Process optimization of low-pressure die casting A356 aluminum alloy wheels based on GA

In order to find a solution to the casting quality control of low-pressure die casting aluminum alloy wheel,genetic algorithm is applied to the optimization of process parameters. Based on casting simulation results,the BP network is employed to build up the nonlinear mapping relationship between process parameters and control objectives,and then the optimization of parameters is realized by using genetic algorithm. A lowpressure die casting A356 aluminum alloy wheel is studied as an instance,and the parameters such as casting temperature,upper die temperature,bottom die temperature,mold core temperature and so on are optimized. Results show that this approach is effective to optimize the process parameters and control the porosity defect and solidification time,which can improve the casting process.