High Quality Content by WIKIPEDIA articles! Robust parameter designs, introduced by Taguchi, are experimental designs used to exploit the interaction between control and uncontrollable noise variables by finding the settings of the control factors that minimize response variation from uncontrollable factors.Control variables are variables of which the experimenter has full control. Noise variables lie on the other side of the spectrum, and while these variables may be easily controlled in an experimental setting, outside of the experimental world they are very hard, if not impossible, to control. Robust parameter designs use a naming convention similar to that of FFDs. A 2(m1+m2)-(p1-p2) is a 2-level design where m1 is the number of control factors, m2 is the number of noise factors, p1 is the level of fractionation for control factors, and p2 is the level of fractionation for noise factors.