中文摘要：

针对多响应稳健参数设计问题,在贝叶斯统计建模的框架下,结合质量损失函数和后验概率方法构建了一种新的优化模型.该方法不仅运用后验概率方法评估了各响应落在规格限内的期望概率（即优化结果的可靠性）,而且运用质量损失函数度量了多变量过程的稳健性.此外,进一步地结合实例讨论了期望概率对优化结果的影响、联合概率与边缘概率之间的关系以及如何获得质量损失与后验概率之间的最佳平衡点.研究结果表明：所提方法能够在优化过程中较好地兼顾多元过程的稳健性和优化结果的可靠性,从而为实现多响应稳健参数设计提供了各方面（如多元过程的稳健性、优化结果的可靠性）均较满意的优化结果.

英文摘要：

A new optimization model,integrating quality loss function and posterior probability approach in the framework of Bayesian statistical modeling,is proposed to solve the problem of multi-response robust parameter design. The proposed method not only assesses the expected probability of each response which falls within its respective specification limit（ i. e.,the reliability of optimization results） using posterior probability approach,but also measures the robustness of multivariate process with quality loss function. In addition,this paper discusses,by illustrative examples,the relationship between joint posterior probability and marginal posterior probability,the influence of different expected probability on the optimization results of the proposed approach,and how to obtain the optimum balance between quality loss and posterior probability. The results show that the proposed method can simultaneously take into consideration the robustness of multivariate process and the reliability of optimization results,and provide a relatively satisfactory optimization result from several respects（ e. g.,robustness of multivariate process,the reliability of optimization results） to achieve robust parameter design with multiple responses.