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Optimization of Injection-Molding Process with Genetic Algorithms

机译:遗传算法优化注塑工艺

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Injection molding is widely used for mass production of polymer products. One important issue is how to determine the gate location(s) and process conditions to produce parts of the best quality. The objective of this paper is to develop an efficient optimization system that can automatically make such determination. The Genetic Algorithm (GA) will be compared with a functional search method, Simulated Annealing (SA) algorithm. The principle of both algorithms will be described and illustrated with examples. Application of these algorithms to determine gate location and optimal process condition in injection molding will be demonstrated with examples. Gate location is determined based on the principle of balanced flow paths, while the optimal process condition is computed by minimizing the warpage across the entire part. Results show that the Genetic Algorithm is more efficient computationally than the SA algorithm.
机译:注射成型被广泛用于聚合物产品的批量生产。一个重要的问题是如何确定浇口位置和工艺条件,以生产出质量最好的零件。本文的目的是开发一种可以自动进行这种确定的高效优化系统。遗传算法(GA)将与功能搜索方法“模拟退火”(SA)算法进行比较。将通过示例描述和说明这两种算法的原理。将通过示例演示如何使用这些算法确定浇口的浇口位置和最佳工艺条件。浇口位置是根据平衡流路原理确定的,而最佳工艺条件是通过使整个零件的翘曲最小化来计算的。结果表明,遗传算法比SA算法具有更高的计算效率。

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