Abstract: 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 manufacturing or use environment. We show that the use of noise factors can dramatically increase power for detecting factors with dispersion effects, provided the noise factors are explicitly modeled in the subsequent analysis.
Key words and phrases: Interactions, off-line QC, parameter design, product array experiments, quality improvement, Taguchi methods, transmitted variation.