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Optimized plastic injection molding process and minimized the warpage and volume shrinkage by response surface methodology with genetic algorithm and firefly algorithm techniques

机译:通过响应面方法,遗传算法和萤火虫算法技术,优化了塑料注射成型工艺,并将翘曲和体积收缩最小化

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This goal of this paper is an optimization approach to generate suitable process setting of multi responses of the minimization of warpage and volume shrinkage in the plastic injection molding (PIM). Central composite design (CCD) was employed to handle the orthogonal array for experimental test runs and using the response surface methodology (RSM) to construct response surface equation model. Then the optimization methods of firefly algorithm (FA) that have never been applied to minimize warpage and volume shrinkage in the plastic injection molding (PIM) and genetic algorithm (GA) were employed to optimal parameter conditions with fitness function generated from RSM. Simulation software Moldex 3D and plastic injection machine were used as the experimental tests to show the comparison of the optimal performance of both metaheuristic algorithms. The results showed that the firefly algorithm created the suitable process parameters to meet the minimization of warpage and volume shrinkage better than the popular genetic algorithm for this study. It can be concluded that FA is very proper to approach the good performance in PIM.
机译:本文的目标是一种优化方法,以生成合适的工艺设置,以对塑料注射成型(PIM)中的翘曲和体积收缩率最小化做出多响应。采用中央复合设计(CCD)处理正交阵列进行实验测试,并使用响应面方法(RSM)构造响应面方程模型。然后,将尚未应用的萤火虫算法(FA)的优化方法从未采用来最小化塑料注射成型(PIM)中的翘曲和体积收缩,并采用遗传算法(GA)来优化具有RSM生成的适应度函数的参数条件。仿真软件Moldex 3D和注塑机被用作实验测试,以显示两种元启发式算法的最佳性能的比较。结果表明,萤火虫算法创建了合适的工艺参数,可以比传统的遗传算法更好地满足最小化翘曲和体积收缩的要求。可以得出结论,FA非常适合实现PIM的良好性能。

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