Taguchi1 has provided 18 orthogonal arrays which have been widely touted as useful frameworks for planning experiments. Thirteen of these are ‘saturated designs’, that is, they are appropriate for investigating (N ‐ 1) factors in N runs, thus using the full capacity of the design. Here, the other five ‘non‐saturated’ designs are discussed. By creating additional, orthogonal columns which provide estimates of interaction effects, we can essentially wring out some additional information over and above that suggested by Taguchi, without additional cost. In particular, if only the linear effect is of interest for any specific factor, one can accommodate more factors than the number suggested by Taguchi. An example is given for illustration.
All Science Journal Classification (ASJC) codes
- Safety, Risk, Reliability and Quality
- Management Science and Operations Research