Robust parameter design, originally proposed by Taguchi [System of Experimental Design, Vols. I and II, UNIPUB, New York, 1987], is an offline production technique for reducing variation and improving a product's quality by using product arrays. However, the use of the product arrays results in...

The two experimental methods most commonly used for reducing the effect of noise factors on a response of interest Y aim either to estimate a model of the variability (V(Y), or an associated function), that is transmitted by the noise factors, or to estimate a model of the ratio between the...

We examine the asymptotic properties of the coefficient of determination, R2, in models with α-stable   random variables. If the regressor and error term share the same index of stability α2, we show that the R2  statistic does not converge to a constant but has a nondegenerate distribution...

Machining with pressurized coolant is nowadays widely accepted technique in the manufacturing industry, especially in high performance machining conditions. The data on the effects of variation of high coolant pressure in drilling operation is limited. This paper presents the effect of high...

An approach for the multiple response robust parameter design problem based on a methodology by Peterson (2000) is presented. The approach is Bayesian, and consists of maximizing the posterior predictive probability that the process satisfies a set of constraints on the responses. In order to...

Parameter design is the most important phase in the development of new products and processes, especially in regards to dynamic systems. Statistics-based approaches are usually employed to address dynamic parameter design problems; however, these approaches have some limitations when applied to...