Introducing Multiple Dispersion Measures to Robust Design

Noise Factors , Dispersion Effects , and Robust Design

There has been great interest recently in the use of designed experiments to improve quality by reducing the variation of industrial products. A major stimulus has been Taguchi’s robust design scheme, in which experiments are used to detect factors that affect process variation. We study here one of Taguchi’s novel ideas, the use of noise factors to represent varying conditions in the manufactu...

A Robust Desirability-based Approach to Optimizing Multiple Correlated Responses

There are many real problems in which multiple responses should be optimized simultaneously by setting of process variables. One of the common approaches for optimization of multi-response problems is desirability function. In most real cases, there is a correlation structure between responses so ignoring the correlation may lead to mistake results. Hence, in this paper a robust approach based ...

Robust Design of Very High-Order Allpass Dispersion Filters

A nonparametric allpass filter design method is presented for matching a desired group delay as a function of frequency. The technique is useful in physical modeling synthesis of musical instruments and emulation of audio effects devices exhibiting dispersive wave propagation. While current group delay filter design methods suffer from numerical difficulties except at low filter orders, the tec...

A Robust Dispersion Control Chart Based on M-estimate

Process control charts are proven techniques for improving quality. Specifying the control limits is the most important step in designing a control chart. The presence of outliers may extremely affect the estimates of parameters using classical methods. Robust estimators which are not affected by outliers or the small departures from the model assumptions are applied in this paper to specify th...

Within Groups Multiple Comparisons Based On Robust Measures Of Location