Authors: Paul L. Goethals, Gregory L. Boylan
Addresses: Department of Mathematical Sciences, United States Military Academy, West Point, NY 10996, USA. ' Department of Industrial Engineering, Clemson University, Clemson, SC 29634, USA
Abstract: Since the integration of response surface methods into process robustness studies, many researchers have suggested numerous approaches to further enhance product development. Generally, these robust design methods seek the factor settings that minimise variability and the deviation of the mean from the desired target value. In the absence of a uniform approach to modelling process variability, researchers have typically chosen the standard deviation, variance, or logarithm of the standard deviation. Each measure, however, can produce a different set of optimal factor settings, thus complicating comparison studies. The purpose of this paper is to examine the effects of variability measure selection on solutions and suggest a uniform approach.
Keywords: robust design; response surface methodology; RSM; desirability function; variability measures; product optimisation; process optimisation; variability measure selection.
International Journal of Quality Engineering and Technology, 2011 Vol.2 No.3, pp.254 - 276
Available online: 13 Jul 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article