Bayesian Taguchi method

The Bayesian Taguchi method integrates Genichi Taguchi's robust parameter design philosophy with Bayesian statistical inference. By encoding prior engineering knowledge as probability distributions and updating these distributions with experimental data, the approach identifies factor settings that simultaneously minimize process variability and keep the mean on target — even when only limited runs are feasible.