Yi Wang
Air knife is the key equipment to determine zinc coating thickness in the hot-dip galvanizing process. The process parameters related to air knife directly determine whether the desired coating thickness can be obtained. Therefore, setting the optimal process parameters is the key step to improve hot dip galvanizing process capability and zinc coating quality. Previous research on zinc layer thickness was based on the principle of physics and simulation to build models and few studies were carried about the interaction between parameters of air knife. In this research, three process parameters (stripe velocity, air pressure and air knife-stripe distance) were considered to optimize coating thickness by Response Surface Method (RSM), Taguchi method and Genetic Algorithm (GA). This paper firstly used response surface method (RSM) to establish polynomial model and discuss interaction effect between air pressure and the range of air knife. Then, this paper used Taguchi method to do the robustness analysis of air knife and validate the polynomial model from response surface method. Finally, this paper built suitable a fitness function and then uses genetic algorithm to find the optimal combination of parameters for a given thickness of zinc layer. This proposed integrated method is a good try to combine RSM, Taguchi method and GA.
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