechanical model includes a surface device mechanical model and a substrate mechanical model; Based on the thermal model, a convective heat transfer model of the reflow soldering process is established, and based on the convective heat transfer model, a temperature boundary condition is added to the mechanical model to construct a thermal-structural coupled simulation model; Construct a simulation surrogate model and a robustness optimization model for the reflow soldering process respectively; Based on the robustness optimization model, use the genetic algorithm to search the simulation surrogate model, and perform robustness optimization of the reflow soldering process parameters considering uncertainty to obtain the target solution of the robustness optimization to characterize the reflow soldering process parameters; The step of establishing a convective heat transfer model of the reflow soldering process based on the thermal model, adding a temperature boundary condition to the mechanical model based on the convective heat transfer model, and constructing a thermal-structural coupled simulation model includes: Determine the target process parameters including the chain speed and the temperature of each temperature zone during the reflow soldering process; Based on the thermal model, use the Flotherm tool and the Ansys Icepak tool to establish a convective heat transfer model of the reflow soldering process; Based on the convective heat transfer model, set the thermal simulation boundary conditions according to the actual passing time and temperature of each temperature zone to perform thermal simulation of the reflow soldering process, and obtain the temperature response time history data of the PCB component; Use the temperature response time history data as the temperature boundary condition for mechanical simulation of the mechanical model to construct a thermal-structural coupled simulation model; The construction process of the robustness optimization model includes: Determine the target process parameters affecting the reflow soldering process quality as design variables; the target process parameters include deterministic process parameters and uncertain process parameters; the deterministic process parameters include the chain speed of the reflow soldering furnace, and the uncertain process parameters include the temperature of each temperature zone; Determine the warpage deformation in the quantitative evaluation criterion of the reflow soldering process quality as the optimization objective; Determine the heating rate, peak temperature, high temperature holding time, cooling rate and the chain speed of the process parameters in the quantitative evaluation criterion of the reflow soldering process quality as design constraints; Wherein, the heating rate, the peak temperature, the high temperature holding time and the cooling rate follow a normal probability distribution, and the mean and variance are set according to the requirements of welding quality assurance.

2. The method for optimizing the robustness of a reflow soldering process according to claim 1, wherein, In the surface device thermal model, the thermal resistances of the top and bottom surfaces of the surface device structure are determined to be thermal resistance and thermal resistance respectively. The thermal resistance is the thermal resistance from the junction node to the case node, and the thermal resistance is the thermal resistance from the junction node to the board node; The substrate thermal model is a thermal grid model of the alternating laminated structure of the multi-layer copper clad layer and glass fiber material of the substrate in the PCB component; the substrate thermal model is set with the thermal conductivity and interface thermal resistance of the copper clad layer and the glass fiber material.

3. The method for optimizing the robustness of a reflow soldering process according to claim 1, wherein, The construction process of the surface device mechanical model includes: According to different package types of the devices, a first finite element mesh model of typical devices is constructed with the device core and pins as the core elements; In the first finite element mesh model, set the mechanical properties of the device core and pins to complete the device mechanical modeling; The construction process of the substrate mechanical model includes: Based on the substrate layout of the PCB component, construct a second finite element mesh model of the PCB component substrate including a multi-layer structure of copper clad layers and fiberglass materials; In the second finite element mesh model, set the mechanical properties of the copper clad layer and fiberglass materials to achieve substrate mechanical modeling; wherein, the mechanical properties include elastic modulus and Poisson's ratio.

4. The method for optimizing the robustness of a reflow soldering process according to claim 1, wherein The simulation surrogate model is a Kriging surrogate model; the temperature response time history data includes heating rate, peak temperature, high temperature holding time, and cooling rate; the construction process of the simulation surrogate model includes: Determine the target process parameters affecting the quality of the reflow soldering process as input variables; Select the temperature response time history data of the solder joints of the PCB component and the warping deformation at the solder joints as the quantitative evaluation criteria for the quality of the reflow soldering process, and determine the quantitative evaluation criteria as the output variables of the surrogate model; For the determined input variables and output variables, through Latin square experimental design, select multiple groups of input sample points in the design space, perform simulation calculations on the reflow soldering process for each sample point, and obtain the output response values corresponding to the input sample points; Combine the obtained input variables and the output response values to establish a Kriging surrogate model.

