Plastic instead of steel technology is one of the important means of automotive lightweighting, which can greatly reduce the weight of the car while ensuring the same performance of the product. For the lightweighting of the automotive all-plastic front-end frame structure, the initial structural design of the front-end frame was carried out by HyperMesh; based on the compromise planning method and entropy weight method, the compromise planning method with weight coefficients was used to unify the planning of each subobjective to obtain the integrated response function, and the minimization of the integrated response function was the objective. The main considerations were the lock limit crash load, the cushion area load, and the pedestrian protection impact load under typical operating conditions, the shape optimization, and topology optimization, respectively. The mass of the sheet metal front-end frame was reduced from the original 10.5 kg to 6.8 kg—a weight reduction of 35.24%. The front-end frame was extracted and the mid-plane was repaired by HyperMesh, the complete mid-plane was meshed, loads and properties were added to the mesh, the front-end frame was subjected to static and modal analysis in the OptiStruct module, and the stiffness and intrinsic frequency were verified. The results show that the smallest first-order mode in the modal analysis is 57.38 Hz, which is much larger than the 30 Hz required before design. The fatigue analysis of the front-end frame was then performed using N-code to derive the damage results; it is concluded that its life is 6122 s, much larger than the specified 1200 s. Through the verification of the relevant resonance test, it is judged that the performance of the test part meets the actual requirements comprehensively by checking the status after the test.

With the continuous development of plastic strip steel technology, optimization of plastic part process parameters has become one of the hot research in the field of injection molding. This paper takes the automobile front door sill pressure plate as the research object, analysis of optimal gate position and design of three pouring systems by Moldflow, evaluation of each index of the three pouring systems using the integrated scoring method, determines the optimal gating system. Five parameters such as mold temperature and melt temperature were selected as experimental factors, volume shrinkage and warpage are used as evaluation indicators, design and completion of signal-to-noise ratio-based orthogonal tests, determining the optimal combination of process parameters using grey correlation analysis, the results showed that the volume shrinkage and warpage deformation of the two evaluation indexes were reduced by 22.27% and 20.82%, respectively, after optimization. The set of Pareto solutions for volume shrinkage and warping deformation is then obtained by building an Ellipsoidal Basis Function Neural Network (EBFNN) model combined with a Non-dominated Sorting Genetic Algorithm (NSGA-II), and the relatively optimal five sets of Pareto solutions are selected for analysis and comparison, the optimum process parameters were determined as mold temperature 40.5°C, melt temperature 221.4°C, injection time 3.9s, packing pressure 54.8 MPa and packing time 39.s, the maximum volume shrinkage of the optimized part is 5.475%, the warpage deformation is 1.010mm, and the forming quality of the part is improved.