Abstract: Taking the injection molding of an automotive interior A and B column trim panel as an example, the injection molding process was optimized, which included the optimization of different gating systems, molding quality and molding process parameters for three processes. For the optimization of molding technology, the traditional BP neural network was modified on the basis of the LM algorithm. The improved LMBP neural network was used to optimize the process pathway through an orthogonal test, and a better prediction for thinning and optimizing process path was achieved. The optimized injection molding process parameters are obtained through auxiliary selection with the LMBP neural network. These process parameters could be used for the practical injection molding to obtain ideal injectionmolded parts. This work provides a good guidance for the injection molding of automotive plastic parts.