Abstract:

In view of  the shortcomings of the besides-star wheel extrusion process,a joint  multi-objective optimization design of structural and process parameters was applied,expecting to improve the severe service conditions and balance the needs between the better filling capacity and longer die life.A fractional factorial experimental design method was used to evaluate main effects of the structural and process parameters on filling capacity and the maximum deformation load.The Latin hypercube method was used to carry out sampling of
parameters,and the obtained samples were analyzed by finite elements simulation.The RBF meta-models were built by taking simulation results as responses and the structural and process parameters as variables. Models were  onverted into single objective function by linear weighting method. The optimum parameters of structure and process were obtained by using particle swarm optimization algorithm for global optimization. Finally, the research object was verified by simulation
tests.

Key words: structural parameter, process parameter, fractional factorial design, radial basis function(RBF) model, particle swarm optimization

摘要：

针对外星轮热挤压过程模具负载大、填充性能波动的问题,
对关键的模具结构参数（入口斜度，根部圆角，模口圆角）及核心工艺参数（挤压速度，摩擦因数，坯料初始温度，模具预热温度，模具硬度）开展联合优化，以期获得负载和填充性能的平衡。首先应用部分析因试验设计，针对最大成形载荷和填充能力进行主参数效应筛选,对得到的关键因子进行拉丁超立方抽样并对样本点进行有限元模拟。以关键因子为变量、有限元模拟结果为响应，分别建立最大成形载荷和填充能力的径向基函数近似模型。基于上述近似模型，采用线性加权和法将所得近似模型转化为单目标函数，利用粒子群算法进行全局寻优，得到优化的关键结构和工艺参数组合，并通过仿真和生产试验验证了优化结果的正确性。

关键词: 模具结构参数, 工艺参数, 部分析因设计, 径向基函数, 粒子群算法