• CN:11-2187/TH
  • ISSN:0577-6686

›› 2008, Vol. 44 ›› Issue (4): 133-137.

• 论文 • 上一篇    下一篇



  1. 天津大学机械工程学院
  • 发布日期:2008-04-15

Construction of Optimizing Standard for Robust Parameter Design in the Target Being Best

ZHANG Zhihong;HE Zhen;GUO Wei   

  1. School of Mechanical Engineering, Tianjin University School of Accounting, Shandong Economic University School of Management, Tianjin University
  • Published:2008-04-15

摘要: 稳健设计是通过降低输入变量的变异效应来提高产品质量的一种成本有效方法,方均误差(Mean square error,MSE)作为望目特性的稳健设计优化标准对不可控因素造成的过程变异和产品质量波动未加以分析。基于此,通过分析MSE标准的合理性及不足并考虑过程方差的重要性,利用响应模型方法给出过程方差的稳健域,构建以MSE为目标函数,以过程方差、均值偏倚为约束的稳健参数设计优化模型。实例比较分析表明,所构建模型的过程能力接近六西格玛水平,而且过程方差在其约束内;最小化MSE虽然得到的过程能力较高,但是过程方差超出过程方差约束,所得到的解不能保证是稳健解,在实际应用中会产生无法预料的变异行为。过程方差约束能够有效地解决偏倚和方差之间的冲突,建立稳健的优化策略。

关键词: 方均误差, 过程方差置信域, 六西格玛, 稳健设计

Abstract: Robust design is an effective cost methodology to improve product quality by reducing the variation effects of input variables. Mean square error (MSE) is usually regarded as the most appropriate standard for robust optimization design process in the target being best, but with MSE standard the process variation and product quality fluctuation resulted from the noise factors could not be analyzed. The rationality and deficiency of MSE standard and the important about process variance are analyzed. Confidence region of process variance is given by response model. Then an optimizing model of robust parameter design is constructed with MSE as target function and process variance and mean bias as constrictions. The simulation example successfully illustrates the developed model’s advantage. Not only can the process capability achieve six sigma level, but the value of process variance lies in the con-striction of minimization process variance. When minimizing MSE, the process capability is higher than the developed model, but the value of process variance is beyond the constriction. So the solution would can not be guaranteed the process robustness and unexpected variation behavior would occur in practice. The conflict between bias and variance in MSE standard is effectively solved with the restriction of process variance. A robust optimized strategy is set up.

Key words: Confidence region of process variance, Mean square error, Robust design, Six sigma