An important problem in experimental procedures is the selection of the appropriate design. A design with generalized minimum aberration (GMA) is often considered the best. However, other designs might suit better practical needs, especially when two factor interactions (2fis) are of interest....

In this paper, we obtain a large class of non-isomorphic two-level orthogonal arrays using juxtaposition of certain orthogonal arrays that arise from Hadamard matrices.

In this paper we examine all the combinatorial non-isomorphic OA(27, q, 3, t), with 3≤q≤13 three level quantitative factors, with respect to model identification, estimation capacity and efficiency. We use the popular D-efficiency criterion to evaluate the ability of each design considered...

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...

Screening designs are useful for situations where a large number of factors (q) is examined but only few (k) of these are expected to be important. It is of practical interest for a given k to know all the inequivalent projections of the design into the k dimensions. In this paper we give all...

Unreplicated factorial designs pose a difficult problem in analysis because there are no degrees of freedom left to estimate the error. Daniel [Technometrics 1 (1959), pp. 311-341] proposed an ingenious graphical method that does not require σ to be estimated. Here we try to put Daniel's method...

When we want to compare two designs we usually assume the standard linear model with uncorrelated observations. In this paper we use the comparison method proposed by Ghosh & Shen (2006) to compare three level orthogonal arrays with 18, 27 and 36 runs under a possible presence of correlation in...

Robust parameter design methodology was originally introduced by Taguchi [14] as an engineering methodology for quality improvement of products and processes. A robust design of a system is one in which two different types of factors are varied; control factors and noise factors. Control factors...