Two-level factorial and fractional factorial designs have played a prominent role in the theory and practice of experimental design. Though commonly used in industrial experiments to identify the significant effects, it is often undesirable to perform the trials of a factorial design (or, fractional factorial design) in a completely random order. Instead, restrictions are imposed on the randomi...

A novel method, BBD-SSPD is proposed by the combination of Box-Behnken Design (BBD) and Split-Split Plot Design (SSPD) which would ensure minimum number of experimental runs, leading to economical utilization in multi- factorial experiments. The brine shrimp Artemia was tested to study the combined effects of photoperiod, temperature and salinity, each with three levels, on the hatching percent...

While split-plot designs have received considerable attention in the literature over the past decade, there seems to be a general lack of intuitive understanding of the error structure of these designs and the resulting statistical analysis. Typically, students learn the proper error terms for testing factors of a split-plot design via expected mean squares. This does not provide any true insig...

Fractional factorial split-plot designs are widely used when it is impractical to perform fractional experiments in a completely random order. When there too many subplots per whole plot, or few plots, with replicated settings of the plot factors preferred. However, such an important study undeveloped literature. This paper considers WP from viewpoint clear effects. We investigate sufficient an...

In some experiments, the levels of factors are difficult to change; then fractional factorial split-plot (FFSP) designs suitable for selection. an FFSP design, divided into two classes—the whole plot (WP) and subplot (SP) factors. selection WP can affect that SP factors, which attracts much attention Paying more a new optimality criterion selecting such is proposed. The robustness proposed meth...