In this dissertation a new way of thinking in the validation of simulation model methods in production and logistics systems is presented. The focus is on finding the most important parameters for the validation of simulation models, the relationships between these parameters in the form of correlations which influence the complexity of the models, the required availability of data for these parameters, and the uncertainty which is largely dependent on data availability. Further, a short assessment is made of sequential bifurcation as a method for model validation in the context of finding important parameters, reducing complexity, and exploring uncertainties.