Function-oriented defect assessment in hybrid sheet molding compound tensile specimen using surrogate models

Abstract

Glass fiber (GF) Sheet Molding Compound (SMC) composites are popular lightweight materials due to their good processability. Hybrid SMCs expand the field of operation, combining the high stiffness of unidirectional carbon fibers (CF) with the economic efficiency of GF. Combinations of manufacturing deviations (delamination, varying GF content, CF misorientation) occur during the production of hybrid SMCs and impede the mechanical performance of the part. A function-oriented quality assurance instead of strict tolerances is proposed. Finite element (FE) simulations are computationally too expensive for an assessment within the cycle time. Hence, surrogate models are trained on multiple parameterized FE simulations. The surrogate models shall allow for an individual functional assessment in real-time based on integrated measurement inputs. This work focuses on the generation of parametrized FE simulations for measurement inputs and surrogate modeling. Simulations and surrogate models show acceptable deviations from tensile tests for multiple combinations of manufacturing deviations. The measurement uncertainty of the stiffness prediction is assessed for both the FE simulation and the surrogate models in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM).