Equivalence of factorial designs with qualitative and quantitative factors

Two symmetric fractional factorial designs with qualitative and quantitative factors are equivalent if the design matrix of one can be obtained from the design matrix of the other by row and column permutations, relabeling of the levels of the qualitative factors and reversal of the levels of the quantitative factors. In this paper, necessary and sufficient methods of determining equivalence of any two symmetric designs with both types of factors are given. An algorithm used to check equivalence or non-equivalence is evaluated. If two designs are equivalent the algorithm gives a set of permutations which map one design to the other. Fast screening methods for non-equivalence are considered. Extensions of results to asymmetric fractional factorial designs with qualitative and quantitative factors are discussed.     

Optimal split‐plot orthogonal arrays

It is well known that many industrial experiments have split‐plot structures. Compared to completely randomised experiments, split‐plot designs are more economical and thus have received much attention among researchers. Much work has been done for two‐level split‐plot designs. In this article, we consider split‐plot designs with factors of three, more than three, or mixed levels and with both qualitative and quantitative factors. We show that if two designs with both qualitative and quantitative factors are geometrically isomorphic, then their generalised wordlength patterns are identical. Three design scenarios are considered for optimal designs. The corresponding wordlength patterns are defined and the minimum aberration mixed‐level split‐plot designs having 18 and 36 runs are tabulated.     

Some robust parameter designs from orthogonal arrays

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 an exorbitant number of runs. To overcome this drawback, several scientists proposed the use of combined arrays, where the control and noise factors are combined in a single array. In this paper, we use non-isomorphic orthogonal arrays as combined arrays, in order to identify a model that contains all the main effects (control and noise), their control-by-noise interactions and their control-by-control interactions with high efficiency. Some cases where the control-by-control-noise are of interest are also considered.     

Optimal blocking and foldover plans for nonregular two-level designs

This paper discusses the issue of choosing optimal designs when both blocking and foldover techniques are simultaneously employed to nonregular two-level fractional factorial designs. By using the indicator function, the treatment and block generalized wordlength patterns of the combined blocked design under a general foldover plan are defined. Some general properties of combined block designs are also obtained. Our results extend the findings of Ai et al. (2010) from regular designs to nonregular designs. Based on these theoretical results, a catalog of optimal blocking and foldover plans in terms of the generalized aberration criterion for nonregular initial design with 12, 16 and 20 runs is tabulated, respectively.     

An orthogonal arrays approach to robust parameter designs methodology

Robust parameter design methodology was originally introduced by Taguchi [14 Taguchi, G. 1986. Introduction to Quality Engineering: Designing Quality Into Products and Process, Tokyo: Asian Productivity Organization.  [Google Scholar]] 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 are variables with levels that are adjustable, whereas noise factors are variables with levels that are hard or impossible to control during normal conditions, such as environmental conditions and raw-material properties. Robust parameter design aims at the reduction of process variation by properly selecting the levels of control factors so that the process becomes insensitive to changes in noise factors. Taguchi [14 Taguchi, G. 1986. Introduction to Quality Engineering: Designing Quality Into Products and Process, Tokyo: Asian Productivity Organization.  [Google Scholar] 15 Taguchi, G. 1987. System of Experimental Design, Vol. I and II, New York: UNIPUB.  [Google Scholar]] proposed the use of crossed arrays (inner–outer arrays) for robust parameter design. A crossed array is the cross-product of an orthogonal array (OA) involving control factors (inner array) and an OA involving noise factors (outer array). Objecting to the run size and the flexibility of crossed arrays, several authors combined control and noise factors in a single design matrix, which is called a combined array, instead of crossed arrays. In this framework, we present the use of OAs in Taguchi's methodology as a useful tool for designing robust parameter designs with economical run size.     

Optimal fractional factorial designs and their construction

Optimal symmetrical fractional factorial designs with n$n$ runs and m$m$ factors of s$s$ levels each are constructed. We consider only designs such that no two factors are aliases. The minimum moment aberration criterion proposed by Xu (2003) is used to judge the optimality of the designs. The minimum moment aberration criterion is equivalent to the popular generalized minimum aberration criterion proposed by Xu and Wu (2001), but the minimum moment criterion is simpler to formulate and employ computationally. Some optimal designs are constructed by using generalized Hadamard matrices.     

An optimality criterion for supersaturated designs with quantitative factors

A supersaturated design (SSD) is a factorial design in which the degrees of freedom for all its main effects exceed the total number of distinct factorial level-combinations (runs) of the design. Designs with quantitative factors, in which level permutation within one or more factors could result in different geometrical structures, are very different from designs with nominal ones which have been treated as traditional designs. In this paper, a new criterion is proposed for SSDs with quantitative factors. Comparison and analysis for this new criterion are made. It is shown that the proposed criterion has a high efficiency in discriminating geometrically nonisomorphic designs and an advantage in computation.     

One-eighth- and one-sixteenth-fraction quaternary code designs with high resolution

The development of a general methodology for the construction of good two-level nonregular designs has received significant attention over the last 10 years. Recent works by Phoa and Xu (2009) and Zhang et al. (2011) indicate that quaternary code (QC) designs are very promising in this regard. This paper explores a systematic construction for 1/8th and 1/16th fraction QC designs with high resolution for any number of factors. The 1/8th fraction QC designs often have larger resolution than regular designs of the same size. A majority of the 1/16th fraction QC designs also have larger resolution than comparable two-level regular designs.     

Optimal designs for accelerated life tests with multiple stress factors and heteroscedasticity

Accelerated life testing (ALT) provides a means of obtaining data on product lifetime and reliability relatively quickly by subjecting products to higher-than-usual levels of stress factors. We present methods for obtaining optimal designs for multiple-factor ALTs with time censoring and heteroscedasticity in order to estimate percentiles of product life at usage conditions. We assume a Weibull life distribution and log-linear life–stress relationships with non constant shape parameter for the ALT stress factors. The primary optimality criterion is the minimization of the asymptotic variance of maximum likelihood estimator of the percentile estimator at usage stress. We also consider a secondary criterion for our design optimization. The design construction methods are illustrated by two practical examples.     

Properties and performance of one-sided cumulative count of conforming chart with parameter estimation in high-quality processes

The one-sided cumulative count of conforming (CCC) chart is a useful method to monitor nonconforming fraction in high-quality manufacturing processes. The nonconforming fraction parameter is assumed to be known when implementing a one-sided CCC chart. In this study, we investigated the impact of estimated nonconforming fraction, [pcirc] ₀, in a one-sided CCC chart. The run length distribution is derived as well as the conditional probability of a false alarm rate (CFAR), conditional average run length (CARL) and its standard deviation (CSDRL). Simulation results are conducted to evaluate the effect of [pcirc] ₀ in a one-sided CCC chart. The results show that values of CFAR, CARL and CSDRL are close to the nominal values for a large sample. The impact of estimation errors was also studied. We find that CFAR decreases for large [pcirc] ₀. Thus, a large value of [pcirc] ₀ is suggested for fewer false alarms.     

Change-over designs with complete balance for first and second residual effects

This paper presents a unified method of constructing change-over designs that permit the estimation of direct effects orthogonal to all other effects when the residual effects of treatments last for two consecutive periods. Explicit methods of analysis of these designs have been obtained for the situations where the first period observations are omitted from the analysis and where the first period observations are included.