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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Minimization of sink mark depth in injection-molded thermoplastic through design of experiments and genetic algorithm
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Minimization of sink mark depth in injection-molded thermoplastic through design of experiments and genetic algorithm

机译:通过实验设计和遗传算法使注射成型热塑性塑料的缩痕深度最小化

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摘要

This paper deals with minimization of sink marks occurring behind the rib in plastic injection molding. In terms of rib structure and injection processing parameters, a theoretical analysis model was created. Meanwhile, finite element flow analysis with design of experiments (DOE) and genetic algorithm (GA) was integrated. Values of sink mark depth depend on design variables and technological parameters. Out of all, the four most influential variables, viz., rib thickness, mold temperature, melt temperature, and coolant temperature, were selected for optimization. The mathematic relation between sink mark depth and variables was established by conducting a set of FE analyses at various combinations of variables based on central composite design (CCD). Furthermore, the influence incidence of each factor and interaction between each variable on sink marks were investigated. The prediction model of sink marks was effectively coupled with GA for optimization of variables to minimize the sink depth. Results of the contrast analysis indicated that the proposed methodology could be used effectively in minimizing sink mark depth and parameter optimization design.
机译:本文致力于将塑料注射成型中肋骨后面出现的缩痕减至最小。根据肋骨结构和注射工艺参数,建立了理论分析模型。同时,将有限元流动分析与实验设计(DOE)和遗传算法(GA)相结合。缩痕深度的值取决于设计变量和技术参数。首先,选择四个最有影响力的变量,即肋厚度,模具温度,熔体温度和冷却液温度进行优化。通过基于中央复合设计(CCD)对变量的各种组合进行一组有限元分析,建立了缩痕深度与变量之间的数学关系。此外,还研究了每个因素对下陷标记的影响发生率以及每个变量之间的相互作用。将凹痕的预测模型有效地与遗传算法结合使用,以优化变量以最小化凹痕深度。对比分析的结果表明,所提出的方法可以有效地用于最小化凹痕深度和参数优化设计。

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