A Multi-objective Constrained Optimization Method for Manufacturing Process Parameters of Electrolytic Copper Foil

The manufacturing of electrolytic copper foil products has strong coupling and multiple influencing factors. Its process parameters are influenced by both equipment status and product quality. However, existing process optimization methods only consider product quality requirements. To overcome these problems, a multi-objective constrained optimization method for manufacturing process parameters of electrolytic copper foil is proposed. First, a non-linear mapping model based on neural networks is established between process-equipment and product quality parameters; then, based on the established mapping model, equipment status information, and product quality requirements, a multi-objective constraints function is constructed, and a genetic algorithm is used to optimize process parameters. Finally, the actual production data of the enterprise proves that the proposed method can effectively improve the product quality and production efficiency of electrolytic copper foil.