Probabilistic design of aluminum sheet drawing for reduced risk of wrinkling and fracture
Probabilistic design of aluminum sheet drawing for reduced risk of wrinkling and fracture
复制标题
DOI：
10.1016/j.ress.2008.02.024
复制
发表时间：
2005-08
期刊：
影响因子：
--
通讯作者：
Wenfeng Zhang;R. Shivpuri
中科院分区：
文献类型：
--
作者：
Wenfeng Zhang;R. Shivpuri
通常，板材拉深工艺的设计是为了提供最终零件的几何形状，然后设计和控制工艺参数，如毛坯尺寸、毛坯压边力（bhf）、冲程和界面摩擦，以提供最大的拉深（最大的拉深，而不违反起皱和变薄的约束）。在这种设计中排除固有的工艺变化往往会导致工艺设计不可靠和不可控。本文提出了一种通用的多准则设计方法来量化不确定性，并将其纳入基于响应面法（RSM）的模型中，从而进行概率优化。利用基于有限元的高保真模型和实验设计（do）建立了过程力学的代理RSM模型，并采用简单的线性加权方法确定了目标函数或质量指数（QI）。为验证该方法的有效性，对某铝件进行了拉深分析。在坯料形状、模具设计和拉深固定的情况下，成功地进行了概率设计（PD），在材料性能变化的情况下找到了压边力和摩擦系数的最佳组合。结果表明，采用概率方法，QI比传统的确定性设计（DD）提高了42%。进一步减小摩擦系数的变化至2%，QI将进一步提高到98.97%。
Often, sheet drawing processes are designed to provide the geometry of the final part, and then the process parameters such as blank dimensions, blank holder forces (BHFs), press strokes and interface friction are designed and controlled to provide the greatest drawability (largest depth of draw without violating the wrinkling and thinning constraints). The exclusion of inherent process variations in this design can often lead to process designs that are unreliable and uncontrollable. In this paper, a general multi-criteria design approach is presented to quantify the uncertainties and to incorporate them into the response surface method (RSM) based model so as to conduct probabilistic optimization. A surrogate RSM model of the process mechanics is generated using FEM-based high-fidelity models and design of experiments (DOEs), and a simple linear weighted approach is used to formulate the objective function or the quality index (QI). To demonstrate this approach, deep drawing of an aluminum Hishida part is analyzed. With the predetermined blank shape, tooling design and fixed drawing depth, a probabilistic design (PD) is successfully carried out to find the optimal combination of BHF and friction coefficient under variation of material properties. The results show that with the probabilistic approach, the QI improved by 42% over the traditional deterministic design (DD). It also shows that by further reducing the variation of friction coefficient to 2%, the QI will improve further to 98.97%.