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Experimental-Based Multi-objective Optimization of Injection Molding Process Parameters

机译:基于实验的注塑工艺参数多目标优化

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In this paper, the framework for determining the optimum injection molding process parameters for minimized product defects through experimental-based multi-objective optimization is presented. Two defects with regard to product quality, namely warpage and volumetric shrinkage, were examined. Seven injection molding process parameters are considered including the mold temperature, melt temperature, packing pressure, packing time, cooling time, injection speed and injection pressure. Specific test points determined, within a defined domain, using the face-centered central composite design approach were used to conduct actual injection molding experiments. Warpage and volumetric shrinkage were computed for the resulting injection-molded experimental products. Two relationships between the two defects and the process parameters, respectively, were constructed and formed the basis for the optimization. Using the two relationships, a multi-objective problem entailing minimization of the two defects was formulated and solved using the genetic algorithm. The results indicate a significant tradeoff between the warpage and the volumetric shrinkage. Assuming equal importance in minimizing both defects, additional experiments were conducted to validate the corresponding optimum. The experimental results revealed close agreements with the optimization results differing by about 7%.
机译:本文提出了通过基于实验的多目标优化确定最小化产品缺陷的最佳注塑工艺参数的框架。检查了产品质量的两个缺陷,即翘曲和体积收缩。考虑了七个注塑工艺参数,包括模具温度,熔融温度,保压压力,保压时间,冷却时间,注塑速度和注塑压力。使用面心为中心的中央复合材料设计方法在定义的范围内确定的特定测试点用于进行实际的注塑实验。计算所得注塑实验产品的翘曲和体积收缩率。分别建立了两个缺陷与工艺参数之间的两种关系,并为优化奠定了基础。利用这两个关系,使用遗传算法制定并解决了导致两个缺陷最小化的多目标问题。结果表明,翘曲和体积收缩之间存在重大折衷。假设在最小化两个缺陷方面具有同等重要的意义,则进行了其他实验以验证相应的最优值。实验结果表明,优化结果相差约7%。

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