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Minimizing Part Sink Marks Using C-Mold And Genetic-Optimization Algorithm

机译:使用C模具和遗传优化算法最小化零件沉降标记

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Injection molding is widely used for mass production of polymer products. One important issue is how to determine the process conditions to produce parts of the best quality. The objective of this paper is to show how C-Mold combined with an efficient optimization system can automatically predict the optimum process to minimize sink marks. C-Mold and Genetic optimization algorithm have been integrated to solve the problem. Sensitivity analysis on part sink marks with respect to process parameters (such as filling time, hold time, cooling time, packing pressure, mold temperature and melt temperature) are also presented in this paper. Simulation results show that holding time, hold pressure and gate size have the greatest effect on part sink marks. A number of examples have been tested and the results show that sink marks can be significantly reduced after optimization.
机译:注塑成型广泛用于聚合物产物的大规模生产。一个重要问题是如何确定生产最佳质量的部分的过程条件。本文的目的是展示C模具与高效优化系统的结合如何自动预测最佳过程以最大限度地减少沉降痕迹。 C模具和遗传优化算法已集成以解决问题。本文还提出了关于工艺参数(如填充时间,保持时间,冷却时间,包装压力,模具温度和熔体温度)的零件沉降标记的灵敏度分析。仿真结果表明,保持时间,保持压力和栅极尺寸对零件沉降标记具有最大的影响。已经测试了许多例子,结果表明优化后可以显着降低沉降标记。

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