Abstract
Mathematical modeling is an important part of the engineering design cycle. Most models require application specific input parameters that are established by calculation or experiment. The accuracy of model predictions depends on underlying model assumptions as well as how uncertainty in knowledge of the parameters is transmitted through the mathematical structure of the model. Knowledge about the relative impact of individual parameters can help establish priorities in developing/choosing specific parameters and provide insight into a range of parameters that produce 'equally good' designs. In this work Global Sensitivity Analysis (GSA) is examined as a technique that can contribute to this insight by developing Sensitivity Indices, a measure of the relative importance, for each parameter. The approach is illustrated on a kinematic model of a metamorphic 4-bar mechanism. The model parameters are the lengths of the four links. The results of this probabilistic analysis highlight the synergy that must exist between all four link lengths to create a design that can follow the desired motion path. The impact of individual link lengths, however, rises and falls depending on where the mechanism is along its motion path.