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 stim- ulus 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.

[1]  David M. Steinberg,et al.  Dispersion Effects in Robust-Design Experiments with Noise Factors , 1994 .

[2]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[3]  Neil R. Ullman,et al.  Signal-to-noise ratios, performance criteria, and transformations , 1988 .

[4]  Kwok-Leung Tsui,et al.  Economical experimentation methods for robust design , 1991 .

[5]  Jerome Sacks,et al.  Computer Experiments for Quality Control by Parameter Design , 1990 .

[6]  G. Geoffrey Vining,et al.  Taguchi's parameter design: a panel discussion , 1992 .

[7]  K. Tsui,et al.  Response model analysis for robust design experiments , 1993 .

[8]  J. Senturia.  System of Experimental Design (Vol. 2) , 1989 .

[9]  Neil R. Ullman,et al.  Signal-to-noise ratios, performance criteria, and transformations , 1988 .

[10]  D. Ruppert,et al.  [Signal-to-Noise Ratios, Performance Criteria, and Transformations]: Discussion , 1988 .

[11]  J. Engel,et al.  Modelling Variation in Industrial Experiments , 1992 .

[12]  D. Pregibon,et al.  Analyzing dispersion effects from replicated factorial experiments , 1988 .

[13]  Robert G. Easterling.  Discussion: Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[14]  R. N. Kackar.  Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[15]  G. Geoffrey Vining,et al.  Combining Taguchi and Response Surface Philosophies: A Dual Response Approach , 1990 .

[16]  Susan M. Lewis,et al.  Response Surface Methodology and Taguchi: A Quality Improvement Study from the Milling Industry , 1993 .

[17]  H. Scheffé,et al.  The Analysis of Variance , 1960 .

[18]  P. Rosenbaum.  DISPERSION EFFECTS FROM FRACTIONAL FACTORIALS IN TAGUCHI'S METHOD OF QUALITY DESIGN , 1994 .

[19]  J. Pignatiello,et al.  Discussion: Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[20]  Subir Ghosh,et al.  Determination of optimum experimental conditions using dispersion main effects and interactions of factors in replicated factorial experiments , 1992 .

[21]  R. H. Myers,et al.  Response Surface Alternatives to the Taguchi Robust Parameter Design Approach , 1992 .