Experimental investigation and multi-response design of FFF-printed PLA honeycomb sandwich panels for flexural performance and mass efficiency

Lightweight sandwich structures produced by fused filament fabrication (FFF) require geometric designs that provide adequate mechanical performance without excessive material usage. However, the geometric parameters governing flexural response and structural mass can favour different design configurations, making response-specific parameter selection unsuitable when both requirements must be considered simultaneously. This study experimentally investigates the effects of honeycomb cell size (HCS), honeycomb cell-wall thickness (HCT), top face-sheet thickness (TFS), and bottom face-sheet thickness (BFS) on the flexural strength and mass of FFF-printed polylactic acid (PLA) honeycomb sandwich panels. Eighteen geometric configurations were fabricated according to a mixed-level Taguchi L18 orthogonal array and evaluated by three-point bending and mass measurement. Analysis of means (ANOM) was used to identify response-specific factor levels, while analysis of variance (ANOVA) quantified the relative contributions of the geometric parameters. HCS and HCT accounted for 45.9% and 34.1% of the modelled variation in flexural strength, respectively, whereas HCT and HCS accounted for 50.9% and 34.0% of the modelled variation in panel mass. Because the parameter settings favoured by maximum flexural strength differed from those favoured by minimum mass, the ANOM factor levels were combined with normalized ANOVA contributions in a contribution-weighted multi-response selection procedure. The resulting configuration, HCS = 6 mm, HCT = 1.08 mm, TFS = 1.18 mm, and BFS = 1 mm, produced a flexural strength of 13.21 MPa and a mass of 34.367 g in the validation experiment. Compared with the highest-strength L18 configuration, the selected design retained 90.54% of the measured flexural strength while reducing panel mass by 50.29%. The results indicate that the core-related variables accounted for most of the modelled variation in the two measured responses. Within the investigated design space, the contribution-weighted procedure was used as a study-specific means of reconciling the response-specific factor settings and selecting a candidate strength–mass compromise for experimental evaluation.