Optimization of the Stamping

In the stamping process, the forming of the product will be affected due to the unreasonable design and selection of process parameters, forming defects such as wrinkles, cracks, and burrs. Optimizing the stamping process can reduce the generation of forming defects and improve the quality. At present, the optimization of the stamping process is achieved by analyzing the influence of various process parameters on the forming quality through the relevant theories of stamping, optimizing the key parameters and establishing a mapping relationship between process parameters and quality of forming through numerical simulation combined with orthogonal experiment, neural network and response surface methods. The optimal process parameters are obtained through the optimization algorithm, and the optimization results are experimentally verified.
 
At present, the most commonly used process optimization method is to analyze the influence of various process parameters on the forming quality through theoretical analysis, combined with simulation, and optimize it. Marumo and others discussed the relationship among thickness of sheets, blank holder force and forming limit during sheet metal forming, and combined simulation and experimentation to optimize the process parameters that cause wrinkling during deep drawing. Zein and others used the simulation method to optimize the process parameters such as stamping force, blank holder force and lubrication conditions in the deep drawing process, aiming to reduce the manufacturing cost, material and processing time. Cebeli and others discussed the influence of the blank holder and die angle and punch radius on the drawing ratio. The experimental results show that with the increase of the blank holder angle and the punch radius, the drawing ratio gradually increases. Xiaohua Kong and others proposed a method of combining a conical die and a radial block blank holder in the deep drawing process, and applied it to the deep drawing of cylindrical parts. The experimental results show that this method can effectively inhibit the wrinkled. In order to reduce the springback of the high-impact sheet in the deep drawing process, Wenjia Mo and others established a mathematical model for the springback of the deep drawing sheet based on the formation mechanism of the sheet metal's springback in the deep drawing process, established the sheet metal's springback control criterion and put forward the optimal design method of the blank holder force to realize the control of the deep-drawing springback of the high-impact sheet. Zhang and others analyzed the causes of defects such as cracking and wrinkling in the flange area in the warm forming process of magnesium alloys, and verified the accuracy of the simulation results through experiments. In order to improve the ultimate drawing ratio of magnesium alloy workpieces, the process parameters are optimized, and the results show that the ultimate drawing ratio of magnesium alloys at temperatures between 105 and 170°C can reach 2.6.
 
Orthogonal experiments are used in the optimization of the stamping process due to their high efficiency, rapidity and economy. PadmanabhanR and others applied the method of orthogonal experiments to analyze the process parameters of sheet metal forming. The results show that the die radius has the greatest influence on the quality of deep drawing of stainless steel billets, followed by blank holder force and friction coefficient, and the process parameters are optimized based on the above research. Ling Long and others obtained the learning samples of the neural network through orthogonal experiments combined with digital simulation technology, constructed the objective function model of the random focus search algorithm based on the back-propagation neural network, and applied the random focus search algorithm to optimize process parameters of sheet metal stamping. Liang Ying and others optimized the strength and toughness process of high-impact hot stamped steel sheets. The Kahn test was introduced to characterize the fracture toughness of materials based on the strength, plasticity and toughness indicators of hot-stamped high-impact steel sheets. Combined with orthogonal tests, the influence law of different quenching process parameters on strength and toughness of stamping high-strength steel was studied.
 
The multi-objective optimization methods are widely used in optimization of stamping through neural network, response surface model combined with genetic algorithm. Liu and others comprehensively considered multi-objective factors such as cracking, wrinkling, thinning rate, combined with Pareto multi-objective genetic algorithm, and process parameters such as blank holder force and bead restraint force are optimized. Jiangfeng Pan and others established a multi-objective optimization model of deep drawing process parameters, and adopted the multi-objective NSGA-II algorithm to obtain the optimal process parameters. Wei Liu and others combined finite element simulation and multi-objective optimization method to optimize the stamping forming process of body panels, and obtained the optimal solution based on the Pareto method multi-objective genetic algorithm. Ingarao and others solved the multi-objective optimization problem of high-impact steel springback through numerical simulation, response surface methods, Pareto optimal solution methods, genetic algorithm and neural network, taking friction conditions and blank holder force as optimization variables, and realized the reduction of rebound while avoiding excessive thinning and geometric distortion. Zhou and others applied the multi-objective genetic algorithm to the optimization of hot stamping of aluminum alloy anti-collision side beams, obtained finite element data samples through Latin hypercube sampling, and used the finite element method to quantize the forming quality corresponding to each sample point. Combined with genetic algorithm, the process parameters such as blank holder force and stamping speed were optimized, and the optimal process parameters were experimentally tested and compared with the simulation results. The results show that the finite element simulation method can effectively predict forming defects. Giuseppe and others proposed a computer-aided design method, which combines the response surface method, the least squares method and the Pareto optimal solution method to solve the partial optimization and overall optimization in the complex stamping process, and provide solutions to all design problems in the stamping process. Qixiang Qing and others applied the Kriging interpolation method to reconstruct the stamping sample points and the optimization points formed in the optimization process, and combined with the response surface approximation method, used the genetic optimization algorithm to optimize the updated initial values ​​of design variables and constraint ranges, and then obtained optimal process parameters. Menghan Wang and others used the response surface method combined with numerical simulation to analyze the reasons for the cracking of the fillet of the high-impact steel plate reinforcement part for automobiles, and determined the optimal combination of process parameters according to the established response surface model.
 
In order to improve the robustness and robustness of the optimization results, Hou and others conducted an optimization analysis to improve the robustness of the stamping process, including the forming quality and processing time of Wanfang Data. The proposed stochastic analysis and robust methods are used to analyze the stamping process parameters, and the results show that the product quality change rate decreases significantly under the robust optimal solution. Combining experimental design with approximate model and Monte Carlo simulation technology, Yongguang Sun and others constructed a robust optimization design method for product quality engineering, which can improve the reliability of design variables and the robustness of objective functions, and improve the quality of the product.