Optimization of porosity formation in AlSi9Cu3 pressure die castings using genetic algorithm analysis
作者： V.D. Tsoukalas
DOI: 10.1016/J.MATDES.2008.04.016
关键词: Genetic algorithm 、 Aluminium alloy 、 Porosity 、 Materials science 、 Plunger 、 Fitness function 、 Die (manufacturing) 、 Orthogonal array 、 Structural engineering 、 Taguchi methods
摘要: Abstract In this investigation, an effective approach based on multivariable linear regression (MVLR) and genetic algorithm (GA) methods has been developed to determine the optimum conditions leading minimum porosity in AlSi9Cu3 aluminium alloy die castings. Experiments were conducted by varying holding furnace temperature, plunger velocities first second stage, multiplied pressure third stage using L27 orthogonal array of Taguchi method. The experimental results from used as training data for MVLR model map relationship between process parameters formation cast parts. With fitness function model, algorithms optimization. By comparing predicted values with data, it was demonstrated that proposed is a useful efficient method find optimal casting associated percent.
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