The Figure 2 shows that Signal to Noise ratio is highest at the lower level i.e. 35 psi for tyre pressure and at 418Ns/m damping coefficient. The plot for spring stiffness is almost horizontal showing that SN ratio is unaffected by the change in levels of spring stiffness. Hence it shows that the combination of higher level of tyre pressure and damping coefficient along with any level of spring stiffness can give the minimum SN ratio in the design.4.2. Main Effects Plot for Standard DeviationIn order to minimize the variability in the model, the aim is to minimize the standard deviation. The plots in Figure3 show that the value of standard deviation is lowest at tyre pressure of 35 psi, 673 Ns/m i.e. higher level of dampingcoefficient and spring stiffness of 26000 N/m. The nearly horizontal line for spring stiffness indicates its insignificance but the slight deviation shows that the standard deviation is slightly less for the higher level compared to the lower.5. Robust DesignTaguchi also predicts the SN ratio and std deviation for any combination of the control factors, implementation ofwhich on the design corroborates the above inferences. The predicted SN ratio and std deviation for the robust combination have been shown in Table 7.Observing the response tables and main effect plots along with the concepts of vehicle dynamics gives that thecombination of tyre pressure of 35 psi, spring stiffness of 26000 N/m and Damping coefficient of 673 Ns/m improvesthe quality of response to a great extent by reducing the variation due to sprung mass to the minimum.For the above stated combination, the SN ratio was found to be -35.0826 which is minimum among the all possiblecombinations of the parameters and Standard deviation of 0.196 m/s2 which is fairly acceptable as far as Ride comfortis concerned.