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Optimization of die design using metaheuristic methods in cold forward extrusion process

机译:冷前挤压过程中使用元启发式方法优化模具设计

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摘要

Selection of processing and geometrical parameters is a crucial step in the extrusion process design. Optimized parameters may result in desirable microstructure at minimum load. The purpose of this paper is determination of the optimal cold forward extrusion parameters with the minimization of tool load as the objective function. This paper deals with different optimization approaches in order to determine the optimal values of logarithmic strain, die angle, and friction with the purpose of finding the minimal tool loading obtained by cold forward extrusion process. The obtained extrusion force model as a fitness function was used to carry out the optimization. Based upon the objective function, metaheuristic algorithms such as genetic algorithm and simulated annealing were adopted as optimization methods for finding the optimum values of cold forward extrusion parameters and the obtained results were compared with those in literature. The better results lead to the smallest energy consumption, longer tool life, better formability of the work material, and the quality of the finished product.
机译:选择工艺和几何参数是挤出工艺设计中的关键步骤。优化的参数可以在最小负载下产生理想的微观结构。本文的目的是确定最佳的冷前挤压参数,并以最小的工具负荷为目标函数。本文研究了不同的优化方法,以便确定对数应变,模具角度和摩擦的最佳值,目的是找到通过冷前挤压工艺获得的最小刀具载荷。使用获得的挤压力模型作为适应度函数进行优化。基于目标函数,采用遗传算法和模拟退火等元启发式算法作为寻找冷前挤压参数最优值的优化方法,并将所得结果与文献进行比较。更好的结果导致最小的能耗,更长的工具寿命,更好的工作材料可成型性以及最终产品的质量。

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