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...

Companies always seek strategies to shorten product development and reduce time-to-market. Although new technologies allow for less effort in prototyping, physical testing still remains an important step in the product development cycle. Well-planned experiments are useful to guide the decision-making process. During the design of an experiment one of the challenges is to balance limited resour...

This paper considers an experimentation strategy when resource constraints permit only a single design replicate per time interval, and one or more design variables are hard-to-change. The experimental designs considered are two-level full or fractional factorial designs run as balanced split-plots. These designs are common in practice and appropriate for fitting a main effects plus interaction...

When it is impractical to perform the experimental runs of a fractional factorial design in a completely random order, restrictions on the randomization can be imposed. The resulting design is said to have a split-plot, or nested, error structure. Similarly to fractional factorials, fractional factorial split-plot designs can be ranked by using the aberration criterion.Techniques that generate ...

Restricting the randomization of hard-to-change factors in industrial experiments is often performed by employing a split-plot design structure. From an economic perspective, these designs minimize the experimental cost by reducing the number of resets of the hard-tochange factors. In this paper, unbalanced designs are considered for cases where the subplots are relatively expensive and the exp...

Split-plot experimental data are often analyzed as if the came from a completely randomized design. As is well known, ignoring different levels of randomization and replication can lead to serious inferential errors. However, in some experiments, including many ocean global change experiments that motivated this research, variation between whole-plot units may be small relative subplot units. E...