Title: Analysis strategies for multiple responses in quality improvement experiments

Authors: Rabindra Nath Das, Youngjo Lee

Addresses: Department of Statistics, The University of Burdwan, Burdwan – 713104, West Bengal, India. ' Department of Statistics, Seoul National University, Seoul 151-747, Korea

Abstract: Quality improvement experiments often aim to find operating condition that achieves the target value for the mean of a process characteristic, and simultaneously minimises the process variability. For this purpose, Taguchi|s techniques of analysis based on signal-to-noise ratios and dual response surface methodology are commonly used to achieve this goal. This paper shows how the generalised linear models approach of modelling the |mean function| and |variance function| jointly can be used to achieve the goal. Two examples illustrate differences among three approaches.

Keywords: dual RSM; response surface methodology; joint generalised linear modelling; JGLM; multiplicative models; signal-to-noise ratios; structured dispersion; multiple responses; quality improvement; Taguchi methods.

DOI: 10.1504/IJQET.2010.035585

International Journal of Quality Engineering and Technology, 2010 Vol.1 No.4, pp.395 - 409

Available online: 30 Sep 2010 *

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