A technique for designing and performing experiments to investigate processes where the output depends on many factors (variables; inputs) without having to tediously and uneconomically run the process using all possible combinations of values of those variables. By systematically choosing certain combinations of variables it is possible to separate their individual effects.
A special variant of Design of Experiments (DOE) that distinguishes itself from classic DOE in the focus on optimizing design parameters to minimize variation BEFORE optimizing design to hit mean target values for output parameters.
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