Design of Experiments (DoE) is a methodology for systematically applying statistics to experimentation. Since experimentation is a frequent activity at industries, most engineers (and scientists) end up using statistics to analyse their experiments, regardless of their background. OFAT (one-factor-at-a-time) is an old-fashioned strategy, usually taught at universities and still widely practiced by companies. The statistical approaches to DoE (Classical, Shainin and Taguchi) are far superior to OFAT. The aforementioned approaches have their proponents and opponents, and the debate between them is known to become heated at times. Therefore, the aim of this paper is to present each approach along with its limitations.
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Tanco, M., Viles, E., Pozueta, L. (2009). Comparing Different Approaches for Design of Experiments (DoE). In: Ao, SI., Gelman, L. (eds) Advances in Electrical Engineering and Computational Science. Lecture Notes in Electrical Engineering, vol 39. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2311-7_52
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