Application of intelligent control system based on machine learning in mold design and manufacturing
This paper focuses on exploring the specific applications of intelligent control systems based on machine learning,particularly neural networks and genetic algorithms,in the design and manufacturing of injection molds.This system employs neural networks for deep learning of relevant data related to injection molds,while optimizing the weights and biases of the neural networks using genetic algorithms.The aim is to enhance the prediction accuracy and generalization ability specifically tailored to the design and manufacturing of injection molds.Experimental data demonstrates that this system responds quickly,operates stably,and can effectively reduce production costs and significantly improve production efficiency in the design and manufacturing process of injection molds.Overall,the intelligent control system developed in this paper provides strong technical support for the intelligent upgrading of the injection mold design and manufacturing industry,showing significant advantages and practical application value,and is expected to inject new momentum into the innovative development of the injection mold industry.
machine learningmold design and manufacturingneural networksgenetic algorithmsintelligent control system
万方数据
维普
