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Optimization design of a gating system for sand casting aluminium A356 using a Taguchi method and multi-objective culture-based QPSO algorithm:

机译:基于Taguchi方法和基于多目标文化的QPSO算法的砂铸铝A356浇口系统的优化设计:

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This article combined Taguchi method and analysis of variance with the culture-based quantum-behaved particle swarm optimization to determine the optimal models of gating system for aluminium (Al) A356 sand casting part. First, the Taguchi method and analysis of variance were, respectively, applied to establish an L27(38) orthogonal array and determine significant process parameters, including riser diameter, pouring temperature, pouring speed, riser position and gating diameter. Subsequently, a response surface methodology was used to construct a second-order regression model, including filling time, solidification time and oxide ratio. Finally, the culture-based quantum-behaved particle swarm optimization was used to determine the multi-objective Pareto optimal solutions and identify corresponding process conditions. The results showed that the proposed method, compared with initial casting model, enabled reducing the filling time, solidification time and oxide ratio by 68.14%, 50.56% and 20.20%, respec...
机译:本文将Taguchi方法和方差分析与基于文化的量子行为粒子群优化算法相结合,以确定铝(Al)A356砂铸件浇口系统的最佳模型。首先,分别使用Taguchi方法和方差分析来建立L27(38)正交阵列,并确定重要的工艺参数,包括立管直径,浇注温度,浇注速度,立管位置和浇口直径。随后,使用响应表面方法构建了一个二级回归模型,包括填充时间,凝固时间和氧化物比。最后,基于文化的量子行为粒子群算法用于确定多目标帕累托最优解并确定相应的工艺条件。结果表明,与初始铸造模型相比,该方法可将填充时间,凝固时间和氧化物比分别降低68.14%,50.56%和20.20%,与传统的铸造模型相比,可节省成本。

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