Optimization of the Solid-State Copper Brazing Condition Using Desirability Function and Genetic Algorithm

This research studies on optimization of solid-state copper brazing condition and comparatively investigates the ability of the desirability function and genetic algorithm (GA) optimization schemes with regard to the optimal brazing condition that yields the maximum brazed-joint tensile shear force, where the brazing parameters included the brazing temperature, holding time and loading pressure. To that end, a second-order mathematical model was first derived based on the Box–Behnken experimental design and the maximum-response desirability function. The findings suggested that the tensile shear force of the brazed joints was significantly influenced by all three brazing parameters. The optimal brazing condition was at 620 °C brazing temperature, 30-min holding time and 12.173 kPa loading pressure. The desirability function- and GA-predicted optimal brazing conditions were effectively identical, thus confirming the comparable power of both optimization schemes. Further experiments were conducted to validate the optimization outcomes, whereby the confirmation tests were carried out under the optimal brazing condition. The results suggest that both optimization schemes are viable for solid-state copper brazing, with the GA demonstrating a slightly higher prediction accuracy.