Strip-plot designs are commonly used in situations where the production process consists of two process stages involving hard-to-change factors and where it is possible to apply the second stage to semifinished products from the first stage. In this paper, we focus on three-stage processes. As opposed to the threestage strip-plot designs in the literature, the third stage does not involve hard-to-change factors but easyto- change factors that are reset independently for each run. For this scenario, the split-split-plot design is a well-known alternative design option. However, we prefer the more statistically efficient strip-plot designs and, therefore, we construct D-optimal strip-plot designs for three-stage processes with no randomization restriction in the third stage. The coordinate-exchange algorithm we use to construct our designs can handle any type of factor and any number of factor levels, runs, rows, and columns.

A-optimality, D-optimality, Easy-to-change factors, Hard-to-change factors, Split-split-plot design, Strip-plot design, Three-stage processes, Update formulas
hdl.handle.net/1765/82833
Journal of Quality Technology: a quarterly journal of methods, applications and related topics
Erasmus University Rotterdam

Arnouts, H, Goos, P.P, & Jones, B. (2013). Three-stage industrial strip-plot experiments. Journal of Quality Technology: a quarterly journal of methods, applications and related topics, 45(1), 1–17. Retrieved from http://hdl.handle.net/1765/82833