Simulation of Metal Forming Processes Under Consideration of Imprecise Probabilities

The design of metal forming processes is an ambitious task in order to ensure a high quality of the subsequent products. The assessments of designs, neglecting the data uncertainty, can result in fallacious prognosis and hence lead to false decisions. Therefore, the consideration of uncertainties in the design process has been brought forward in the recent past. Until now merely probabilistic uncertainty models are applied, solely allowing to model information with the characteristic randomness. This is insufficient for engineering applications reasoning that available information are dubious, incomplete, or fragmentary. To model those information appropriately enhanced uncertainty models on the basis of imprecise probabilities have been developed, e.g., the data model fuzzy randomness. This enables the assessment of alternative design variants on the basis of truly available information. The numerical realization is performed by means of generic optimization algorithms and fuzzy stochastic structural analysis. Both are introduced in this paper and their applicability is demonstrated by an example.

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