Multi objective optimization of FDM 3D printing parameters set via design of experiments and machine learning algorithms

The choice of the optimal printing setup for Fused Deposition Modeling (FDM) 3D-printing technology is challenging due to complex interactions between process parameters and mechanical properties. This especially affects engineering applications where the maximum performance is required. To address this challenge, this study explores the influence of main controllable printing parameters including layer thickness, extrusion temperature, printing speed and deposition patterns, on the mechanical properties of FDM-printed ABS specimens using the Design-of-Experiments (DoE) approach by a $$3^4$$ full factorial design. Main-effects and Interaction-effects on tensile strength, elastic modulus, and strain at maximum…