Abstract: To minimize the fracture of lock springs during the use，a neural network model was developed to map the complex nonlinear relationship between the processing conditions and quality indexes of the lock springs, and a genetic algorithm was used to optimize the molding process parameters on the basis of the neural network model mentioned above. The results indicated that the combination of neural network and genetic algorithm method was feasible to improve the product quality, and the residual stress decreased by 16.02 %. Moreover, the sum of packing time and cooling time was shortened by 5.4 s. This suggested that the production time was reduced, and the production efficiency was improved when the lock springs were mass produced.

Key words: injection molding, process parameter, neural network, genetic algorithm, optimization