Innovative design strategies in industrial design practice

In automotive engineering, the design and process parameters in an early design stage are vague, uncertain and partially unknown. This lack of information can be captured with the help of uncertainty models. In this transfer project, non-deterministic simulations and design strategies in industrial design practice are tested. The use of non-deterministic simulation strategies inevitably leads to imprecise results. They reflect the range of variation of parameters that forms the basis of sensible technical decisions. The design is based either on the inverse solution of the optimization problem or on fuzzy optimization. As part of the transfer project, the solutions developed at TU Dresden are adapted, in order to enable reliable designs for the deep drawing process chain - Crash with uncertain date base. This requires the development of practical interfaces and visualizations for different processes. The transfer project is based on scientific methods of research and  development of numerical simulation and design strategies. The starting point of the simulation and design strategies are the theory of fuzzy-random numbers, the fuzzy set theory, possibility theory, stochastics and methods of exploratory data analysis. Those concepts are applied in which the generalized theoretical approaches are used to capture uncertainty and contain the space and time dependence of parameters (Fuzzy-stochastic finite element methods). The algorithms are integrated into a software environment, which is the prerequisite for numerical simulations and measurements with fuzzy data.