Printed circuit board, commonly known as printed circuit board, is a mechanical component that combines electronic components together and connects them electrically. Printed circuit boards have many sandwich layers, and the building materials of these layers are also different. The variability of this sandwich structure makes it very difficult to establish and verify finite element models of circuit boards. In the literature, many studies on obtaining the optimal circuit board model can be found through experimental design and optimization methods.

In the process of virtual prototype design and the practical application of computer-aided engineering optimization, it is not always possible to reduce the complexity of physical models and obtain numerical models that can be quickly solved. Generally speaking, each numerical simulation takes several hours or even days. Therefore, effective metamodels have become a substitute for costly design research. In addition to providing an automated method to select the most suitable problem metamodel, an independent test dataset should be used to evaluate the quality of the metamodel for prediction. Therefore, choosing the best prognostic metamodel is called the metamodel for optimizing prognosis. By utilizing advanced filtering techniques, an effective method is provided for high-dimensional problems with automatic restoration of variable space. three

In the literature, many different studies on analysis can be found, which use experimental design methods to test the reliability of polychlorinated biphenyls under different environmental conditions. Fang et al. 4 analyzed the temperature deviation between the experiment and simulation, and determined the main influencing parameters through sensitivity analysis. The modal frequencies of the circuit board were obtained using finite element software, and the first six modes were extracted. Gao 5 established an optimization model with the coordinates of the boundary condition points on the circuit board as the design parameters and the modal frequency as the response function. We have obtained a model that is most suitable for connecting central coordinates. Xu et al. Perform modal and fatigue analysis to obtain the most suitable polychlorinated biphenyl model, and determine design variables (material properties of anisotropic polychlorinated biphenyls) and response functions (solder joints between components and polychlorinated biphenyls). In the study, the most suitable polychlorinated biphenyl material was obtained for the safety of welding materials in key areas. Han and others. Seven pairs of circuit boards were subjected to vibration analysis, solving the problem of the model at different component positions. The positions of each component on the circuit board were compared, and the optimal finite element was found using optimization tools. Xia and others. 8 determined design variable parameters such as material properties, plate thickness, terminal thickness, and coefficient of expansion, and improved thermal fatigue resistance using experimental design methods. Meiya Filo and others. For the purpose of describing the mechanical properties of circuit boards, three different component positions were experimentally designed. He obtained the strain values on the circuit board by using a strain gauge and created an optimization model to find the optimal design. Jordahari and others. By establishing finite element analysis and solving thermal mechanical analysis, the mechanical properties of the circuit board under high temperature changes were tested. Serebreni et al. We studied the influence of boundary conditions on circuit boards, established a thermal mechanical finite element analysis (FEA) model with electronic components, and obtained strain values on the circuit board. Most and so on. Conduct sensitivity and optimization research. Sensitivity analysis was conducted using the Adaptive Optimal Prognostic Metamodel (AMOP) method, and optimization was performed using advanced Latin hypercube sampling methods. Hungary and others. Starting from the idea of removing insignificant input variables from the model, AMOP was developed. The results show that the prediction quality of the model has been improved. By using advanced filtering techniques, automatic elimination of variables has been achieved. For large-sized problems, effective optimization has also been achieved. Sarahuiraj 12 established a finite element model using anisotropic materials and studied the influence of parameters on the performance of circuit boards, such as board thickness, tuyere diameter, and board thickness. McLeish and others. 2. Studied the application of Sherlock software in circuit board model creation. Hu and others. 13 studied the conductive copper layer of polychlorinated biphenyls and investigated the effect of copper cover on the structure of circuit boards. Novak et al. 14. Checked the thermal mechanical properties of the circuit board, conducted various load conditions, and compared them with the results of physical tests. Caliani 15 examined the material properties of polychlorinated biphenyls and conducted modal analysis on circuit boards made of two anisotropic and anisotropic materials. Arabi and others. 16 pairs of circuit boards were subjected to finite element analysis and modal vibration analysis to obtain the influence of the material type used in the circuit board. Gharaibeh et al. By establishing a FEA model with both free and fixed boundary conditions, the influence of anisotropic material properties on printed circuit boards and their components was studied, and it was linked to physical testing. Mr. Wei investigated the influence of boundary conditions on polychlorinated biphenyls in finite element analysis and found that the design of three different boundary conditions made the analysis results effective.