Experimental design and optimisation (4): Plackett–Burman designs

Abstract

Good experimental design is important in many studies of analytical and other chemical processes. Complete factorial designs, which study all the factors (experimental variables) affecting the system response, using at least two levels (values) for each factor, can give rise to an unacceptably large number of trial experiments. This is because even apparently simple processes may be affected by a large number of factors. Moreover these factors may affect the system response interactively, i.e. the effect of one factor may depend on the levels of others. Any interactions must also be distinguished from random measurement errors. So it is more common to use partial factorial designs in which some information, especially about interactions, may be sacrificed in the interests of a manageable number of experiments.