Analysis of Functional Responses from Robust Design Studies

Abstract

Robust design studies with functional responses are becoming increasingly common. The goal in these studies is to analyze location and dispersion effects and optimize performance over a range of input-output values. Taguchi and others have proposed the so-called signal-to-noise ratio analysis for robust design with dynamic characteristics. We consider more general and flexible methods for analyzing location and dispersion effects from such studies and use three real applications to illustrate the methods. Two applications demonstrate the usefulness of functional regression techniques for location and dispersion analysis while the third illustrates a parametric analysis with two-stage modeling. Both a mean-variance analysis for random selection of noise settings as well as a control-by-noise interaction analysis for explicitly controlled noise factors are considered.

• Design of Experiments
• Functional Data Analysis
• Quality Improvement
• Variation Reduction

Additional information

Notes on contributors

Vijayan N. Nair

Dr. Nair is Professor of Statistics and Professor of Industrial & Operations Engineering. He is a Senior Member of ASQ. His e-mail address is [email protected].

Winson Taam

Dr. Taam is an Associate Professor of Statistics in the Department of Mathematics and Statistics. His e-mail address is [email protected].

Kenny Q. Ye

Dr. Ye is Assistant Professor in the Department of Applied Mathematics and Statistics. His e-mail address is [email protected].