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Parameter Optimization of Fused Filament Fabrication Processes

21.11.2025

Multiple algorithms are explored and compared to improve process parameters optimization in Fused Filament Fabrication (FFF). While methods like traditional design of experiments approaches provide structured, intuitive setups, they often struggle with high-dimensional or complex parameter spaces. In contrast, techniques such as Particle Swarm Optimization (PSO) and Bayesian Optimization (BO) use iterative, adaptive strategies to explore the design space. This allows them to efficiently search large, multi-variable design spaces and achieve high-quality outcomes with significantly fewer experiments. PSO, in particular, demonstrates strong robustness and generalizability, making it well-suited for optimizing complex manufacturing processes such as FFF and potentially other manufacturing applications.

Speaker: Yixue Wang, Scientific researcher, Frauenhofer IPK