Designed of Experiments (DOE) is a structured approach for varying process and/or product factors (x’s) and quantifying their effects on process outputs (y’s), so that those outputs can be controlled to optimal levels.
For example, a DC motor manufacturer might wish to understand the effects of two process variables, wire tension and trickle resin volume, on motor life. In this case, a simple two factor (wire tension and trickle resin volume), two level (low and high values established for each of the two factors) experiment would be a good starting point. Randomizing the order of trials in an experiment can help prevent false conclusions when other significant variables, not known to the experimenter, affect the results. There are a number of statistical tools available for planning and analyzing designed experiments.
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