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.
International Journal of Quality Engineering and Technology, 2010 Vol.1 No.4, pp.395 - 409
Available online: 30 Sep 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article