optimization of plastic injection molding process by combination of artificial neural network and genetic algorithm

injection molding is one of the most important and common plastic formation methods. combination of modeling tools and optimization algorithms can be used in order to determine optimum process conditions for the injection molding of a special part. because of the complication of the injection molding process and multiplicity of parameters and their interactive effects on one another, analytical modeling of the process is either impossible or difficult. therefore artificial neural network (ann) is used for modeling the process. process conditions data is needed for modeling the process by the neural network. after modeling step, the model is combined with the genetic algorithm (ga). based on the injection molding goals that have been turned into fitness function, the optimized conditions are obtained.