中文摘要：

薄板冲压成形过程中，其设计变量和噪声因素都具有一定的波动，都存在不确定性。传统的优化设计由于忽略不确定因素的影响，当设计变量产生波动时，往往会导致设计最优目标超出约束界限或者目标函数对设计变量的波动极为敏感，从而使设计失效。采用自主开发的STLMesher软件建立了模具的参数化模型，在此基础上将试验设计、能代表实际冲压过程精度较高的近似模型和蒙特卡罗模拟技术相结合，构造了基于产品质量工程的6σ稳健优化设计方法。该方法在设计初始阶段就考虑了各种不确定因素的影响，因此在获得近似最优解的同时能够提高设计变量的可靠性和目标函数的稳健性，大幅提高产品的质量。在优化过程中调用的是近似模型，能大大减少调用有限元模型的次数，提高优化效率。算例表明，该方法具有较高的精度和较强的工程实用性。

英文摘要：

Design variables and noise factors have certain fluctuation during the process of sheet metal forming, so there exists uncertainty. Conventional optimization strategies, however, do not incorporate this uncertainty into the process of sheet metal forming, which often causes the optimal object function to go beyond constraints or the object function to become very sensitive to the fluctuation of design variables, thereby resulting in design failure. A parametric mould model is established by means of a self-developed STLMesher sofwware. On this basis, the experimentally designed high -precision approximate model that can represent the actual forming process is combined with Monte Carlo simulation technique, thereby constituting a six sigma robust optimization design method based on the product quality engineering. The method takes the influence of various uncertainty factors into consideration in the initial stage of design, therefore it not only obtains an approximate optimal solution but also improves the reliability of design variables and the robustness of objective function. The product quality can also be improved greatly. It is the approximate model that is called in the optimization procedure, so the times of calling the finite element model can be decreased greatly and the efficiency of optimization can be improved. Numeral example indicates this method has high precision and good engineering practicability.