Manufacturing bio-based fiber-reinforced polymer composites: process performance in RTM and VARI processes - Ulrike Kirschnick; Michael Feuchter; Bharath Ravindran; Moritz Salzmann; Ivica Duretek; Ewald Fauster; Ralf Schledjewski (Advanced Manufacturing: Polymer & Composites Science, 2024)
The utilization of bio-based materials for the manufacturing of fiber-reinforced polymer composites is gaining importance under the sustainability paradigm. The identification of suitable process parameters and limited process reproducibility remain among the major challenges to enhance the industrial application potential of bio-based composites. This is especially relevant, as the manufacturing process influences composite quality, economic performance and environmental impacts. This study compares Resin Transfer Molding and Vacuum Assisted Resin Infusion for two sets of process parameters in order to manufacture a composite plate consisting of a flax-fiber textile impregnated with a partially bio-based epoxy matrix. Process quality is described through statistical analysis of processing and composite properties, and performance in terms of process replicability and reliability using performance estimates. Processing parameters were selected to depict a range of manufacturing scenarios that were suitable for the selected bio-based material system from curing for 180 min at 60 °C to curing for 30 min at 100 °C. For an identical set of process conditions, Resin Transfer Molding outperforms Vacuum Assisted Resin Infusion in terms of tensile and flexural characteristics. Conversely, the latter shows the strongest fiber-matrix adhesion and the most homogeneous impregnation. Whereas manufacturing at lower temperature leads to positive effects on composite quality, higher processing temperature with shorter curing cycles achieve highest process performance in terms of Pp and Ppk indices. An additional annealing at 120 °C neither increases composite quality nor reduces manufacturing-induced variability. Results depend on processing differences and indicators to determine process performance, as well as methodological choices.