关于参数设计中调节因子的一个注记

参数设计是日本质量专家田口倡导的一种质量工程方法,调节因子的存在性在参数设计中非常重要.在附加了分布假定的条件下,本文对傅珏生等的定理给出了证明,也指出了从函数结构上研究参数设计的重要性.     

信噪比的分解及其在稳健设计中的应用

本文讨论了信噪比的分解及其在稳健设计中的应用, 引用PerMIA的概念给出了田口的信噪比和社会平均二次损失联系\bd 最后将97年中国大学生数学建模的赛题作为算例, 其参数设计的优化过程更为简洁.     

一类PerMIA的识别方法

PerMIA是对信噪比的重要推广。本文将针对一类较常见的PerMIA ,用Gamma 图方法以及标准Gamma 图方法来判定调节因子并估计PerMIA。     

Minimizing a general loss function in off‐line quality control

We consider in the present paper the analysis of parameter designs in off‐line quality control. The main objective is to seek levels of the production factors that would minimize the expected loss. Unlike classical analyses which focus on the analysis of the mean and variance in minimizing a quadratic loss function, the proposed method is applicable to a general loss function. An appropriate transformation is first sought to eliminate the dependency of the variance on the mean (to achieve ‘separation’ in the terminology of Box). This is accomplished through a preliminary analysis using a recently proposed parametric heteroscedastic regression model. With the dependency of the variance on the mean eliminated, methods with established properties can be applied to estimate simultaneously the mean and the variance functions in the new metric. The expected loss function is then estimated and minimized based on a distributional free procedure using the empirical distribution of the standardized residuals. This alleviates the need for a full parametric model, which, if incorrectly specified, may lead to biased results. Although a transformation is employed as an intermediate step of analysis, the loss function is minimized in its original metric. Copyright © 2002 John Wiley & Sons, Ltd.