5. The method for optimizing the robustness of a reflow soldering process according to claim 1, characterized in that, The robustness optimization model satisfies the expression: Among them, and are design variables, is the conveyor speed of the reflow soldering furnace, is the temperature of the th temperature zone of the reflow soldering furnace, is the optimization objective and characterizes the warpage deformation of the th solder joint; is the heating rate of the th solder joint, and are the mean and variance of the heating rate , is the maximum allowable heating rate; is the high-temperature holding time of the th solder joint, and are the mean and variance of the high-temperature holding time , and are the minimum allowable high-temperature holding time and the maximum allowable high-temperature holding time, respectively; is the cooling rate of the th solder joint, and are the mean and variance of the cooling rate , is the maximum allowable cooling rate; is the peak temperature of the th solder joint, and are the mean and variance of the peak temperature , and are the minimum allowable peak temperature and the maximum allowable peak temperature, respectively; is the temperature of each temperature zone, and are the mean and variance of the temperature of each temperature zone , is the maximum allowable temperature of each temperature zone; is the conveyor speed, and are the minimum allowable conveyor speed and the maximum allowable conveyor speed, respectively.

6. A reflow soldering process robustness optimization system, characterized in that Including: A thermal model construction module, configured to construct a thermal model of the PCB component during the reflow soldering process based on the obtained surface device structure and substrate layout in the PCB component; wherein, the thermal model includes a surface device thermal model and a substrate thermal model; A mechanical model construction module, configured to construct a mechanical model of the PCB component, the mechanical model including a surface device mechanical model and a substrate mechanical model; A mechanical-thermal coupling module, configured to establish a convective heat transfer model of the reflow soldering process based on the thermal model, add temperature boundary conditions to the mechanical model based on the convective heat transfer model, and construct a mechanical-thermal coupling simulation model; A surrogate optimization module, configured to respectively construct a simulation surrogate model and a robustness optimization model of the reflow soldering process; A search and optimization module, configured to search the simulation surrogate model based on the robustness optimization model using a genetic algorithm, perform robustness optimization of the reflow soldering process parameters considering uncertainties, and obtain a target solution for robustness optimization to characterize the reflow soldering process parameters; The establishing a convective heat transfer model of the reflow soldering process based on the thermal model, adding temperature boundary conditions to the mechanical model based on the convective heat transfer model, and constructing a mechanical-thermal coupling simulation model includes: Determine the target process parameters including chain speed and temperature of each temperature zone during the reflow soldering process; Based on the thermal model, use Flotherm tool and Ansys Icepak tool to establish a convective heat transfer model of the reflow soldering process; Based on the convective heat transfer model, set thermal simulation boundary conditions according to the actual time of each temperature zone and the temperature of the temperature zone to perform thermal simulation of the reflow soldering process, and obtain the temperature response time history data of the PCB component; Use the temperature response time history data as the temperature boundary condition for mechanical simulation of the mechanical model to construct a thermal-structural coupled simulation model; The construction process of the robustness optimization model includes: Determine the target process parameters that affect the quality of the reflow soldering process as design variables; the target process parameters include deterministic process parameters and uncertain process parameters; the deterministic process parameters include the chain speed of the reflow soldering furnace, and the uncertain process parameters include the temperatures of each temperature zone; Determine the warpage deformation in the quantitative evaluation criterion of the reflow soldering process quality as the optimization objective; Determine the heating rate, peak temperature, high-temperature holding time, cooling rate in the quantitative evaluation criterion of the reflow soldering process quality, and the chain speed setting of the process parameters as design constraints; Among them, the heating rate, the peak temperature, the high-temperature holding time, and the cooling rate follow a normal probability distribution, and the mean and variance are set according to the requirements for ensuring welding quality.

7. An electronic device, characterized in that, It includes: A processor, a memory, and a program stored on the memory and executable on the processor, where when the program is executed by the processor, it implements a reflow soldering process robustness optimization method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, A program or instruction is stored on the computer-readable storage medium, and when the program or instruction is executed by the processor, it implements a reflow soldering process robustness optimization method according to any one of claims 1 to 5.

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