基于遗传算法的注塑成型充模过程优化

在注塑成型的过程中 ,非均匀的熔体前沿充填速度将导致非一致的取向及非均匀收缩和翘曲变形 ,理想的充填模式应尽可能使熔体在充填过程中保持MFV不变 .控制MFV的关键是优化充模过程的注射流率 .针对这一问题 ,将遗传算法和数值模拟技术相结合 ,用于注塑成型充模过程的优化 ,确定螺杆行程中的最佳控制点 ,以及控制点处的注射体积流率的最优值 ,以获得均匀一致的MFV .算例表明 ,利用遗传算法得到的优化流率设置 ,可以使MFV的均匀性提高 70 %左右 .

Optimization of Filling Process in Injection Molding Using Genetic Algorithm

In injection filling processing, varying Melt Front Velocity (MFV) induces variable orientation within the part and,thus,leads to differential shrinkage and part warpage Therefore,it is desirable to maintain a constant velocity at the melt front to generate uniform molecular and fiber orientation throughout the part To control MFV,the optimal control points in ram stroke and injection flow rates should be determined Genetic algorithm and numerical simulation are integrated to optimize injection velocity, and some optimum points and flow rates in ram stroke were determined The proposed computational tool is applied to a test,and a significant improvement of the quality is achieved,reducing by approximately 70% the flow unevenness