Optimization of Solidification Process Parameters for Photosensitive Resin Based on Artificial Intelligence

This paper presents an optimization approach for photosensitive resin solidification process based on artificial neural network combined with orthogonal experiment and genetic algorithm. A predictive model for solidification is established using artificial neural network and the sample for neural network model is designed by using orthogonal experimental method. In the model, the solidification process parameters including circumstance temperature, illumination distance and illumination time are treated as design variables and the objective is to obtain the maximum value of rigidity. Optimization of solidification process parameters for photosensitive resin was conducted by introducing artificial neural network prediction models into genetic algorithm. The results indicate that the optimization method based on artificial neural network and the genetic algorithm is feasible for improve the design quality of the solidification process.