Research On Multi-objective Optimization Of Staged Injection Molding Of Electric Vehicle Hood

With the increasing demand for plastic products,plastic products tend to be more complex,sophisticated and integrated,therefore,it promoted the development of graded injection molding technology.Plastic molding quality is mainly affected by molds,materials and process parameters.The determination of the graded point of the graded injection molding and the improvement of the quality of the plastic parts by optimizing the process parameters have always been the difficulties in this field.Therefore,for the characteristics of graded injection molding,T this article takes the electric head cover as the research object,first classifies the molding process,then uses a combination of mathematical algorithms to seek the best combination of process parameters,and finally uses CAE for simulation verification.The main research contents of the study are:(1)Take the electric head cover as the research object,the cooling system and the gating system were established according to the structure and function of the product.According to the flow analysis and cooling analysis,the rationality of the gating system and the cooling system were verified respectively.Finally,the actual production process parameters were used to reproduce the product problems area to verify the validity of the entire analysis model.(2)Apply the recommended screw speed in the Moldflow flow analysis to determine the graded injection point and preliminary injection rate for the electric hood.(3)Orthogonal experimental design is used to establish the corresponding maximum warpage amount and maximum volumetric shrinkage ratio under different molding process parameter combinations;then TOPSIS comprehensive analysis method is used to evaluate the evaluation indexes under different process parameter combinations;finally,the mean value is used,Range and variance analysis yields the best combination of process parameters and the four factors that affect the maximum product quality.(4)First refine the level of the four factors that affect the product quality and establish a second orthogonal test;then construct a generalized regression neural network GRNN model,and use the orthogonal experiment in(3)above.32 the group experiment was used as a network training sample,and the 9 groups of the second orthogonal experiment were used as prediction samples to make network predictions and seek the best combination of process parameters.After the lease,CAE was used for simulation verification.The results show that the combination of CAE numerical simulation technology,orthogonal test,TOPSIS comprehensive evaluation method and GRNN method can find the best combination of process parameters for graded injection molding,the melt temperature is 245℃,the pressure holding pressure is 75 MPa,and the pressure holding time2 s,cooling time 5s,primary injection rate 10%,secondary injection rate 45%,tertiary injection rate 77.5%,4 injection rate 55%,and 5 injection rate 20%.The maximum amount of warpage under the optimal process parameters is 1.276 mm,and the maximum volumetric shrinkage is 6.422%.This method provides a feasible solution to solve the optimization of the process parameters of the graded injection molding.