The cost of experimentation can often be reduced by forgoing complete randomization. A well-known design with restricted randomization is a split-plot design, which is commonly used in industry when some experimental factors are harder to change than others or when a two-stage production process is studied. Split-plot designs are also often used in robust product design to develop products that are insensitive to environmental or noise factors. Another, lesser known, type of experimental design plan that can be used in such situations is the strip-plot experimental design. Strip-plot designs are economically attractive in situations where the factors are hard to change and the process under investigation consists of two distinct stages, and where it is possible to apply the second stage to groups of semi-finished products from the first stage. They have a correlation structure similar to row-column designs and can be seen as special cases of split-lot designs. In this paper, we show how optimal design of experiments allows for the creation of a broad range of strip-plot designs.

D-optimal strip-plot design, experimental cost reduction, post-fractionated strip-plot design, robust product design, row-column design, split-lot design, two-stage processes
dx.doi.org/10.1002/qre.1047, hdl.handle.net/1765/19218
ERIM Article Series (EAS)
Quality and Reliability Engineering International
Erasmus Research Institute of Management

Arnouts, H, Goos, P.P, & Jones, B. (2010). Design and analysis of industrial strip-plot experiments. Quality and Reliability Engineering International, 26(2), 127–136. doi:10.1002/qre.1047